goal

Optimization of a novel and effective antiviral agent targeting Zika NS4B

This project focuses on developing novel anti-Zika virus (ZIKV) compounds targeting the NS4B protein, which is crucial for viral replication. ZIKV poses a significant medical challenge due to its potential for severe pathogenic outcomes, such as congenital Zika syndrome and Guillain-Barré Syndrome. Furthermore, its pandemic potential has been increasing with the expansion of carrier mosquito habitats. The project aims to address the urgent need for anti-ZIKV therapeutics that could greatly reduce severity of symptoms and minimize vertical and community transmissions. We have identified a novel small-molecule series with a benzamide scaffold through a cell-based, antiviral ultra-high-throughput screen. This series demonstrates strong potency against ZIKV without measurable cytotoxicity or non-specific antiviral effects, justifying this scaffold as a lead series for further development. Preliminary mechanism-of-action studies, utilizing genetic, biochemical, and virological assays, suggest that this series may inhibit the formation of the ZIKV viral replicase complex by interfering with NS4B. Our goal for this project is to develop a preclinical therapeutic candidate for ZIKV that demonstrates promising therapeutic activity following oral administration in ZIKV-infected mice, at a dosage that shows no clinical toxicity. The project has the following significant and novel objectives: 1) Optimize the benzamide lead for potency and drug-likeness; 2) Develop a lead candidate and a backup compound with optimized pharmacokinetic, pharmacodynamic, and toxicity profiles; 3) Determine the molecular mechanisms of action of the benzamide series using novel structural approaches to assist medicinal chemistry studies; 4) Evaluate the in vivo therapeutic efficacy and safety in mouse models and develop the best therapeutic regime. This project seeks to develop effective antivirals for ZIKV with high retention in the blood and central nervous system (CNS) and high oral bioavailability. The expected successful outcomes will provide significant advancements in ZIKV therapeutics and open new avenues for treating other flavivirus infections

Structural and functional characterization of autoimmune antibodies against NMDAR

Project Summary. The goal of this project is to understand the origins and molecular mechanisms underlying the anti-cancer autoimmune response against the N-methyl-D-aspartate receptor (NMDAR) and its correlation with anti-N-methyl-D-aspartate receptor autoimmune encephalitis (NMDARAE). While anti-cancer immune responses can promote tumor elimination, they may also lead to the production of self-reactive antibodies that trigger autoimmune diseases. NMDARAE is the most common form of immune-mediated encephalitis, which results in prominent neuropsychiatric symptoms, including seizures, psychosis, and memory deficits. NMDARs belong to a family of ligand-gated ion channels expressed exclusively in the central nervous system. They are involved in various aspects of brain development and function, including learning and memory. They respond to the neurotransmitter glutamate and a co-agonist, glycine or D-serine, to mediate excitatory neurotransmission, which plays a central role in synaptic plasticity. NMDARAE is associated with ovarian teratomas, where aberrant NMDAR expression is believed to trigger an autoimmune response. In NMDARAE, anti-NMDAR antibodies, as well as B cells and antibody-secreting cells, cross the blood-brain barrier via unknown mechanisms, resulting in the presence of anti-NMDAR antibodies at high titers within the brain and cerebrospinal fluid (CSF). These antibodies target NMDARs, modulating their function and contributing to disease pathology. Emerging evidence, supported by our preliminary data, suggests that NMDARs are also expressed in triple-negative breast cancer (TNBC), extending the relevance of anti-NMDAR autoimmunity beyond ovarian teratomas. In our TNBC mouse model, which ectopically expresses NMDARs (TNBC-NMDAR), we observed the onset of anti-NMDAR autoimmunity, where the produced antibodies cause both anti-tumor activity and symptoms such as lowered seizure threshold, mirroring key features of NMDARAE. Here, we will establish this TNBC mouse model as we develop molecular methods to characterize it. Aim 1 will focus on establishing and characterizing the TNBC- NMDAR mouse model. We will develop a detection method utilizing the intact tetrameric NMDAR channel proteins and a method to isolate B cells expressing B cell receptors against NMDAR from biological samples by using fluorescently labeled intact NMDAR proteins, followed by single-cell RNA sequencing. Aim 2 will utilize single-particle cryo-electron microscopy (cryo-EM) to investigate the interactions between NMDAR and the cloned antibodies, providing insights into epitope recognition, NMDAR subtype specificity, and conformational changes induced by antibody binding. Aim 3 will assess the impact of the cloned antibodies on NMDAR channel activity using electrophysiology. We will also assess anti-tumor activity and NMDARAE onset by each antibody clone. Together, the proposed research will gain insights into the link between anti-cancer anti-NMDAR autoimmunity and NMDARAE. It will also elucidate which functional properties of the cloned antibodies promote anti-tumor activity while contributing to NMDARAE, thereby informing potential therapeutic strategies.

Utilizing integrin-targeted PET imaging and therapeutics to predict and treat radiation-induced pulmonary fibrosis

Project Summary/Abstract. Lung cancer is the leading cause of cancer death in the US, with over 125,000 deaths annually. Radiation therapy (RT) is a critical component of curative lung cancer treatment for many patients. However, radiationinduced pulmonary fibrosis (RIPF) is a common side effect that carries a poor prognosis with limited treatment options. Up to 40% of patients with lung cancer who receive RT may experience RIPF. RIPF is a late effect of RT, typically occurring 3 or more months after treatment. The symptoms of RIPF can include shortness of breath, pleural effusions, decreased lung function, and respiratory failure. Cell surface integrin heterodimers play a key role in the pathogenesis of RIPF. In particular, the integrin αvβ6, which is expressed at a low level in the alveolar epithelium at baseline, is significantly upregulated upon RT damage. The key role of integrin αvβ6 in RIPF is illustrated by studies in which mice lacking integrin αvβ6, or treated with an αvβ6-blocking antibody, do not develop RIPF. Here, we propose to translate this mechanistic understanding of RIPF into novel approaches for monitoring and treating RIPF. We hypothesize that non-invasive αvβ6 PET imaging will be safe and can specifically bind to αvβ6 in patients with RIPF. Additionally, we hypothesize that a novel small-molecule integrin antagonist, IDL2965, can mitigate and treat RIPF in mice. In this project, we are utilizing mice to model RIPF, as mice develop RIPF that mimics human disease. In addition, cellular and in vitro models do not approximate the complex biology leading to the development of RIPF. Our data using [64Cu]Cu-DOTA-αvβ6-BP to detect early RIPF in mice are compelling in both single-fraction high-dose RT and lower dose-larger volume RT models (Lo et. al, IJROBP 2025). However, to progress to clinical trials in patients with cancer, we will obtain data to submit an Investigational New Drug (IND) application to the FDA. Importantly, we propose translating [64Cu]Cu-DOTA-αvβ6-BP PET imaging into patients with lung cancer, allowing us to better identify RIPF and develop a tool to determine the efficacy of IDL-2965 in future clinical studies. The specific aims of the proposal are: (1) Characterize the utility of [64Cu]Cu-DOTA-αvβ6-BP in mice with conventionally fractionated RT and identify circulating biomarkers of RIPF, and determine the in vivo toxicology of [64Cu]Cu-DOTA-αvβ6-BP to prepare and submit an exploratory Investigational New Drug (eIND) application to the FDA, (2) Conduct a first-in-human clinical trial of [64Cu]Cu-DOTA-αvβ6-BP to determine its safety and human dosimetry in patients with evidence of RIPF from computed tomography or in healthy controls, and (3) Determine the effect of integrin antagonism using IDL-2965 on mitigating RIPF in preclinical mouse models. The goals of this proposal are two-fold: (1) demonstrate safety and target specificity for [64Cu]Cu-DOTA-αvβ6-BP so that it can be used in future studies to identify RIPF and evaluate the efficacy of anti-fibrotic therapies, and 2) determine the ability of IDL-2965 to prevent RIPF in preclinical mouse models.

Mechanisms of Commensal- Specific CD8+ T Cell Differentiation, Restraint and Dysregulation in Intestinal Inflammation

PROJECT SUMMARY Our understanding of immunity largely stems from models of infection with pathogenic microbes. However, the vast majority of microbial-immune encounters occur as a symbiotic relationship with the commensal microbiota. Recently, the contribution of commensal-specific T cells to host physiology has received significant attention. These commensal-specific responses not only control microbiota containment but also promote immune tolerance within the gastrointestinal tract. While commensal-specific CD4+ T cell responses in the lamina propria have dominated models of mucosal immune regulation, these are vastly outnumbered by CD8+ intraepithelial lymphocytes within the epithelium. How CD8+ T cell responses to gut microbiota are primed, differentiate and function under homeostasis has not been addressed. Conversely, aberrant immunity to commensal microbes has been proposed to underlie pathologies of barrier tissues, including inflammatory bowel disease (IBD), where commensal-specific T cells accumulate in blood and intestinal tissues of afflicted patients. A better understanding of the properties and functions of commensal-specific T cell responses is therefore fundamental to studies of tissue immunity in health and disease. Our long term goal is to better understand how commensal-specific T cell responses contribute to barrier tissue homeostasis, and the objective in this application is to investigate the mechanisms regulating induction of commensal-specific CD8+ T cells in homeostasis and how they become dysregulated in IBD. Our rationale for the proposed work is that uncovering these mechanisms has the potential to translate into new therapeutic approaches. Our central hypothesis is that commensal-specific CD8+ T cells develop as functionally restrained intraepithelial lymphocytes (IEL) under homeostasis, but that perturbation of local immune regulation within the intestinal epithelium, in the case of patients with ulcerative colitis, by autoantibody-mediated blockade of integrin avb6 results in aberrant CD8+ effector T cell responses in IBD. Based on strong preliminary data, we will test three specific aims: (1) Determine key antigen-presenting cells (APC) priming SFB-specific CD8⍺β+ IEL. (2) Identify how cell-intrinsic pathways drive differentiation, maintenance and restraint of SFB-specific CD8⍺β+ pIEL. (3) Determine how pathogenic KLRG1+Eomes+ CD8+ T cells arise and contribute to inflammation in murine models of ulcerative colitis Our approach is innovative as it investigates new mechanisms of immunity unique to commensal-specific CD8+ T cell responses. The proposed work is significant because it will establish new insights into the interaction and communication between commensal microbes and immune cells in the gut environment and identify potential targets for therapeutic intervention in conditions of chronic intestinal inflammation.

Mechanisms of antigen-specific T cell activation in MOGAD

PROJECT SUMMARY / ABSTRACT The overarching goal of this application is to train Dr. Carson E. Moseley, MD, PhD, who is a clinical neurologist and a research immunologist, to become an independent investigator studying and treating neuroimmunologic disorders. Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is a recently described, severe, neuroinflammatory syndrome of the central nervous system (CNS) with no approved therapies. Although MOG-specific antibodies helped define the disease, MOG antibodies alone are not clearly pathogenic and our understanding of MOGAD immunopathology is limited. CD4+ T cells are a dominant lymphocyte population in MOGAD lesions, yet the targets of T cell responses to MOG and how T and B cells interact to drive pathogenic immune response in MOGAD are unknown. This proposal uses a complementary approach of human and mouse immunology along with new technologies in T cell repertoire mapping and genome editing to dissect MOG-specific CD4+ T cell responses in MOGAD. Additionally, it will use new models to investigate how B cells promote pathogenic T cell differentiation and select pathogenic T cell receptors. The proposed training plan involves mentored training, seminars, formal learning, and advising to ensure completion of the proposed research and Dr. Moseley’s career development. He will train at UCSF, which is an outstanding institute for research and environment for physician-scientists. He will receive training in human immunology and CRISPR-based gene editing technologies. He will be mentored by Dr. Scott Zamvil, a leader in identifying antigen-specific T cell responses in neuroimmunologic disorders, and co-mentored by Dr. Alexander Marson, an expert in CRISPR gene editing to understand lymphocyte function. This application will provide Dr. Moseley with the long-term skills needed to become an independent investigator leading efforts to study and treat neuroimmunologic disorders.

Antibody-guided design of a human astrovirus vaccine

PROJECT SUMMARY Viral diarrheal diseases cause substantial global morbidity and mortality. Diarrheal disease is the second leading cause of childhood mortality in the world, accounting for over 10% of all deaths of children under 5 years old. Gobally, over 1 billion cases of diarrheal diseases occur every year, making prevention of these diseases a public health concern of the highest priority. Human astrovirus (HAstV) infection is a leading cause of viral diarrhea in children and has been shown to cause chronic gastrointestinal disease and fatal neurological disease in immunocompromised patients. There are nearly 4 million cases of HAstV infection each year in the United States alone, and there are no clinically approved HAstV-specific vaccines or therapeutics. Antibody-guided vaccine development leverages a deep understanding of productive antiviral antibody responses in order to design vaccine immunogens that deliberately focus the induced response toward highly conserved epitopes with the goal of reliably inducing broad, durable immunity. Using a cutting-edge monoclonal antibody (mAb) discovery approach based on next-generation antigen barcoding, single cell multi-omics, and sophisticated bioinformatics, we will exhaustively screen the HAstV- specific antibody repertoires of geographically distinct donor cohorts to uncover the structural and immunogenetic features that differentiate broad and potently neutralizing HAstV mAbs. A more complete understanding of these exceptional – and potentially very rare – mAbs will accelerate the development of HAstV vaccines and therapeutics. We have assembled a collaborative, multidisciplinary group of investigators with a long history of productive collaboration and with highly complementary areas of expertise. We expect our work will result in the discovery of thousands of novel anti-HAstV mAbs from cohorts of healthy adult and pediatric participants. Detailed genetic, functional, and structural characterization of these mAbs will reveal conserved sites of viral vulnerability, uncover the precise molecular mechanisms of viral neutralization, and inform our development of a broadly protective HAstV vaccine.

NeuroASCENT- Advancing Science through Career Enhancement and Neuroscience Training

The NeuroASCENT- Advancing Science through Career Enhancement and Neuroscience Training program will support neuroscience‑focused PhD students across multiple graduate programs by providing comprehensive scientific, professional, and research‑development training during their doctoral education. Strengthening the national neuroscience workforce requires ensuring that trainees have access to high‑quality research preparation, strong mentoring, and structured opportunities that enhance their scientific growth and career readiness. Recent analyses of U.S. doctoral recipients indicate that many talented trainees encounter barriers that limit full participation in research careers, underscoring the need for intentional support mechanisms that promote successful advancement. Over the last five years, CU Anschutz PhD programs have seen a substantial increase in students entering from a broad range of academic backgrounds. NeuroASCENT is designed to help these trainees progress efficiently by 1) promoting research excellence, 2) fostering leadership skills, 3) facilitating career development, and 4) providing individualized guidance. To achieve these goals, the program will provide career‑focused workshops, structured research externship opportunities, enhanced mentoring frameworks, and coordinated access to campus resources that extend beyond those offered by individual graduate programs. In partnership with the Office of Research Education, NeuroASCENT will complement and enhance the scientific training provided across biomedical PhD programs while offering added value to the broader CU Anschutz graduate community. Program Directors Dr. Quillinan and Dr. Hughes will oversee training activities, mentor matching, evaluation, program operations, and dissemination. An Institutional Advisory Board composed of research leaders will guide program oversight, and an External Advisory Board of graduate‑education experts will provide additional evaluation and strategic input. NeuroASCENT scholars will also serve on an Executive Advisory Board to develop leadership experience and contribute directly to program refinement. Trainees will typically enter the program after their second year of graduate training and will participate in activities focused on building a supportive peer/mentor network, strengthening scientific confidence and competence, and preparing for careers in academia, government, industry, or non‑profit research organizations.

Regulation of neutrophil endoplasmic reticulum stress response by IRE1a

Project Summary/Abstract: The lungs are exposed to pathogens and environmental toxins that trigger stress and cause numerous respiratory diseases. Effective host defenses against lung infection by bacterial pathogens, including methicillin- resistant Staphylococcus aureus (MRSA), rely on innate immune cells including neutrophils, prominent early responders to sites of infection. If host defenses are ineffective, MRSA causes serious lung infection, resulting in severe morbidity and a significant economic burden on healthcare facilities, where it is endemic. MRSA infections have a mortality rate of up to 14% and an estimated $500 million in healthcare costs in the US alone. Increasing resistance to vancomycin, the last resort antibiotic for MRSA infections, underscore the urgent need for innovative treatment approaches. Although directly targeting pathogens with antibiotics has been a successful approach for treating infections, many pathogens, including MRSA, eventually will become resistant to these drugs. As an alternative, immunomodulatory strategies to enhance host defenses, such as those shown to be effective against cancer cells, have the potential for treating drug-resistant pathogen infections. Recently, we showed that the inositol-requiring enzyme 1-α (IRE1α), an endoplasmic reticulum (ER) stress sensor, is required for clearance of MRSA in a murine skin abscess model, where neutrophils are robustly recruited to the site of infection. Further, IRE1α coordinates signaling events upstream of calcium (Ca2+) mobilization, histone citrullination, and production of mitochondrial reactive oxygen species (mitoROS), all of which are important for neutrophil inflammatory responses including the formation of antimicrobial neutrophil extracellular traps (NETs). Because excessive neutrophil activation and NET release can be detrimental to vital organs, it is not clear whether neutrophil IRE1α-mediated stress responses aid or impede the resolution of infection in the lungs. While IRE1α activation has been linked to the development of lung fibrosis through the regulation of alveolar epithelial- to-mesenchymal transition in the context of chronic inflammatory diseases, its role in pulmonary neutrophil defenses is unknown. Thus, there is a gap in our knowledge of how cellular stress responses modulate pulmonary neutrophil defenses and infection outcomes in the lungs. The overarching goal of this proposal is to elucidate the mechanisms by which neutrophil IRE1α signaling influences production of mitoROS and Ca2+ mobilization to drive NET release, injure lungs, and regulate pulmonary host defense against MRSA. We will accomplish the following Aims: (1) Define the molecular mechanisms underlying IRE1α-mediated mitoROS hyperactivation of human and mouse primary neutrophils and excessive NET release, and (2) Elucidate the role of neutrophil IRE1α signaling in excessive NET release, lung injury, and immunity in vivo using a MRSA pneumonia infection mouse model. These studies will yield mechanistic insight into how IRE1α-driven ER stress responses impact pulmonary neutrophil defenses and lung injury revealing potential targets for anti-microbial immunotherapies.

Th17 plasticity in rheumatoid arthritis

ABSTRACT The objective of this grant application is to explore the plasticity of Th17 in arthritis. Interleukin-17A (IL-17A) producing Th17 are present in the blood and synovium of patients with rheumatoid arthritis (RA). However, targeting of IL17A has been insufficient to control joint inflammation of RA patients. One potential scenario is that in the context of worsening RA joint inflammation, Th17 undergo conversion into pathogenic IL17A- negative cell populations, collectively called exTh17. The conversion of Th17 into exTh17 has been documented in the context of neuroinflammation, colitis, and infection. However, the occurrence of Th17 plasticity in autoimmune arthritis and its potential role in perpetuating synovial inflammation has remained mostly unexplored. We generated a novel fate-mapping mouse model of autoimmune arthritis, which allows to follow the conversion of Th17 into exTh17, and collected preliminary data suggesting that Th17 undergo significant loss of IL17A expression and conversion into exTh17 in the context of synovial inflammation. We also identified exTh17 signatures which might help exTh17 perpetuate joint inflammation despite their loss of IL17A expression. Here our objective is to further elucidate intrinsic (Aim 1) and extrinsic (Aim 2) mechanism of Th17-exTh17 conversion and exTh17-mediated joint inflammation, and explore the potential role of exTh17 in RA interstitial lung disease (ILD, Aim 3) a feared and often untreatable complication of established RA. Our long-term goal is to leverage the knowledge of local immune cell phenotypes and how they change at various stages of disease to enable stage-specific and personalized therapies of RA which minimize non- specific immunosuppression.

Modulating the Action of Cylindrical Proteases to Eliminate Neisseria Gonorrhea and Chlamydia Trachomatis Infections

Project Summary/Abstract Sexually transmitted bacteria diseases caused by Chlamydia trachomatis (Ctr) and Neisseria gonorrhoeae (NG) are the two most common sexually transmitted bacterial diseases. The infections caused by these pathogens may result in infertility, ectopic pregnancy, blindness, and perinatal mortality. Over 1.70 M cases of chlamydia and 0.65 M cases of drug-resistant gonorrhea are reported yearly in the US. Women with gonorrhea are co- infected with chlamydia in 17.6%–57.9% of cases, while women with chlamydia are co-infected with gonorrhea in 2.1%–17.2% of cases. These infections are treated with broad spectrum antibiotics, which can favor the development of resistance on NG/CTr but also in other bacteria, or damage the microbiota, diminishing its protective function and allowing bacteria and viruses to infect the patient. The Caseinolytic protease (ClpP) proteolytic machinery regulates protein turnover and homeostasis and is key in bacterial growth and development The machinery consists of the proteolytic unit (the ClpP) and its chaperone (ClpX), which transports proteins to be degraded, and it is termed the ClpXP. Our theory is that molecules that inhibit the action of the ClpX chaperone can become efficient antibacterial agents against both pathogens. We have found that the dihydrothiazepines can erradicate both pathogens and prevent the action of the ClpXP complex. Our goal is to advance the dihydrothiazepines as selective agents against Ctr and NG infections. To develop these therapeutic agents, we have envisioned four specific aims. Specific Aim 1. Synthesis and Optimization of the Pharmacophore. Our goal is to use computational models to design dihydrothiazepines molecule that will be synthesized, purified, and characterized using chemical techniques. The molecules will be tested against Ctr and NG and their toxicity against human cells evaluated. Also, we will determine their effect in other bacterial, including those from the microbiota. Specific Aim 2. Assessment of Stability and In Vivo Activity. We will study the stability of the most active molecules under various conditions. Then, we will study the pharmacokinetics, biodistribution , and antibacterial activity against Ctr and NG in mice. Specific Aim 3. Target Validation and Effect. We will study the ability of the compounds to inhibit the activity of ClpX using a luciferase assay and to block protein degradation. We will try grow crystal of the protein and the molecule and will study if the molecules prevent the assembly of the ClpXP system. Finally, we will assess the ability of the bacteria to develop resistance to the molecules.

Role of cellular physical interactions in pancreatic cancer progression

Pancreatic cancer, with a 5-year overall survival rate of 13%, has the lowest survival rate of all cancers. The goal of this project is to better understand the biological processes of pancreatic cancer progression and discover their potential as targets for efficient therapies. Pancreatic ductal adenocarcinoma (PDAC) underdoes epithelial architecture changes during its progression. However, the underlying mechanisms for these changes are largely unknown. Interestingly, our recent data demonstrate the recapitulation of the distinct epithelial architectures in the organoid culture of cells derived from the human normal pancreas, primary tumor, and metastatic lesions, thereby developing a unique organoid model for the in vitro studies of PDAC epithelial architecture changes. The primary objective of this project is to understand the regulation of the differential PDAC epithelial architectures as well as their contribution to PDAC progression. Our central hypothesis is that disruption in lumen structure drives PDAC epithelial architecture transition and promotes PDAC progression. We will combine experimental and computational approaches to test our central hypothesis by pursuing the following two specific aims: (Aim 1) define the regulators of PDAC epithelial architecture that drives PDAC progression and (Aim 2) determine the functional consequences of PDAC epithelial architecture on PDAC progression. With the completion of this aims, we expect: (Aim 1) to identify ion and water channels that are important for lumen structure as well as PDAC progression, revealing potential novel targets for therapeutic intervention, and (Aim 2) to uncover YAP’s role in PDAC progression and guide the development of YAP- targeted therapies.

The Role of the Intestinal Microbiota in Sepsis Mortality

Project Summary/Abstract Sepsis is a life-threatening condition characterized by a dysregulated host response to infection that can cause multi-organ damage and death. As the leading cause of in-hospital mortality, sepsis mortality rates reach up to 50%, and account for approximately 270,000 deaths and $38 billion annually in health care costs in the United States. Notably, patients with similar medical backgrounds can have vastly different sepsis outcomes— some survive with medical treatment while others die. The reasons for this dichotomy are unknown but is seen across all forms of bacterial bloodstream infections, is not specific to any strain-level differences in the infecting pathogen and cannot be explained by human genetic differences. Human microbiota studies suggest that gut microbial dysbiosis is associated with sepsis mortality and that these alterations influence gut barrier breakdown, leading to gram-negative bacteremia—one of the most common causes of sepsis and mortality. However, there are a lack of studies that investigate the causal role of the intestinal microbiota in sepsis mortality. This K08 proposal will elucidate the role of the intestinal microbiota in sepsis mortality. Utilizing the well- established murine model of sepsis by intraperitoneal injection of lipopolysaccharide (LPS), we combine microbiota taxonomic sequencing and metagenomics, advanced bioinformatic techniques and prediction modeling, with knowledge of mucosal immunity and germ-free mouse systems to characterize the microbiota features and members that correlate with, predict, and cause sepsis mortality. This proposal is organized into two specific aims: (1) identify baseline stool microbial features associated with and predictive of sepsis outcomes and (2) determine how colonization with immunostimulatory microbes heightens sepsis mortality. In this work, I will holistically characterize the host immunologic and microbiota features that are associated with and predictive of mortality and experimentally identify microbes and microbial pathways that cause death in our model. These findings will reveal new microbial and host biomarkers of sepsis mortality and identify novel targets for sepsis prevention and treatment to reduce the overall mortality rate of this deadly disease. My long-term goal is to become an independent physician-scientist who integrates cutting-edge computational methods with experimental biology to identify predictive biomarkers of disease onset and outcomes, investigate how they influence disease processes, and develop novel therapeutic and preventive strategies to improve patient care. This proposal details specific research aims and a structured career development and training plan that will allow me to acquire focused, in-depth and multidisciplinary training under the guidance of an internationally recognized team of experts in clinical infectious diseases, host-microbiota interactions, immunology, immunometabolism, and computational biology. The knowledge generated will address the fundamental role of the microbiota in sepsis outcomes and inform future preventative and therapeutic strategies that will lower the sepsis mortality rate worldwide.

Causal mechanisms driving germline predisposition to myeloproliferative disorders

SUMMARY/ABSTRACT Although human genetic studies have indicated a significant hereditary predisposition to myeloproliferative neoplasms (MPNs) the underlying mechanisms driving the genetic risk remains unknown. Our large genome wide association study (GWAS) on MPNs identified several non-coding genetic risk loci associated with disease and implicated modulation of hematopoietic stem cell (HSC) self-renewal by the genetic variants. The long-term goal is to utilize our GWAS results to better understand MPN disease initiation and progression and draw out key unknown MPN predisposition genes. The overall objectives in this application are to elucidate the mechanisms by which MPN risk variants promote disease initiation and progression. The central hypothesis is that common genetic variants increase MPN risk by affecting regulatory elements that influence clonal expansion of HSCs carrying MPN driver mutations. The rationale for this project is that the HSC clones with most prevalent driver mutation found in MPN, JAK2V617F show individual specific growth rates and can develop into MPN or remain as clonal hematopoiesis without any consequences indicating that germline genetic factors influence this process. The central hypothesis will be tested by pursuing two specific aims: 1) To determine the mechanisms by which genetic variation at the GFI1B locus influences MPN predisposition in vivo. 2) To define upstream transcriptional mechanisms disrupted by common genetic variants that predispose to MPN. Under the first aim, a newly generated mouse model will be used to evaluate clonal expansion of JAK2V617F HSCs in the context of a germline Gfi1b enhancer deletion by in vivo competitive transplantation assays. The murine studies will be complemented by an assessment of Gfi1b allele specific clonal expansion in primary human hematopoietic stem and progenitor cells (HSPCs) engineered to carry JAK2V617F mutation. Mechanistically activated mitochondrial respiration will be examined in germline enhancer inactivated JAK2V617F HSPCs in murine models and human patient samples. For the second aim, perturbation of RUNX1 bound cis-regulatory elements by MPN risk variants will be evaluated as a mechanism of clonal expansion in MPN by using lentiviral reporter assays and endogenous CRISPR/Cas9 editing approaches in primary human HSPCs and degron tagged RUNX1 cell lines. A Runx1 haploinsufficiency mouse model will be used to assess global influences of RUNX1 transcriptional network on MPN initiation. Collectively, our proposed studies aim to bridge the gap between inherited genetic variations and the clonal expansion dynamics of MPN stem cells, shedding light on crucial factors influencing disease development. The mouse models proposed in this study provide the in vivo physiological context and functional readouts required to investigate HSC clonal expansion and MPN pathogenesis.

Increasing Lung Cancer Screening Uptake Among High-Risk Emergency Department Patients

PROJECT SUMMARY/ABSTRACT Lung cancer is the leading cause of cancer death in the US. Although lung cancer screening (LCS), using low- dose CT scan, decreases lung cancer mortality through early disease identification, fewer than 1 in 6 eligible individuals get screened, with significant differences based on demographic and socio-economic factors. LCS is a process, not just a test. The critical first steps in this process are (1) identification of high-risk individuals who are eligible for LCS, and (2) recruitment of these individuals into an LCS program. The Emergency Department (ED) setting is optimal for an intervention to promote LCS by accomplishing these steps. Individuals at high risk for lung cancer are over-represented in the ED population, including: individuals that smoke, non-White individuals, patients with lower education levels, and the under-insured. In fact, over 2.3 million high-risk people pass through EDs every year who are eligible for LCS but have never been screened. The investigators’ long-term goal is to develop a low-cost, scalable intervention that increases LCS uptake among ED patients and is deployable in any ED with a regionally referrable LCS program. The objective of the proposed randomized clinical trial is to test the efficacies of text messaging and a facilitated referral strategy to promote uptake of LCS in order to achieve this goal. Step 1 of the approach is to identify participants that are eligible for LCS. Step 2 is to randomize eligible participants, using a 2x2 design, among four study arms: (1) basic referral for LCS (i.e. verbal referral with written materials; comprising an enhanced control arm), (2) basic referral plus a subsequent series of text messages, grounded in behavioral change theory, aimed at generating intention and motivation to get screened, (3) facilitated referral for LCS (i.e. submission of a requisition to LCS program by staff), and (4) facilitated referral plus text messages. The investigators’ pilot work demonstrated the feasibility and efficacy of the proposed approach. A total of 1036 individuals eligible for LCS will be recruited from a high-volume urban ED and a low-volume rural ED, randomized among study arms, and followed-up at 120 days to assess interval LCS uptake. The Specific Aims of the proposed project are, (1) Compare LCS program uptake among study arms that receive text messages to study arms that do not, (2) Compare LCS program uptake among study arms with basic referral to study arms with facilitated referral, (3) Investigate the interaction between receipt of text messages (yes/no) and referral type (basic/facilitated), and (4) Evaluate participant feedback on (a) differential barriers to LCS across sub-groups and (b) acceptability and appropriateness of ED-based promotion of LCS. The study team is at the forefront of developing ED-based interventions to promote cancer screening. This project leverages the universal access setting of the ED to identify individuals at greatest risk for lung cancer and get them screened. A scalable ED-based intervention that increases LCS uptake would save lives.

Mentoring investigators in patient-oriented research on HIV and public health

PROJECT SUMMARY/ABSTRACT Despite marked progress in treatment and prevention, HIV remains a significant public health threat in the US and globally. Innovative strategies are needed to effectively deploy interventions and reduce HIV incidence, which requires a sustained and committed workforce. Dr. Dennis is an infectious disease physician and researcher at the University of North Carolina (UNC) at Chapel Hill, Division of Infectious Diseases. She seeks the protected time of the K24 award to ensure adequate time and effort to provide mentorship in patient- oriented HIV research focused on applied public health strategies. Dr. Dennis has a track record of performing high-quality patient-oriented research supported by independent funding. Her research bridges basic, clinical, and epidemiologic science by using HIV-1 molecular epidemiology and phylogenetics to understand HIV transmission at the population level and to use this information to direct prevention. She has expanded this work to optimize strategies to detect and respond to HIV networks using mixed-methods approaches. The overall goal of this work is to uncover the links between these sub-epidemics - which are overlapping sub- epidemics defined by risk groups, geography, social interaction - to facilitate the design of timely, effective interventions. The research specific aims are 1) Investigate HIV transmission networks using molecular epidemiology and phylodynamics (R01AI135970), 2) Evaluate uptake of HIV treatment and prevention services in public health with social network approaches (supported by R01AI169602), and 3) Pilot a network-based characterization of early syphilis infections to inform strategies to increase the uptake of injectable antiretrovirals for HIV treatment and prevention (supported by K24). With the support of the K24, she will leverage resources at UNC to support mentorship and professional development to strengthen new directions (implementation science, community-engaged research). Dr. Dennis is deeply committed to expanding her mentorship and dedicated to fostering diverse mentees with lived experiences that are critical for sustaining the HIV workforce. Dr. Dennis is Co-Director of the UNC Center for AIDS Research (CFAR) Scientific Working Group which focuses on Ending the HIV Epidemic efforts in North and South Carolina. She has strong institutional support and a multidisciplinary team of advisors, including the UNC CFAR, and is an advisor on the UNC T32 HIV/STI institutional training program. She has collaborated for the past 10 years with NC Division of Public Health and with multiple investigators and trainees at the UNC Gillings School of Public Health. She is active in the UNC Infectious Diseases Fellowship program, providing clinical and research mentorship to numerous ID fellows. Her clinical activity provides practical grounding and relevance in patient-oriented research. The K24 will provide 50% of Dr. Dennis’ salary and additional funds to support mentees’ research. The proposed research is timely and aligned with the National HIV/AIDS Strategy and will support the protected time needed to mentor the next-generation of investigators in HIV patient-oriented research.

Baby Toolbox Training and Certification Program

PROJECT SUMMARY Our objective is to improve early childhood outcomes and support the expansion of the NIH Infant and Toddler Toolbox (Baby Toolbox) by providing comprehensive training support to those interested in using it. The Baby Toolbox is a brand new, nationally-normed assessment for infants 1-42 months, commissioned by NICHD and released for public use in 2025. The Baby Toolbox is administered entirely on an iPad and includes 35 measures across six domains using novel technology (e.g., gaze tracking, automatic scoring, computerized adaptive testing). It has the potential to bring harmonization to the developmental fields, but in order for it to become a common currency for developmental research as envisioned, researchers need to know how to administer it and how to train others to administer it. We propose an education program that will include a week-long training workshop, certification activities, and post-workshop support to create expert cohorts of Baby Toolbox test administrators. Individuals who attend the workshops can become certified test trainers, capable of training others at their home institutions to administer the assessment thus creating a self-sufficient training model. Through the proposed educational program, we will provide funding to cover lodging, meals, and incidentals during the workshop, in addition to subsidizing transportation to/from the workshop and provide a one-year subscription to the Baby Toolbox. A portion of slots will also be set aside for those without current grant funding. Our team is highly qualified to complete these tasks because we have led the effort to develop the Baby Toolbox assessment and have already completed multiple training workshops for contract deliverables. This grant would continue the efforts started by the NICHD in funding the Baby Toolbox by helping support its rollout, implementation, and growth. To meet these goals, we have the following aims: Aim 1: Create cohorts of trained Baby Toolbox examiners who can catapult the Baby Toolbox into widespread use by hosting a comprehensive week-long education program (training workshop) yearly for individuals to learn how to administer and train others to administer the Baby Toolbox, Aim 2: Expand the use of the Baby Toolbox by recruiting and financially supporting individuals who will bring the Baby Toolbox into a variety of research and clinical settings. Aim 3: Build a virtual training resource of videos and materials to support ongoing fidelity checks with certified trainers, and future training efforts.

Optimizing CD45-Targeted Astatine-211-Radioimmunotherapy for Malignant and Non-Malignant Blood Disorders

ABSTRACT CD45 is expressed on almost all normal and neoplastic hematopoietic cells but not on non-blood cells and has, therefore, been pursued as a drug target. Initially centered on augmenting conditioning before hematopoietic cell transplantation (HCT) for blood cancers, there is increasing interest in expanding CD45-directed therapies into other settings, with radioimmunotherapy (RIT) being the major therapeutic modality so far. Investigators at our institution pioneered CD45 RIT with b-emitters such as iodine-131 (131I) using the murine monoclonal antibody (mAb), BC8. A phase 3 trial testing 131I-BC8 (131I-apamistamab [Iomab-B]) with allogeneic HCT in older adults with relapsed/refractory acute myeloid leukemia showed improved outcomes over conventional care, validating this approach. More recently, attention has shifted toward a-emitters that deliver substantially higher decay energies over much shorter distances than b-emitters, rendering them more suitable for precise and potent target cell killing. In our work, we focus on astatine-211 (211At) for its ideal half-life and decay without a-emitting daughters. For clinical application, mAbs are conjugated with the bifunctional boron cage molecule, isothiocyantophenethyl-ureido-closo-decaborate(2-) (B10-NCS), to enable stable protein astatination. Three early-phase trials testing 211At-BC8-B10 as augmentation of HCT conditioning for patients with malignant and non-malignant blood disorders are ongoing, with emerging data indicating significant anti-tumor efficacy. Nonetheless, relapses still occur. Other important limitations include marked infusion toxicities and human antimouse antibody (HAMA) responses related to the murine nature of BC8 and dimer formation after 211At labeling of mAb-B10 conjugates with tissue residualization from 211At atom oxidation. The latter may contribute to the risk of liver cell injury, the dose limiting extramedullary toxicity of CD45 RIT. As a first step toward our goal of optimizing CD45 RIT, we have raised new, fully human CD45 mAbs as basis for novel therapeutics. In preliminary in vivo studies in immunodeficient mice, we found some of these mAbs to have greater anti-tumor efficacy than a humanized version of BC8 (HuBC8) we generated as a reference mAb. We will now conduct comparative in vivo CD45+ cell targeting (“biodistribution”) and anti-tumor efficacy studies to select a lead candidate mAb for clinical application and use protein engineering to maximize the selectivity and efficacy of targeted radiation delivery. We will use immunodeficient mice xenotransplanted with human leukemia cells for this purpose as no human approaches are available and in vitro testing is inadequate to measure both the targeting and biologic RIT effects on human leukemia cells. Mice provide the in vivo milieu needed for comprehensive evaluation. Development of improved mAb astatination methodologies to minimize off-target toxicities of 211At-RIT will further increase therapy specificity and reduce toxicity. In parallel, we will conduct genome-scale, unbiased target identification/validation studies to identify partner drugs for rational combination therapies aimed at enhancing the anti-tumor efficacy of 211At-CD45 RIT.

Improved Surgical Visibility and Navigation during Endoscopic Treatment of Upper Tract Urothelial Carcinoma

Project Summary The importance of localizing and treating all upper tract urothelial cancer (UTUC) tumors during a renal sparing, endoscopic treatment is emphasized by the high risk of cancer progression from inadequate tumor treatment. Insufficient treatment necessitates kidney and ureteral removal (i.e., nephroureterectomy). Nephroureterectomy permanently compromises renal function, and increases morbidity and mortality, while negatively impacting a patient’s quality of life. In contrast, endoscopic treatment (i.e., using a laser to ablate only the tumors) improves long-term outcomes by sparing healthy kidney tissue. However, endoscopic treatment is underutilized compared to nephroureterectomy because it is difficult to accomplish. Successful endoscopic treatment is dependent on the surgeon’s ability to create a mental 3D map of the branched, intrarenal endoscopic anatomy intraoperatively from preoperative 2D imaging, which is extremely difficult. Since mental mapping relies on hand-eye coordination, memory, and spatial reasoning, it is inherently imprecise and its impact on accuracy and tumor treatment is dependent on the surgeon’s experience. To make matters worse, even when tumors are successfully visualized, the surgeon often cannot accurately assess the location of tumor margins or infer pathologic grade due to the limited field of view and depth of field (10mm and 6mm on average, respectively) of current scopes. The scopes only provide visualization of a small part of the surgical field at any instant. These inherent challenges prevent many surgeons from attempting endoscopic tumor treatment since incomplete treatment leads to a devastating, oncologic outcome. Our overall goal is to create an enhanced visualization and navigational system that makes endoscopic UTUC tumor treatment easier and more accurate for all surgeons, enabling wider utilization. Toward this goal, our specific objective in this proposal is to test the hypothesis that our system can make endoscopic UTUC surgery more accurate and efficient. To test this hypothesis, we propose three Specific Aims: Aim 1 involves the development of an automatic, real-time segmentation and grading system of UTUC tumors during endoscopic treatment. Aim 2 integrates a 3D navigational map of collecting system anatomy, which includes tumor and endoscope location, during endoscopic surgery. Aim 3 evaluates the system in patients, with zero risk to the human subjects. The endpoint of this R01 will be a fully validated enhanced visualization and navigational system for endoscopic UTUC surgery, which would provide the necessary experimental data towards a large-scale, multi-center clinical trial and future FDA approval. As our system would require only software integration to current endoscopic surgical cameras, all existing endoscopic surgical systems could in principle immediately benefit from the results of this project. In this way, we believe the success of our project will facilitate improved UTUC treatment and mitigate progression to a higher risk extirpative surgery.

Pilot and Feasibility Program

PILOT AND FEASIBILITY PROGRAM: PROJECT SUMMARY The goal of the Cedars-Sinai Digestive Diseases Research Center (CSDDRC) Pilot and Feasibility (P&F) Program is to provide monetary support, expertise, and technical support to advance innovative basic, translational, and clinical research that matches the overall goal and themes of the Center. The central theme of the CSDDRC is mechanisms and measurements of the fibroinflammatory response in gastrointestinal (GI) tissues, which reflects Center members’ research in three subthemes: 1) Gut Microbiome, 2) Gastrointestinal (GI) and Liver Metabolism, and 3) GI and Liver Injury. The mission of CSDDRC P&F Program is to support new investigators, established investigators who are new to digestive and liver disease research, and established digestive and liver disease investigators who want to start new or collaborative research that promises to lead to a paradigm shift in the digestive diseases field. In partnership with the Enrichment Program, we will provide guidance for P&F awardees in the form of mentorship and collaboration opportunities. The CSDDRC Biomedical Research Cores will also support P&F awardees, facilitating rapid progress of their new and collaborative digestive and liver disease research. The P&F Program’s outcome measures will include the number of high-impact research publications, grant applications, and subsequent extramural funding for P&F awardees. We will accomplish our goals through the following three specific aims. Aim 1 will solicit research proposals from P&F candidates whose proposed research aligns with the central theme and the subthemes of the CSDDRC. We will advertise P&F support widely across campuses, in addition to contacting department/institute directors to solicit their recommendations for promising young and established investigators who are interested in working in digestive and liver diseases. Aim 2 will select pilot project applications that meet CSDDRC P&F Program goals using rigorous review criteria. Each year, the P&F Program will select four pilot projects to be funded by the P30 grant and matched by institutional support. Submitted applications will be peer- reviewed and preliminarily scored based on the NIH review format by three local expert reviewers. Subsequently, after oral presentations by the P&F applicants, the External Advisory Board (EAB) members will undertake a second round of review, scoring, and discussion at the P&F Program Review meeting following the CSDDRC Annual Symposium. Funding decisions will be made during the P&F Program Review meeting. Aim 3 will assist P&F project investigators with career development and obtaining extramural funding for digestive disease research. P&F awardees will benefit from the Enrichment Program’s well-organized mentoring structure, led by experienced members of the CSDDRC, which includes the Grants-in-Progress Mentoring Program, Gastrointestinal Research-in-Progress meetings, and grant application workshops. P&F awardees will also be mentored through direct interactions with P&F Program Directors, Core Directors, members of the Internal Advisory Board and EAB, and individual or collaborative mentor teams.

Transcriptional control of activation induced deaminase (AID) function

SUMMARY Somatic hypermutation (SHM) and class switch recombination (CSR) are vital for the generation of high affinity antibodies with appropriate effector function, protection against infection, and vaccine efficiency. They are initiated when the activation induced deaminase (AID) deaminates cytidines in single-stranded DNA in the context of transcription by RNA polymerase 2 (Pol2). Aberrant DNA deamination by AID is an important driver of genetic instability and the development of B cell malignancies. Understanding the factors and mechanisms that coordinate AID-mediated deamination with Pol2 transcription is an important objective in the study of humoral immunity and the central goal of research under this grant. Our preliminary data demonstrate that Pol2 pause factor NELF, Super Elongation Complex (SEC) components MLLT1/3, and the phosphatase module of the Integrator-protein phosphatase complex (INT-PP2A) are required for SHM, with MLLT1/3 but not NELF being required for AID binding to its chromatin targets. Our findings yield a new conceptual framework and model for AID-Pol2 collaboration in which NELF and a balance between kinase and phosphatase activities of SEC and INT-PP2A regulate Pol2 pausing/elongation to generate the critical stalled Pol2 complex on which AID acts. Further, our work has yielded major methodological advances that allow us to overcome obstacles that have stymied progress in the field. In this proposal, we take advantage of these conceptual and technical advances to pursue our central goal through the following two aims: Aim 1: Determine the molecular mechanisms by which NELF and other Pol2 regulatory factors enable AID-Pol2 collaboration and SHM/CSR. It has previously been very difficult to assess the role of cell-essential factors in SHM. By combining our new Rapid Assay for SHM (RASH) cells with degron technology, we will determine the mechanism of action of our newly discovered regulators of SHM using genomic, transcriptomic, and interaction assays that assess Pol2 distribution, phosphorylation, and activity, and the chromatin binding profiles of and interactions between AID and components of NELF, SEC, and INT-PP2A. AID and MLLT1 appear to co-associate in a complex and we will test for a direct interaction between AID and MLLT1/3. Factors will be tested for roles in CSR and validated in human cell line and germinal center B cell models and in mice. Aim 2: Hypothesis testing and deep mechanistic analysis through perturbation of the balance between Pol2 pause/arrest and elongation. We will rigorously test our new model for AID-Pol2 collaboration using degron, reconstitution, mutagenesis, and small molecular inhibitor approaches to perturb the balance between Pol2 pausing and elongation, revealing how altering NELF-Pol2 interactions and the balance between SEC kinase and INT-PP2A phosphatase activities influences SHM efficiencies and AID binding. Together, our proposed studies are significant for the development of new technologies and for understanding mechanisms of antibody gene diversification and causes of genome instability and cancer.

Systems Biology of Early Atopy: Role of Human Milk (SunBEAm-Milk)

Surprisingly little is known about the effect of breastfeeding (BF) on infant immune system development besides an effect on the gut microbiome, but its impact on metabolites and Tregs could support protection against food allergy (FA). BF is currently recommended to prevent the development of allergic diseases, especially asthma/recurrent wheezing and AD in early childhood, but firm conclusions could not be drawn regarding FA due to high heterogeneity and low quality of studies. Reverse causation, recall bias and the poor accuracy of outcome assessment are significant limitations. Most are inadequately powered to specific FA; however, a recent study showed that exclusively BF infants had lower odds of egg, sesame, and peanut allergies. Importantly, immunomodulatory composition of HM varies between mothers, which has not been taken into consideration. For over two decades we have been developing methods to assess immunomodulatory factors in the complex matrix of HM and their association with infant FA. We have shown that high levels of HM total and specific IgA are associated with protection against cow’s milk allergy, but it is unclear whether HM IgA is responsible for or is a biomarker of the vertical transfer of protection. Infant fecal and systemic IgA levels during breastfeeding and after weaning are also elevated in infants at low risk for atopic disease raising the question of whether HM factors such as cytokines can promote IgA production in infants. Consistent with this, we showed that HM cytokines, such as APRIL, induce IgA production in naïve infant B cells, and infants receiving HM with higher levels of APRIL had lower incidence of allergic disease. Finally, lower levels of several HM fatty acids including short-chain fatty acids and DHA were associated with FA. While some these factors were are associated with maternal atopic disease, several of them are not and suggest a role for diet instead. The System Biology of Early Atopy (SunBEAm) population-based cohort of 2500 mother-infant pairs is >50% recruited and provides an unprecedented opportunity to assess association of HM feeding and immune factors in HM with development of infant immune system and FA/AD. The Common Sample comprises a subset of 100 dyads with FA, 100 with FA+AD, 100 with AD, 100 with no FA or AD and more extensively profiled biological data. Utilizing all 2-month HM samples available in the Common Sample, we will assess levels of immune factors in HM and their association with maternal/infant characteristics (Aim 1). Utilizing data from the whole cohort, we will assess the association between HM vs formula feeding on well-defined FA/AD further adjusted based on high vs low levels of HM immune components in the Common Sample (Aim 2b). Finally, we will examine the immune cell and epithelial effects of HM on infant immune markers and intestinal organoids (Aim 3). Key findings will be validated in an independent birth cohort. The ultimate goal is to uncover protective properties of BF and HM in FA and subsequent design of policies and prevention strategies to address the increasing rates of FA.

Behavioral, Implementation & Community Sciences Core

PROJECT SUMMARY: BEHAVIORAL, IMPLEMENTATION, AND COMMUNITY SCIENCES (BICS) CORE Like many US jurisdictions, New York City (NYC) is not on track to achieve 2030 End the Epidemic (EHE) 95- 95-95 goals. By the end of 2023, 95% of people with HIV (PWH) in NYC had been diagnosed with HIV, but only 88% of those were in HIV care, and of those, only 80% were virally suppressed. Further, in 2022, only 40% of individuals estimated to need PrEP were prescribed it. Highly efficacious biomedical HIV treatment and prevention interventions have the potential to end the HIV epidemic, but only if they are accessed and used. Yet, behavioral, social, and structural determinants of real-world adoption as well as population-level impact of HIV prevention, care, and treatment innovations have not been addressed adequately for individuals or communities. Meeting EHE goals will depend on behavioral, implementation, and community sciences research that identifies factors contributing to these outcomes, informs interventions to address them, and ensures that communities affected by HIV are engaged throughout the research process. The Behavioral, Implementation, and Community Sciences (BICS) Core will facilitate such rigorous, innovative research by Columbia University (CU) and Weill Cornell Medicine (WCM) investigators – particularly early career investigators (ECIs) and those new to HIV research – to help achieve EHE 2030 goals. The BICS Core will support the use of relevant theories, methods, and analytic approaches to advance the integration of context-specific behavioral, implementation, and community sciences perspectives across the research continuum – from basic research through scale-up and sustainment of evidence-based interventions. The Core has three Aims: (1) Behavioral science: To support CFAR users in developing, selecting, and integrating behavioral science methodologies across the research continuum; (2) Implementation science: To support CFAR users in designing and conducting implementation studies and related health services research and (3) Community science: To facilitate rigorous community-based participatory research across the research continuum to strengthen and sustain stakeholder engagement that will optimize research translation and impact. Led by Core Co-Directors Robert Remien and Bruce Schackman and Core Associate Directors Delivette Castor, Shashi Kapadia, and Justin Knox, the BICS Core will use multiple approaches to achieve each of these aims, including substantive scientific consultations on proposed or ongoing research; access to resources and tools; and seminars and educational activities that promote integration of these methods into EHE research. The Core, thus, will support CU-WCM CFAR investigators and outside collaborators – including ECIs and investigators new to HIV research – to advance local and national EHE goals.

Neural circuits for disinhibition in the cerebellum

ABSTRACT Our long-term goal is to understand how the cerebellum adapts and improves movements in response to motor errors. A critical component of this process is signaling from olivary climbing fibers that, by providing strong excitatory drive onto Purkinje cells, induces long-term synaptic plasticity to instantiate corrective adjustments in motor behavior. However, this signaling process is tightly regulated by molecular layer interneurons (MLIs). By strongly inhibiting Purkinje cells, MLIs oppose climbing fiber-driven excitation and gate the induction of corrective plasticity. Thus, for error-driven climbing fiber-induced plasticity and learning to occur effectively, Purkinje cells must undergo disinhibition through the suppression of MLI-mediated input. Notably, MLI ensembles are composed of several subtypes and have a highly structured interconnectivity and are responsive to convergent climbing fiber inputs, suggesting that climbing fiber synchrony- whose functional significance is poorly understood- can selectively engage MLI networks to alter the state of Purkinje cell inhibition. This engagement may balance inhibition and excitation of Purkinje cells during motor errors, creating a circuit mechanism conducive for the acquisition of adaptive learning. The objective of this proposal is to determine how distinct MLI circuits are organized to modulate Purkinje cell excitability through disinhibition in a context-dependent manner, enabling plasticity and learning in response to motor errors. We will employ functional recordings, circuit-targeted activity manipulations, and behavioral analysis to reveal how error-driven instructive signaling emerges from these circuits. In the first aim, we will use in vivo high-density electrophysiology to map functional interactions among MLIs, climbing fibers, and Purkinje cells in the flocculus during the vestibulo-ocular reflex. We will test whether, during motor errors, climbing fibers synchronize their firing to selectively engage disinhibition of Purkinje cells through MLI subtypes in adapting versus non-adapting contexts. In the second aim, we will combine acute slice recordings and molecular anatomy to define direct versus spillover climbing fiber synapses onto MLI subtypes. We will identify synaptic markers and measure climbing-fiber-evoked currents in MLI subtypes, revealing how structural connectivity supports rapid, subtype-specific circuit engagement. In the third aim, we will determine how long-range inputs to the inferior olive, specifically inhibitory projections from the vestibular nuclei, dynamically tune climbing fiber synchrony in vivo and thereby learning through differential engagement of disinhibitory MLI networks. Using functional recording and optogenetic manipulation during the vestibulo- ocular reflex performance, we will establish causal links between climbing fiber synchrony, MLI network state, and adaptive behavior. By fully understanding the logic of instructive signaling, emergent from cerebellar circuit organization and behavioral engagement, we will advance our knowledge of cerebellum-dependent learning processes and provide broader insights into the neural mechanisms of learning and adaptation more generally.

Cytoskeletal connectors: Deciphering the fundamental mechanisms of cytoskeletal dynamics and transport

PROJECT SUMMARY The cytoskeleton is a dynamic network of filamentous structures, including microtubules and actin, that regulate essential cellular processes such as cell shape, growth, and signaling. Cytoskeleton also serves as tracks for molecular motors, which transport a variety of cellular cargoes, including organelles, macromolecules, and vesicles. These cargoes are linked to motors by specialized connector proteins. Disruptions in connector proteins are implicated in a range of neurodevelopmental and neurodegenerative diseases, as well as cancers. Despite their importance, these proteins continue to be understudied, primarily due to their perceived role as passive linkers and the technical challenges in working with them. However, recent discoveries suggest that connector proteins may play more active roles, in some cases even have enzymatic functions. This proposal aims to uncover mechanisms of connector protein functions through a detailed investigation of actin-microtubule and motor-cargo interactions. Actin and microtubules are linked by the spectraplakin family of large and evolutionarily conserved proteins, critical for neuronal development and differentiation. Recent discoveries of ATPase domains within these proteins suggest they may haves beyond simply linking cytoskeletal components. One goal of this proposal is to investigate the role of spectraplakin’s ATPase domains via structural, biochemical, and cell biology approaches. Another goal is to explore how dynamic changes in motor-cargo connectors facilitate the transport of diverse cargoes along microtubule tracks. The focus will be on the cytoplasmic dynein-1 (dynein) and the connectors (adaptors) that activate and link dynein to cargo. Dynein is a microtubule minus-end directed motor that plays essential roles in cell division, and transports hundreds of different cellular cargoes. While several motor-cargo connectors have been identified, the regulatory mechanisms enabling cargo transport are not fully understood. We are investigating whether connector proteins work together to activate dynein movement and/or facilitate cargo handoff between different dynein complexes. Using innovative approaches, including time- resolved cryo-EM, complex in-vitro reconstitutions, and live-cell imaging in induced neurons, we are uncovering critical mechanisms that govern cytoskeletal connector proteins, furthering our understanding of how the cytoskeleton regulates essential cellular processes.

Examining the foundations of reading comprehension: a longitudinal study of brain and behavior starting in infancy

SUMMARY Reading comprehension (RC) is one of the most complex skills that we utilize daily and is crucial for functioning in modern society, but despite its significance for academic achievement, employment prospects, and mental health, many children and adults do not exhibit proficient RC abilities. New theoretical models aiming to explain variability in RC suggest a dynamic interplay and co-development among ‘precursor’ foundational and cognitive- linguistic skills, interacting with environmental and socio-ecological factors across the developmental timeline of learning to read. Behavioral and neuroimaging studies in school-age children have demonstrated critical mechanistic support for these multifactorial RC models by identifying the developmental trajectories of precursor skills and further showing that brain areas, tracts, and networks typically underlying language and cognitive skills are also involved in RC. Nevertheless, the precursor skills that support RC start developing in infancy and the brain correlates underlying these precursors begin to develop in utero, which suggests that typical and atypical RC developmental trajectories could diverge long before school age. As such, examining RC development using a multifactorial, longitudinal approach that includes brain and behavior starting in infancy is critical for developing theoretical frameworks that can inform early preventative and intervention strategies. Here, we propose a comprehensive longitudinal study of RC development in which we examine direct and indirect effects on RC from brain, behavioral, familial risk, and environmental data from infancy to adolescence. To achieve this goal, we will combine two existing longitudinal cohorts, one ranging from infancy to late childhood (n = 174) and the other from preschool to early adolescence (n = 137). By applying state-of-the-art pediatric neuroimaging analyses, multiple indicator growth model structural equation models, and an innovative behavior- brain co-development measurement index to this unique, combined dataset, we will be able to identify brain and behavioral measures in infancy that directly and indirectly support subsequent RC development (Aim1). We will further characterize how longitudinal trajectories of behavioral measures as well as brain structure, function, and white matter organization contribute to RC development and how familial risk and environmental factors shape these trajectories (Aim 2). Finally, we will examine how the co-development of brain and behavior, as measured with an innovative co-development index, relates to subsequent RC (Aim 3). If successful, we will contribute the first multifactorial longitudinal model of RC development comprising direct and indirect effects from brain, behavior, brain-behavior co-development, familial risk, and environmental measures beginning in infancy. Understanding RC development using a multifactorial longitudinal lens will be crucial for building theoretical models and developing experimental designs focused on early preventative and intervention approaches long before the start of formal schooling.

Circulating extracellular vesicles as functional indicators of maternal mental and physical health in pregnancy and postpartum

Women with high levels of adverse childhood experiences (ACEs) are at significantly greater risk for negative health outcomes in pregnancy and postpartum, including gestational diabetes, PTB, and depressed mood. However, we still lack biomarkers or a sufficient understanding of causal mechanisms. Extracellular vesicles (EVs) are one of the most dynamic and abundant biological signals secreted into maternal circulation, largely produced by the placenta – where levels increase 4-5-fold during pregnancy. Similarly, removal of the placenta at delivery produces a dramatic drop in maternal EV concentration. Across species, we and others have identified significant EV changes during pregnancy associated with homeostatic regulation, including glucose and glucocorticoid levels, supporting key roles for EVs in maternal health. However, longitudinal studies in human pregnancy and postpartum have not been conducted. We know little as to the mechanisms controlling EV secretion or the roles for EVs in maternal pregnancy and postpartum health. Our decade’s long work identified the X-linked gene, O-glycosyltransferase (OGT), in mouse and human placenta as a master gage of the maternal milieu, where OGT regulation of annexin A1 (AA1) is key to EV cargo loading and secretion from the placenta. We recently reported that placental OGT levels positively correlate with maternal EV concentration. How this association may contribute toward postpartum health, including regulating maternal stress physiology and mood in humans is not known. We hypothesize that increased ACEs, similar to stress in preclinical models, are negatively associated with a cell’s ability to secrete EVs important to maintain homeostasis in the face of the challenges of pregnancy and postpartum, producing an increasingly unhealthy state. Therefore, the goals of these proposed studies in both mice and humans are as follows: 1) To identify cellular mechanisms involved in EV secretion important to maternal health outcomes utilizing the placenta as a tool to genetically target OGT in mice and examine maternal homeostatic control related to EV concentration and composition during pregnancy; 2) To examine the functional ability for a dynamic elevation in maternal EV concentration to improve homeostatic regulation in pregnancy and postpartum using chemogenetic activation (DREADDs) of placenta trophoblast cells in pregnancy, and by EV transfer by tail vein injection postpartum; and 3) To examine in women changes in maternal EVs in a longitudinal pregnancy and postpartum study in association with maternal glucose and cortisol changes, we will examine markers of physical (glucose challenge test), HPA stress (hair cortisol & stress- stimulated salivary cortisol) and psychological (Hamilton Rating Scale for Depression, Perceived Stress Scale) health across pregnancy and the postpartum period in 150 healthy women with varying degrees of exposure to ACEs as measured using the ACE Questionnaire (ACE-Q).

Maternal Depression and Antidepressant Effects on Fetal Brain Structure and Function (FABMOMS)

PROJECT ABSTRACT Major depressive disorder (MDD) is one of the most common diseases in childbearing women, with a prevalence of 12.7% in pregnancy and 21.9% the year after birth. Exposure to maternal stress and depressive symptoms alters fetal/infant neurodevelopment, functional brain connectivity, and networks implicated in stress processing. About 5% of pregnant women are prescribed a serotonin selective or serotonin norepinephrine reuptake inhibitor (collectively, SRI). Remission of maternal MDD is crucial to the health and functioning of the mother and family. In observational studies typical of this field, differentiating the effects of drug exposure on offspring from the sequelae of the underlying psychiatric disease, both physiological and psychosocial, is challenging. Substantial progress has been made using sophisticated study designs and analytic approaches with large pregnancy cohorts that reduce the risk of spurious associations. Increased rates of overall and cardiac defects, stillbirth, preterm birth, and fetal growth have been largely explained by confounding by factors associated with both MDD and these outcomes rather than SRI exposure. Assessing the neurobehavioral development of children exposed in utero to SRI is the current research priority in this field. Our team pioneered the development of novel and safe fetal and neonatal quantitative magnetic resonance imaging (qMRI) tools, which will be combined with an evaluation of maternal heart rate variability to explore associations between exposures to stress, psychiatric symptoms and SRI on fetal and neonatal brain structure and function. The overarching goal of this project is to evaluate the separate and interactive effects of exposure to antidepressants in utero and maternal MDD on fetal and infant brain structure and function, with a specific focus on the hippocampus. We will accomplish this by evaluating four groups of pregnant women who have: 1) MDD treated with SRI to remission), 2) MDD treated with SRI (non-remitted, with both depressive symptom and SRI exposure), 3) MDD untreated with antidepressants, and 4) no current MDD or SRI treatment. Maternal assessments will occur at intake and in the early third trimesters and in then newborn period (at the time of fetal/newborn MRI) after birth. Maternal and infant evaluations will continue at 6 and 12 months postpartum. Maternal psychosocial and psychiatric status will provide extensive data on the context in which mothers experience pregnancy and infant care and allow adjustment for factors that will inevitably differ across groups. Lastly, we will explore the effects of maternal choline on MDD and offspring brain development. As these exposures and neurodevelopmental studies are conducted, exploring primary preventive strategies is a public health imperative. We will explore a potential mediator, poor maternal choline intake, a modifiable risk factor for both maternal MDD and altered fetal hippocampal growth and infant neurobehavior.

TAR RNA binding to INI1/SMARCB1 and its role in HIV-1 transcription and latency reactivation

Abstract The goal of this application is to study the role of interplay between the components of chromatin remodeling SWI/SNF (BAF complex) and HIV-1 transcription machinery, focusing on the interaction of a BAF component, INI1 (Integrase Interactor 1) with TAR RNA. HIV-1 reservoirs are a mixture of latent cells harboring proviruses silenced at transcriptional level. Cure strategies need a deeper understanding of HIV-1 transcriptional regulation. HIV-1 transcription, initiated by RNA Pol II, pauses producing short TAR transcripts. pTEFb recruitment to TAR by Tat overcomes this transcriptional pause, facilitating elongation. Beyond Tat, the action of chromatin remodeling complexes (CRCs) is required to facilitate elongation. The BAF complexes CBAF and PBAF play distinct roles. While CBAF represses proviral transcription by maintaining nucleosomes in an unfavorable state, PBAF remodels nucleosomes to facilitate elongation. INI1 is a component of both CBAF and PBAF, and its role in transcription is not fully understood. INI1 was identified as a binding partner for HIV-1 integrase (IN) and exerts multifacted roles in virus assembly, production and morphogenesis. INI1 has multiple functional domains. IN binding Rpt1 domain structurally mimics TAR RNA & is necessary for late events. We have made a novel observation that another domain of INI1, the N-terminal Winged Helix DNA binding domain (WHD) specifically binds to TAR RNA and that this interaction is necessary for mediating HIV-1 transcriptional elongation. These exciting results suggest that different functional domains of INI1(Rpt1 and WHD) involved in “TAR RNA mimicry” or “TAR RNA binding” regulate distinct stages of replication. We hypothesize that INI1 WHD domain-TAR interaction is necessary for recruitment of PBAF to HIV-1 LTR for transcriptional elongation and latency reactivation. Disrupting this interaction results in transcriptional repression. We will investigate the role of this novel INI1:TAR RNA interaction in HIV-1 transcription and latency reactivation. This is a multi-PI application involving Drs. Kalpana (HIV-1 virologist), Heng (NMR biophysicist) and Zou (computational biologist/protein-RNA structure). In Aim 1, we will characterize INI1-WHD:TAR interaction in vitro and in vivo via molecular/genetic analyses (Kalpana/Heng). We will employ alanine scanning mutagenesis based on WHD NMR structure to test WHD:TAR interaction. We will use biophysical & biochemical approaches to probe TAR structural elements required for this interaction. In Aim 2, we will employ computational modeling and NMR to determine the structure of INI1- WHD:TAR RNA complex (Zou/Heng). In Aim 3, we will determine the role of INI1:TAR interactions in HIV-1 transcription, latency reactivation and mechanism of action (Kalpana). We will analyze the effect of TAR- Interaction-Defective (TID) INI1 mutants on transcription of LTR-reporters and full-length HIV in INI1-/- cells. Latent cells in which TID-INI1 mutants are knocked in (KI) will be used to assess effect on reactivation via RNA-FISH and qRT-PCR assays. Our studies will establish INI1:TAR interaction as a drug target. Inhibiting this interaction could block latency reactivation promoting deep latency and advancing cure strategies.

Protective efficacy and immunogenicity of a live attenuated Chlamydia strain

PROJECT SUMMARY The main goal of this project is to rigorously evaluate the immunogenicity and protective efficacy of a mutant, live attenuated Chlamydia trachomatis (CT) vaccine strain in an established nonhuman primate (NHP) model that accurately mimics many aspects of human CT infection. This work is highly significant, as CT is the leading cause of bacterial sexually transmitted infection and an important causative agent of morbidity in women. Although the development of an effective CT vaccine is an urgent medical priority, no approved vaccines exist and it is imperative to pursue new candidates. Historical evidence supports the vaccine efficacy of whole Chlamydia organisms in protecting the reproductive tract from reinfection, primarily using C. muridarum infections in a mouse model. Recent advances in Chlamydia genetic engineering now allow for the development of genetically attenuated strains which can be evaluated as live vaccines in preclinical models. We recently characterized a human-tropic CT mutant with a disruption in garD (CT∆garD); this mutant is sensitive to an intracellular, IFNγ activated defense mechanism and we demonstrated that this strain was attenuated in the female NHP genital tract. In a pilot vaccine efficacy study, we further demonstrated that immunization of macaques with CT∆garD was safe and elicited protection against subsequent challenge with wildtype CT. A unique feature of this strain is that it arrests at an intracellular stage and thus presents a broad array of desirable T and B cell antigens that are broadly conserved across circulating CT strains. We will first generate an improved genetically attenuated CT strain that harbors a clean deletion of garD, and we will subsequently genetically and phenotypically validate its attenuation phenotype. We will then conduct an immunogenicity and efficacy study in female macaques to determine the optimal dosing regimen of live attenuated CT for eliciting protective cellular and humoral immune responses, and also protective efficacy, against challenge with a wild type circulating clinical CT strain. These studies will investigate the potential for a live attenuated human tropic vaccine candidate in a macaque preclinical model and pave the way for greater understanding of immune correlates of protection against CT.

Mechanisms and consequences of cerebrovascular dysfunction in preeclampsia

PROJECT SUMMARY/ABSTRACT Preeclampsia (PE) is a common hypertensive disorder of pregnancy that causes significant maternal and fetal morbidity and mortality worldwide. PE women are at a high risk of stroke, including intracerebral hemorrhage, during the peripartum period, suggesting the sequelae of PE adversely impacts the cerebral circulation to promote hemorrhage. In addition, women with severe early-onset PE are at an 85-fold increased risk of death from intracerebral hemorrhage, importantly suggesting severity of disease promotes greater vulnerability of the cerebral circulation to degradation and rupture. However, the consequences of PE extend far beyond pregnancy and are associated with excessive cardiovascular and cerebrovascular disease risk later in life. Women with previous pregnancy complicated by PE can develop cognitive impairment as early as in their 30’s and 40’s, suggesting PE predisposes the brain to early-onset cognitive impairment. Studies have shown that formerly PE women have changes in gray matter volume and increased white matter lesion burden that occurs as a function of time from pregnancy, suggesting that PE continues to progressively damage the brain long after the affected pregnancy. Thus, our overall goal is to elucidate mechanisms by which women with PE are at risk of intracerebral hemorrhage in pregnancy and cognitive decline later in life. Our preliminary studies found greater vascular degradation, hematoma and cerebral edema in a model of severe PE that was associated with vascular inflammation and microglia activation (neuroinflammation). In addition, we found endothelial dysfunction and diminished neurovascular coupling in PE rats that persisted 5 months postpartum. Impaired neurovascular coupling is well-recognized as an underlying contributor to cognitive decline. These effects in postpartum animals with previous exposure to PE were associated with memory impairment that was not present in the pregnant state, suggesting neurovascular dysfunction precedes cognitive decline. Our central hypothesis is that the sequela of PE accelerates hypertension-induced cerebrovascular dysfunction that predisposes to intracerebral hemorrhage during pregnancy and its persistence postpartum results in early-onset cognitive decline. We will therefore elucidate mechanisms by which PE accelerates vascular degradation and worsens outcome from hemorrhagic stroke, probing pathways involved in oxidative degradative processes using multi-omics and multivariate analysis (Aim 1). We will also determine underlying molecular mechanisms that cause persistent cerebral microvascular dysfunction and cognitive decline postpartum, including oxidative stress-induced BBB leakage and persistent neuroinflammation that drives potassium channel dysfunction, reduced neurovascular coupling and neurovascular uncoupling (Aim 2). We will also use machine learning approaches together with multi-omics and outcome measures to identify factors and cellular pathways that are most impactful for prediction of intracerebral hemorrhage and cognitive impairment. The ability to predict and prevent devasting neurovascular disorders associated with PE has the potential to have long-lasting impacts on the lives of women with PE.

Role of stress signals in the pathogenesis of pulmonary veno-occlusive disease

PROJECT SUMMARY/ABSTRACT Pulmonary veno-occlusive disease (PVOD) is a subclass of pulmonary hypertension characterized by preferential remodeling of the pulmonary venules and capillaries, and currently, there are no efficacious drug therapies. The clinical presentations and the radiographic findings of PVOD are indistinguishable from PAH, and therefore, it is often misclassified as PAH. However, the application of PAH therapeutics to PVOD patients leads to life-threatening pulmonary edema, thus, there is a critical need for diagnostic methods that accurately differentiate PVOD from PAH. Genetically, PVOD is associated with biallelic loss of function (LOF) mutations in the EIF2AK4 gene encoding GCN2. GCN2 phosphorylates the alpha subunit of eukaryotic initiation factor 2 (eIF2α), shuts down protein synthesis, and activates the integrated stress response (ISR). However, the molecular mechanisms connecting the loss of GCN2 with pulmonary vascular remodeling are poorly understood. Recent studies find that biallelic EIF2AK4 mutations are identified in ~9% of PAH patients. Conversely, heterozygous mutations in the BMPR2 gene, a leading cause of PAH, have been reported in PVOD patients. These results suggest that (i) PVOD and PAH share some of the pathophysiological mechanisms, and (ii) the presence of EIF2AK4 or BMPR2 mutations does not provide an accurate genetic diagnosis for PVOD. The long-term goal of this proposal is to elucidate the pathophysiological mechanisms involved in remodeling not only pulmonary arterioles but also venules and capillaries and develop those pathways as potential therapies for POVD. It has been observed that cancer patients administered with the chemotherapeutic agent mitomycin-C (MMC) rapidly develop PVOD. Rats administered with MMC develop PVOD-like phenotypes, including right ventricular (RV) hypertrophy, increased RV systolic pressure, and pulmonary vascular lesions in arteries and veins. We found that Rad51, an essential enzyme for double-strand DNA break repair, associates with VE-Cad in the vascular endothelium; however, upon MMC treatment, Rad51 and VE-Cad complex (VRC) were released into the circulation, resulting in increased vascular permeability and reduced barrier integrity. MMC treatment also mediates the depletion of GCN2, which recapitulates the genetic cause of PVOD (LOF EIF2AK4 mutations). Based on these data, this proposal will test the hypothesis that the vascular remodeling in PVOD involves (i) the release of VRC, (ii) the aberrant protein synthesis due to the activation of ISR, and (iii) the mechanism of maladaptive ISR activation. Finally, we will explore the potential application of the circulating VRC as a blood biomarker for PVOD.

Development of an at-home weight-shifting balance game with musical biofeedback for older adults

Reducing fall risk is a dire societal need that requires interventions that over-prepare individuals to perform maneuvers important to daily mobility. Falling is often caused by improper weight shifting, and interventions that focus on developing weight-shifting abilities have shown improvements in clinical balance outcomes, including reduced fall incidence. Interventions that combine challenges to the cognitive and motor systems may be necessary to reduce fall-risk. Our central hypothesis is that leveraging gamification and “musical biofeedback” will improve balance abilities through practicing weight-shifting skills with increased cognitive and physical demands. Musical biofeedback conveys biological sensor data from the participant through specific musical sound parameters in real-time. Of particular interest in the proposal is the applicability to use musical biofeedback to train weight-shifting skills in a musical game. The goal is to develop a wearable sensor system that can be used at-home to practice and develop balance skills, while supporting cognitive engagement and motivation to adhere to exercise goals. To start, we are focusing on older adult end-users who typically have home exercise programs focused on weight-shifting. However, in the future, many other populations can benefit from this technology. In this Trailblazer award, the PI is leveraging her background in studying complex human maneuvers, developing musical biofeedback for older adults, and in algorithm development for mHealth sensors. The transdisciplinary team includes expertise in engineering, gamified rehabilitation technologies, home exercise programs, psychology of aging, and music. In the proposed research, our goals are to evaluate responses to the musical biofeedback game (Aim 1), validate the mHealth sensor system (Aim 2), and phenotype the gameplay behavior of fallers vs. non-fallers (Aim 3), relative to their baseline characteristics (Sub-Aim 3). Our long-term goal is for a variety of people to improve their balance control patterns while supporting and building their self-efficacy. We envision users, including older adults, training with musical biofeedback to safely (and enjoyably) prepare themselves to ambulate in their community – improving and preserving their mobility. The proposed research will pioneer using an emerging clinical technology – musical biofeedback – to train balance during weight-shifting tasks. The proposed research innovates how musical biofeedback, gamification, and focusing on weight-shifting and turns in balance training can be leveraged to challenge cognitive and physical body systems in fall-risk populations. By developing new therapy options and better understanding responses relative to baseline characteristics, this research improves clinical practices to reduce fall risk and deepens our understanding of dynamic balance control. Finally, the results of the proposed research will have translational impacts to help other fall-risk groups.

Response and defense mechanisms of extraintestinal Escherichia coli to reactive oxygen and chlorine species

Members of the Escherichia coli species are remarkably diverse and comprise commensal, probiotic and pathogenic strains. While some pathogenic E. coli cause intestinal diseases, extraintestinal E. coli (ExPEC) can colonize and infect environments outside the gut. For instance, members of this pathotype can inhabit the urinary tract where they are confronted with a multitude of bactericidal host defense strategies, which requires specialized genetic adaption for survival. ExPEC must defend highly toxic antimicrobials such as hypochlorous acid (HOCl), a potent reactive oxygen and chlorine species (RO/CS) generated during neutrophil-mediated phagocytosis and by enzymes in uroepithelial cells to control bacterial colonization. The increasing rate of ExPEC infections in humans due to changing infection dynamics demonstrate the critical need for a better understanding of ExPEC pathogenesis, which is desperately needed to improve approaches for infection prevention and treatment given the rise in antibiotic resistance spreading among E. coli. Our lab has reported that members of the ExPEC pathotype are more resistant to RCS in vitro and to neutrophil-mediated phagocytosis when compared to non-pathogenic and enteropathogenic E. coli. We identified the defense system responsible for these phenotypes and characterized its regulation during RCS stress: the RcrR regulon consisting of the rcrARB genes is controlled by the RCS-sensing transcriptional repressor RcrR, which reversibly loses its repressor activity upon oxidation by RCS, resulting in de-repression of its downstream targets. Induced expression of rcrB contributes significantly to ExPEC’s increased RCS resistance, however, the precise mechanism of RcrB and the role of RcrA (and potentially other defense players) during RCS stress remain enigmatic. Our long-term goal is to increase the efficacy of existing antimicrobial therapies by purposefully and selectively sensitizing ExPEC to clearance by innate immune cells. The overall objective of this application is a comprehensive analysis of ExPEC’s RCS defense with particular focus on the mechanism of the RcrR regulon. We hypothesize that RcrB directly protects cells from HOCl, while RcrA, another member of the RcrR regulon, mediates evasion from HOCl and invasion into host cells. In Aim 1, we will use phenotypic, biochemical, and imaging approaches to investigate the mechanism by which RcrB contributes to ExPEC’s increased RCS resistance. In Aim 2, we will study the role of RcrA for ExPEC motility, biofilm formation, and host cell invasion. In Aim 3, we will use independent unbiased and targeted approaches, including phenotypic characterization of transposon mutants, to fully comprehend ExPEC-specific responses to and defenses against RCS. Identifying, characterizing and targeting ExPEC-specific defense systems has the potential to increase the body’s own capacity to fight UTIs. Overall, we will involve at least four undergraduate students in our research projects, which we believe will provide an excellent training opportunity for the next generation of scientists.

Temporomandibular Joint Disc Replacement: Biomechanical Characterization and Novel Implant Assessment

Project Summary/Abstract Temporomandibular joint (TMJ) disorders inflict approximately 5% to 12% of the population. For advanced disorders of the articular TMJ disc, which typically do not respond to conservative treatments, disc resection is the most common surgical intervention. However, the TMJ disc plays a critical role in distributing mechanical stress and preventing wear to the articular surfaces of the joint. Thus, removing the disc can further disrupt joint homeostasis, driving degeneration and the development of osteoarthritis, which can lead to highly invasive and challenging surgical interventions such as joint reconstructions and total joint replacement. Therefore, there is a critical need for disc replacements that can restore the homeostasis of the joint when disc resection is required. Prior attempts at replacing the disc with alloplastic implants have led to deleterious pathological changes related to wear debris, implant fragmentation, and adverse inflammatory responses. Therefore, it is crucial to consider wear, mechanical strength, and biocompatibility of disc replacement materials in the context of long-term cyclic loading in the TMJ. Accordingly, the objective of this proposal is to create an artificial TMJ disc that replaces the mechanical function of the native disc and prevents subsequent degeneration of the joint. Towards this goal, the proposed research will characterize the mechanical loading environment of the TMJ in order to determine the mechanical criteria of a TMJ disc replacement needed to minimize internal stress in the joint (Specific Aim 1). Further, non-resorbable composite hydrogels will be fabricated using biocompatible materials, refined to exhibit biomimetic properties, and molded into a TMJ disc implant. Rigorous mechanical evaluations will determine material durability and suitability as a TMJ disc replacement (Specific Aim 2). Finally, a large animal study will be utilized to evaluate the safety and efficacy of the developed TMJ disc replacement (Specific Aim 3). Successful completion of the proposed work would represent a paradigm shift in the treatment of TMJ disc disorders that can mitigate further joint degeneration and prevent more invasive and complicated surgeries.

From Evidence to Scale: Implementation Science and Simulation Modeling to Transform HIV-Hypertension Care Integration

Project Summary As HIV programs mature, cardiovascular disease (CVD) is becoming a leading contributor to morbidity and mortality. Integration of HIV and CVD prevention, with a focus on hypertension–the most prevalent and impactful modifiable CVD risk factor, presents an opportunity to build more robust primary health systems that improve health outcomes and advance health system sustainability–a key priority for the U.S. PEPFAR program. Using an expanded version of the HIV Synthesis microsimulation model—which incorporates hypertension and CVD outcomes—and data from the NHLBI-funded HLB-SIMPLe consortium’s cluster randomized trials in six African countries, we will evaluate the health effects, cost-effectiveness, and scalability of implementation strategies to promote HIV-hypertension integration to improve health outcomes for people with and without HIV under a range of health system constraints. Our first aim is to develop and validate an additional layer to HIV Synthesis model that accounts for health system constraints and implementation strategies for integration of HIV and hypertension care. This will include parameterization using data from the WHO Health System Building Blocks framework and empiric data from trials in the HLB-SIMPLe consortium. Our second aim is to evaluate the health effects and cost-effectiveness of implementation strategies for HIV-hypertension integration to identify the most effective and scalable approaches for settings with varying health system constraints representative of conditions in west, east, and southern Africa. Analyses will include scenarios targeting people with HIV and scaling up to the broader population. Our third aim focuses on engaging policymakers and program managers to promote uptake of findings through dissemination workshops and interactive modeling tools, with tailored model outputs to specific health system contexts. Using qualitative interviews with policymakers, we will use the Weiss schema for conceptualizing research utilization to assess model impact on decision-making. We will use the Translational Science Benefits Model, to capture, classify and conceptualize the clinical, policy, economic, and operational impacts and identify barriers and facilitators to use in country programs focused on HIV, hypertension, and related NCDs. The overarching project goal is to inform evidence-based, cost-effective implementation strategies for integrating NCD care into HIV platforms, improving population health outcomes in Africa and advancing implementation science through generalizable knowledge about the intersection of implementation strategies, health system strength, and service integration.

Targeting subtype specification as a driver of PDAC health disparities

PROJECT SUMMARY Pancreatic ductal adenocarcinoma (PDAC) is a deadly disease that is refractory to current treatment strategies due in part to adaptive mechanisms of chemoresistance. Racial health disparities also confound the treatment and care of these patients. Blacks (people with African genetic ancestry) have significantly higher incidence rates of PDAC and decreased survival times compared to Caucasians (White genetic ancestry) even after socioeconomic status and tumor stages are controlled. Therefore, it is possible different racial groups exhibit unique molecular characteristics in PDAC tumors that contribute to these health disparities. The unique molecular characteristics that distinguish PDAC tumors between racial groups exhibiting disparities have the potential to identify new therapeutic targets. In a previous study, we identified 4 distinct subtypes of PDAC (Metabolic, Progenitor-like, Proliferative, and Inflammatory) that can be distinguished using multivariate analysis of quantitative proteomic data. While these PDAC subtypes are predictive of therapeutic response, this has not yet been analyzed in disparity factor balanced studies. We have examined the proteomes of primary PDAC tumors using quantitative mass spectrometry and identified unique protein signatures for Blacks and Whites. PDAC tumors from Black patients display features consistent with the Inflammatory subtype of PDAC, which is characterized by an inflamed microenvironment expressing complement proteins that can promote resistance to chemotherapy. Therefore, it is possible that race influences subtype and Blacks could preferentially develop the more aggressive and treatment refractory Inflammatory subtype. Strategies are needed to modulate subtype to improve response to chemotherapy. Toward this goal, our proteomic analysis identified polycomb repressor complex 1 (PRC1) protein RNF2 as being upregulated in PDACs from Blacks compared to Whites. We have also discovered that RNF2 regulates mRNA expression of the PDAC subtype specification factor GATA6 and inhibiting RNF2 promotes a molecular shift toward the more chemosensitive Classical subtype of PDAC. Therapeutic targeting can be achieved with Tazemetostat that inhibits the upstream PRC2 to prevent RNF2 binding the GATA6 promoter leading to its increased expression. Additionally, the Inflammatory subtype characterized by innate immune complement protein activation could be targeted with another FDA approved drug, Avacopan, which has not previously been studied in PDAC. Therefore, the Specific Aims of this proposal are designed to: 1) Evaluate the extent to which Tazemetostat treatment impacts chemotherapy-induced subtype plasticity in patient derived organoids; and 2) To determine the extent to which strategies targeting pathways associated with PDAC disparities affect progression and subtype characteristics in vivo. The successful completion of these aims has the potential to be moved quickly into phase I clinical trials since both Tazemetostat and Avacopan are FDA approved drugs. Furthermore, if successful, this project has the potential to mitigate health disparities in PDAC and broadly improve patient outcomes by implementing new precision interventions. The mouse models we propose faithfully recapitulate pancreatic cancer's clinical syndrome, histopathology and molecular properties, including the often-unique features of the stromal and immune responses that constitute the complex desmoplasia of this disease, which cannot be addressed using in vitro model systems

I3-BC: Image-Based Infiltrating Immune Cell Detection and Outcomes in Breast Cancer Clinical Trials

PROJECT SUMMARY Tumor infiltrating lymphocytes (TILs) represent an accessible biomarker of the tumor-immune microenvironment (TIME) in breast cancer, demonstrating consistent association with response to neoadjuvant chemotherapy and outcomes in HER2-positive and triple-negative breast cancer. Despite efforts to standardize TIL enumeration from hematoxylin and eosin stained tumor slides, TILs have not gained widespread adoption due to inter- observer variability, and time limitations in pathologic assessment, among others. Further, other key elements of the microenvironment, such as tumor-associated macrophages (TAMs), do not yet have standardized approaches for quantification or characterization. As a result, there is no assessment of the TIME for the vast majority of breast cancers diagnosed in the US and around the world. However, the rapid growth of digital pathology offers the potential to leverage computational approaches to overcome these limitations and democratize access to TIL and TAM enumeration. The overall goal of this project is to determine if computational approaches to TILs (existing) and TAMs (to be developed within this grant) are comparable to pathologist- enumerated TILs and TAMs and, further, associated with relevant patient outcomes from two phase III breast cancer clinical trials. Prior to project initiation, we have developed both a compute-intensive artificial intelligence- based TILs approach, an open source software (QuPath)-based TILs approach, and expertise in RNAseq-based immune quantification. We will first focus on TILs - benchmarking the two computational and RNAseq immune approaches against pathologist TIL counts (‘gold standard’) then evaluating association of each with event-free survival in two completed clinical trials (Aim 1). In parallel, we will develop a novel computational approache to enumerate and phenotype TAMs by using immunohistochemical staining for macrophage markers on the same slide with standard H&E, then apply in the same two clinical trials (Aim 2). Our approach is innovative because we will benchmark diverse approaches at scale in relevant clinical studies. The study is significant because we will determine if computational approaches to TILs/TAMs align with pathologist estimates and clinical outcomes, then ensure these algorithms are available to the community. Our long-term goal is to democratize computational TIL and TAM enumeration as pathology decision-support to facilitate integration of accessible tumor-immune microenvironment into clinical trials and care.

2-Deoxyglucose Therapy for Organophosphate Intoxication

Project Summary The main goal of this project is to determine the therapeutic potential of glycolysis inhibition as an adjunct to midazolam therapy in mitigating the long-term neurological effects from acute organophosphate pesticide and nerve agent (OPNA) exposure. Novel countermeasures are desperately needed for effective mitigation of morbidity and long-term effects of OPNAs. A variety of agents targeting glutamate, GABA and oxidative stress have been proposed, but glycolysis inhibitors have not been widely studied in OPNA intoxication. Dysregulated glucose metabolism plays a key role in seizures and neuronal injury following OPNA exposure. 2-Deoxyglucose (2-DG), a selective glycolysis inhibitor, has anticonvulsant and neuroprotection effects and hence can effectively mitigate acute and long-term OPNA neurotoxicity. In this project, we seek to identify the glycolysis inhibition as novel adjunct neuroprotection to midazolam therapy for OPNA exposure, with the goal of identifying 2-DG or related drugs as medical countermeasures. The glycolytic pathway represents a logical target for such intervention because glycolysis controls seizures and neuronal injury by regulating glucose utilization and activity in neurons and astrocytes in the brain. The proposed therapy is based on the hypothesis that acute OPNA neurotoxicity imparts sustained activation of the glycolysis pathway in the brain and therefore, 2- DG and selective glycolysis inhibitors prevents long-term neuronal damage neurological dysfunction. This hypothesis will be tested by using the FDA-approved (2-DG) or clinical-stage glycolytic inhibitors in two distinct OPNA models in rats: (Aim 1) To investigate the protective efficacy of 2-DG and novel glycolysis inhibitors against DFP-induced acute and long-term neuronal damage and neurological dysfunction. (Aim 2) Aim 2 (Year 2). To determine brain penetration, pilot toxicity and pharmacokinetic of 2-DG or other lead drug in naïve and DFP-exposed animals. Test drugs will be evaluated as per the NIH rigor criteria in a dose-related design in male and female rats and behavior/neuropathology will be checked for 3 months post-exposure. 2-DG and test drugs will be given starting 40-min after exposure to ONAs. Three primary outcome measures will be addressed for therapy effectiveness: (i) acute adjunct neuroprotection; (ii) chronic neuroprotectant efficacy; and (iii) prevention of neurological and behavioral deficits. The primary measures of neuroprotection include longitudinal MRI scanning, and extent of neurodegeneration, neuroinflammation, aberrant neurogenesis, and mossy fiber sprouting. Key neurological outcomes include memory deficits, depression, anxiety behavior, and neurological/motor deficits. The outcome of this project will provide “proof-of-efficacy” of a novel glycolytic therapy with FDA-approvable, repurposed drugs with promising potential to limit long-term effects of OPNAs in humans. Thus, the overall impact of the outcome is enormous for civilians, especially in developing a highly effective and safe post-exposure medical countermeasure for chemical nerve agents.

Understanding antiretroviral phosphorylation and dephosphorylation using mass spectrometry imaging-based enzyme histochemistry

PROJECT SUMMARY Our overall goal is to understand the mechanistic differences in the activation and deactivation of two widely used first-line antiretroviral drugs: tenofovir (TFV) and emtricitabine (FTC) in colonic tissues. HIV is a global health problem and roughly 1.3 million people became newly infected with HIV globally in 2022. Pre-exposure prophylaxis (PrEP) is an HIV prevention strategy where HIV-negative individuals use antiretrovirals to reduce the risk of HIV infection. Specifically, oral fixed-dose combinations of two antiretrovirals, namely, TFV (TFV; prescribed as TFV disoproxil fumarate or TFV alafenamide prodrugs) and FTC are FDA-approved for HIV PrEP. The pharmacologically active forms of TFV and FTC are TFV-diphosphate (TFV-DP) and FTC-triphosphate (FTC-TP), respectively, and these phosphorylated metabolites are found in cells. Unfortunately, high variability in the responses of TFV and FTC can lead to poor clinical outcomes, including therapeutic failure. However, the molecular mechanisms responsible for the observed variability in TFV and FTC responses are poorly understood. Although the observed variability in TFV and FTC drug responses is likely to be multifactorial, alterations in drug activation and deactivation can contribute to the observed variability in drug responses. Phosphorylation of TFV is known and recent studies suggest that nucleotidases may involve in the dephosphorylation of TFV metabolites. Although the kinases that phosphorylate FTC in peripheral blood mononuclear cells are known, the kinases that are responsible for the phosphorylation of FTC in putative sites of HIV infection such as colonic tissues are yet to be determined. Notably, unprotected receptive anal intercourse has a 20-fold higher risk of HIV transmission than vaginal intercourse. Thus, understanding the biotransformation of TFV and FTC in colonic tissue is important since it is a susceptible tissue to HIV infection. Recently, we have reported the enzymatic activities of nucleotidases toward the pharmacologically active metabolites of TFV and FTC in vitro. However, the mechanistic details of the biotransformation of the above drugs in HIV susceptible tissues such as colonic tissues are yet to be elucidated. Gaining a mechanistic understanding of the biotransformation of TFV and FTC in putative sites of HIV infection is important to improve their therapeutic efficacy. As such, in this application, we propose an innovative mass spectrometry imaging-based interdisciplinary approach to understand the biotransformation of TFV and FTC in the colon. Aim 1 will establish the role of nucleotide kinases and nucleotidases in regulating TFV and FTC metabolites in colonic cells mechanistically. Aim 2 will characterize the region- and cell-type-specific expression patterns, as well as enzymatic activities of nucleotide kinases and nucleotidases in situ. The proposed project will provide novel understandings of TFV and FTC activating and deactivating mechanisms that can be leveraged to optimize the therapeutic efficacy of the above drugs.

RECONJOINT: A Preference Elicitation Tool to Improve Shared Decision Making for Breast Reconstruction Surgery

PROJECT SUMMARY/ABSTRACT Breast reconstruction is a critical component of comprehensive breast cancer care, offering physical and emotional restoration after mastectomy. However, 40% of women undergoing breast reconstruction report dissatisfaction and decisional regret due to low involvement with treatment decisions and poor alignment between treatment preferences and the chosen reconstructive technique. Current approaches to shared decision-making (SDM) often fail to elicit and integrate individual-level preferences into treatment planning. This serves as a barrier to effective SDM and patient-centered care. To address this gap, we developed a web- based decision tool that uses adaptive choice–based conjoint (ACBC) analysis to elicit patient-level preferences for breast reconstruction. Preliminary studies indicate that the decision tool is acceptable and usable; patients wanted to view their results and use the tool in clinic, which we could not accommodate at the time because the decision tool currently lacks a structured method for clinical integration. We propose to develop an implementation toolkit for the decision tool to facilitate clinical integration and then test the feasibility, acceptability, and implementation of the intervention, RECONJOINT (decision tool and toolkit). In Aim 1, we will design an implementation toolkit informed by focus groups and developed with input from key partners, including patients, providers, and patient advocates. Candidate elements for the implementation toolkit include components developed for site-level implementation: treatment preferences report, video introducing the tool and existing evidence, and recommendations for patients and providers to incorporate preferences into SDM. In Aim 2, we will evaluate the feasibility, acceptability, and preliminary efficacy of the intervention in a pilot cluster-randomized hybrid type 1 trial conducted at two cancer centers (Memorial Sloan Kettering and Duke University). Our primary outcome of interest is the feasibility of the intervention. Secondary outcomes include acceptability and preliminary efficacy. Using a hybrid design, we will simultaneously evaluate facilitators, barriers, and strategies to implementation and how these factors influence the feasibility and acceptability of the intervention. The Consolidated Framework for Implementation Research and the Theoretical Domains Framework will serve as conceptual frameworks. This study is innovative as it leverages ACBC analysis to elicit patient preferences, designs an intervention with multilevel input from clinical and community partners, and uses a hybrid trial design to simultaneously evaluate feasibility, acceptability, preliminary efficacy, and implementation. By addressing critical barriers to SDM and enhancing patient–provider communication, this research aligns with the goals of PA-25-253 and the National Cancer Plan to deliver high quality, patient-centered cancer care. Findings from this study will inform a full-scale multi-site trial to evaluate the efficacy of the intervention and implementation outcomes (e.g., reach).

sensorimotor control, mouvement, touch, EEG

Traditionally, touch is associated with exteroception and is rarely considered a relevant sensory cue for controlling movements in space, unlike vision. We developed a technique to isolate and measure tactile involvement in controlling sliding finger movements over a surface. Young adults traced a 2D shape with their index finger under direct or mirror-reversed visual feedback to create a conflict between visual and somatosensory inputs. In this context, increased reliance on somatosensory input compromises movement accuracy. Based on the hypothesis that tactile cues contribute to guiding hand movements when in contact with a surface, we predicted poorer performance when the participants traced with their bare finger compared to when their tactile sensation was dampened by a smooth, rigid finger splint. The results supported this prediction. EEG source analyses revealed smaller current in the source-localized somatosensory cortex during sensory conflict when the finger directly touched the surface. This finding supports the hypothesis that, in response to mirror-reversed visual feedback, the central nervous system selectively gated task-irrelevant somatosensory inputs, thereby mitigating, though not entirely resolving, the visuo-somatosensory conflict. Together, our results emphasize touch’s involvement in movement control over a surface, challenging the notion that vision predominantly governs goal-directed hand or finger movements.

Prefrontal-thalamic goal-state coding segregates navigation episodes into spatially consistent parallel hippocampal maps

Understanding reward-guided learning using large-scale datasets

Understanding the neural mechanisms of reward-guided learning is a long-standing goal of computational neuroscience. Recent methodological innovations enable us to collect ever larger neural and behavioral datasets. This presents opportunities to achieve greater understanding of learning in the brain at scale, as well as methodological challenges. In the first part of the talk, I will discuss our recent insights into the mechanisms by which zebra finch songbirds learn to sing. Dopamine has been long thought to guide reward-based trial-and-error learning by encoding reward prediction errors. However, it is unknown whether the learning of natural behaviours, such as developmental vocal learning, occurs through dopamine-based reinforcement. Longitudinal recordings of dopamine and bird songs reveal that dopamine activity is indeed consistent with encoding a reward prediction error during naturalistic learning. In the second part of the talk, I will talk about recent work we are doing at DeepMind to develop tools for automatically discovering interpretable models of behavior directly from animal choice data. Our method, dubbed CogFunSearch, uses LLMs within an evolutionary search process in order to "discover" novel models in the form of Python programs that excel at accurately predicting animal behavior during reward-guided learning. The discovered programs reveal novel patterns of learning and choice behavior that update our understanding of how the brain solves reinforcement learning problems.

“Development and application of gaze control models for active perception”

Gaze shifts in humans serve to direct high-resolution vision provided by the fovea towards areas in the environment. Gaze can be considered a proxy for attention or indicator of the relative importance of different parts of the environment. In this talk, we discuss the development of generative models of human gaze in response to visual input. We discuss how such models can be learned, both using supervised learning and using implicit feedback as an agent interacts with the environment, the latter being more plausible in biological agents. We also discuss two ways such models can be used. First, they can be used to improve the performance of artificial autonomous systems, in applications such as autonomous navigation. Second, because these models are contingent on the human’s task, goals, and/or state in the context of the environment, observations of gaze can be used to infer information about user intent. This information can be used to improve human-machine and human robot interaction, by making interfaces more anticipative. We discuss example applications in gaze-typing, robotic tele-operation and human-robot interaction.

Understanding reward-guided learning using large-scale datasets

Understanding the neural mechanisms of reward-guided learning is a long-standing goal of computational neuroscience. Recent methodological innovations enable us to collect ever larger neural and behavioral datasets. This presents opportunities to achieve greater understanding of learning in the brain at scale, as well as methodological challenges. In the first part of the talk, I will discuss our recent insights into the mechanisms by which zebra finch songbirds learn to sing. Dopamine has been long thought to guide reward-based trial-and-error learning by encoding reward prediction errors. However, it is unknown whether the learning of natural behaviours, such as developmental vocal learning, occurs through dopamine-based reinforcement. Longitudinal recordings of dopamine and bird songs reveal that dopamine activity is indeed consistent with encoding a reward prediction error during naturalistic learning. In the second part of the talk, I will talk about recent work we are doing at DeepMind to develop tools for automatically discovering interpretable models of behavior directly from animal choice data. Our method, dubbed CogFunSearch, uses LLMs within an evolutionary search process in order to "discover" novel models in the form of Python programs that excel at accurately predicting animal behavior during reward-guided learning. The discovered programs reveal novel patterns of learning and choice behavior that update our understanding of how the brain solves reinforcement learning problems.

Continuous guidance of human goal-directed movements

Brain circuits for spatial navigation

In this webinar on spatial navigation circuits, three researchers—Ann Hermundstad, Ila Fiete, and Barbara Webb—discussed how diverse species solve navigation problems using specialized yet evolutionarily conserved brain structures. Hermundstad illustrated the fruit fly’s central complex, focusing on how hardwired circuit motifs (e.g., sinusoidal steering curves) enable rapid, flexible learning of goal-directed navigation. This framework combines internal heading representations with modifiable goal signals, leveraging activity-dependent plasticity to adapt to new environments. Fiete explored the mammalian head-direction system, demonstrating how population recordings reveal a one-dimensional ring attractor underlying continuous integration of angular velocity. She showed that key theoretical predictions—low-dimensional manifold structure, isometry, uniform stability—are experimentally validated, underscoring parallels to insect circuits. Finally, Webb described honeybee navigation, featuring path integration, vector memories, route optimization, and the famous waggle dance. She proposed that allocentric velocity signals and vector manipulation within the central complex can encode and transmit distances and directions, enabling both sophisticated foraging and inter-bee communication via dance-based cues.

Generative models for video games (rescheduled)

Developing agents capable of modeling complex environments and human behaviors within them is a key goal of artificial intelligence research. Progress towards this goal has exciting potential for applications in video games, from new tools that empower game developers to realize new creative visions, to enabling new kinds of immersive player experiences. This talk focuses on recent advances of my team at Microsoft Research towards scalable machine learning architectures that effectively capture human gameplay data. In the first part of my talk, I will focus on diffusion models as generative models of human behavior. Previously shown to have impressive image generation capabilities, I present insights that unlock applications to imitation learning for sequential decision making. In the second part of my talk, I discuss a recent project taking ideas from language modeling to build a generative sequence model of an Xbox game.

Generative models for video games

Developing agents capable of modeling complex environments and human behaviors within them is a key goal of artificial intelligence research. Progress towards this goal has exciting potential for applications in video games, from new tools that empower game developers to realize new creative visions, to enabling new kinds of immersive player experiences. This talk focuses on recent advances of my team at Microsoft Research towards scalable machine learning architectures that effectively capture human gameplay data. In the first part of my talk, I will focus on diffusion models as generative models of human behavior. Previously shown to have impressive image generation capabilities, I present insights that unlock applications to imitation learning for sequential decision making. In the second part of my talk, I discuss a recent project taking ideas from language modeling to build a generative sequence model of an Xbox game.

Executive functions in the brain of deaf individuals – sensory and language effects

Executive functions are cognitive processes that allow us to plan, monitor and execute our goals. Using fMRI, we investigated how early deafness influences crossmodal plasticity and the organisation of executive functions in the adult human brain. Results from a range of visual executive function tasks (working memory, task switching, planning, inhibition) show that deaf individuals specifically recruit superior temporal “auditory” regions during task switching. Neural activity in auditory regions predicts behavioural performance during task switching in deaf individuals, highlighting the functional relevance of the observed cortical reorganisation. Furthermore, language grammatical skills were correlated with the level of activation and functional connectivity of fronto-parietal networks. Together, these findings show the interplay between sensory and language experience in the organisation of executive processing in the brain.

Using Adversarial Collaboration to Harness Collective Intelligence

There are many mysteries in the universe. One of the most significant, often considered the final frontier in science, is understanding how our subjective experience, or consciousness, emerges from the collective action of neurons in biological systems. While substantial progress has been made over the past decades, a unified and widely accepted explanation of the neural mechanisms underpinning consciousness remains elusive. The field is rife with theories that frequently provide contradictory explanations of the phenomenon. To accelerate progress, we have adopted a new model of science: adversarial collaboration in team science. Our goal is to test theories of consciousness in an adversarial setting. Adversarial collaboration offers a unique way to bolster creativity and rigor in scientific research by merging the expertise of teams with diverse viewpoints. Ideally, we aim to harness collective intelligence, embracing various perspectives, to expedite the uncovering of scientific truths. In this talk, I will highlight the effectiveness (and challenges) of this approach using selected case studies, showcasing its potential to counter biases, challenge traditional viewpoints, and foster innovative thought. Through the joint design of experiments, teams incorporate a competitive aspect, ensuring comprehensive exploration of problems. This method underscores the importance of structured conflict and diversity in propelling scientific advancement and innovation.

Sensory Consequences of Visual Actions

We use rapid eye, head, and body movements to extract information from a new part of the visual scene upon each new gaze fixation. But the consequences of such visual actions go beyond their intended sensory outcomes. On the one hand, intrinsic consequences accompany movement preparation as covert internal processes (e.g., predictive changes in the deployment of visual attention). On the other hand, visual actions have incidental consequences, side effects of moving the sensory surface to its intended goal (e.g., global motion of the retinal image during saccades). In this talk, I will present studies in which we investigated intrinsic and incidental sensory consequences of visual actions and their sensorimotor functions. Our results provide insights into continuously interacting top-down and bottom-up sensory processes, and they reify the necessity to study perception in connection to motor behavior that shapes its fundamental processes.

Connectome-based models of neurodegenerative disease

Neurodegenerative diseases involve accumulation of aberrant proteins in the brain, leading to brain damage and progressive cognitive and behavioral dysfunction. Many gaps exist in our understanding of how these diseases initiate and how they progress through the brain. However, evidence has accumulated supporting the hypothesis that aberrant proteins can be transported using the brain’s intrinsic network architecture — in other words, using the brain’s natural communication pathways. This theory forms the basis of connectome-based computational models, which combine real human data and theoretical disease mechanisms to simulate the progression of neurodegenerative diseases through the brain. In this talk, I will first review work leading to the development of connectome-based models, and work from my lab and others that have used these models to test hypothetical modes of disease progression. Second, I will discuss the future and potential of connectome-based models to achieve clinically useful individual-level predictions, as well as to generate novel biological insights into disease progression. Along the way, I will highlight recent work by my lab and others that is already moving the needle toward these lofty goals.

Modeling the Navigational Circuitry of the Fly

Navigation requires orienting oneself relative to landmarks in the environment, evaluating relevant sensory data, remembering goals, and convert all this information into motor commands that direct locomotion. I will present models, highly constrained by connectomic, physiological and behavioral data, for how these functions are accomplished in the fly brain.

Identifying mechanisms of cognitive computations from spikes

Higher cortical areas carry a wide range of sensory, cognitive, and motor signals supporting complex goal-directed behavior. These signals mix in heterogeneous responses of single neurons, making it difficult to untangle underlying mechanisms. I will present two approaches for revealing interpretable circuit mechanisms from heterogeneous neural responses during cognitive tasks. First, I will show a flexible nonparametric framework for simultaneously inferring population dynamics on single trials and tuning functions of individual neurons to the latent population state. When applied to recordings from the premotor cortex during decision-making, our approach revealed that populations of neurons encoded the same dynamic variable predicting choices, and heterogeneous firing rates resulted from the diverse tuning of single neurons to this decision variable. The inferred dynamics indicated an attractor mechanism for decision computation. Second, I will show an approach for inferring an interpretable network model of a cognitive task—the latent circuit—from neural response data. We developed a theory to causally validate latent circuit mechanisms via patterned perturbations of activity and connectivity in the high-dimensional network. This work opens new possibilities for deriving testable mechanistic hypotheses from complex neural response data.

Brain network communication: concepts, models and applications

Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models.

Walk the talk: concrete actions to promote diversity in neuroscience in Latin America

Building upon the webinar "What are the main barriers to succeed in brain sciences in Latin America?" (February 2021) and the paper "Addressing the opportunity gap in the Latin American neuroscience community" (Silva, A., Iyer, K., Cirulli, F. et al. Nat Neurosci August 2022), this ALBA-IBRO Webinar is the next chapter in our journey towards fostering inclusivity and diversity in neuroscience in Latin America. The webinar is designed to go beyond theoretical discussions and provide tangible solutions. We will showcase 3-4 best practice case studies, shining a spotlight on real-life actions and campaigns implemented at the institutional level, be it within government bodies, universities, or other organisations. Our goal is to empower neuroscientists across Latin America by equipping them with practical knowledge they can apply in their own institutions and countries.

The Effects of Movement Parameters on Time Perception

Mobile organisms must be capable of deciding both where and when to move in order to keep up with a changing environment; therefore, a strong sense of time is necessary, otherwise, we would fail in many of our movement goals. Despite this intrinsic link between movement and timing, only recently has research begun to investigate the interaction. Two primary effects that have been observed include: movements biasing time estimates (i.e., affecting accuracy) as well as making time estimates more precise. The goal of this presentation is to review this literature, discuss a Bayesian cue combination framework to explain these effects, and discuss the experiments I have conducted to test the framework. The experiments herein include: a motor timing task comparing the effects of movement vs non-movement with and without feedback (Exp. 1A & 1B), a transcranial magnetic stimulation (TMS) study on the role of the supplementary motor area (SMA) in transforming temporal information (Exp. 2), and a perceptual timing task investigating the effect of noisy movement on time perception with both visual and auditory modalities (Exp. 3A & 3B). Together, the results of these studies support the Bayesian cue combination framework, in that: movement improves the precision of time perception not only in perceptual timing tasks but also motor timing tasks (Exp. 1A & 1B), stimulating the SMA appears to disrupt the transformation of temporal information (Exp. 2), and when movement becomes unreliable or noisy there is no longer an improvement in precision of time perception (Exp. 3A & 3B). Although there is support for the proposed framework, more studies (i.e., fMRI, TMS, EEG, etc.) need to be conducted in order to better understand where and how this may be instantiated in the brain; however, this work provides a starting point to better understanding the intrinsic connection between time and movement

Immunosuppression for Parkinson's disease - a new therapeutic strategy?

Caroline Williams-Gray is a Principal Research Associate in the Department of Clinical Neurosciences, University of Cambridge, and an honorary consultant neurologist specializing in Parkinson’s disease and movement disorders. She leads a translational research group investigating the clinical and biological heterogeneity of PD, with the ultimate goal of developing more targeted therapies for different Parkinson’s subtypes. Her recent work has focused on the theory that the immune system plays a significant role in mediating the heterogeneity of PD and its progression. Her lab is investigating this using blood and CSF -based immune markers, PET neuroimaging and neuropathology in stratified PD cohorts; and she is leading the first randomized controlled trial repurposing a peripheral immunosuppressive drug (azathioprine) to slow the progression of PD.

Feedback control in the nervous system: from cells and circuits to behaviour

The nervous system is fundamentally a closed loop control device: the output of actions continually influences the internal state and subsequent actions. This is true at the single cell and even the molecular level, where “actions” take the form of signals that are fed back to achieve a variety of functions, including homeostasis, excitability and various kinds of multistability that allow switching and storage of memory. It is also true at the behavioural level, where an animal’s motor actions directly influence sensory input on short timescales, and higher level information about goals and intended actions are continually updated on the basis of current and past actions. Studying the brain in a closed loop setting requires a multidisciplinary approach, leveraging engineering and theory as well as advances in measuring and manipulating the nervous system. I will describe our recent attempts to achieve this fusion of approaches at multiple levels in the nervous system, from synaptic signalling to closed loop brain machine interfaces.

Relations and Predictions in Brains and Machines

Humans and animals learn and plan with flexibility and efficiency well beyond that of modern Machine Learning methods. This is hypothesized to owe in part to the ability of animals to build structured representations of their environments, and modulate these representations to rapidly adapt to new settings. In the first part of this talk, I will discuss theoretical work describing how learned representations in hippocampus enable rapid adaptation to new goals by learning predictive representations, while entorhinal cortex compresses these predictive representations with spectral methods that support smooth generalization among related states. I will also cover recent work extending this account, in which we show how the predictive model can be adapted to the probabilistic setting to describe a broader array of generalization results in humans and animals, and how entorhinal representations can be modulated to support sample generation optimized for different behavioral states. In the second part of the talk, I will overview some of the ways in which we have combined many of the same mathematical concepts with state-of-the-art deep learning methods to improve efficiency and performance in machine learning applications like physical simulation, relational reasoning, and design.

Hallucinating mice, dopamine and immunity; towards mechanistic treatment targets for psychosis

Hallucinations are a core symptom of psychotic disorders and have traditionally been difficult to study biologically. We developed a new behavioral computational approach to measure hallucinations-like perception in humans and mice alike. Using targeted neural circuit manipulations, we identified a causal role for striatal dopamine in mediating hallucination-like perception. Building on this, we currently investigate the neural and immunological upstream regulators of these dopaminergic circuits with the goal to identify new biological treatment targets for psychosis

Autopoiesis and Enaction in the Game of Life

Enaction plays a central role in the broader fabric of so-called 4E (embodied, embedded, extended, enactive) cognition. Although the origin of the enactive approach is widely dated to the 1991 publication of the book "The Embodied Mind" by Varela, Thompson and Rosch, many of the central ideas trace to much earlier work. Over 40 years ago, the Chilean biologists Humberto Maturana and Francisco Varela put forward the notion of autopoiesis as a way to understand living systems and the phenomena that they generate, including cognition. Varela and others subsequently extended this framework to an enactive approach that places biological autonomy at the foundation of situated and embodied behavior and cognition. I will describe an attempt to place Maturana and Varela's original ideas on a firmer foundation by studying them within the context of a toy model universe, John Conway's Game of Life (GoL) cellular automata. This work has both pedagogical and theoretical goals. Simple concrete models provide an excellent vehicle for introducing some of the core concepts of autopoiesis and enaction and explaining how these concepts fit together into a broader whole. In addition, a careful analysis of such toy models can hone our intuitions about these concepts, probe their strengths and weaknesses, and move the entire enterprise in the direction of a more mathematically rigorous theory. In particular, I will identify the primitive processes that can occur in GoL, show how these can be linked together into mutually-supporting networks that underlie persistent bounded entities, map the responses of such entities to environmental perturbations, and investigate the paths of mutual perturbation that these entities and their environments can undergo.

Integrative Neuromodulation: from biomarker identification to optimizing neuromodulation

Why do we make decisions impulsively blinded in an emotionally rash moment? Or caught in the same repetitive suboptimal loop, avoiding fears or rushing headlong towards illusory rewards? These cognitive constructs underlying self-control and compulsive behaviours and their influence by emotion or incentives are relevant dimensionally across healthy individuals and hijacked across disorders of addiction, compulsivity and mood. My lab focuses on identifying theory-driven modifiable biomarkers focusing on these cognitive constructs with the ultimate goal to optimize and develop novel means of neuromodulation. Here I will provide a few examples of my group’s recent work to illustrate this approach. I describe a series of recent studies on intracranial physiology and acute stimulation focusing on risk taking and emotional processing. This talk highlights the subthalamic nucleus, a common target for deep brain stimulation for Parkinson’s disease and obsessive-compulsive disorder. I further describe recent translational work in non-invasive neuromodulation. Together these examples illustrate the approach of the lab highlighting modifiable biomarkers and optimizing neuromodulation.

The medial prefrontal cortex replays generalized sequences

Whilst spatial navigation is a function ascribed to the hippocampus, flexibly adapting to a change in rule depends on the medial prefrontal cortex (mPFC). Single-units were recorded from the hippocampus and mPFC of rats shifting between a spatially- and cue-guided rule on a plus-maze. The mPFC population coded for the relative position between start and goal arm. During awake immobility periods, the mPFC replayed organized sequences of generalized positions which positively correlated with rule-switching performance. Conversely, hippocampal replay negatively correlated with performance and occurred independently of mPFC replay. Sequential replay in the hippocampus and mPFC may thus serve different functions.

Modern Approaches to Behavioural Analysis

The goal of neuroscience is to understand how the nervous system controls behaviour, not only in the simplified environments of the lab, but also in the natural environments for which nervous systems evolved. In pursuing this goal, neuroscience research is supported by an ever-larger toolbox, ranging from optogenetics to connectomics. However, often these tools are coupled with reductionist approaches for linking nervous systems and behaviour. This course will introduce advanced techniques for measuring and analysing behaviour, as well as three fundamental principles as necessary to understanding biological behaviour: (1) morphology and environment; (2) action-perception closed loops and purpose; and (3) individuality and historical contingencies [1]. [1] Gomez-Marin, A., & Ghazanfar, A. A. (2019). The life of behavior. Neuron, 104(1), 25-36

Exploring emotion in the expression of ape gesture

Language appears to be the most complex system of animal communication described to date. However, its precursors were present in the communication of our evolutionary ancestors and are likely shared by our modern ape cousins.  All great apes, including humans, employ a rich repertoire of vocalizations, facial expressions, and gestures. Great ape gestural repertoires are particularly elaborate, with ape species employing over 80 different gesture types intentionally: that is towards a recipient with a specific goal in mind. Intentional usage allows us to ask not only what information is encoded in ape gestures, but what do apes mean when they use them. I will discuss recent research on ape gesture, on how we approach the question of decoding meaning, and how with new methods we are starting to integrate long overlooked aspects of ape gesture such as group and individual variation, and expression and emotion into our study of these signals.

Development of Interictal Networks: Implications for Epilepsy Progression and Cognition

Epilepsy is a common and disabling neurologic condition affecting adults and children that results from complex dysfunction of neural networks and is ineffectively treated with current therapies in up to one third of patients. This dysfunction can have especially severe consequences in pediatric age group, where neurodevelopment may be irreversibly affected. Furthermore, although seizures are the most obvious manifestation of epilepsy, the cognitive and psychiatric dysfunction that often coexists in patients with this disorder has the potential to be equally disabling.  Given these challenges, her research program aims to better understand how epileptic activity disrupts the proper development and function of neural networks, with the overall goal of identifying novel biomarkers and systems level treatments for epileptic disorders and their comorbidities, especially those affecting children.

Mouse visual cortex as a limited resource system that self-learns an ecologically-general representation

Studies of the mouse visual system have revealed a variety of visual brain areas in a roughly hierarchical arrangement, together with a multitude of behavioral capacities, ranging from stimulus-reward associations, to goal-directed navigation, and object-centric discriminations. However, an overall understanding of the mouse’s visual cortex organization, and how this organization supports visual behaviors, remains unknown. Here, we take a computational approach to help address these questions, providing a high-fidelity quantitative model of mouse visual cortex. By analyzing factors contributing to model fidelity, we identified key principles underlying the organization of mouse visual cortex. Structurally, we find that comparatively low-resolution and shallow structure were both important for model correctness. Functionally, we find that models trained with task-agnostic, unsupervised objective functions, based on the concept of contrastive embeddings were substantially better than models trained with supervised objectives. Finally, the unsupervised objective builds a general-purpose visual representation that enables the system to achieve better transfer on out-of-distribution visual, scene understanding and reward-based navigation tasks. Our results suggest that mouse visual cortex is a low-resolution, shallow network that makes best use of the mouse’s limited resources to create a light-weight, general-purpose visual system – in contrast to the deep, high-resolution, and more task-specific visual system of primates.

Multi-level theory of neural representations in the era of large-scale neural recordings: Task-efficiency, representation geometry, and single neuron properties

A central goal in neuroscience is to understand how orchestrated computations in the brain arise from the properties of single neurons and networks of such neurons. Answering this question requires theoretical advances that shine light into the ‘black box’ of representations in neural circuits. In this talk, we will demonstrate theoretical approaches that help describe how cognitive and behavioral task implementations emerge from the structure in neural populations and from biologically plausible neural networks. First, we will introduce an analytic theory that connects geometric structures that arise from neural responses (i.e., neural manifolds) to the neural population’s efficiency in implementing a task. In particular, this theory describes a perceptron’s capacity for linearly classifying object categories based on the underlying neural manifolds’ structural properties. Next, we will describe how such methods can, in fact, open the ‘black box’ of distributed neuronal circuits in a range of experimental neural datasets. In particular, our method overcomes the limitations of traditional dimensionality reduction techniques, as it operates directly on the high-dimensional representations, rather than relying on low-dimensionality assumptions for visualization. Furthermore, this method allows for simultaneous multi-level analysis, by measuring geometric properties in neural population data, and estimating the amount of task information embedded in the same population. These geometric frameworks are general and can be used across different brain areas and task modalities, as demonstrated in the work of ours and others, ranging from the visual cortex to parietal cortex to hippocampus, and from calcium imaging to electrophysiology to fMRI datasets. Finally, we will discuss our recent efforts to fully extend this multi-level description of neural populations, by (1) investigating how single neuron properties shape the representation geometry in early sensory areas, and by (2) understanding how task-efficient neural manifolds emerge in biologically-constrained neural networks. By extending our mathematical toolkit for analyzing representations underlying complex neuronal networks, we hope to contribute to the long-term challenge of understanding the neuronal basis of tasks and behaviors.

Investigating activity-dependent processes in cerebral cortex development and disease

The cerebral cortex contains an extraordinary diversity of excitatory projection neuron (PN) and inhibitory interneurons (IN), wired together to form complex circuits. Spatiotemporally coordinated execution of intrinsic molecular programs by PNs and INs and activity-dependent processes, contribute to cortical development and cortical microcircuits formation. Alterations of these delicate processes have often been associated to neurological/neurodevelopmental disorders. However, despite the groundbreaking discovery that spontaneous activity in the embryonic brain can shape regional identities of distinct cortical territories, it is still unclear whether this early activity contributes to define subtype-specific neuronal fate as well as circuit assembly. In this study, we combined in utero genetic perturbations via CRISPR/Cas9 system and pharmacological inhibition of selected ion channels with RNA-sequencing and live imaging technologies to identify the activity-regulated processes controlling the development of different cortical PN classes, their wiring and the acquisition of subtype specific features. Moreover, we generated human induced pluripotent stem cells (iPSCs) form patients affected by a severe, rare and untreatable form of developmental epileptic encephalopathy. By differentiating cortical organoids form patient-derived iPSCs we create human models of early electrical alterations for studying molecular, structural and functional consequences of the genetic mutations during cortical development. Our ultimate goal is to define the activity-conditioned processes that physiologically occur during the development of cortical circuits, to identify novel therapeutical paths to address the pathological consequences of neonatal epilepsies.

Flexible codes and loci of visual working memory

Neural correlates of visual working memory have been found in early visual, parietal, and prefrontal regions. These findings have spurred fruitful debate over how and where in the brain memories might be represented. Here, I will present data from multiple experiments to demonstrate how a focus on behavioral requirements can unveil a more comprehensive understanding of the visual working memory system. Specifically, items in working memory must be maintained in a highly robust manner, resilient to interference. At the same time, storage mechanisms must preserve a high degree of flexibility in case of changing behavioral goals. Several examples will be explored in which visual memory representations are shown to undergo transformations, and even shift their cortical locus alongside their coding format based on specifics of the task.

A Game Theoretical Framework for Quantifying​ Causes in Neural Networks

Which nodes in a brain network causally influence one another, and how do such interactions utilize the underlying structural connectivity? One of the fundamental goals of neuroscience is to pinpoint such causal relations. Conventionally, these relationships are established by manipulating a node while tracking changes in another node. A causal role is then assigned to the first node if this intervention led to a significant change in the state of the tracked node. In this presentation, I use a series of intuitive thought experiments to demonstrate the methodological shortcomings of the current ‘causation via manipulation’ framework. Namely, a node might causally influence another node, but how much and through which mechanistic interactions? Therefore, establishing a causal relationship, however reliable, does not provide the proper causal understanding of the system, because there often exists a wide range of causal influences that require to be adequately decomposed. To do so, I introduce a game-theoretical framework called Multi-perturbation Shapley value Analysis (MSA). Then, I present our work in which we employed MSA on an Echo State Network (ESN), quantified how much its nodes were influencing each other, and compared these measures with the underlying synaptic strength. We found that: 1. Even though the network itself was sparse, every node could causally influence other nodes. In this case, a mere elucidation of causal relationships did not provide any useful information. 2. Additionally, the full knowledge of the structural connectome did not provide a complete causal picture of the system either, since nodes frequently influenced each other indirectly, that is, via other intermediate nodes. Our results show that just elucidating causal contributions in complex networks such as the brain is not sufficient to draw mechanistic conclusions. Moreover, quantifying causal interactions requires a systematic and extensive manipulation framework. The framework put forward here benefits from employing neural network models, and in turn, provides explainability for them.

Pro-regenerative functions of microglia in demyelinating diseases

Our goal is to understand why myelin repair fails in multiple sclerosis and to develop regenerative medicines for the nervous system. A central obstacle for progress in this area has been the complex biology underlying the response to CNS injury. Acute CNS damage is followed by a multicellular response that encompasses different cell types and spans different scales. Currently, we do not understand which factors determines lesion recovery. Failure of inflammation to resolve is a key underlying reason of poor regeneration, and one focus is therefore on the biology of microglia during de- and remyelination, and their cross talk to other cells, in particular oligodendrocytes and the progenitor cells. In addition, we are exploring the link between lipid metabolism and inflammation, and its role in the regulation of regeneration. I will report about our recent progress in our understanding of how microglia promote regeneration in the CNS.

What the fly’s eye tells the fly’s brain…and beyond

Fly Escape Behaviors: Flexible and Modular We have identified a set of escape maneuvers performed by a fly when confronted by a looming object. These escape responses can be divided into distinct behavioral modules. Some of the modules are very stereotyped, as when the fly rapidly extends its middle legs to jump off the ground. Other modules are more complex and require the fly to combine information about both the location of the threat and its own body posture. In response to an approaching object, a fly chooses some varying subset of these behaviors to perform. We would like to understand the neural process by which a fly chooses when to perform a given escape behavior. Beyond an appealing set of behaviors, this system has two other distinct advantages for probing neural circuitry. First, the fly will perform escape behaviors even when tethered such that its head is fixed and neural activity can be imaged or monitored using electrophysiology. Second, using Drosophila as an experimental animal makes available a rich suite of genetic tools to activate, silence, or image small numbers of cells potentially involved in the behaviors. Neural Circuits for Escape Until recently, visually induced escape responses have been considered a hardwired reflex in Drosophila. White-eyed flies with deficient visual pigment will perform a stereotyped middle-leg jump in response to a light-off stimulus, and this reflexive response is known to be coordinated by the well-studied giant fiber (GF) pathway. The GFs are a pair of electrically connected, large-diameter interneurons that traverse the cervical connective. A single GF spike results in a stereotyped pattern of muscle potentials on both sides of the body that extends the fly's middle pair of legs and starts the flight motor. Recently, we have found that a fly escaping a looming object displays many more behaviors than just leg extension. Most of these behaviors could not possibly be coordinated by the known anatomy of the GF pathway. Response to a looming threat thus appears to involve activation of numerous different neural pathways, which the fly may decide if and when to employ. Our goal is to identify the descending pathways involved in coordinating these escape behaviors as well as the central brain circuits, if any, that govern their activation. Automated Single-Fly Screening We have developed a new kind of high-throughput genetic screen to automatically capture fly escape sequences and quantify individual behaviors. We use this system to perform a high-throughput genetic silencing screen to identify cell types of interest. Automation permits analysis at the level of individual fly movements, while retaining the capacity to screen through thousands of GAL4 promoter lines. Single-fly behavioral analysis is essential to detect more subtle changes in behavior during the silencing screen, and thus to identify more specific components of the contributing circuits than previously possible when screening populations of flies. Our goal is to identify candidate neurons involved in coordination and choice of escape behaviors. Measuring Neural Activity During Behavior We use whole-cell patch-clamp electrophysiology to determine the functional roles of any identified candidate neurons. Flies perform escape behaviors even when their head and thorax are immobilized for physiological recording. This allows us to link a neuron's responses directly to an action.

The neural basis of flexible semantic cognition (BACN Mid-career Prize Lecture 2022)

Semantic cognition brings meaning to our world – it allows us to make sense of what we see and hear, and to produce adaptive thoughts and behaviour. Since we have a wealth of information about any given concept, our store of knowledge is not sufficient for successful semantic cognition; we also need mechanisms that can steer the information that we retrieve so it suits the context or our current goals. This talk traces the neural networks that underpin this flexibility in semantic cognition. It draws on evidence from multiple methods (neuropsychology, neuroimaging, neural stimulation) to show that two interacting heteromodal networks underpin different aspects of flexibility. Regions including anterior temporal cortex and left angular gyrus respond more strongly when semantic retrieval follows highly-related concepts or multiple convergent cues; the multivariate responses in these regions correspond to context-dependent aspects of meaning. A second network centred on left inferior frontal gyrus and left posterior middle temporal gyrus is associated with controlled semantic retrieval, responding more strongly when weak associations are required or there is more competition between concepts. This semantic control network is linked to creativity and also captures context-dependent aspects of meaning; however, this network specifically shows more similar multivariate responses across trials when association strength is weak, reflecting a common controlled retrieval state when more unusual associations are the focus. Evidence from neuropsychology, fMRI and TMS suggests that this semantic control network is distinct from multiple-demand cortex which supports executive control across domains, although challenging semantic tasks recruit both networks. The semantic control network is juxtaposed between regions of default mode network that might be sufficient for the retrieval of strong semantic relationships and multiple-demand regions in the left hemisphere, suggesting that the large-scale organisation of flexible semantic cognition can be understood in terms of cortical gradients that capture systematic functional transitions that are repeated in temporal, parietal and frontal cortex.

Can I be bothered? Neural and computational mechanisms underlying the dynamics of effort processing (BACN Early-career Prize Lecture 2021)

From a workout at the gym to helping a colleague with their work, everyday we make decisions about whether we are willing to exert effort to obtain some sort of benefit. Increases in how effortful actions and cognitive processes are perceived to be has been linked to clinically severe impairments to motivation, such as apathy and fatigue, across many neurological and psychiatric conditions. However, the vast majority of neuroscience research has focused on understanding the benefits for acting, the rewards, and not on the effort required. As a result, the computational and neural mechanisms underlying how effort is processed are poorly understood. How do we compute how effortful we perceive a task to be? How does this feed into our motivation and decisions of whether to act? How are such computations implemented in the brain? and how do they change in different environments? I will present a series of studies examining these questions using novel behavioural tasks, computational modelling, fMRI, pharmacological manipulations, and testing in a range of different populations. These studies highlight how the brain represents the costs of exerting effort, and the dynamic processes underlying how our sensitivity to effort changes as a function of our goals, traits, and socio-cognitive processes. This work provides new computational frameworks for understanding and examining impaired motivation across psychiatric and neurological conditions, as well as why all of us, sometimes, can’t be bothered.

Visualising time in the human brain

We all have a sense of time. Yet it is a particularly intangible sensation. So how is our “sense” of time represented in the brain? Functional neuroimaging studies have consistently identified a network of regions, including Supplementary Motor Area and basal ganglia, that are activated when participants make judgements about the duration of currently unfolding events. In parallel, left parietal cortex and cerebellum are activated when participants predict when future events are likely to occur. These structures are activated by temporal processing even when task goals are purely perceptual. So why should the perception of time be represented in regions of the brain that have more traditionally been implicated in motor function? One possibility is that we learn about time through action. In other words, action could provide the functional scaffolding for learning about time in childhood, explaining why it has come to be represented in motor circuits of the adult brain.

Neural circuits of visuospatial working memory

One elementary brain function that underlies many of our cognitive behaviors is the ability to maintain parametric information briefly in mind, in the time scale of seconds, to span delays between sensory information and actions. This component of working memory is fragile and quickly degrades with delay length. Under the assumption that behavioral delay-dependencies mark core functions of the working memory system, our goal is to find a neural circuit model that represents their neural mechanisms and apply it to research on working memory deficits in neuropsychiatric disorders. We have constrained computational models of spatial working memory with delay-dependent behavioral effects and with neural recordings in the prefrontal cortex during visuospatial working memory. I will show that a simple bump attractor model with weak inhomogeneities and short-term plasticity mechanisms can link neural data with fine-grained behavioral output in a trial-by-trial basis and account for the main delay-dependent limitations of working memory: precision, cardinal repulsion biases and serial dependence. I will finally present data from participants with neuropsychiatric disorders that suggest that serial dependence in working memory is specifically altered, and I will use the model to infer the possible neural mechanisms affected.

Cortex-dependent corrections as the mouse tongue reaches for and misses targets

Brendan Ito (Cornell University, USA) and Teja Bollu (Salk Institute, USA) share unique insights into rapid online motor corrections during mouse licking, analogous to primate goal-oriented reaching. Techniques covered include large-scale single unit recording during behaviour with optogenetics, and a deep-learning-based neural network to resolve 3D tongue kinematics during licking.

Probabilistic computation in natural vision

A central goal of vision science is to understand the principles underlying the perception and neural coding of the complex visual environment of our everyday experience. In the visual cortex, foundational work with artificial stimuli, and more recent work combining natural images and deep convolutional neural networks, have revealed much about the tuning of cortical neurons to specific image features. However, a major limitation of this existing work is its focus on single-neuron response strength to isolated images. First, during natural vision, the inputs to cortical neurons are not isolated but rather embedded in a rich spatial and temporal context. Second, the full structure of population activity—including the substantial trial-to-trial variability that is shared among neurons—determines encoded information and, ultimately, perception. In the first part of this talk, I will argue for a normative approach to study encoding of natural images in primary visual cortex (V1), which combines a detailed understanding of the sensory inputs with a theory of how those inputs should be represented. Specifically, we hypothesize that V1 response structure serves to approximate a probabilistic representation optimized to the statistics of natural visual inputs, and that contextual modulation is an integral aspect of achieving this goal. I will present a concrete computational framework that instantiates this hypothesis, and data recorded using multielectrode arrays in macaque V1 to test its predictions. In the second part, I will discuss how we are leveraging this framework to develop deep probabilistic algorithms for natural image and video segmentation.

Experience-Dependent Transcription: From Genomic Mechanisms to Neural Circuit Function

Experience-dependent transcription is a key molecular mechanisms for regulating the development and plasticity of synapses and neural circuits and is thought to underlie cognitive functions such as perception, learning and memory. After two years of COVID-pandemic, the goal of this online conference is to allow investigators in the field to reconnect and to discuss their recent scientific findings.

Effects of pathological Tau on hippocampal neuronal activity and spatial memory in ageing mice

The gradual accumulation of hyperphosphorylated forms of the Tau protein (pTau) in the human brain correlate with cognitive dysfunction and neurodegeneration. I will present our recent findings on the consequences of human pTau aggregation in the hippocampal formation of a mouse tauopathy model. We show that pTau preferentially accumulates in deep-layer pyramidal neurons, leading to their neurodegeneration. In aged but not younger mice, pTau spreads to oligodendrocytes. During ‘goal-directed’ navigation, we detect fewer high-firing pyramidal cells, but coupling to network oscillations is maintained in the remaining cells. The firing patterns of individually recorded and labelled pyramidal and GABAergic neurons are similar in transgenic and non-transgenic mice, as are network oscillations, suggesting intact neuronal coordination. This is consistent with a lack of pTau in subcortical brain areas that provide rhythmic input to the cortex. Spatial memory tests reveal a reduction in short-term familiarity of spatial cues but unimpaired spatial working and reference memory. These results suggest that preserved subcortical network mechanisms compensate for the widespread pTau aggregation in the hippocampal formation. I will also briefly discuss ideas on the subcortical origins of spatial memory and the concept of the cortex as a monitoring device.

Structure, Function, and Learning in Distributed Neuronal Networks

A central goal in neuroscience is to understand how orchestrated computations in the brain arise from the properties of single neurons and networks of such neurons. Answering this question requires theoretical advances that shine light into the ‘black box’ of neuronal networks. In this talk, I will demonstrate theoretical approaches that help describe how cognitive and behavioral task implementations emerge from structure in neural populations and from biologically plausible learning rules. First, I will introduce an analytic theory that connects geometric structures that arise from neural responses (i.e., neural manifolds) to the neural population’s efficiency in implementing a task. In particular, this theory describes how easy or hard it is to discriminate between object categories based on the underlying neural manifolds’ structural properties. Next, I will describe how such methods can, in fact, open the ‘black box’ of neuronal networks, by showing how we can understand a) the role of network motifs in task implementation in neural networks and b) the role of neural noise in adversarial robustness in vision and audition. Finally, I will discuss my recent efforts to develop biologically plausible learning rules for neuronal networks, inspired by recent experimental findings in synaptic plasticity. By extending our mathematical toolkit for analyzing representations and learning rules underlying complex neuronal networks, I hope to contribute toward the long-term challenge of understanding the neuronal basis of behaviors.

Neuronal RNA signatures: Regulation and Function

Neurons are uniquely complex cells characterized by the expression of RNA sequences that are found in no other cell type: neuron-specific mRNA splice isoforms, circular RNAs, microRNAs, and ultra-long 3’UTRs. Although relatively little is known about how these neuronal RNA signatures control neuronal development and function, the importance of RNA-directed regulation in the brain is exemplified by its implication in neurological diseases. Our goal is to gain mechanistic and functional insight of the neuron-specific RNA landscape that drives neural function in health and disease.

Stress deceleration theory: chronic adolescent stress exposure results in decelerated neurobehavioral maturation

Normative development in adolescence indicates that the prefrontal cortex is still under development thereby unable to exert efficient top-down inhibitory control on subcortical regions such as the basolateral amygdala and the nucleus accumbens. This imbalance in the developmental trajectory between cortical and subcortical regions is implicated in expression of the prototypical impulsive, compulsive, reward seeking and risk-taking adolescent behavior. Here we demonstrate that a chronic mild unpredictable stress procedure during adolescence in male Wistar rats arrests the normal behavioral maturation such that they continue to express adolescent-like impulsive, hyperactive, and compulsive behaviors into late adulthood. This arrest in behavioral maturation is associated with the hypoexcitability of prelimbic cortex (PLC) pyramidal neurons and reduced PLC-mediated synaptic glutamatergic control of BLA and nucleus accumbens core (NAcC) neurons that lasts late into adulthood. At the same time stress exposure in adolescence results in the hyperexcitability of the BLA pyramidal neurons sending stronger glutamatergic projections to the NAcC. Chemogenetic reversal of the PLC hypoexcitability decreased compulsivity and improved the expression of goal-directed behavior in rats exposed to stress during adolescence, suggesting a causal role for PLC hypoexcitability in this stress-induced arrested behavioral development. (https://www.biorxiv.org/content/10.1101/2021.11.21.469381v1.abstract)

Brain chart for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure.

A Network for Computing Value Equilibrium in the Human Medial Prefrontal Corte

Humans and other animals make decisions in order to satisfy their goals. However, it remains unknown how neural circuits compute which of multiple possible goals should be pursued (e.g., when balancing hunger and thirst) and how to combine these signals with estimates of available reward alternatives. Here, humans undergoing fMRI accumulated two distinct assets over a sequence of trials. Financial outcomes depended on the minimum cumulate of either asset, creating a need to maintain “value equilibrium” by redressing any imbalance among the assets. Blood-oxygen-level-dependent (BOLD) signals in the rostral anterior cingulate cortex (rACC) tracked the level of imbalance among goals, whereas the ventromedial prefrontal cortex (vmPFC) signaled the level of redress incurred by a choice rather than the overall amount received. These results suggest that a network of medial frontal brain regions compute a value signal that maintains value equilibrium among internal goals.

The organization of neural representations for control

Cognitive control allows us to think and behave flexibly based on our context and goals. Most theories of cognitive control propose a control representation that enables the same input to produce different outputs contingent on contextual factors. In this talk, I will focus on an important property of the control representation's neural code: its representational dimensionality. Dimensionality of a neural representation balances a basic separability/generalizability trade-off in neural computation. This tradeoff has important implications for cognitive control. In this talk, I will present initial evidence from fMRI and EEG showing that task representations in the human brain leverage both ends of this tradeoff during flexible behavior.

Mice identify subgoals locations through an action-driven mapping process

Mammals instinctively explore and form mental maps of their spatial environments. Models of cognitive mapping in neuroscience mostly depict map-learning as a process of random or biased diffusion. In practice, however, animals explore spaces using structured, purposeful, sensory-guided actions. We have used threat-evoked escape behavior in mice to probe the relationship between ethological exploratory behavior and abstract spatial cognition. First, we show that in arenas with obstacles and a shelter, mice spontaneously learn efficient multi-step escape routes by memorizing allocentric subgoal locations. Using closed-loop neural manipulations to interrupt running movements during exploration, we next found that blocking runs targeting an obstacle edge abolished subgoal learning. We conclude that mice use an action-driven learning process to identify subgoals, and these subgoals are then integrated into an allocentric map-like representation. We suggest a conceptual framework for spatial learning that is compatible with the successor representation from reinforcement learning and sensorimotor enactivism from cognitive science.

Behavioral and Neuronal Correlates of Exploration and Goal-Directed Navigation

Bernstein Conference 2024

Human-like Behavior and Neural Representations Emerge in a Goal-driven Model of Overt Visual Search for Natural Objects

Bernstein Conference 2024

VTA dopamine neurons signal phasic and ramping reward prediction error in goal-directed navigation

COSYNE 2022

Goal-directed processing flexibly controls the flow of interhemispheric tactile cues

COSYNE 2022

Goal-directed processing flexibly controls the flow of interhemispheric tactile cues

COSYNE 2022

Goal-directed remapping of enthorhinal cortex neural coding

COSYNE 2022

Goal-directed remapping of enthorhinal cortex neural coding

COSYNE 2022

Mice identify subgoal locations through an action-driven mapping process

COSYNE 2022

Mice identify subgoal locations through an action-driven mapping process

COSYNE 2022

Optogenetic mapping of circuit connectivity in the motor cortex during goal-directed behavior

COSYNE 2022

Optogenetic mapping of circuit connectivity in the motor cortex during goal-directed behavior

COSYNE 2022

Revealing latent knowledge in cortical networks during goal-directed learning

COSYNE 2022

Revealing latent knowledge in cortical networks during goal-directed learning

COSYNE 2022

In silico manipulation of cortical computation underlying goal-directed learning

COSYNE 2022

In silico manipulation of cortical computation underlying goal-directed learning

COSYNE 2022

Beyond perception: the sensory cortex as an associative engine during goal-directed learning

COSYNE 2023

Direct cortical inputs to hippocampal area CA1 transmit complementary signals for goal-directed navigation

COSYNE 2023

Prioritizing experience replay when future goals are unknown

COSYNE 2023

Revealing sudden transitions from goal-directed to habitual behavior during learning in mice

COSYNE 2023

Transforming a head direction signal into a goal-oriented steering command

COSYNE 2023

Uncertainty-robust goal embedding in the prefrontal cortex for flexibly stable learning

COSYNE 2023

Brain-wide neural dynamics accompanying fast goal-directed sensorimotor learning

COSYNE 2025

A combination of plasticity rules underlies learning of flexible goal-directed behaviors.

COSYNE 2025

Complementary goal and prediction-driven learning systems in a model of mammalian sensorimotor areas

COSYNE 2025

Continuous and compositional mixing of goals in continuous choice

COSYNE 2025

The neural representations of spatial subgoals

COSYNE 2025

Novel Maze Paradigm for Assessing Behavioral \& Neural States Underlying Goal-Directed Navigation

COSYNE 2025

Revealing abrupt transitions from goal-directed to habitual behavior

COSYNE 2025

World structure emerges from inferring basic actions for goal-directed behavior

COSYNE 2025

Behavioural and neural mechanisms of commitment and abandonment in sequential goal pursuit

Cell type-specific visual information routing via the Superior Colliculus is indispensable for goal-directed forelimb reaching movements

Coding and control of goal-directed behavior by amygdala

Dopamine correlates of habit versus goal-directed behavior in the ventral tegmental area

Exploring offline memory consolidation in goal-directed sensorimotor tasks

Grid cells rescale to match goal distance during path-integration

Identifying sign-tracking and goal-tracking behaviours in humans – an eye-tracking translational study

Implication of medial prefrontal cortex and nucleus accumbens dopamine transmission in goal-directed behaviors: a role for dopamine and NMDA receptors heteromers ?

Interference-based forgetting in a goal-directed spatial navigation task for rodents

Lipopolysaccharide-induced neuroinflammation in the posterior dorsomedial striatum facilitates goal-directed action

Mesolimbic dopamine neuron stimulation influence’s goal directed action initiation and restraint