complement

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.

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.

Targeting VIP–VPAC Signaling to Reverse Immune Exclusion and Enhance Immunotherapy Response in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer that is largely unresponsive to chemotherapy and current immune checkpoint blockade drugs, highlighting a critical need for the development of innovative therapeutic strategies. This R01 proposal targets vasoactive intestinal peptide (VIP), an immunosuppressive neuropeptide overexpressed in PDAC, which signals through VIP receptors (VPAC) on cancer cells, T cells, and myeloid cells within the tumor microenvironment. Based on our recent success in developing selective and potent VPAC receptor antagonists, we hypothesize that blocking VPAC signaling will reverse immunosuppression in the PDAC TME by reducing immune checkpoint expression, enhancing chemokine-driven infiltration of cytotoxic T cells, and disrupting immunosuppressive interactions between T cells and myeloid cells, ultimately leading to durable anti-cancer immunity. We propose three specific aims to explore the immunosuppressive roles of VPAC signaling in PDAC. Aim 1 will identify the primary sources of VIP in PDAC tumors and characterize the effects of VPAC signaling on immune cell function and phenotype within the tumor microenvironment. Aim 2 will investigate how VPAC signaling influences immune cell migration into tumors by modulating chemokine receptors and directional signaling. Aim 3 will determine how VPAC signaling regulates interactions between T cells and immunosuppressive myeloid cells, particularly tumor-associated macrophages, and the resulting impact on anti-cancer immune responses and immunological memory. Our preliminary findings indicate that combined inhibition of VPAC signaling and PD-1 significantly enhances the regression of PDAC tumors in multiple mouse models, generating lasting protective immunity in cured mice without triggering autoimmune responses. We will use novel methods to pursue our aims, including inducible genetically engineered mouse models (GEMM) of PDAC, long-acting VPAC antagonists engineered with immunoglobulin Fc domains to improve their plasma half-life, and advanced microfluidics technologies to analyze immune cell movement within tumors. Animal experiments will be used to validate the translational potential of observations from in vitro organoids and microfluidic experiments. The GEMM and orthotopic mouse models of PDAC are necessary to provide critical insights into the 3-D structure of the TME and tumor regression in response to our novel immunotherapy. This research will be conducted by a multidisciplinary team with complementary expertise that will clarify the therapeutic potential of VPAC signaling inhibition in PDAC using sophisticated experimental tools and single-cell RNA sequencing. Ultimately, these findings could significantly improve the development of immunotherapeutic strategies for PDAC, potentially enhancing patient outcomes in pancreatic cancer and other malignancies expressing high VIP levels.

Targeting disulfidptosis in cancer: mechanisms and preclinical translation

Project Summary Studying regulated cell death is critical for our understanding of cellular homeostasis and tumor suppression. We recently discovered disulfidptosis as a new form of regulated cell death induced by disulfide stress under NADPH-depleting conditions in SLC7A11-high cancer cells. However, in contrast to our deep understanding of other cell death modalities such as apoptosis and ferroptosis, the molecular and metabolic underpinnings of disulfidptosis, along with its therapeutic implications, remain largely unexplored. The objectives of this application are to elucidate the mechanisms underlying disulfidptosis and to therapeutically target this form of cell death in SLC7A11-high cancers. The proposed studies will make extensive use of human cancer cell lines and integrated human cellbased molecular analyses, including metabolomics, proteomics, CRISPR screening, and biochemical studies, to define the metabolic and signaling mechanisms governing disulfidptosis. In addition, select in vivo studies are incorporated in the therapeutic validation components of the project, where tumor growth response, systemic drug exposure and tolerability, tumor microenvironmental influences, and host immune/stromal interactions must be evaluated in an organismal context to ensure translational rigor. Alternative in vitro systems such as organoids may provide useful complementary information on tumor-intrinsic responses, but they cannot fully recapitulate the systemic metabolic stress, pharmacologic exposure, and organism-level therapeutic efficacy required for these studies. It is expected that our proposed studies will reveal novel mechanisms underlying disulfidptosis and identify effective therapies to induce this form of cell death in SLC7A11-high cancers. Our proposal is highly innovative because it focuses on a previously unexplored cell death pathway in cancer therapy. Our proposed studies will have significant impact on both our understanding of the fundamental mechanisms of disulfidptosis and our ability to target this cell death pathway in cancer treatment.

Cardiorespiratory and autonomic impacts of coolants in e-cigarette aerosols

PROJECT SUMMARY / ABSTRACT Coolants such as menthol, WS-3, and WS-23 are widely used in electronic cigarettes (e-cigs) to reduce irritation and enhance appeal—especially among youth. Despite their prevalence, the cardiopulmonary toxicity of these agents remains poorly characterized. Recent work shows that e-cig aerosols can disrupt autonomic nervous system regulation and cardiac electrophysiology, increasing catecholamine release, enhancing sympathetic regulation of cardiac rhythm, and provoking arrhythmias. Proof is also mounting that nicotine’s sympathomimetic traits mediate these pathogenic effects. Preliminary data from our laboratory show that coolants increase systemic nicotine levels, blunt respiratory reflexes, and potentiate arrhythmias upon exposures to e-cigarette aerosols, suggesting a paradoxical role for coolants in suppressing ventilatory responses while intensifying cardiovascular risk. These findings take on added significance in light of recent case reports of sudden cardiac arrest in young e-cigarette users, including some in otherwise healthy individuals. This project will elucidate how e-cigarette coolants alter exposure to harmful and potentially harmful constituents (HPHCs)—particularly nicotine and aldehydes—concurrent with their effects on cardiovascular and respiratory physiology. Using robust murine models with continuous ECG, blood pressure, and pleural pressure telemetry, we will assess how coolants alter the acute and chronic effects of e-cigarette aerosols on cardiac electrophysiology, autonomic tone, ventilatory function, hemodynamics, and toxicant exposure. We will also evaluate how coolant concentration and device power modulate these effects. In parallel, we will determine whether adolescent mice exhibit heightened susceptibility to these effects compared to adults, with attention to sex differences and the persistence of cardiotoxicity after exposure cessation. This comprehensive, multi-modal approach incorporates novel protocols for arrhythmia inducibility, high-resolution physiologic monitoring, and complementary analyses of biomarkers of exposure and effect. By clarifying how coolants interact with HPHCs—especially nicotine and aldehydes—to drive cardiopulmonary injury across age and sex, this work addresses high-priority research areas identified in RFA-OD-25-001, including the toxicological evaluation of e-cigarette constituents and their cardiopulmonary effects. The results will inform regulatory policy and public health strategies aimed at mitigating cardiovascular risk associated with e-cigarette use, particularly among vulnerable youth.

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.

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.

Investigating the nonlinear complex dynamics of the tuft cell-microbiome cross-talk: the impact of feedback loops on immune regulation, microbial modulation and response to tissue insults

Project Abstract Tuft cells (TCs) are specialized chemosensory epithelial cells that are emerging as critical regulators of intestinal homeostasis. Named over 70 years ago based on their distinct morphology, a defined function for TCs was only elucidated in the last decade. TCs in the small intestine sense succinate from helminths to initiate type 2 immune responses that mediate parasite expulsion. Recently, we discovered a novel physiologic function for TCs in the colon, where their role had been considered minimal. Succinate, a key microbial metabolite, is produced by colonic microbiota as both a precursor to other metabolites and a cross-feeding fuel source for pathogens. TCs respond to succinate by secreting interleukin-25 (IL-25), which activates type 2 cytokine- producing lymphocytes (T2Ls), amplifying TC expansion and reinforcing barrier function. We recently demonstrated that this SPB–TC–IL-25–T2L feedback loop is essential for protection against pathogen-induced colitis. Our preliminary data further suggest that TCs actively promote colonization by succinate-producing bacteria (SPBs), establishing positive feedback on TC-supporting microbes, while other epithelial cells such as goblet cells (GCs) and Paneth cells (PCs) may exert complementary or counterbalancing influences. Supported by new modeling insights, we hypothesize that these epithelial–immune–microbiome interactions form coordinated feedback loops that collectively optimize intestinal resilience. These loops may create a dynamic, multi-stable system that flexibly transitions between homeostatic and hyperplastic states, buffering against microbial fluctuations and pathogenic insults while preventing uncontrolled type 2 inflammation. Using a combination of mathematical modeling and experimental validation, we will develop a multi- layered systems framework to explore how epithelial–immune–microbial feedbacks shape resilience or breakdown in clinically relevant models of colonic infection and inflammation. Our three Aims will (1) develop, calibrate, and validate a mathematical model that integrates TCs, GCs, PCs, SPBs, and SCBs; (2) define the immunological circuits governing epithelial–microbiome equilibrium; and (3) determine how epithelial feedbacks regulate microbial community structure and resilience. In line with NIH’s new initiative to prioritize human-based research, our proposal combines computational modeling, human colonic organoids, and complementary mouse models. Organoid experiments will provide human-relevant data for model calibration, while in vivo studies validate systemic predictions, ensuring both rigor and translational relevance while minimizing reliance on animal models. This work will generate interoperable models that integrate epithelial, microbial, and immune networks, providing predictive insight into intestinal outcomes under homeostatic, infectious, and inflammatory conditions and informing therapeutic strategies for microbiome-targeted interventions.

Biostatistics, Ethics, Data Management, Research Design and Community Engagement(BEDRoC) Core

Biostatistics, Ethics, Data Management, Research Design and Community Engagement (BEDRoC) Core Abstract The Biostatistics, Ethics, Data Management, Research Design and Community Engagement (BEDRoC) Core will promote and support aging with serious illness science for the Center for Aging with Serious Illness (CASI). BEDRoC will provide expertise in statistical design and analysis, research ethics, and community engagement for all components of CASI. The Core's services will support the Research Project Leaders (RPLs) and Pilot Project Leaders (PPLs) and build capacity for the broader Dartmouth Health aging research community to conduct rigorous, impactful research to inform and improve care delivery for older adults with serious illness. BEDRoC includes expertise in mixed methods approaches that feature both quantitative and qualitative research methods to provide a comprehensive understanding of the complex issues related to aging with serious illness, ethical approaches to consent in research trials, multidimensional quality of life measurement, and innovative modeling approaches to studying clinical decision making. BEDRoC faculty have actively collaborated in study planning with each RPL, serving as both mentors and experienced collaborators on the three different projects involving decision aids for patients considering carotid revascularization, a patient-reported outcome-directed referral intervention to improve referral rates to palliative care services, and a pilot trial for a virtual/home-based exercise and a weight management osteoarthritis treatment program in older patients with osteoarthritis and multimorbidity. The BEDRoC Core will further support CASI by establishing an innovative training curriculum with workshops, tutorials, resources, and services, offered locally to RPLs and PPLs and extended to regional and national investigators in the IDeA network. In addition to their primary individual project mentors, each RPL will receive training and guidance from BEDRoC leaders through co-mentoring and RPL-focused works-in-progress sessions. BEDRoC will also provide access to a comprehensive inventory of patient-reported outcomes instruments, which are crucial in geriatric research to provide validated measures of health status, quality of life and functional ability outcomes. BEDRoC will coordinate with the Administrative and Mentoring Core to integrate community advisors in guiding their activities in support of the RPLs. BEDRoC will also enable research collaboration with and within the larger Dartmouth and IDeA investigator communities. The BEDRoC Core will build capacity for aging research and disseminate new resources to RPLs and PPLs, including innovative solutions created through robust community engagement. These services, resources, and solutions will ensure all projects operate in a cohesive, complementary, and collaborative manner to study approaches to improving the health of older patients with serious illness.

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

Chromatin-Based Mechanisms Linking Transcriptional Dysregulation to Genome Instability in Neurodevelopmental Disorders.

PROJECT SUMMARY/ABSTRACT Neurons depend on a finely tuned interplay between chromatin regulation and genome maintenance, yet they are acutely vulnerable to DNA damage generated during activity-dependent transcription of long, synaptic genes. Disruption of this balance is increasingly recognized as a driver of neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD), intellectual disability, and epilepsy. High-confidence genetic studies converge on regulators of histone H3 lysine 4 (H3K4) methylation, such as the writers ASHIL and Klv1T2C and the eraser KDNISB, as recurrently mutated loci in NTIDs. The overarching goal of this study is to investigate how dysregulated H3K4 methylation compromises genome integrity in human neurons, thereby contributing to the pathogenesis of NDDs. The central, hypothesis is that coordinated II3K4 methylation safeguards neuronal genomes by maintaining an open chromatin architecture that permits the efficient detection and repair of transcription-coupled DNA lesions. The rationale/Or this study is to define the epigenetic control of DNA repair, which will illuminate a shared pathogenic hub across multiple ~I)D-linked genes. During the mentoredK99 phase, I will define how ASHIL, KMT2C, and KDM5B regulate chromatin structure and DNA repair at baseline and during transcriptional stress. Aim-1: I will use isogenic iPSC-derived cortical neurons with patient-relevant mutations or CRrSPRi knockdowns of these regulators, applying an integrated multi-omic pipeline: CUT&Tag and Micro-C to map H3K4 methylation and 3D chromatin topology. Aim-2: I will use Paired-Damage-seq, and CUT&RUN to chart oxidative lesions, repair synthesis, and recruitment of key repair factors; and RNA-seq to relate damage hotspots to altered gene expression. Aims l and 2 will be performed under the guidance of Dr. Lizarraga and Dr. Morrow, experts in the field of neurodevelopmental biology. My advisory team brings unique and complementary skills, enhancing my knowledge in 3D chromatin structure, transcription-coupled repair, gene editing, and multi-omics analysis. I will utilize these skills in the R00 phase (Aim 3), expanding the framework to include additional H3K4 regulators (e.g., LSD1, KMT2A) and broader neural lineages, thereby developing a comprehensive model. This study is innovative in its integration of single-cell D.NA damage mapping with chromatin topology and transcriptional profiling, enabling a direct and mechanistic connection between disrupted H3K4 methylation and genome instability. By uncovering how H3.K4 methylation prevents transcription-coupled genome instability in the developing brain, this research will address a critical gap in our understanding of NDD mechanisms. This award will enable me to launch an independent research program dedicated to determining mechanisms of chromatin-based processes that maintain genome stability in the developing human brain.

Addressing C-F bonds and amyloid-formation in biological systems

The ingestion, pulmonary inhalation, and dermal infiltration of C-F bond-containing compounds, most commonly found in the form of per- and polyfluoroalkyl organic acids, causes oxidative stress, inflammation, DNA damage, and developmental defects in infants and adults. These chemicals accumulate in the brain, disrupt neurological function and compromise cognitive and locomotory behavior. Yet, we lack a high-resolution road-map of the interactions between C-F bonds and biomolecular assemblies driving the trajectory towards neurodegenerative outcomes. This gap constitutes a significant barrier to advancing measures designed to mitigate C-F chemistry-associated neurotoxicity. Emerging experimental and computational data from our laboratory reveals that perfluorooctanoic acid, perfluorodecanoic acid and perfluorosulfonic acid corrupt biomolecular structures through C-F:side-chain interactions in tested soluble, globular proteins found in milk and tissues (matrices where C-F chemistries have been detected). Furthermore, they impaired the physiological function in these proteins through displacement of physiological ligands or by compromising the binding of co-factors. The neuroblastoma-derived SHSY-5Y cell line insulted with the said C-F moieties displayed altered gene expression corresponding to reactive oxygen species (ROS), protein ubiquitination, inflammation along with compromised cytoskeletal integrity. C-F bond ingestion ablated dopaminergic (DA) neurons in the nematode C. elegans and induced locomotory deficits in a manner mimicking paraquat. Based on these findings, we propose to gather data towards our hypothesis that C-F bond exposure perturbs biomolecular, cellular and organismal assemblies to onset neurodegeneration-linked trajectories. In Aim 1, we will determine whether organic fluoroacids alter mRNA levels in differentiated SHSY-5Y cells and in neuroprotective gut bacteria (Lactobacillus rhamnosus, Bifidobacterium lactis and Lactobacillus acidophilus). We will examine whether the neuroblastoma cell line exposed to C-F chemistry displays readouts designed to inform the onset of neurodegeneration-associated trajectories (including α-synuclein aggregation). In Aim 2, we will further address in a preclinical model whether C-F burden induces protein aggregation (α-synuclein, amyloid β, mHTT), interferes with dopaminergic neuronal assembles and induces locomotory deficits. Completion of the proposed work will complement ongoing experimental biophysical, structural (crystallographic, NMR) and computational (docking, molecular dynamics simulations) mapping of the interactions between these anthropogenic “forever” chemicals and amyloid-forming proteins potentially resulting in a soluble-to-toxic transformation. It will prepare the stage for vertebrate testing. The findings from this relatively understudied area likely exposes interventional targets for C-F chemistry associated neurotoxicity, spurs therapeutic efforts and can also guide the development of more biocompatible alternatives.

Overcoming Treatment Resistance by Targeting Polyploid Breast Cancer Cells with AI assisted Single-Cell Analysis

Therapy resistance remains a formidable challenge in breast cancer treatment, with emerging evidence identifying polyploid giant cancer cells (PGCCs) as key drivers. These cells, arising through whole-genome doubling (WGD) events, exhibit enhanced resistance to therapies, contributing to disease relapse. PGCCs are characterized by enlarged cell and nuclear sizes, increased DNA content, and greater resilience compared to non-PGCCs. Their prevalence escalates with disease progression and therapeutic stress, underscoring their critical role in treatment resistance. As such, we hypothesize that inhibiting polyploid cancer cells can effectively reduce therapeutic resistance. Despite this, effective strategies targeting PGCCs are limited, hindered by the lack of high-throughput methods to assess PGCC viability and abundance. Traditional screening assays lack the sensitivity to detect the elimination of small populations of PGCCs, while current detection methods, such as visual inspection and flow cytometry, are not suited for high-throughput compound screening. Our preliminary work has established a high-throughput single-cell morphological analysis pipeline capable of quantifying PGCCs, and we successfully screened 2,726 compounds for their efficacy on PGCCs. Based on the preliminary success, we aim to further improve its robustness and accuracy under diverse staining and imaging conditions, ensuring consistent performance across multiple labs for widespread use in PGCC/WGD studies, with deep learning to accelerate the discovery of therapeutic strategies targeting PGCCs. In addition to empirical screening, our scRNA-Seq analysis of PGCCs has revealed altered gene expression, particularly in genes associated with FOXM1, a transcription factor critical in cell cycle regulation and linked to poor outcomes in various cancers. PGCCs also show altered ferroptosis regulators and elevated reactive oxygen species (ROS), indicating susceptibility to ferroptosis. Here, we propose two independent and complementary aims. Aim 1: We will develop and validate a robust deep learning–based single-cell morphological analysis pipeline for accurate PGCC/non-PGCC discrimination across variable staining, imaging, and lab settings. The model will be benchmarked on independent datasets from external labs and released as open-source, version-controlled software with full documentation to support reproducibility and broad adoption in PGCC/WGD research. Aim 2: Leveraging our screen of 2,726 FDA-approved compounds and mechanistic studies of FOXM1 and ferroptosis, we will prioritize and validate therapies that eradicate PGCCs and reduce treatment resistance. Using patient- derived cells, 3D spheroids, and syngeneic/xenograft models, we will rigorously assess top candidates as monotherapy and in combination with standard-of-care agents. Successful completion of this project will accelerate PGCC/WGD research, advance therapeutic strategies to overcome breast cancer resistance, and especially deliver benefits to patients with high PGCC burden. Given the prevalence of WGD across solid tumors and its induction by standard therapies, our approach holds broad clinical relevance and translational impact.

Development of a multi-modal mouse model of cluster headache

PROJECT SUMMARY / ABSTRACT Cluster headache (CH), which affects about 1 in 1,000 people, is a severe and debilitating primary headache disorder characterized by repeated attacks occurring in clusters over weeks or months. CH has clearly defined features: severe pain (worse than childbirth), facial autonomic changes (such as a watery eye), restlessness, and a striking circadian pattern of attacks (at the same time each day like clockwork in approximately 70.5% of patients). CH also has a well-defined pathophysiology of 3 systems: the trigeminovascular pain system, the autonomic nervous system, and the hypothalamic system (in particular the posterior hypothalamus, the first brain area activated during an attack). Despite the well-known features and systems involved in CH, no disease- specific treatments are available: all CH treatments are repurposed medications from other diseases. This lack of CH-specific treatments is due in large part to the lack of a viable animal model that faithfully recapitulates the aforementioned CH features. To develop a specific animal model for CH, we previously studied a trigeminovascular headache model (repeated nitroglycerin injections), and discovered a circadian pattern of pain responses that reflects the clockwork-like pattern of attacks in CH patients. Furthermore, our analysis also identified a recently discovered CH modifier gene Mertk (MER proto-oncogene, tyrosine receptor kinase) to be highly rhythmically expressed in the trigeminal ganglion. Deletion of Mertk (Mertk-KO) altered the normal circadian rhythm of pain sensitivity by increasing pain sensitivity over 24 hours. Finally, activation of the posterior hypothalamus (via c-Fos staining) was observed after NTG administration in wild-type mice. Based on these exciting preliminary findings, we hypothesize that a combination of trigeminovascular (nitroglycerin), genetic (Mertk-KO), and hypothalamic (direct optogenetic activation of the posterior hypothalamus) manipulations will generate the first multi-modal animal model of CH. In Aim 1 (the R61 phase), we will determine the contributions of each aspect of our combined model, alone or in combination (a 4x2 grid of NTG or control, Mertk KO mouse or wild-type control, and optogenetic injection or control). Our milestone for progression to the R33 phase will be significant differences in at least two pain behaviors in our model compared to controls. In Aims 2 and 3 (the R33 phase), we will validate our model through face validity (lacrimation and restlessness), construct validity (CGRP, PACAP, and VIP in the trigeminal ganglion and hypothalamus), and predictive validity (ability of first-line and new treatments to ameliorate the pain behaviors of our model). This project is highly significant and innovative, addressing a profound need for a specific and comprehensive animal model for this devastating yet understudied disease. With the unique combination of complementary expertise in CH (laboratory and clinical), circadian biology, pharmacology, optogenetics and pain, we are ideally suited to generate this combined CH model with the goal of providing insights into CH pathophysiology and developing novel therapeutics.

“Brain theory, what is it or what should it be?”

n the neurosciences the need for some 'overarching' theory is sometimes expressed, but it is not always obvious what is meant by this. One can perhaps agree that in modern science observation and experimentation is normally complemented by 'theory', i.e. the development of theoretical concepts that help guiding and evaluating experiments and measurements. A deeper discussion of 'brain theory' will require the clarification of some further distictions, in particular: theory vs. model and brain research (and its theory) vs. neuroscience. Other questions are: Does a theory require mathematics? Or even differential equations? Today it is often taken for granted that the whole universe including everything in it, for example humans, animals, and plants, can be adequately treated by physics and therefore theoretical physics is the overarching theory. Even if this is the case, it has turned out that in some particular parts of physics (the historical example is thermodynamics) it may be useful to simplify the theory by introducing additional theoretical concepts that can in principle be 'reduced' to more complex descriptions on the 'microscopic' level of basic physical particals and forces. In this sense, brain theory may be regarded as part of theoretical neuroscience, which is inside biophysics and therefore inside physics, or theoretical physics. Still, in neuroscience and brain research, additional concepts are typically used to describe results and help guiding experimentation that are 'outside' physics, beginning with neurons and synapses, names of brain parts and areas, up to concepts like 'learning', 'motivation', 'attention'. Certainly, we do not yet have one theory that includes all these concepts. So 'brain theory' is still in a 'pre-newtonian' state. However, it may still be useful to understand in general the relations between a larger theory and its 'parts', or between microscopic and macroscopic theories, or between theories at different 'levels' of description. This is what I plan to do.

Learning representations of specifics and generalities over time

There is a fundamental tension between storing discrete traces of individual experiences, which allows recall of particular moments in our past without interference, and extracting regularities across these experiences, which supports generalization and prediction in similar situations in the future. One influential proposal for how the brain resolves this tension is that it separates the processes anatomically into Complementary Learning Systems, with the hippocampus rapidly encoding individual episodes and the neocortex slowly extracting regularities over days, months, and years. But this does not explain our ability to learn and generalize from new regularities in our environment quickly, often within minutes. We have put forward a neural network model of the hippocampus that suggests that the hippocampus itself may contain complementary learning systems, with one pathway specializing in the rapid learning of regularities and a separate pathway handling the region’s classic episodic memory functions. This proposal has broad implications for how we learn and represent novel information of specific and generalized types, which we test across statistical learning, inference, and category learning paradigms. We also explore how this system interacts with slower-learning neocortical memory systems, with empirical and modeling investigations into how the hippocampus shapes neocortical representations during sleep. Together, the work helps us understand how structured information in our environment is initially encoded and how it then transforms over time.

Tracking subjects' strategies in behavioural choice experiments at trial resolution

Psychology and neuroscience are increasingly looking to fine-grained analyses of decision-making behaviour, seeking to characterise not just the variation between subjects but also a subject's variability across time. When analysing the behaviour of each subject in a choice task, we ideally want to know not only when the subject has learnt the correct choice rule but also what the subject tried while learning. I introduce a simple but effective Bayesian approach to inferring the probability of different choice strategies at trial resolution. This can be used both for inferring when subjects learn, by tracking the probability of the strategy matching the target rule, and for inferring subjects use of exploratory strategies during learning. Applied to data from rodent and human decision tasks, we find learning occurs earlier and more often than estimated using classical approaches. Around both learning and changes in the rewarded rules the exploratory strategies of win-stay and lose-shift, often considered complementary, are consistently used independently. Indeed, we find the use of lose-shift is strong evidence that animals have latently learnt the salient features of a new rewarded rule. Our approach can be extended to any discrete choice strategy, and its low computational cost is ideally suited for real-time analysis and closed-loop control.

Event-related frequency adjustment (ERFA): A methodology for investigating neural entrainment

Neural entrainment has become a phenomenon of exceptional interest to neuroscience, given its involvement in rhythm perception, production, and overt synchronized behavior. Yet, traditional methods fail to quantify neural entrainment due to a misalignment with its fundamental definition (e.g., see Novembre and Iannetti, 2018; Rajandran and Schupp, 2019). The definition of entrainment assumes that endogenous oscillatory brain activity undergoes dynamic frequency adjustments to synchronize with environmental rhythms (Lakatos et al., 2019). Following this definition, we recently developed a method sensitive to this process. Our aim was to isolate from the electroencephalographic (EEG) signal an oscillatory component that is attuned to the frequency of a rhythmic stimulation, hypothesizing that the oscillation would adaptively speed up and slow down to achieve stable synchronization over time. To induce and measure these adaptive changes in a controlled fashion, we developed the event-related frequency adjustment (ERFA) paradigm (Rosso et al., 2023). A total of twenty healthy participants took part in our study. They were instructed to tap their finger synchronously with an isochronous auditory metronome, which was unpredictably perturbed by phase-shifts and tempo-changes in both positive and negative directions across different experimental conditions. EEG was recorded during the task, and ERFA responses were quantified as changes in instantaneous frequency of the entrained component. Our results indicate that ERFAs track the stimulus dynamics in accordance with the perturbation type and direction, preferentially for a sensorimotor component. The clear and consistent patterns confirm that our method is sensitive to the process of frequency adjustment that defines neural entrainment. In this Virtual Journal Club, the discussion of our findings will be complemented by methodological insights beneficial to researchers in the fields of rhythm perception and production, as well as timing in general. We discuss the dos and don’ts of using instantaneous frequency to quantify oscillatory dynamics, the advantages of adopting a multivariate approach to source separation, the robustness against the confounder of responses evoked by periodic stimulation, and provide an overview of domains and concrete examples where the methodological framework can be applied.

The role of sub-population structure in computations through neural dynamics

Neural computations are currently conceptualised using two separate approaches: sorting neurons into functional sub-populations or examining distributed collective dynamics. Whether and how these two aspects interact to shape computations is currently unclear. Using a novel approach to extract computational mechanisms from recurrent networks trained on neuroscience tasks, we show that the collective dynamics and sub-population structure play fundamentally complementary roles. Although various tasks can be implemented in networks with fully random population structure, we found that flexible input–output mappings instead require a non-random population structure that can be described in terms of multiple sub-populations. Our analyses revealed that such a sub-population organisation enables flexible computations through a mechanism based on gain-controlled modulations that flexibly shape the collective dynamics.

Microbial modulation of zebrafish behavior and brain development

There is growing recognition that host-associated microbiotas modulate intrinsic neurodevelopmental programs including those underlying human social behavior. Despite this awareness, the fundamental processes are generally not understood. We discovered that the zebrafish microbiota is necessary for normal social behavior. By examining neuronal correlates of behavior, we found that the microbiota restrains neurite complexity and targeting of key forebrain neurons within the social behavior circuitry. The microbiota is also necessary for both localization and molecular functions of forebrain microglia, brain-resident phagocytes that remodel neuronal arbors. In particular, the microbiota promotes expression of complement signaling pathway components important for synapse remodeling. Our work provides evidence that the microbiota modulates zebrafish social behavior by stimulating microglial remodeling of forebrain circuits during early neurodevelopment and suggests molecular pathways for therapeutic interventions during atypical neurodevelopment.

Distinct contributions of different anterior frontal regions to rule-guided decision-making in primates: complementary evidence from lesions, electrophysiology, and neurostimulation

Different prefrontal areas contribute in distinctly different ways to rule-guided behaviour in the context of a Wisconsin Card Sorting Test (WCST) analog for macaques. For example, causal evidence from circumscribed lesions in NHPs reveals that dorsolateral prefrontal cortex (dlPFC) is necessary to maintain a reinforced abstract rule in working memory, orbitofrontal cortex (OFC) is needed to rapidly update representations of rule value, and the anterior cingulate cortex (ACC) plays a key role in cognitive control and integrating information for correct and incorrect trials over recent outcomes. Moreover, recent lesion studies of frontopolar cortex (FPC) suggest it contributes to representing the relative value of unchosen alternatives, including rules. Yet we do not understand how these functional specializations relate to intrinsic neuronal activities nor the extent to which these neuronal activities differ between different prefrontal regions. After reviewing the aforementioned causal evidence I will present our new data from studies using multi-area multi-electrode recording techniques in NHPs to simultaneously record from four different prefrontal regions implicated in rule-guided behaviour. Multi-electrode micro-arrays (‘Utah arrays’) were chronically implanted in dlPFC, vlPFC, OFC, and FPC of two macaques, allowing us to simultaneously record single and multiunit activity, and local field potential (LFP), from all regions while the monkey performs the WCST analog. Rule-related neuronal activity was widespread in all areas recorded but it differed in degree and in timing between different areas. I will also present preliminary results from decoding analyses applied to rule-related neuronal activities both from individual clusters and also from population measures. These results confirm and help quantify dynamic task-related activities that differ between prefrontal regions. We also found task-related modulation of LFPs within beta and gamma bands in FPC. By combining this correlational recording methods with trial-specific causal interventions (electrical microstimulation) to FPC we could significantly enhance and impair animals performance in distinct task epochs in functionally relevant ways, further consistent with an emerging picture of regional functional specialization within a distributed framework of interacting and interconnected cortical regions.

Modelling metaphor comprehension as a form of analogizing

What do people do when they comprehend language in discourse? According to many psychologists, they build and maintain cognitive representations of utterances in four complementary mental models for discourse that interact with each other: the surface text, the text base, the situation model, and the context model. When people encounter metaphors in these utterances, they need to incorporate them into each of these mental representations for the discourse. Since influential metaphor theories define metaphor as a form of (figurative) analogy, involving cross-domain mapping of a smaller or greater extent, the general expectation has been that metaphor comprehension is also based on analogizing. This expectation, however, has been partly borne out by the data, but not completely. There is no one-to-one relationship between metaphor as (conceptual) structure (analogy) and metaphor as (psychological) process (analogizing). According to Deliberate Metaphor Theory (DMT), only some metaphors are handled by analogy. Instead, most metaphors are presumably handled by lexical disambiguation. This is a hypothesis that brings together most metaphor research in a provocatively new way: it means that most metaphors are not processed metaphorically, which produces a paradox of metaphor. In this talk I will sketch out how this paradox arises and how it can be resolved by a new version of DMT, which I have described in my forthcoming book Slowing metaphor down: Updating Deliberate Metaphor Theory (currently under review). In this theory, the distinction between, but also the relation between, analogy in metaphorical structure versus analogy in metaphorical process is of central importance.

Driving human visual cortex, visually and electrically

The development of circuit-based therapeutics to treat neurological and neuropsychiatric diseases require detailed localization and understanding of electrophysiological signals in the human brain. Electrodes can record and stimulate circuits in many ways, and we often rely on non-invasive imaging methods to predict the location to implant electrodes. However, electrophysiological and imaging signals measure the underlying tissue in a fundamentally different manner. To integrate multimodal data and benefit from these complementary measurements, I will describe an approach that considers how different measurements integrate signals across the underlying tissue. I will show how this approach helps relate fMRI and intracranial EEG measurements and provides new insights into how electrical stimulation influences human brain networks.

Time as its own representation? Exploring a link between timing of cognition and time perception

The way we represent and perceive time has crucial implications for studying temporality in conscious experience. Contrasting positions posit that temporal information is separately abstracted out like any other perceptual property, or that time is represented through representations having temporal properties themselves. To add to this debate, we investigated alterations in felt time in conditions where only conscious visual experience is altered while a bistable figure remains physically unchanged. In this talk, I will discuss two studies that we have done in relation to answering this question. In study 1, we investigated whether perceptual switches in fixed intervals altered felt time. In three experiments we showed that a break in visual experience (via a perceptual switch) also leads to a break in felt time. In study 2, we are currently looking at figure-ground perception in ambigous displays. Here, in experiment 1 we show that differences in flicker frequencies on ambigous regions can induce figure-ground segregation. To see if a reverse complementarity exists for felt time, we ask participants to view ambigous regions as figure/ground and show that they have different temporal resolutions for the same region based on whether it is seen as figure or background. Overall, the two studies provide evidence for temporal mirroring and isomorphism in visual experience, arguing for a link between the timing of experience and time perception.

Computational modelling of neurotransmitter release

Synaptic transmission provides the basis for neuronal communication. When an action-potential propagates through the axonal arbour, it activates voltage-gated Ca2+ channels located in the vicinity of release-ready synaptic vesicles docked at the presynaptic active zone. Ca2+ ions enter the presynaptic terminal and activate the vesicular Ca2+ sensor, thereby triggering neurotransmitter release. This whole process occurs on a timescale of a few milliseconds. In addition to fast, synchronous release, which keeps pace with action potentials, many synapses also exhibit delayed asynchronous release that persists for tens to hundreds of milliseconds. In this talk I will demonstrate how experimentally constrained computational modelling of underlying biological processes can complement laboratory studies (using electrophysiology and imaging techniques) and provide insights into the mechanisms of synaptic transmission.

Mapping the Dynamics of the Linear and 3D Genome of Single Cells in the Developing Brain

Three intimately related dimensions of the mammalian genome—linear DNA sequence, gene transcription, and 3D genome architecture—are crucial for the development of nervous systems. Changes in the linear genome (e.g., de novo mutations), transcriptome, and 3D genome structure lead to debilitating neurodevelopmental disorders, such as autism and schizophrenia. However, current technologies and data are severely limited: (1) 3D genome structures of single brain cells have not been solved; (2) little is known about the dynamics of single-cell transcriptome and 3D genome after birth; (3) true de novo mutations are extremely difficult to distinguish from false positives (DNA damage and/or amplification errors). Here, I filled in this longstanding technological and knowledge gap. I recently developed a high-resolution method—diploid chromatin conformation capture (Dip-C)—which resolved the first 3D structure of the human genome, tackling a longstanding problem dating back to the 1880s. Using Dip-C, I obtained the first 3D genome structure of a single brain cell, and created the first transcriptome and 3D genome atlas of the mouse brain during postnatal development. I found that in adults, 3D genome “structure types” delineate all major cell types, with high correlation between chromatin A/B compartments and gene expression. During development, both transcriptome and 3D genome are extensively transformed in the first month of life. In neurons, 3D genome is rewired across scales, correlated with gene expression modules, and independent of sensory experience. Finally, I examined allele-specific structure of imprinted genes, revealing local and chromosome-wide differences. More recently, I expanded my 3D genome atlas to the human and mouse cerebellum—the most consistently affected brain region in autism. I uncovered unique 3D genome rewiring throughout life, providing a structural basis for the cerebellum’s unique mode of development and aging. In addition, to accurately measure de novo mutations in a single cell, I developed a new method—multiplex end-tagging amplification of complementary strands (META-CS), which eliminates nearly all false positives by virtue of DNA complementarity. Using META-CS, I determined the true mutation spectrum of single human brain cells, free from chemical artifacts. Together, my findings uncovered an unknown dimension of neurodevelopment, and open up opportunities for new treatments for autism and other developmental disorders.

How sleep contributes to visual perceptual learning

Sleep is crucial for the continuity and development of life. Sleep-related problems can alter brain function, and cause potentially severe psychological and behavioral consequences. However, the role of sleep in our mind and behavior is far from clear. In this talk, I will present our research on how sleep may play a role in visual perceptual learning (VPL) by using simultaneous magnetic resonance spectroscopy and polysomnography in human subjects. We measured the concentrations of neurotransmitters in the early visual areas during sleep and obtained the excitation/inhibition (E/I) ratio which represents the amount of plasticity in the visual system. We found that the E/I ratio significantly increased during NREM sleep while it decreased during REM sleep. The E/I ratio during NREM sleep was correlated with offline performance gains by sleep, while the E/I ratio during REM sleep was correlated with the amount of learning stabilization. These suggest that NREM sleep increases plasticity, while REM sleep decreases it to solidify once enhanced learning. NREM and REM sleep may play complementary roles, reflected by significantly different neurochemical processing, in VPL.

Cross-modality imaging of the neural systems that support executive functions

Executive functions refer to a collection of mental processes such as attention, planning and problem solving, supported by a frontoparietal distributed brain network. These functions are essential for everyday life. Specifically in the context of patients with brain tumours there is a need to preserve them in order to enable good quality of life for patients. During surgeries for the removal of a brain tumour, the aim is to remove as much as possible of the tumour and at the same time prevent damage to the areas around it to preserve function and enable good quality of life for patients. In many cases, functional mapping is conducted during an awake surgery in order to identify areas critical for certain functions and avoid their surgical resection. While mapping is routinely done for functions such as movement and language, mapping executive functions is more challenging. Despite growing recognition in the importance of these functions for patient well-being in recent years, only a handful of studies addressed their intraoperative mapping. In the talk, I will present our new approach for mapping executive function areas using electrocorticography during awake brain surgery. These results will be complemented by neuroimaging data from healthy volunteers, directed at reliably localizing executive function regions in individuals using fMRI. I will also discuss more broadly challenges ofß using neuroimaging for neurosurgical applications. We aim to advance cross-modality neuroimaging of cognitive function which is pivotal to patient-tailored surgical interventions, and will ultimately lead to improved clinical outcomes.

Astrocytes encode complex behaviorally relevant information

While it is generally accepted that neurons control complex behavior and brain computation, the role of non-neuronal cells in this context remains unclear. Astrocytes, glial cells of the central nervous system, exhibit complex forms of chemical excitation, most prominently calcium transients, evoked by local and projection neuron activity. In this talk, I will provide mechanistic links between astrocytes’ spatiotemporally complex activity patterns, neuronal molecular signaling, and behavior. Using a visual detection task, in vivo calcium imaging, robust statistical analyses, and machine learning approaches, my work shows that cortical astrocytes encode the animal's decision, reward, performance level, and sensory properties. Behavioral context and motor activity-related parameters strongly impact astrocyte responses. Error analysis confirms that astrocytes carry behaviorally relevant information, supporting astrocytes' complementary role to neuronal coding beyond their established homeostatic and metabolic roles.

Spatial alignment supports visual comparisons

Visual comparisons are ubiquitous, and they can also be an important source for learning (e.g., Gentner et al., 2016; Kok et al., 2013). In science, technology, engineering, and math (STEM), key information is often conveyed through figures, graphs, and diagrams (Mayer, 1993). Comparing within and across visuals is critical for gleaning insight into the underlying concepts, structures, and processes that they represent. This talk addresses how people make visual comparisons and how visual comparisons can be best supported to improve learning. In particular, the talk will present a series of studies exploring the Spatial Alignment Principle (Matlen et al., 2020), derived from Structure-Mapping Theory (Gentner, 1983). Structure-mapping theory proposes that comparisons involve a process of finding correspondences between elements based on structured relationships. The Spatial Alignment Principle suggests that spatially arranging compared figures directly – to support correct correspondences and minimize interference from incorrect correspondences – will facilitate visual comparisons. We find that direct placement can facilitate visual comparison in educationally relevant stimuli, and that it may be especially important when figures are less familiar. We also present complementary evidence illustrating the preponderance of visual comparisons in 7th grade science textbooks.

NMC4 Keynote: A network perspective on cognitive effort

Cognitive effort has long been an important explanatory factor in the study of human behavior in health and disease. Yet, the biophysical nature of cognitive effort remains far from understood. In this talk, I will offer a network perspective on cognitive effort. I will begin by canvassing a recent perspective that casts cognitive effort in the framework of network control theory, developed and frequently used in systems engineering. The theory describes how much energy is required to move the brain from one activity state to another, when activity is constrained to pass along physical pathways in a connectome. I will then turn to empirical studies that link this theoretical notion of energy with cognitive effort in a behaviorally demanding task, and with a metabolic notion of energy as accessible to FDG-PET imaging. Finally, I will ask how this structurally-constrained activity flow can provide us with insights about the brain’s non-equilibrium nature. Using a general tool for quantifying entropy production in macroscopic systems, I will provide evidence to suggest that states of marked cognitive effort are also states of greater entropy production. Collectively, the work I discuss offers a complementary view of cognitive effort as a dynamical process occurring atop a complex network.

Self-organized formation of discrete grid cell modules from smooth gradients

Modular structures in myriad forms — genetic, structural, functional — are ubiquitous in the brain. While modularization may be shaped by genetic instruction or extensive learning, the mechanisms of module emergence are poorly understood. Here, we explore complementary mechanisms in the form of bottom-up dynamics that push systems spontaneously toward modularization. As a paradigmatic example of modularity in the brain, we focus on the grid cell system. Grid cells of the mammalian medial entorhinal cortex (mEC) exhibit periodic lattice-like tuning curves in their encoding of space as animals navigate the world. Nearby grid cells have identical lattice periods, but at larger separations along the long axis of mEC the period jumps in discrete steps so that the full set of periods cluster into 5-7 discrete modules. These modules endow the grid code with many striking properties such as an exponential capacity to represent space and unprecedented robustness to noise. However, the formation of discrete modules is puzzling given that biophysical properties of mEC stellate cells (including inhibitory inputs from PV interneurons, time constants of EPSPs, intrinsic resonance frequency and differences in gene expression) vary smoothly in continuous topographic gradients along the mEC. How does discreteness in grid modules arise from continuous gradients? We propose a novel mechanism involving two simple types of lateral interaction that leads a continuous network to robustly decompose into discrete functional modules. We show analytically that this mechanism is a generic multi-scale linear instability that converts smooth gradients into discrete modules via a topological “peak selection” process. Further, this model generates detailed predictions about the sequence of adjacent period ratios, and explains existing grid cell data better than existing models. Thus, we contribute a robust new principle for bottom-up module formation in biology, and show that it might be leveraged by grid cells in the brain.

Will it keep me awake? Common caffeine intake habits and sleep in real life situations

Daily caffeine consumption and chronic sleep restriction are highly prevalent in society. It is well established that acute caffeine intake under controlled conditions enhances vigilance and promotes wakefulness but can also delay sleep initiation and reduce electroencephalographic (EEG) markers of sleep intensity, particularly in susceptible individuals. To investigate whether these effects are also present during chronic consumption of coffee/caffeine, we recently conducted several complementary studies. We examined whether repeated coffee intake in dose and timing mimicking ‘real world’ habits maintains simple and complex attentional processes during chronic sleep restriction, such as during a busy work week. We found in genetically caffeine-sensitive individuals that regular coffee (300 mg caffeine/day) benefits most attentional tasks for 3-4 days when compared to decaffeinated coffee. Genetic variants were also used in the population-based HypnoLaus cohort, to investigate whether habitual caffeine consumption causally affects time to fall asleep, number of awakenings during sleep, and EEG-derived sleep intensity. The multi-level statistical analyses consistently showed that sleep quality was virtually unaffected when >3 caffeine-containing beverages/day were compared to 0-3 beverages/day. This conclusion was further corroborated by quantifying the sleep EEG in the laboratory in habitual caffeine consumers. Compared to placebo, daily intake of 3 x 150 mg caffeine over 10 days did not strongly impair nocturnal sleep nor subjective sleep quality in good sleepers. Finally, we tested whether an engineered delayed, pulsatile-release caffeine formula can improve the quality of morning awakening in sleep-restricted volunteers. We found that 160 mg caffeine taken at bedtime ameliorated the quality of awakening, increased positive and reduced negative affect scores, and promoted sustained attention immediately upon scheduled wake-up. Such an approach could prevent over-night caffeine withdrawal and provide a proactive strategy to attenuate disabling sleep inertia. Taken together, the studies suggest that common coffee/caffeine intake habits can transiently attenuate detrimental consequences of reduced sleep virtually without disturbing subjective and objective markers of sleep quality. Nevertheless, coffee/caffeine consumption cannot compensate for chronic sleep restriction.

- CANCELLED -

A recent formulation of predictive coding theory proposes that a subset of neurons in each cortical area encodes sensory prediction errors, the difference between predictions relayed from higher cortex and the sensory input. Here, we test for evidence of prediction error responses in spiking responses and local field potentials (LFP) recorded in primary visual cortex and area V4 of macaque monkeys, and in complementary electroencephalographic (EEG) scalp recordings in human participants. We presented a fixed sequence of visual stimuli on most trials, and violated the expected ordering on a small subset of trials. Under predictive coding theory, pattern-violating stimuli should trigger robust prediction errors, but we found that spiking, LFP and EEG responses to expected and pattern-violating stimuli were nearly identical. Our results challenge the assertion that a fundamental computational motif in sensory cortex is to signal prediction errors, at least those based on predictions derived from temporal patterns of visual stimulation.

Collective Construction in Natural and Artificial Swarms

Natural systems provide both puzzles to unravel and demonstrations of what's possible. The natural world is full of complex systems of dynamically interchangeable, individually unreliable components that produce effective and reliable outcomes at the group level. A complementary goal to understanding the operation of such systems is that of being able to engineer artifacts that work in a similar way. One notable type of collective behavior is collective construction, epitomized by mound-building termites, which build towering, intricate mounds through the joint activity of millions of independent and limited insects. The artificial counterpart would be swarms of robots designed to build human-relevant structures. I will discuss work on both aspects of the problem, including studies of cues that individual termite workers use to help direct their actions and coordinate colony activity, and development of robot systems that build user-specified structures despite limited information and unpredictable variability in the process. These examples illustrate principles used by the insects and show how they can be applied in systems we create.

Encoding and perceiving the texture of sounds: auditory midbrain codes for recognizing and categorizing auditory texture and for listening in noise

Natural soundscapes such as from a forest, a busy restaurant, or a busy intersection are generally composed of a cacophony of sounds that the brain needs to interpret either independently or collectively. In certain instances sounds - such as from moving cars, sirens, and people talking - are perceived in unison and are recognized collectively as single sound (e.g., city noise). In other instances, such as for the cocktail party problem, multiple sounds compete for attention so that the surrounding background noise (e.g., speech babble) interferes with the perception of a single sound source (e.g., a single talker). I will describe results from my lab on the perception and neural representation of auditory textures. Textures, such as a from a babbling brook, restaurant noise, or speech babble are stationary sounds consisting of multiple independent sound sources that can be quantitatively defined by summary statistics of an auditory model (McDermott & Simoncelli 2011). How and where in the auditory system are summary statistics represented and the neural codes that potentially contribute towards their perception, however, are largely unknown. Using high-density multi-channel recordings from the auditory midbrain of unanesthetized rabbits and complementary perceptual studies on human listeners, I will first describe neural and perceptual strategies for encoding and perceiving auditory textures. I will demonstrate how distinct statistics of sounds, including the sound spectrum and high-order statistics related to the temporal and spectral correlation structure of sounds, contribute to texture perception and are reflected in neural activity. Using decoding methods I will then demonstrate how various low and high-order neural response statistics can differentially contribute towards a variety of auditory tasks including texture recognition, discrimination, and categorization. Finally, I will show examples from our recent studies on how high-order sound statistics and accompanying neural activity underlie difficulties for recognizing speech in background noise.

Learning from unexpected events in the neocortical microcircuit

Predictive learning hypotheses posit that the neocortex learns a hierarchical model of the structure of features in the environment. Under these hypotheses, expected or predictable features are differentiated from unexpected ones by comparing bottom-up and top-down streams of data, with unexpected features then driving changes in the representation of incoming stimuli. This is supported by numerous studies in early sensory cortices showing that pyramidal neurons respond particularly strongly to unexpected stimulus events. However, it remains unknown how their responses govern subsequent changes in stimulus representations, and thus, govern learning. Here, I present results from our study of layer 2/3 and layer 5 pyramidal neurons imaged in primary visual cortex of awake, behaving mice using two-photon calcium microscopy at both the somatic and distal apical planes. Our data reveals that individual neurons and distal apical dendrites show distinct, but predictable changes in unexpected event responses when tracked over several days. Considering existing evidence that bottom-up information is primarily targeted to somata, with distal apical dendrites receiving the bulk of top-down inputs, our findings corroborate hypothesized complementary roles for these two neuronal compartments in hierarchical computing. Altogether, our work provides novel evidence that the neocortex indeed instantiates a predictive hierarchical model in which unexpected events drive learning.

Using extra-hippocampal cognitive maps for goal-directed spatial navigation

Goal-directed navigation requires precise estimates of spatial relationships between current position and future goal, as well as planning of an associated route or action. While neurons in the hippocampal formation can represent the animal’s position and nearby trajectories, their role in determining the animal’s destination or action has been questioned. We thus hypothesize that brain regions outside the hippocampal formation may play complementary roles in navigation, particularly for guiding goal-directed behaviours based on the brain’s internal cognitive map. In this seminar, I will first describe a subpopulation of neurons in the retrosplenial cortex (RSC) that increase their firing when the animal approaches environmental boundaries, such as walls or edges. This boundary coding is independent of direct visual or tactile sensation but instead depends on inputs from the medial entorhinal cortex (MEC) that contains spatial tuning cells, such as grid cells or border cells. However, unlike MEC border cells, we found that RSC border cells encode environmental boundaries in a self-centred egocentric coordinate frame, which may allow an animal for efficient avoidance from approaching walls or edges during navigation. I will then discuss whether the brain can possess a precise estimate of remote target location during active environmental exploration. Such a spatial code has not been described in the hippocampal formation. However, we found that neurons in the rat orbitofrontal cortex (OFC) form spatial representations that persistently point to the animal’s subsequent goal destination throughout navigation. This destination coding emerges before navigation onset without direct sensory access to a distal goal, and are maintained via destination-specific neural ensemble dynamics. These findings together suggest key roles for extra-hippocampal regions in spatial navigation, enabling animals to choose appropriate actions toward a desired destination by avoiding possible dangers.

Inclusive Human Participant Research

Human participant research is somehow both antithetical and complementary to science. On the one hand, working with human participants provides incredibly rich and complex data with ‘real-world’ ecological validity. On the other, this richness is due to the incredible number of variables which uncontrollably become intertwined with your research interest, potentially limiting the conclusions you can draw from your work. Historical over-representation of white men as research participants, coupled with often overly-stringent exclusion criteria has led to a diversity crisis in human participant research. For our research to be truly inclusive, representative and generalisable to the rest of the population, our data must be collected from diverse individuals. This session will explore common barriers to diversity in studies with human participants, and will provide guidance on how to make sure your own research is accessible and inclusive.

Neuro-Immune Coupling: How the Immune System Sculpts Brain Circuitry

In this lecture, Dr Stevens will discuss recent work that implicates brain immune cells, called microglia, in sculpting of synaptic connections during development and their relevance to autism, schizophrenia and other brain disorders. Her recent work revealed a key role for microglia and a group of immune related molecules called complement in normal developmental synaptic pruning, a normal process required to establish precise brain wiring. Emerging evidence suggests aberrant regulation of this pruning pathway may contribute to synaptic and cognitive dysfunction in a host of brain disorders, including schizophrenia. Recent research has revealed that a person’s risk of schizophrenia is increased if they inherit specific variants in complement C4, gene plays a well-known role in the immune system but also helps sculpt developing synapses in the mouse visual system (Sekar et al., 2016). Together these findings may help explain known features of schizophrenia, including reduced numbers of synapses in key cortical regions and an adolescent age of onset that corresponds with developmentally timed waves of synaptic pruning in these regions. Stevens will discuss this and ongoing work to understand the mechanisms by which complement and microglia prune specific synapses in the brain. A deeper understanding of how these immune mechanisms mediate synaptic pruning may provide novel insight into how to protect synapses in autism and other brain disorders, including Alzheimer’s and Huntington’s Disease.

The role of the complement pathway in post-traumatic sleep disruption and epilepsy

While traumatic brain injury (TBI) acutely disrupts the cortex, most TBI-related disabilities reflect secondary injuries that accrue over time. The thalamus is a likely site of secondary damage because of its reciprocal connections with the cortex. Using a mouse model of mild cortical injury that does not directly damage subcortical structures (mTBI), we found a chronic increase in C1q expression specifically in the corticothalamic circuit. Increased C1q expression co-localized with neuron loss and chronic inflammation, and correlated with disruption in sleep spindles and emergence of epileptic activities. Blocking C1q counteracted these outcomes, suggesting that C1q is a disease modifier in mTBI. Single-nucleus RNA sequencing demonstrated that microglia are the source of thalamic C1q. Since the corticothalamic circuit is important for cognition and sleep, which can be impaired by TBI, this circuit could be a new target for treating TBI-related disabilities

From 1D to 5D: Data-driven Discovery of Whole-brain Dynamic Connectivity in fMRI Data

The analysis of functional magnetic resonance imaging (fMRI) data can greatly benefit from flexible analytic approaches. In particular, the advent of data-driven approaches to identify whole-brain time-varying connectivity and activity has revealed a number of interesting relevant variation in the data which, when ignored, can provide misleading information. In this lecture I will provide a comparative introduction of a range of data-driven approaches to estimating time-varying connectivity. I will also present detailed examples where studies of both brain health and disorder have been advanced by approaches designed to capture and estimate time-varying information in resting fMRI data. I will review several exemplar data sets analyzed in different ways to demonstrate the complementarity as well as trade-offs of various modeling approaches to answer questions about brain function. Finally, I will review and provide examples of strategies for validating time-varying connectivity including simulations, multimodal imaging, and comparative prediction within clinical populations, among others. As part of the interactive aspect I will provide a hands-on guide to the dynamic functional network connectivity toolbox within the GIFT software, including an online didactic analytic decision tree to introduce the various concepts and decisions that need to be made when using such tools

State-dependent cortical circuits

Spontaneous and sensory-evoked cortical activity is highly state-dependent, promoting the functional flexibility of cortical circuits underlying perception and cognition. Using neural recordings in combination with behavioral state monitoring, we find that arousal and motor activity have complementary roles in regulating local cortical operations, providing dynamic control of sensory encoding. These changes in encoding are linked to altered performance on perceptual tasks. Neuromodulators, such as acetylcholine, may regulate this state-dependent flexibility of cortical network function. We therefore recently developed an approach for dual mesoscopic imaging of acetylcholine release and neural activity across the entire cortical mantle in behaving mice. We find spatiotemporally heterogeneous patterns of cholinergic signaling across the cortex. Transitions between distinct behavioral states reorganize the structure of large-scale cortico-cortical networks and differentially regulate the relationship between cholinergic signals and neural activity. Together, our findings suggest dynamic state-dependent regulation of cortical network operations at the levels of both local and large-scale circuits. Zoom Meeting ID: 964 8138 3003 Contact host if you cannot connect.

Unpacking Nature from Nurture: Understanding how Family Processes Affect Child and Adolescent Mental Health

Mental Health problems among youth constitutes an area of significant social, educational, clinical, policy and public health concern. Understanding processes and mechanisms that underlie the development of mental health problems during childhood and adolescence requires theoretical and methodological integration across multiple scientific domains, including developmental science, neuroscience, genetics, education and prevention science. The primary focus of this presentation is to examine the relative role of genetic and family environmental influences on children’s emotional and behavioural development. Specifically, a complementary array of genetically sensitive and longitudinal research designs will be employed to examine the role of early environmental adversity (e.g. inter-parental conflict, negative parenting practices) relative to inherited factors in accounting for individual differences in children’s symptoms of psychopathology (e.g. depression, aggression, ADHD ). Examples of recent applications of this research to the development of evidence-based intervention programmes aimed at reducing psychopathology in the context of high-risk family settings will also be presented.

Organization and control of hippocampal circuits in epilepsy

Basket cells are key GABAergic inhibitory interneurons that target the somata and proximal dendrites, enabling efficient control of the timing and rate of spiking of their postsynaptic targets. In all cortical circuits, there are two major types of basket cell that exhibit striking developmental, molecular, anatomical, and physiological differences. In this talk, I will discuss recent results that reveal the tightly coupled complementarity of these two key microcircuit regulatory modules, demonstrating a novel form of brain-state-specific segregation of inhibition during spontaneous behavior, with implications for the assessment of dysregulated inhibition in epilepsy. In addition, I will describe recent advances in our understanding of the spatio-temporal dynamics of endocannabinoid signaling in hippocampal circuits and discuss how abnormal amplification of these activity-dependent signaling processes leads to surprising downstream effects in seizures.

New Strategies and Approaches to Tackle and Understand Neurological Disorder

Broadly, the Mauro Costa-Mattioli laboratory (The MCM Lab) encompasses two complementary lines of research. The first one, more traditional but very important, aims at unraveling the molecular mechanisms underlying memory formation (e.g., using state-of-the-art molecular and cell-specific genetic approaches). Learning and memory disorders can strike the brain during development (e.g., Autism Spectrum Disorders and Down Syndrome), as well as during adulthood (e.g., Alzheimer’s disease). We are interested in understanding the specific circuits and molecular pathways that are primarily targeted in these disorders and how they can be restored. To tackle these questions, we use a multidisciplinary, convergent and cross-species approach that combines mouse and fly genetics, molecular biology, electrophysiology, stem cell biology, optogenetics and behavioral techniques. The second line of research, more recent and relatively unexplored, is focused on understanding how gut microbes control CNS driven-behavior and brain function. Our recent discoveries, that microbes in the gut could modulate brain function and behavior in a very powerful way, have added a whole new dimension to the classic view of how complex behaviors are controlled. The unexpected findings have opened new avenues of study for us and are currently driving my lab to answer a host of new and very interesting questions: - What are the gut microbes (and metabolites) that regulate CNS-driven behaviors? Would it be possible to develop an unbiased screening method to identify specific microbes that regulate different behaviors? - If this is the case, can we identify how members of the gut microbiome (and their metabolites) mechanistically influence brain function? - What is the communication channel between the gut microbiota and the brain? Do different gut microbes use different ways to interact with the brain? - Could disruption of the gut microbial ecology cause neurodevelopmental dysfunction? If so, what is the impact of disruption in young and adult animals? - More importantly, could specific restoration of selected bacterial strains (new generation probiotics) represent a novel therapeutic approach for the targeted treatment of neurodevelopmental disorders? - Finally, can we develop microbiota-directed therapeutic foods to repair brain dysfunction in a variety of neurological disorders?

LAB COGNITION GOING WILD: Field experiments on vervet monkeys'

I will present field experiments on vervet monkeys testing physical and social cognition, with a focus on social learning. The understanding of the emergence of cultural behaviours in animals has advanced significantly with contributions from complementary approaches: natural observations and controlled field experiments. Experiments with wild vervet monkeys highlight that monkeys are selective about ‘who’ they learn from socially and that they will abandon personal foraging preferences in favour of group norms new to them. The reported findings highlight the feasibility to study cognition under field conditions.

Conflict or complement: Parallel memories control behaviour in Drosophila

Drosophila can learn to associate odours with reward or punishment and the resulting memories direct odour-specific approach or avoidance behaviours. Recent progress has revealed a straightforward model for learning in which reinforcing dopaminergic neurons assign valence to odour representations in the neural ensemble of the mushroom bodies. Dopamine directed synaptic depression alters the route of odour-driven activity through the mushroom body output network. This circuit configuration and influence of internal state guide the expression of appropriate behaviour. Importantly, learned behaviour is flexible and can be updated as the fly accumulates additional experience. Our latest studies demonstrate that well-informed behaviour is guided by combining parallel conflicting and complementary memories of opposite valence.

State-dependent cortical circuits

Spontaneous and sensory-evoked cortical activity is highly state-dependent, promoting the functional flexibility of cortical circuits underlying perception and cognition. Using neural recordings in combination with behavioral state monitoring, we find that arousal and motor activity have complementary roles in regulating local cortical operations, providing dynamic control of sensory encoding. These changes in encoding are linked to altered performance on perceptual tasks. Neuromodulators, such as acetylcholine, may regulate this state-dependent flexibility of cortical network function. We therefore recently developed an approach for dual mesoscopic imaging of acetylcholine release and neural activity across the entire cortical mantle in behaving mice. We find spatiotemporally heterogeneous patterns of cholinergic signaling across the cortex. Transitions between distinct behavioral states reorganize the structure of large-scale cortico-cortical networks and differentially regulate the relationship between cholinergic signals and neural activity. Together, our findings suggest dynamic state-dependent regulation of cortical network operations at the levels of both local and large-scale circuits.

The Role of Hippocampal Replay in Memory Consolidation

The hippocampus lies at the centre of a network of brain regions thought to support spatial and episodic memory. Place cells - the principal cell of the hippocampus, represent information about an animal’s spatial location. Yet, during rest and awake quiescence place cells spontaneously recapitulate past trajectories (‘replay’). Replay has been hypothesised to support systems consolidation – the stabilisation of new memories via maturation of complementary cortical memory traces. Indeed, in recent work we found place and grid cells, from the deep medial entorhinal cortex (dMEC, the principal cortical output region of the hippocampus), replayed coherently during rest periods. Importantly, dMEC grid cells lagged place cells by ~11ms; suggesting the coordination may reflect consolidation. Moreover, preliminary data shows that the dMEC-hippocampal coordination strengthens as an animal becomes familiar with a task and that it may be led by directionally modulated cells. Finally, on-going work, in my recently established lab, shows replay may represent the mechanism underlying the maturation of episodic/spatial memory in pre-weanling pups. Together, these results indicate replay may play a central role in ensuring the permanency of memories.

State-dependent regulation of cortical circuits

Spontaneous and sensory-evoked cortical activity is highly state-dependent, promoting the functional flexibility of cortical circuits underlying perception and cognition. Using neural recordings in combination with behavioral state monitoring, we find that arousal and motor activity have complementary roles in regulating local cortical operations, providing dynamic control of sensory encoding. These changes in encoding are linked to altered performance on perceptual tasks. Neuromodulators, such as acetylcholine, may regulate this state-dependent flexibility of cortical network function. We therefore recently developed an approach for dual mesoscopic imaging of acetylcholine release and neural activity across the entire cortical mantle in behaving mice. We find spatiotemporally heterogeneous patterns of cholinergic signaling across the cortex. Transitions between distinct behavioral states reorganize the structure of large-scale cortico-cortical networks and differentially regulate the relationship between cholinergic signals and neural activity. Together, our findings suggest dynamic state-dependent regulation of cortical network operations at the levels of both local and large-scale circuits.

Molecular controls over corticospinal neuron axon branching at specific spinal segments

Corticospinal neurons (CSN) are the cortical projection neurons that innervate the spinal cord and some brainstem targets with segmental precision to control voluntary movement of specific functional motor groups, limb sections, or individual digits, yet molecular regulation over CSN segmental target specificity is essentially unknown. CSN subpopulations exhibit striking axon targeting specificity from development into maturity: Evolutionarily newer rostrolateral CSN exclusively innervate bulbar-cervical targets (CSNBC-lat), while evolutionarily older caudomedial CSN (CSNmed) are more heterogeneous, with distinct subpopulations extending axons to either bulbar-cervical or thoraco-lumbar segments. The cervical cord, with its evolutionarily enhanced precision of forelimb movement, is innervated by multiple CSN subpopulations, suggesting inter-neuronal interactions in establishing corticospinal connectivity. I identify that Lumican, previously unrecognized in axon development, controls the specificity of cervical spinal cord innervation by CSN. Remarkably, Lumican, an extracellular matrix protein expressed by CSNBC-lat, non-cell-autonomously suppresses axon collateralization in the cervical cord by CSNmed. Intersectional viral labeling and mouse genetics further identify that Lumican controls axon collateralization by multiple subpopulations in caudomedial sensorimotor cortex. These results identify inter-axonal molecular crosstalk between CSN subpopulations as a novel mechanism controlling corticospinal connectivity and competitive specificity. Further, this mechanism has potential implications for evolutionary diversification of corticospinal circuitry with finer scale precision. "" Complementing this work, to comprehensively elucidate related axon projection mechanisms functioning at tips of growing CSN axons in vivo, I am currently applying experimental and analytic approaches recently developed in my postdoc lab (Poulopoulos*, Murphy*, Nature, 2019) to quantitatively and subcellularly “map” RNA and protein molecular machinery of subtype-specific growth cones, in parallel to their parent somata, isolated directly in vivo from developing subcerebral projection neurons (SCPN; the broader cortical output neuron population targeting both brainstem and spinal cord; includes CSN). I am investigating both normal development and GC-soma dysregulation with mutation of central CSN-SCPN transcriptional regulator Ctip2/Bcl11b.

Using Developmental Trajectories to Understand Change in Children’s Analogical Reasoning

Analogical reasoning is a complex ‘high-level’ cognitive process characterised by making inferences based on analogical comparisons. As with other high-level processes, development takes place over a protracted time period and believed to result from changes in multiple ‘lower-level’ systems. In the case of analogical reasoning, changes in systems responsible for conceptual knowledge, task knowledge, inhibition, and working memory have all been causally implicated in development. Whilst there is evidence that each of these systems contributes to development, what the relative contribution of each across development is, and how they interact with each, remain largely unanswered questions. In this presentation, I will describe how cross-sectional trajectory analysis can be used as a complementary method to shed light on these questions.

Neuroscience in the mud: interplay between lab and field research for understanding animal behavior

Investigations of the neurophysiological processes underlying animal behaviors are almost exclusively done inside the laboratory, typically using few animal models born and reared under artificially stabilized conditions. Yet, animals living in the wild have to cope with much complex and variable environments. Thus, while the laboratory provides the technical possibilities for physiological research, the field offers a more realistic perspective about the animal´s behavioral abilities. We study neural circuits underlying the visually guided prey and predator behaviors in a semiterrestrial crab. By combining lab and field experiments we have, for example, found that the level of predation risk experienced by the animals in the wild affects the responsiveness of identified neurons involved in the animal escape response. Using this and other results from my lab I will illustrate and discuss the importance of complementing lab with field studies in wild animals for understanding the neural mechanisms subserving behavior.

Microglia function and dysfunction in Alzheimer’s disease

Emerging genetic studies of late-onset Alzheimer’s Disease implicate the brain’s resident macrophages in the pathogenesis of AD. More than half the risk genes associated with late-onset AD are selectively expressed in microglia and peripheral myeloid cells; yet we know little about the underlying biology or how myeloid cells contribute to AD pathogenesis. Using single-cell RNA sequencing and spatial transcriptomics we identified molecular signatures that can be used to localize and monitor distinct microglia functional states in the human and mouse brain. Our results show that microglia assume diverse functional states in development, aging and injury, including populations corresponding to known microglial functions including proliferation, migration, inflammation, and synaptic phagocytosis. We identified several innate immune pathways by which microglia recognize and prune synapses during development and in models of Alzheimer’s disease, including the classical complement cascade. Illuminating the mechanisms by which developing synaptic circuits are sculpted is providing important insight on understanding how to protect synapses in Alzheimer’s and other neurodegenerative diseases of synaptic dysfunction.

More than Bystanders in Dementia, Learning What Microglia Do

Genome-wide association studies implicate microglia in Alzheimer’s disease (AD) pathogenesis, but how microglia contribute to cognitive decline in AD is unclear. Emerging research suggests microglia, the resident macrophages of the central nervous system, to be active participants in brain wiring. One mechanism by which microglia help eliminate synapses is through the classical complement pathway (C1q, CR3/C3). Data from multiple laboratories collectively suggest that there may be an aberrant reactivation of the complement-dependent pruning pathway in multiple models of neurologic diseases including AD. These data altogether suggest that microglia participate in synaptic pathology. However, how and which synapses are targeted are unknown. Furthermore, whether microglia directly impair synaptic function is unknown. Primary goals of my laboratory are to understand how higher cognitive functions such as learning and memory involve microglial biology in the healthy adult brain and dissect immune mechanisms behind the region-specific vulnerability of synapse loss and neuronal dysfunction during disease. Mechanistic insight into local signals that regulate neuroglia interactions will be key to developing potential therapeutic avenues to target in disease.

Analogical Reasoning and Executive Functions - A Life Span Approach

From a developmental standpoint, it has been argued that two major complementary factors contribute to the development of analogy comprehension: world knowledge and executive functions. Here I will provide evidence in support of the second view. Beyond paradigms that manipulate task difficulty (e.g., number and types of distractors and semantic distance between domains) we will provide eye-tracking data that describes differences in the way children and adults compare the base and target domains in analogy problems. We will follow the same approach with ageing people. This latter population provides a unique opportunity to disentangle the contribution of knowledge and executive processes in analogy making since knowledge is (more than) preserved and executive control is decreasing. Using this paradigm, I will show the extent to which world knowledge (assessed through vocabulary) compensates for decreasing executive control in older populations. Our eye-tracking data suggests that, to a certain extent, differences between younger and older adults are analogous to the differences between younger adults and children in the way they compare the base and the target domains in analogy problems.

Cortical plasticity

Plasticity shapes the brain during development, and mechanisms of plasticity continue into adulthood to enable learning and memory. Nearly all brain functions are influenced by past events, reinforcing the view that the confluence of plasticity and computation in the same circuit elements is a core component of biological intelligence. My laboratory studies plasticity in the cerebral cortex during development, and plasticity during behaviour that is manifest as cortical dynamics. I will describe how cortical plasticity is implemented by learning rules that involve not only Hebbian changes and synaptic scaling but also dendritic renormalization. By using advanced techniques such as optical measurements of single-synapse function and structure in identified neurons in awake behaving mice, we have recently demonstrated locally coordinated plasticity in dendrites whereby specific synapses are strengthened and adjacent synapses with complementary features are weakened. Together, these changes cooperatively implement functional plasticity in neurons. Such plasticity relies on the dynamics of activity-dependent molecules within and between synapses. Alongside, it is increasingly clear that risk genes associated with neurodevelopmental disorders disproportionately target molecules of plasticity. Deficits in renormalization contribute fundamentally to dysfunctional neuronal circuits and computations, and may be a unifying mechanistic feature of these disorders.

A complementary systems theory of meta-learning

COSYNE 2023

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

COSYNE 2023

Model metamers complement existing benchmarks of biological and artificial neural network alignment

COSYNE 2023

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

COSYNE 2025

Activation of complement C3 in the course of rat experimental autoimmune encephalomyelitis

Complement receptors C3aR and CR3 mediate loss of synaptic inputs and NMDAR hypofunction in a mouse model of schizophrenia-associated high C4 expression

Complement responses and synaptic changes after transient microglia deficiency in the adolescent prefrontal cortex

Complementary coding of movement, reward expectation and outcome in the cerebellum and Basal Ganglia

Complementary lateral hypothalamic populations resist hunger pressure to balance nutritional and social needs

Engagement and strategy: complementary neural circuits for self-driven speed and accuracy changes in macaques

Grey and white matter microstructure play complementary roles supporting cognitive performance in adolescence of the ABCD cohort

Investigating the Effects of Ayurvedic Anti-Depressant Drug (Nardostachys Jatamansi DC.) Complementing Allopathic Medication in Patients with Major Depressive Disorder(MDD) - A double-blind study

Multiple beta oscillations bands underlie complementary cognitive and sensorimotor roles in the macaque frontal motor areas

Neuroprotective effect of sodium butyrate – the HDAC inhibitor - on the activation of the complement system in rat model of neonatal asphyxia

Simultaneous activation of two complementary targets, Kv7.2/3 and TSPO: a promising and novel treatment for Amyotrophic Lateral Sclerosis

Complement C3aR impacts functional brain connectivity in adolescence

FENS Forum 2024

Neurotensin and somatostatin cells of lateral septum are involved in the complementary regulation of social and feeding behaviors

FENS Forum 2024

Role of complement in regulating glutamate transmission in an experimental model of multiple sclerosis

FENS Forum 2024