Latest
Improved Surgical Visibility and Navigation during Endoscopic Treatment of Upper Tract Urothelial Carcinoma
Project Summary The importance of localizing and treating all upper tract urothelial cancer (UTUC) tumors during a renal sparing, endoscopic treatment is emphasized by the high risk of cancer progression from inadequate tumor treatment. Insufficient treatment necessitates kidney and ureteral removal (i.e., nephroureterectomy). Nephroureterectomy permanently compromises renal function, and increases morbidity and mortality, while negatively impacting a patient’s quality of life. In contrast, endoscopic treatment (i.e., using a laser to ablate only the tumors) improves long-term outcomes by sparing healthy kidney tissue. However, endoscopic treatment is underutilized compared to nephroureterectomy because it is difficult to accomplish. Successful endoscopic treatment is dependent on the surgeon’s ability to create a mental 3D map of the branched, intrarenal endoscopic anatomy intraoperatively from preoperative 2D imaging, which is extremely difficult. Since mental mapping relies on hand-eye coordination, memory, and spatial reasoning, it is inherently imprecise and its impact on accuracy and tumor treatment is dependent on the surgeon’s experience. To make matters worse, even when tumors are successfully visualized, the surgeon often cannot accurately assess the location of tumor margins or infer pathologic grade due to the limited field of view and depth of field (10mm and 6mm on average, respectively) of current scopes. The scopes only provide visualization of a small part of the surgical field at any instant. These inherent challenges prevent many surgeons from attempting endoscopic tumor treatment since incomplete treatment leads to a devastating, oncologic outcome. Our overall goal is to create an enhanced visualization and navigational system that makes endoscopic UTUC tumor treatment easier and more accurate for all surgeons, enabling wider utilization. Toward this goal, our specific objective in this proposal is to test the hypothesis that our system can make endoscopic UTUC surgery more accurate and efficient. To test this hypothesis, we propose three Specific Aims: Aim 1 involves the development of an automatic, real-time segmentation and grading system of UTUC tumors during endoscopic treatment. Aim 2 integrates a 3D navigational map of collecting system anatomy, which includes tumor and endoscope location, during endoscopic surgery. Aim 3 evaluates the system in patients, with zero risk to the human subjects. The endpoint of this R01 will be a fully validated enhanced visualization and navigational system for endoscopic UTUC surgery, which would provide the necessary experimental data towards a large-scale, multi-center clinical trial and future FDA approval. As our system would require only software integration to current endoscopic surgical cameras, all existing endoscopic surgical systems could in principle immediately benefit from the results of this project. In this way, we believe the success of our project will facilitate improved UTUC treatment and mitigate progression to a higher risk extirpative surgery.
Assessing the Efficacy of Mindfulness Apps
PROJECT SUMMARY: Rates of depression continue to rise and the mental health impact of COVID-19 has only accelerated trends. While mental health apps, specifically mindfulness apps, are not a panacea, they are popular tools that millions are turning to today for easy access, affordable, and low-stigma help. But increased reliance on mindfulness apps has not been supported by rigorous scientific evidence exemplified by few studies employing appropriate control conditions. Thus, this research is designed to focus on using 100% remote but robust methodology to assess the efficacy of mindfulness apps by applying a novel precision medicine framework. Our study first assesses the impact of the Digital Working Alliance by matching people with depression with a mindfulness app that may better support their personalized needs. We will compare those randomized to the to this matching condition to a digital placebo to better evaluate the efficacy of these mindfulness apps. For the first six weeks, participants will be asked to use the mindfulness app or digital placebo daily, and if not engaged, will receive reminders, allowing for the analysis of clinical outcomes during ideal usage patterns. For an additional six weeks, participants will be asked to use the app or digital placebo naturally, allowing for the elucidation of naturalistic usage patterns and evaluation if these usage patterns impact clinical outcomes. Across the entire study, we will capture smartphone-based digital phenotypes of behaviors (eg sleep, step, screen time), environments (eg home time, greenspace exposure), and symptoms (longitudinal ecological momentary assessment) to create personalized and predictive models of response that can be utilized to better understand factors impacting the efficacy of mindfulness apps, and in the future, better tailor apps to each person.
Communication and Hospice Online with Optimal Support and Engagement (CHOOSE)
Abstract Drawing upon the principles of social identity theory, existing literature, and our initial findings from family caregiver (FCG) online support groups (OSGs), our objective is to identify fundamental facilitator communication strategies that promote safe communication engage participants, and strengthen mechanisms of action (MOAs) within OSGs, ultimately enhancing health outcomes for hospice FCGs. Our pioneering initiative, Communication and Hospice Online with Optimal Support and Engagement (CHOOSE) is backed by compelling evidence highlighting the critical role of facilitator communication in reinforcing MOAs (a shared identity, social support, and social networks) in OSGs. Preliminary research underscores the transformative power of these MOAs in improving health outcomes for FCGs, yet current studies lack generalizability and statistical robustness. CHOOSE represents the first major, multisite, rigorously designed, and theoretically informed OSG intervention explicitly tailored for hospice FCGs of cancer patients. We aim to strengthen MOAs to enhance FCG well-being, reduce depression and anxiety, improve quality of life, and diminish loneliness. By advancing this critical research, we seek to provide a well-founded, evidence-based solution to the urgent needs of FCGs, making a significant impact on their health and well-being. We have outlined the following study aims: Aim 1. Determine the effect of the CHOOSE intervention on FCGs’ health outcomes compared to usual OSGs and usual hospice care. Aim 2. Examine direct and mediational relationships between CHOOSE participation, MOAs, and health outcomes. Aim 3. Explore the relationship between facilitator communication strategies and the FCG experience of the MOA to allow for future calibration of the intervention 1
Neuroinflammation in Cerebral Small Vessel Disease
Project Summary/Abstract Cerebral small vessel disease (cSVD) is a leading cause of vascular contributions to cognitive impairment and dementia (VCID), which is the 2nd leading cause of dementia and a significant contributor to Alzheimer’s disease (AD). Thus far, the underlying pathogenesis of cSVD is poorly understood. Several lines of evidence, including animal models, postmortem human brain pathology, and systemic inflammatory markers, demonstrated the damaging role of chronic neuroinflammation in cSVD. Direct evidence of neuroinflammation at the tissue level in patients with cSVD is still critically needed. The sphingosine-1-phosphate receptor 1 (S1PR1) regulates neuroinflammation through microglial and astrocyte activation and trafficking and has emerged as a promising target for neuroinflammation. In postmortem brains of patients with cSVD, we observed elevated S1PR1 expression and colocalization of S1PR1 with astrocytes and microglia. A novel 11C-CS1P1 PET radiotracer with high affinity and specificity targeting S1PR1 has been recently developed and validated in animal models and post-mortem human specimens. Under an FDA-approved eIND (IND 146548), we have successfully completed the safety and dosimetry study in healthy participants and performed preliminary studies in patients with cSVD. We found that 11C-CS1P1 PET uptake is significantly associated with WMH lesion burden in patients with cSVD after controlling for age, sex, race, vascular risk factors, and amyloid deposition. We hypothesize that 11C-CS1P1 PET uptake is a tissue-level biomarker of neuroinflammation to provide insight into cSVD severity, progression, and prognosis. We will 1) evaluate the relationship between 11C-CS1P1 PET uptake and cSVD neuroimaging abnormalities and cognitive impairment, 2) evaluate the test-retest repeatability and longitudinal evolution, and 3) determine whether 11C-CS1P1 PET uptake at baseline predict cSVD progression. The successful completion of this study will establish 11C-CS1P1 PET as an neuroinflammation imaging biomarker and investigate the role of neuroinflammation in cSVD pathogenesis and progression. It will lay a foundation for developing future therapies in modulating neuroinflammation.
Research on End-user Acceptability.and Long-term Impacts of HIV Cure Strategies (REALISE)
ABSTRACT Despite remarkable advances in HIV cure science, emerging cure candidates will likely involve trade-offs (e.g., incomplete eradication, monitoring burdens) and must compete with increasingly convenient long-acting ART; without early implementation guidance, even efficacious products may see limited uptake, particularly among the ~30–40% of people with HIV (PWH) in the U.S. who are not durably suppressed. We propose REALISE, a multidisciplinary program to define plausible cure profiles, quantify end-user preferences, and project population-level impact to inform product design and policy before market entry. Aim 1 conducts qualitative interviews with ~30 researchers and developers to delineate credible 10–20-year cure and long-acting treatment scenarios (eradication vs functional control, safety, monitoring, durability), yielding bounded “target product profiles.” Aim 2 elicits patient-centered preferences through a two-stage study: formative interviews (n=60; ≥50% not virally suppressed) to identify salient attributes; best-worst scaling (n=360 across Missouri, Georgia, and San Francisco) to prioritize attributes; and a discrete choice experiment (n=360) to quantify trade-offs versus alternative therapies, with latent class analysis to identify preference segments and estimate potential reach. Aim 3 integrates preference-based uptake from Aim 2 with Aim 1 efficacy and cost inputs in a mathematical model to estimate health impact, QALYs, net QALYs, and incremental cost-effectiveness across heterogeneous populations and Ending the HIV Epidemic jurisdictions. Innovation lies in linking cure R&D horizons to end-user preferences and transmission-dynamic outcomes, an approach that anticipates real-world use rather than retrofitting after approval. Deliverables include ranked cure attributes for product optimization, uptake projections including among unsuppressed PWH, and jurisdiction-specific value assessments to guide public health investment. By aligning cure design with what patients will accept and systems can sustain, REALISE will accelerate effective deployment of future cure strategies and maximize their contribution to Ending the HIV Epidemic. In doing so, this study advances NIH's priorities by connecting implementation science with prevention, treatment, and cure research. Using a multidisciplinary strategy to refine and extend `target product profiles,' REALISE will ensure cure development reflects patient needs and accelerate translation into real-world benefit.
The Role of the Intestinal Microbiota in Sepsis Mortality
Project Summary/Abstract Sepsis is a life-threatening condition characterized by a dysregulated host response to infection that can cause multi-organ damage and death. As the leading cause of in-hospital mortality, sepsis mortality rates reach up to 50%, and account for approximately 270,000 deaths and $38 billion annually in health care costs in the United States. Notably, patients with similar medical backgrounds can have vastly different sepsis outcomes— some survive with medical treatment while others die. The reasons for this dichotomy are unknown but is seen across all forms of bacterial bloodstream infections, is not specific to any strain-level differences in the infecting pathogen and cannot be explained by human genetic differences. Human microbiota studies suggest that gut microbial dysbiosis is associated with sepsis mortality and that these alterations influence gut barrier breakdown, leading to gram-negative bacteremia—one of the most common causes of sepsis and mortality. However, there are a lack of studies that investigate the causal role of the intestinal microbiota in sepsis mortality. This K08 proposal will elucidate the role of the intestinal microbiota in sepsis mortality. Utilizing the well- established murine model of sepsis by intraperitoneal injection of lipopolysaccharide (LPS), we combine microbiota taxonomic sequencing and metagenomics, advanced bioinformatic techniques and prediction modeling, with knowledge of mucosal immunity and germ-free mouse systems to characterize the microbiota features and members that correlate with, predict, and cause sepsis mortality. This proposal is organized into two specific aims: (1) identify baseline stool microbial features associated with and predictive of sepsis outcomes and (2) determine how colonization with immunostimulatory microbes heightens sepsis mortality. In this work, I will holistically characterize the host immunologic and microbiota features that are associated with and predictive of mortality and experimentally identify microbes and microbial pathways that cause death in our model. These findings will reveal new microbial and host biomarkers of sepsis mortality and identify novel targets for sepsis prevention and treatment to reduce the overall mortality rate of this deadly disease. My long-term goal is to become an independent physician-scientist who integrates cutting-edge computational methods with experimental biology to identify predictive biomarkers of disease onset and outcomes, investigate how they influence disease processes, and develop novel therapeutic and preventive strategies to improve patient care. This proposal details specific research aims and a structured career development and training plan that will allow me to acquire focused, in-depth and multidisciplinary training under the guidance of an internationally recognized team of experts in clinical infectious diseases, host-microbiota interactions, immunology, immunometabolism, and computational biology. The knowledge generated will address the fundamental role of the microbiota in sepsis outcomes and inform future preventative and therapeutic strategies that will lower the sepsis mortality rate worldwide.
FIRE-PF: Developing and Testing a Trauma-Informed Alcohol Intervention to Enhance Mental Health in Firefighters
PROJECT SUMMARY Alcohol use and hazardous drinking are ubiquitous among firefighters in the United states and is associated with significant physical and mental health risks for this population. Due to the nature of their work, firefighters experience substantially higher rates of trauma exposure and are subsequently at greater risk of developing specific mental health conditions compared to the general population, particularly trauma-related psychopathology (e.g., posttraumatic stress). Hazardous drinking and posttraumatic stress frequently co-occur among firefighters, leading to poorer health outcomes compared to either condition alone. Despite this elevated risk, firefighters often lack access to tailored, empirically supported interventions, and no existing mental health interventions address hazardous drinking in a trauma-informed framework for this at-risk population. Personalized feedback interventions (PFIs) are a promising approach that could address this gap. By delivering brief, patient-centered feedback on drinking behaviors and perceptions within the context of trauma and occupational stress, PFIs aim to reduce problematic drinking behaviors and stigma related to coping-orientated drinking and improve stress management strategies. PFIs can be brief, cost-effective, and easily disseminated in a format accessible to large groups, making them a strong candidate for use with firefighters who face critical barriers to engaging in traditional mental health programs. This innovative study aims to develop a single-session, trauma-informed, online PFI tailored specifically for firefighters, using a comprehensive, three-phase approach to address three primary aims. The Development Phase involves developing, adapting, and enhancing a trauma-informed PFI by gathering qualitative feedback from firefighters (N = 45) and using an iterative, rapid user-centered design approach to ensure the intervention is engaging for firefighters as well as relevant and aligned with fire service culture. The Evaluation Phase will assess the feasibility, acceptability, and preliminary impact of the PFI in a mixed-methods longitudinal open trial with firefighters (N = 50), with a focus on the intervention's usability, delivery, and influence on drinking behaviors. The Implementation Planning Phase will involve qualitative and quantitative assessments with fire service leaders (N = 15) to identify implementation barriers and shape future research testing the implementation process for the intervention and inform future strategies for resource integration and fostering sustainable community partnerships. This proposal will equip Dr. Lebeaut with essential training for an independent research career, including training in (1) qualitative methodologies, (2) user-centered design, (3) developing, adapting, and enhancing trauma-informed alcohol interventions, and (4) developing collaborative relationships with community partners in the fire service. The proposed study will directly inform a future R01 to evaluate the intervention’s efficacy and scalability and support the development of a firefighter-focused research program.
Urothelial Resurfacing with Irreversible Electroporation for Adjuvant Therapy of Bladder Cancer
PROJECT SUMMARY Over 70% of bladder cancer (BCa) patients are diagnosed with early-stage and localized non-muscle invasive disease (NMIBC), yet achieving durable cancer-free survival remains a significant challenge. Most of these patients will experience local tumor recurrence within five years following standard of care (SoC) transurethral resection of bladder tumor (TURBT) and intravesical adjuvant chemo- or immunotherapy. Recurrence is driven by microscopic tumors and premalignant lesions dispersed within the urothelial layer that survive and escape these treatments. As TURBT effectively treats tumors visible on imaging, current research has predominantly focused on drugs and biologics for improving intravesical adjuvant therapy. In this proposal we pose the provocative question whether a TURBT-like ablative technique can be extended to debulk malignancy in the entire bladder and investigate the synergy with intravesical adjuvant therapy in improving outcomes. Our objective is to address this technology and knowledge gap by developing and validating whole bladder urothelial resurfacing (WBUR) using irreversible electroporation (IRE). During IRE, microsecond-long pulsed electric fields (PEF) are used to induce rapid cell death by catastrophic permeabilization of the cell membrane, without affecting the extracellular matrix (ECM) within the treated tissue. In prior work, we designed devices that utilized this unique mechanism of IRE for performing penetrative ablation in the ureter, bile duct and bronchus of swine while preserving lumen function. Our findings provided strong rationale for IRE being an ideal candidate for WBUR as alternate techniques such as thermal ablation or ionizing radiation must be performed with extreme care in the bladder to avoid perforation or fistula formation. In subsequent preliminary work we developed technology to demonstrate the feasibility and safety of WBUR with IRE in a rat model of BCa and scalability in human-sized swine bladder. In Aim 1, we will investigate the cancer treatment efficacy of combination WBUR and intravesical adjuvant therapy. In Aim 2, validate WBUR derived liquid biopsy for monitoring cancer status. In Aim 3, engineer PEF delivery strategy to enhance the safety and specificity of WBUR. The innovation of our proposed work is defined by developing whole bladder ablation as a debulking strategy and examining its synergy with SOC adjuvant therapy (Aim 1), enabled by new electrode paradigm and PEF delivery strategy (Aim 3), monitoring by an unconventional liquid biopsy approach (Aim 2). Our work can immediately aid the management of NMIBC patients who cannot undergo radical cystectomy, with future application as a cancer prevention strategy in high-risk patients. Success of individual aims will result in major contributions to the topics of IRE, BCa treatment and diagnosis.
Baby Toolbox Training and Certification Program
PROJECT SUMMARY Our objective is to improve early childhood outcomes and support the expansion of the NIH Infant and Toddler Toolbox (Baby Toolbox) by providing comprehensive training support to those interested in using it. The Baby Toolbox is a brand new, nationally-normed assessment for infants 1-42 months, commissioned by NICHD and released for public use in 2025. The Baby Toolbox is administered entirely on an iPad and includes 35 measures across six domains using novel technology (e.g., gaze tracking, automatic scoring, computerized adaptive testing). It has the potential to bring harmonization to the developmental fields, but in order for it to become a common currency for developmental research as envisioned, researchers need to know how to administer it and how to train others to administer it. We propose an education program that will include a week-long training workshop, certification activities, and post-workshop support to create expert cohorts of Baby Toolbox test administrators. Individuals who attend the workshops can become certified test trainers, capable of training others at their home institutions to administer the assessment thus creating a self-sufficient training model. Through the proposed educational program, we will provide funding to cover lodging, meals, and incidentals during the workshop, in addition to subsidizing transportation to/from the workshop and provide a one-year subscription to the Baby Toolbox. A portion of slots will also be set aside for those without current grant funding. Our team is highly qualified to complete these tasks because we have led the effort to develop the Baby Toolbox assessment and have already completed multiple training workshops for contract deliverables. This grant would continue the efforts started by the NICHD in funding the Baby Toolbox by helping support its rollout, implementation, and growth. To meet these goals, we have the following aims: Aim 1: Create cohorts of trained Baby Toolbox examiners who can catapult the Baby Toolbox into widespread use by hosting a comprehensive week-long education program (training workshop) yearly for individuals to learn how to administer and train others to administer the Baby Toolbox, Aim 2: Expand the use of the Baby Toolbox by recruiting and financially supporting individuals who will bring the Baby Toolbox into a variety of research and clinical settings. Aim 3: Build a virtual training resource of videos and materials to support ongoing fidelity checks with certified trainers, and future training efforts.
Utilizing integrin-targeted PET imaging and therapeutics to predict and treat radiation-induced pulmonary fibrosis
Project Summary/Abstract. Lung cancer is the leading cause of cancer death in the US, with over 125,000 deaths annually. Radiation therapy (RT) is a critical component of curative lung cancer treatment for many patients. However, radiationinduced pulmonary fibrosis (RIPF) is a common side effect that carries a poor prognosis with limited treatment options. Up to 40% of patients with lung cancer who receive RT may experience RIPF. RIPF is a late effect of RT, typically occurring 3 or more months after treatment. The symptoms of RIPF can include shortness of breath, pleural effusions, decreased lung function, and respiratory failure. Cell surface integrin heterodimers play a key role in the pathogenesis of RIPF. In particular, the integrin αvβ6, which is expressed at a low level in the alveolar epithelium at baseline, is significantly upregulated upon RT damage. The key role of integrin αvβ6 in RIPF is illustrated by studies in which mice lacking integrin αvβ6, or treated with an αvβ6-blocking antibody, do not develop RIPF. Here, we propose to translate this mechanistic understanding of RIPF into novel approaches for monitoring and treating RIPF. We hypothesize that non-invasive αvβ6 PET imaging will be safe and can specifically bind to αvβ6 in patients with RIPF. Additionally, we hypothesize that a novel small-molecule integrin antagonist, IDL2965, can mitigate and treat RIPF in mice. In this project, we are utilizing mice to model RIPF, as mice develop RIPF that mimics human disease. In addition, cellular and in vitro models do not approximate the complex biology leading to the development of RIPF. Our data using [64Cu]Cu-DOTA-αvβ6-BP to detect early RIPF in mice are compelling in both single-fraction high-dose RT and lower dose-larger volume RT models (Lo et. al, IJROBP 2025). However, to progress to clinical trials in patients with cancer, we will obtain data to submit an Investigational New Drug (IND) application to the FDA. Importantly, we propose translating [64Cu]Cu-DOTA-αvβ6-BP PET imaging into patients with lung cancer, allowing us to better identify RIPF and develop a tool to determine the efficacy of IDL-2965 in future clinical studies. The specific aims of the proposal are: (1) Characterize the utility of [64Cu]Cu-DOTA-αvβ6-BP in mice with conventionally fractionated RT and identify circulating biomarkers of RIPF, and determine the in vivo toxicology of [64Cu]Cu-DOTA-αvβ6-BP to prepare and submit an exploratory Investigational New Drug (eIND) application to the FDA, (2) Conduct a first-in-human clinical trial of [64Cu]Cu-DOTA-αvβ6-BP to determine its safety and human dosimetry in patients with evidence of RIPF from computed tomography or in healthy controls, and (3) Determine the effect of integrin antagonism using IDL-2965 on mitigating RIPF in preclinical mouse models. The goals of this proposal are two-fold: (1) demonstrate safety and target specificity for [64Cu]Cu-DOTA-αvβ6-BP so that it can be used in future studies to identify RIPF and evaluate the efficacy of anti-fibrotic therapies, and 2) determine the ability of IDL-2965 to prevent RIPF in preclinical mouse models.
Characterization and functional impact of somatic numtogenesis in the human cortex
Project Summary This project focuses on studying nuclear mitochondrial insertions (numts), which are fragments of mitochondrial DNA that get integrated into the nuclear DNA of human cells. While this process, called numtogenesis, occurs naturally and can be passed down to future generations, it has also been observed to occur somatically in our bodies. Historically the function of numts has been difficult to study because they are repetitive and difficult to map with short read sequencing technologies, but there is emerging evidence that they can influence cell function and play a role in diseases, aging, and even complicate genetic studies. Our recent research discovered numts in the human brain’s cortex, and their presence appeared to be linked with earlier death, suggesting they may play a role in aging. However, due to limitations in the data we used, we could not fully explore the extent or impact of these insertions across different tissues or individuals. This project aims to map and study numts in more detail, especially in the human cortex, to further explore this ongoing transfer of DNA from the mitochondria to the nuclear genome and their potential to impact aging and brain function. We will accomplish this by 1) improving sequencing methods to detect numts, 2) comparing their presence across different tissues, and 3) investigating how they affect gene expression and DNA structure. By the end of the project, we aim to provide a model for how such somatic variation may occur and impact cellular function at the tissue level.
The Pyruvate-Lactate Metabolic Axis in Heart Failure and Recovery
PROJECT SUMMARY/ABSTRACT Heart failure (HF) is a leading cause of mortality worldwide. The metabolism of the failing heart is commonly characterized by increased glucose uptake, glycolytic dependence, and reduced oxidative phosphorylation. We previously demonstrated that blocking glucose oxidation is sufficient to cause hypertrophy and subsequent HF. Additionally, our preliminary data shows that an altered pyruvate-lactate metabolic axis may be pivotal in human HF. Research investigating both the mechanistic regulation and biological roles of the pyruvate-lactate metabolic axis in cardiac metabolism during HF and cardiac recovery is warranted and also has the potential to identify novel druggable pathways to target for future pharmacological approaches. The overall objective of this application is to test the hypothesis that impaired pyruvate oxidation is a cardinal feature of HF in humans and animal models and that myocardial recovery is tightly coupled to normalization of the pyruvate-lactate metabolic axis. We will quantify the pyruvate-lactate metabolic axis in human HF and myocardial recovery (Aim 1). Next, we will determine the essentiality of the pyruvate-lactate metabolic axis for HF and cardiac recovery (Aim 2). Lastly, we will define cell-autonomous mechanisms that regulate the pyruvate-lactate axis in HF and recovery (Aim 3). These experiments will allow us to identify patterns of metabolic alteration in the pyruvate-lactate axis and molecular pathways during HF and myocardial recovery. Understanding the role of pyruvate and lactate metabolism in HF and myocardial recovery is cutting-edge research. Our unique access to human HF myocardium from patients administered stable isotope-labeled glucose or lactate to quantitate pyruvate metabolism in HF and recovery is state-of-the-art and will likely help us reveal new fundamental mechanisms of cardiac metabolism and expedite the successful translation of therapeutics being validated in various models of HF and recovery.
Development of an at-home weight-shifting balance game with musical biofeedback for older adults
Reducing fall risk is a dire societal need that requires interventions that over-prepare individuals to perform maneuvers important to daily mobility. Falling is often caused by improper weight shifting, and interventions that focus on developing weight-shifting abilities have shown improvements in clinical balance outcomes, including reduced fall incidence. Interventions that combine challenges to the cognitive and motor systems may be necessary to reduce fall-risk. Our central hypothesis is that leveraging gamification and “musical biofeedback” will improve balance abilities through practicing weight-shifting skills with increased cognitive and physical demands. Musical biofeedback conveys biological sensor data from the participant through specific musical sound parameters in real-time. Of particular interest in the proposal is the applicability to use musical biofeedback to train weight-shifting skills in a musical game. The goal is to develop a wearable sensor system that can be used at-home to practice and develop balance skills, while supporting cognitive engagement and motivation to adhere to exercise goals. To start, we are focusing on older adult end-users who typically have home exercise programs focused on weight-shifting. However, in the future, many other populations can benefit from this technology. In this Trailblazer award, the PI is leveraging her background in studying complex human maneuvers, developing musical biofeedback for older adults, and in algorithm development for mHealth sensors. The transdisciplinary team includes expertise in engineering, gamified rehabilitation technologies, home exercise programs, psychology of aging, and music. In the proposed research, our goals are to evaluate responses to the musical biofeedback game (Aim 1), validate the mHealth sensor system (Aim 2), and phenotype the gameplay behavior of fallers vs. non-fallers (Aim 3), relative to their baseline characteristics (Sub-Aim 3). Our long-term goal is for a variety of people to improve their balance control patterns while supporting and building their self-efficacy. We envision users, including older adults, training with musical biofeedback to safely (and enjoyably) prepare themselves to ambulate in their community – improving and preserving their mobility. The proposed research will pioneer using an emerging clinical technology – musical biofeedback – to train balance during weight-shifting tasks. The proposed research innovates how musical biofeedback, gamification, and focusing on weight-shifting and turns in balance training can be leveraged to challenge cognitive and physical body systems in fall-risk populations. By developing new therapy options and better understanding responses relative to baseline characteristics, this research improves clinical practices to reduce fall risk and deepens our understanding of dynamic balance control. Finally, the results of the proposed research will have translational impacts to help other fall-risk groups.
Multiplex single-cell chemical genomics to identify small molecule modulators of tumor cell-intrinsic immunogenicity in glioblastoma
PROJECT SUMMARY/ABSTRACT Glioblastoma multiforme is the most common and aggressive primary brain cancer. Despite a multimodal treatment regimen of surgical resection, chemotherapy, radiotherapy, and tumor-treating fields, most patients succumb to the disease within two years of diagnosis. Cancer immunotherapy strategies have emerged as a powerful tool for treating aggressive solid tumors such as melanoma and non-small cell lung cancer. However, current strategies have led to low response rates in glioblastoma, resulting from its low immunogenicity. The proposed research program aims to identify small molecules capable of increasing the immunogenicity of glioblastoma cells, focusing on altering gene expression programs associated with recognition by the immune system and the ability of cytotoxic immune cells to target glioblastoma for destruction. We will use highly multiplex chemical transcriptomic profiling to determine the molecular consequence of exposing glioblastoma neurosphere models to 3,792 small molecules, targeting the majority of cellular activities and clinically relevant drug targets as well as a collection of previously identified immunomodulators. We will then determine how each exposure alters the expression of gene programs associated with tumor cell immunogenicity and response to therapy, including the expression of genes associated with the recognition by the immune system and those associated with immune checkpoints, as well as programs more broadly correlated with resistance to anti-cancer therapies. Chemical hits that meet specific criteria will be subjected to a medicinal chemistry review to further classify compounds by their suitability for treating malignancies in the brain. We will then screen chemical hits to determine their ability to modulate immune-mediated tumor cell killing using tumor- immune cell co-culture. Lastly, we will leverage gene editing and flow cytometry to validate hits based on on- target molecular effects and further refine the mechanism of action by inspecting the ability of drugs to modulate immunogenic programs at the protein level. Our chemical genomics screens aim to provide crucial information regarding the link between pathway activity and immunomodulation in GBM, a critical step to guide future efforts in GBM immunotherapy. More broadly, our study will establish single-cell chemical genomics as a scalable platform for phenotype-based screening for preclinical prioritization of chemical modulators of complex transcriptional phenotypes and provide a framework for hit prioritization, establishment of pipeline robustness and hit validation in the context of single- cell chemical genomics screens.
Molecular strategies for resolving differential regulation of dopamine subpopulations
Project Summary/Abstract Dopamine neurons in the ventral tegmental area (VTA) fire action potentials in complex patterns of tonic and phasic activity in response to environmental stimuli and during behavioral tasks. Transcriptomic, anatomical, and functional studies have established that VTA dopamine neurons can be divided into multiple subpopulations with variable gene expression, projection patterns, and response profiles. We recently completed a transcriptomic study that identified genetic markers for three distinct subpopulations of VTA dopamine neurons, and also found evidence for variability in ion channel gene expression between populations that correlated with differences in activity-dependent gene expression. However, much remains unknown regarding how specific genes encoding ion channels, receptors, transcription factors, or other signaling components contribute to the variability in baseline physiological properties observed across the VTA. Here we propose to combine slice electrophysiology recordings of VTA dopamine neurons with post-hoc single-cell sequencing analysis (i.e. patch-seq), which will allow us to directly correlate gene expression and physiological properties in order to identify candidate genes that may be key drivers of the variability between subpopulations. We also propose to validate and utilize a novel dual-recombinase CRISPR/Cas9 system for targeted gene mutagenesis in intersectional neuronal populations, which will provide a mechanism for testing gene function with unprecedented precision. We will use this approach to test the function of two candidate ion channel genes, the potassium channels Kcnh5 and Kcnh7, previously identified in our transcriptomic study as potential contributors to dopamine neuron action potential firing properties. We hypothesize that these genes are important for enabling rapid action potential firing in highly excitable dopamine neurons found in specific subpopulations. As a whole, with this proposal we aim to generate a valuable dataset linking gene expression in VTA dopamine neurons with physiology and subpopulation identification, as well as develop an intersectional gene mutagenesis strategy that can be used throughout the brain to precisely target neuronal subpopulations to test gene function. With this approach, we hope to facilitate future precision targeting of the dopamine system and dopamine-dependent behaviors.
Transposable element silencing as a regulator of salivary gland immune homeostasis
PROJECT SUMMARY/ABSTRACT Sjogren’s syndrome (SjS) is a chronic autoimmune disorder marked by salivary and lacrimal gland dysfunction, lymphocytic infiltration, and progressive secretory decline. While traditionally viewed as immune cell–driven, emerging evidence suggests that epithelial cells may initiate local inflammation. However, the molecular triggers originating from epithelial cells remain poorly defined. Transposable elements (TEs), including endogenous retroviruses (ERVs) and LINEs, are normally repressed through DNA methylation, histone modifications, and heterochromatin organization. Failure of TE silencing mechanisms due to aging, hormonal changes, or stress results in cytoplasmic dsRNA accumulation, nucleic acid sensor activation, and type I interferon signaling. These TE-derived nucleic acids are increasingly recognized as endogenous triggers of immunological stress that disrupt cellular homeostasis. Our preliminary data show widespread TE derepression and upregulation of interferon-stimulated genes in salivary glands from patients with SjS. To mimic this phenomenon, we will inducibly delete Setdb1, a key histone H3K9 methyltransferase, in defined epithelial compartments of the salivary gland. This will allow us to model compartment-specific TE derepression and assess its impact on both innate immune activation and adaptive immune responses. We will also test how aging and estrogen deficiency disrupt TE repression in basal/ductal versus acinar cells using lineage tracing and epigenomic profiling. Finally, we will evaluate the therapeutic potential of reverse transcriptase inhibitors and chromatin-modifying drugs in attenuating TE-driven inflammation. This exploratory study will uncover how failure of TE silencing contributes to epithelial-driven autoimmunity in SjS and will provide a foundation for future targeted epigenetic manipulations in human tissues and patients.
Uncovering genetic determinants of carbapenem resistance in Klebsiella pneumoniae
Carbapenem-resistant Klebsiella pneumoniae represents an urgent global health threat due to its increasing prevalence and high mortality rates, necessitating a comprehensive understanding of its resistance mechanisms. While key resistance mechanisms and their genetic determinants are known, such as beta- lactamases and porin mutations, the cause of resistance in many strains remains elusive. Moreover, other strains that carry known genetic carbapenem-resistance factors have been found to still be susceptible to carbapenems for unclear reasons. Further, strains can carry genetic elements which, while not conferring resistance directly, can promote resistance indirectly by accelerating its acquisition, such as through mutations in DNA repair systems or mobile genetic elements. To address these knowledge gaps, we propose a genome-wide association study (GWAS), with the aim of maximizing the discovery of gene variants associated with meropenem resistance, with experimental validation of candidates to identify true causal variants. We will overcome limitations of prior studies in the following ways: 1) We have compiled an expanded data set of publicly available K. pneumoniae genomes from strains isolated across a wide distribution of countries, with in hand access to >100 isolates upon which experimental validation studies will be performed. 2) We will perform comprehensive capture of genetic variants by employing a reference-free GWAS, utilizing unitigs, stretches of DNA sequence that represent the entire spectrum of genetic variation. 3) We will enhance statistical power to detect genetic variants with even subtle effects on resistance by using a quantitative, continuous minimum inhibitory concentration (MIC) phenotype to meropenem rather than a binary designation of resistant or susceptible. 4) We will reduce the number of false positives arising from correlation, or linkage disequilibrium (LD), with known carbapenemase and other known resistance factors by performing a conditional GWAS, where known factors are included as covariates. 5) We will further mitigate confounding effects due to population structure and LD, which cause non-random relationships between variants, by utilizing a pangenome-wide regression with an elastic net penalty. 6) Crucially, we will functionally validate our findings, which will include genetic variants associated with increased resistance, whether through direct or indirect mechanisms, as well as those that may restore susceptibility in strains already possessing known resistance factors. We will bridge the gap between GWAS findings and functional validation by leveraging our high-throughput experimental capabilities. This integrated approach promises to uncover novel mechanisms of carbapenem resistance, its acquisition, and susceptibility in K. pneumoniae, with the potential to inform the development of future diagnostics or therapeutic strategies.
Circulating and Mucosal Predictors and Effects of Therapeutic Interleukin-23 Blockade in Crohn's Disease
PROJECT SUMMARY/ABSTRACT Since its discovery 20 years ago, the cytokine interleukin (IL)-23 has increasingly been implicated in the pathogenesis of immune mediated diseases, such as Crohn’s disease (CD). Consequently, four monoclonal antibodies that block IL-23 are currently approved CD therapies, including risankizumab. Although suppression of pathogenic Th17 cells has been widely cited as the mechanism by which IL-23 blockade controls disease, there is a paucity of data to indicate that this is how such therapy works, and a few other immune cell populations expressing the IL-23 receptor could instead be its target. We therefore propose to study how risankizumab affects not only Th17 cells, but also mucosa-associate invariant T (MAIT) cells γδ T cells and (in the colon) type 3 innate lymphoid cells (ILC3s). In addition to quantifying these cells, we will study their gene expression to detect phenotypic differences in treated patients, and in the case of T cells, track their clonal expansion and deletion through their unique T cell receptor sequences. In colon samples, we will use a combination of single cell sequencing of sort-enriched immune cell populations and spatial transcriptomics to characterize cells in situ, at the site of disease, and determine how IL-23 blockade affects their microenvironment in vivo. By contrasting results in patients who do or do not respond therapeutically to IL-23 blockade, we will reveal valuable insights into how this treatment succeeds or fails in CD, in the process identifying predictive biomarkers to guide treatment decisions, and potentially identifying future molecular targets with which to prevent treatment failure.
Autoreactive T cells in lupus
The autoimmune disease systemic lupus erythematosus (SLE) is characterized by loss of adaptive immune tolerance in conjunction with innate immune system hyperactivity. Autoantibodies, produced by plasma cells derived from activated B cells, form proinflammatory immune complexes. These immune complexes drive feed forward loops that sustain a systemic inflammatory environment and deposit in tissues leading to potentially fatal organ damage. B cells receive help from T cells to produce antibodies. They also contribute to disease by shaping T cell responses and secreting cytokines. Recent case reports in which SLE patients were treated with anti-CD19 CAR-T cell therapy to deplete B cells highlight the pathogenic role of B cells in lupus and their value as a therapeutic target. However, a better understanding of how autoreactive B cells interact with autoreactive T cells may reveal more targeted points of therapeutic intervention that specifically block autoreactive responses while sparing protective ones. Antigen specific interactions between CD4+ T cells and B cells are required for the development of autoimmune disease in lupus. However, whether these critical interactions occur in germinal centers, where competition for CD4+ T cell help selects high affinity B cells, or in extrafollicular responses, where B cells may avoid peripheral tolerance checkpoints, is unclear. Gene expression profiles and pathways specific to autoreactive CD4+ T cells, and how they are shaped by their interaction with autoreactive B cells, are also ill defined. CD8+ T cells, which recognize antigen presented on MHC Class I, have also been suggested to modulate the fate of autoreactive B cells. They can directly kill autoreactive B cells as a means of tolerance, and a subset of CD8+ T cells has recently been shown to have B cell helper function. Whether and how such interactions between B and CD8+ T cells enhance or suppress the development of lupus is unknown. Here, we will use genetic and in vivo proximity labeling approaches to address these knowledge gaps. In Aim 1, we will test the hypothesis that antigen specific interactions between B and CD8+ T cells promote B cell activation and autoantibody production in lupus. We will prevent B cells, but not other cells, from undergoing cognate interactions with CD8+ T cells via B cell-specific deletion of B2M, a component of the MHC Class I complex, in two lupus models. In Aim 2, will use the uLIPSTIC in vivo proximity system to label all T cells interacting with B cells in lupus models compared to wild type controls. Features specific to these autoreactive T cells will be defined by flow cytometry, scRNA Seq, and scTCR-Seq. These studies will provide valuable molecular and cellular insight into the mutual activation of B and T cells in lupus. They will set the stage for future mechanistic studies defining the role of autoreactive T cell specific genes and pathways and potentially highlight new therapeutic targets specific to autoreactive B/T interactions.
Bacterial ferrous iron sensing via the BqsRS (CarRS) two-component system
Project Summary Pseudomonas aeruginosa (Pa) is an opportunistic and increasingly antibiotic resistant Gram-negative bacterium that is one of the major causes of chronic nosocomial infections in the United States. The colonization of Pa within a host is often linked to the bioavailability of nutrients, such as iron, and Pa has multiple iron acquisition pathways that allow it to adapt readily to the variety of environments it may encounter within a human host. Pa responds to these dynamic environments commonly through the use of two-component signal transduction systems (TCSs) that are important mediators of signal transduction and allow pathogens to detect chemical and/or physical changes in the environment in order to control basic cellular processes. Previous studies have identified a biofilm and quorum sensing TCS known as BqsRS (also known as CarRS) that regulates biofilm formation and decay in Pa through the sensing of extracytoplasmic Fe2+ and Ca2+. Among its targets, the BqsRS TCS is known to regulate rhlAB and rhlC, critical genes for rhamnolipid production and biofilm formation that are also known to be connected to iron homeostasis and antibiotic resistance. Moreover, the deletion of either bqsR or bqsS in PAO1 results in a significant increase in biofilm formation but reduced biofilm dispersion, the latter of which is important for downstream infections. These observations highlight the importance of the BqsRS TCS to Pa virulence, but there is a foundational lack of understanding regarding the structure, the selectivity, and the mechanism of this system. The ultimate goal of this proposal is to generate a mechanistic and functional understanding of BqsRS at atomic, molecular, and organismal levels in order to exploit this system as a means of reducing or stemming the virulence of opportunistic pathogens such as Pa. The objectives of this exploratory grant are to determine the structural and molecular characteristics of BqsRS, to define how these properties govern BqsRS metal selectivity and function, and to examine a new role of the BqsRS system in regulating the Feo system in P. aeruginosa. Ultimately, the accomplishment of this exploratory grant will deliver fundamental mechanistic insight into a critical metal-sensing TCS and lay the groundwork for future studies that may be designed to target this system and its homologs for additional bacterial exploits.
A Novel Mitochondrial-Targeted Inhibitor of NLRP3 Inflammasome Activation
PROJECT ABSTRACT Inflammasomes are multiprotein complexes of the innate immune system that assemble upon detecting specific molecular patterns associated with pathogens and cellular damage. Once assembled, activated inflammasomes trigger a cascade of downstream events that culminate in cell death and inflammation. Aberrant activation of the NLRP3 inflammasome contributes to the pathogenesis of numerous inflammatory and degenerative diseases, including gout, atherosclerosis, type 2 diabetes, and Alzheimer’s disease. Despite its central role in innate immunity and inflammation, there are no FDA-approved therapies that directly target the NLRP3 inflammasome. Current strategies rely on biologics that inhibit downstream pro-inflammatory cytokines produced from inflammasome activation, such as interleukin-1β (IL-1β), but do not block upstream inflammasome assembly or pyroptotic cell death, highlighting a critical unmet need for selective small-molecule inhibitors with novel mechanisms of action. To address this gap, we identified a covalent small molecule, Compound-2 (C-2), that robustly inhibits NLRP3 inflammasome activation in murine and human immune cells. C-2 suppresses multiple downstream events triggered by inflammasome activation, including IL-1β secretion and pyroptosis, with no apparent toxicity. Chemoproteomic profiling revealed that C-2 interacts with SLC25A3, a mitochondrial phosphate and copper transporter, suggesting a previously unrecognized regulatory node in inflammasome signaling. This R21 project aims to (1) elucidate the mechanism by which C-2 suppresses NLRP3 activation and (2) define the molecular interaction between C-2 and SLC25A3 and its functional consequences. Our studies will integrate biochemical, cellular, and in vivo approaches to uncover a novel mitochondrial mechanism of inflammasome regulation and validate C-2 as a first-in-class inflammasome inhibitor. Successful completion of this project will lay the foundation for future therapeutic development targeting mitochondrial- inflammasome crosstalk in inflammatory disease.
Augmented-reality guided lumpectomy
Abstract Far too many women with a newly diagnosed breast cancer must undergo repeat surgery because positive margins were found at the time of their initial lumpectomy. Supine volumetric MRI has potential to improve surgical accuracy, and reduce re-excision rates by nearly 50%. Spurred by our preliminary results improving depth perception via projected apertures and integrating intra-operative marker tracking into commercial Augmented Reality systems, we have developed a highly accurate initial prototype Augmented Reality system to project volumetric MRI data inside the breast to guide surgery. In Aim 1, we will compare methods of projecting apertures in a phantom model of lumpectomy. In Aim 2, we will test the final prototype system in a pilot study of 30 women with new breast cancer. Standardized use of cavity- and shave-margins will enable paired comparisons between standard and AR-guided techniques in the same patients, including ability to reduce positive margin rates and minimize overexcision. Ultimately the system will be ready for future randomized controlled trials to measure efficacy as the next step toward broad clinical adoption.
Targeted Prodrug Cytokines for Metastatic Breast Cancer Immunotherapy
Project Summary. Our approach directly addresses key limitations in targeting and treating metastatic breast cancer, where we propose the selective activation of modular immune-modulating cytokines within the hypoxic and ROS-active TME for delivery across the BBB, providing the necessary pre-clinical data for future clinical translation. The in vitro and in vivo investigations of this novel immunotherapeutic in immunocompetent models will allow our team to study the interplay between tumor-driven immune activation, cytokine signaling, and anti-tumor immunity in both primary and metastatic sites, and establish a robust groundwork for subsequent clinical validation within the OSUCCC. This proposal addresses two key challenges in developing a novel immunotherapy strategy for breast cancer by answering two hypotheses: (1) can a modular immunotherapy platform with tumor-selective activation of prodrug recombinant cytokines overcome these limitations in drug delivery, and (2) can the development of nanobody-cytokine fusions that can selectively target primary breast cancer tumors and cross the BBB to reach metastatic tumor sites? The first hypothesis focuses on achieving tumor environment-specific activation of prodrug-based recombinant cytokines. Protein cytokines are highly potent, and while others have tried to block their activity using a fused genetic linker to ‘mask’ functionality, no one has yet attempted to use a non-canonical-based chemical strategy to achieve this inhibition. Immune-modulating cytokines will be recombinantly expressed with integrated ncAAs that block cytokine activity until the function is regenerated in the breast cancer TME. Once the cytokine activity is controlled, our second hypothesis will be to achieve selective delivery of the cytokine via fusion to nanobodies. While success has been found in targeting primary tumors in drug and protein delivery, a key challenge remains in reaching secondary metastatic tumors in hard-to-reach sites (i.e., brain). Engineered nanobodies, with affinity for breast cancer tumors and the ability to bind to BBB transcytosis receptors, will enable selective delivery to metastatic breast-to-brain tumors, resulting in tumor- specific activation, immune responses, and improved therapeutic outcomes. This system can significantly improve therapeutic outcomes for patients with mBC by integrating selective activation and delivery mechanisms to reduce off-target effects and enhance tumor-specific immune responses in both primary and secondary metastatic tumor sites. Optimizing drug delivery systems to tune immune responses could offer more effective and less invasive treatment options when compared to traditional and engineered cell-based approaches. Our momentum towards precision medicine and targeted therapies holds significant promise for improving outcomes for mBC patients, and has the potential to serve as a pan-cancer treatment for aggressive metastatic cancers from the following aims: (1) generating a modular platform for tumor-specific activation of prodrug cytokines, (2) evaluating cytokine delivery and anti-cancer immune phenotypes in mBC.
A NOVEL GEMM TO ELUCIDATE THE ROLE OF CHAF1A IN NEUROBLASTOMA DEVELOPMENT
PROJECT SUMMARY: This proposal focuses on the fundamental understanding on how the CHAF1A oncogene drives molecular mechanisms, cellular signaling, and metabolic processes in the oncogenesis of neuroblastoma (NB). NB is an aggressive pediatric cancer, which accounts for 15% of pediatric cancer mortalities. High-risk NB is thought to arise from a small number of recurrent genetic alterations that block the ability of neural crest cells (NCCs) to differentiate. To assess the molecular mechanisms governing NC differentiation, our laboratory has established a definitive role of the epigenetic regulator CHAF1A in blocking NC differentiation and driving NB oncogenesis. In this proposal, we will determine the impact of CHAF1A on NB initiation and progression. To accomplish this goal, we propose to develop a novel CHAF1A-driven genetically-engineered mouse model (GEMM) of NB and test the impact of CHAF1A on NB incidence, histology and metastasis, and the tumor immune microenvironment (TIME). We hypothesize that CHAF1A will increase de novo incidence of NB, reduce mouse survival, and promote a suppressive TIME. By developing a novel GEMM of NB and employing innovative technology (including ATAC-seq, lipidomics, and scRNA-seq), we will: 1- elucidate the role of CHAF1A in NB tumor initiation and progression; and 2- determine the impact of CHAF1A on MYCN-induced oncogenesis. These findings will provide a novel view on the molecular mechanisms driving NB initiation, and will have high clinical implications, informing future differentiation-based interventions for high-risk NBs.
Environmental sampling for the fungal pathogen Coccidioides spp. in New Mexico
PROJECT SUMMARY/ABSTRACT Coccidioidomycosis (also known as Valley fever) is a fungal disease endemic to the arid and semi-arid portions of the United States. Due to its alarming health impacts, it has recently been deemed as one of the fungal diseases of highest concern by the World Health Organization. Disease cases continue to rise, causing increasing concern and warranting further understanding of this disease. Though New Mexico has been considered endemic to the disease since the 1940s, few cases are reported in the state each year, suggesting cases may be going vastly underreported. Indeed, recent epidemiologic models suggest New Mexico is likely underreporting cases, which may be a result of low disease awareness in the state or a lack of understanding what populations are at risk. Meanwhile, the neighboring state of Arizona reports the highest number of cases in the country, despite similarities in climate and ecology to New Mexico. In general, very little is known about the health burden of coccidioidomycosis and the geographical distribution of the causative fungal pathogen, Coccidioides spp., in New Mexico. Interestingly, both species of Coccidioides are likely endemic to New Mexico and hybridization of the species may occur. This, in combination with a variety of different ecosystems across the state, makes New Mexico an ideal location for studying the ecology of Coccidioides spp. The objective of our proposal is to generate preliminary data to gain a better understanding of the geographical distribution of Coccidioides spp. in New Mexico, including any regions where hybridization of the species may be occurring. To achieve this, we will collect soil samples throughout New Mexico to: (1) identify what ecosystems are conducive for the growth of Coccidioides and each Coccidioides species in New Mexico and (2) assess whether locations directly surrounding New Mexico’s five largest population centers (Albuquerque, Las Cruces, Rio Rancho, Santa Fe, and Roswell) are endemic to Coccidioides spp. The positive impacts of our proposal are an understanding of what populations are at risk for contracting this disease, where future disease surveillance efforts should be targeted in the state, and where future soil samples should be collected to further explore the genomics and phenotypes of Coccidioides spp. and potential for hybridization. This will help us achieve our long-term goal: to understand the ecology and endemicity of Coccidioides spp. to increase disease awareness, mitigate the negative health impacts from coccidioidomycosis, and ultimately protect the health of all Americans.
AI-guided structural biology of Cav1.2
Project Summary/Abstract The L-type calcium channel Cav1.2 plays a critical role in excitation-contraction coupling in the heart. Its calcium flux generates the plateau phase of the cardiac action potential and results in the calcium-induced calcium release needed to trigger cardiac contractions. Cav1.2 is a multi-subunit protein consisting of a large, transmembrane 1 subunit and smaller, auxiliary subunits important for trafficking and channel regulation. Recent cryogenic electron microscopy (cryo-EM) experiments have revealed much of the three-dimensional structure of Cav1.2’s core domains, though the final 571 residues of the 1 subunit’s intracellular C-terminal domain (CTD) have not yet been resolved despite key regulatory roles in channel function. This domain has been shown to be important for Cav1.2’s regulation by calcium/calmodulin and has an important role in cross- talk between Cav1.2 and the sympathetic nervous system, amongst other cell signaling pathways. In this proposal, I will use insights from artificial intelligence to develop a platform for CTD structural biology, then validate that platform by measuring its ability to form protein-protein interactions with known binding partners of Cav1.2, including calcium/calmodulin and an autoregulatory distal C-terminal fragment. If successful, I will also attempt crystallization of the CTD in complex with several binding partners. Together these data will provide the starting point for future structural biology projects on Cav1.2 regulation and protein-protein interactions.
Noninvasive Neuromodulation to Improve Hand Motor Function in Multiple Sclerosis
Project Summary/Abstract Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating, and degenerative disease that affects nearly one million Americans. Although more than 75% of persons with MS (PwMS) experience hand motor impairments that reduce independence and quality of life, current treatments primarily aim to slow disease progression through pharmacological approaches and rehabilitation and often do not improve motor function. Recent evidence shows that reduced corticospinal transmission is strongly associated with motor impairment severity in PwMS, highlighting the need for targeted strategies to strengthen residual corticospinal pathways. Therefore, this project aims to evaluate the therapeutic potential of paired corticospinal-motoneuronal stimulation (PCMS) in improving hand dexterity in PwMS. PCMS, a noninvasive mechanism-driven neuromodulation approach, enhances corticospinal transmission by producing long-term potentiation-like effects at the corticospinal-motoneuronal synapse by precisely pairing transcranial magnetic stimulation (TMS) with peripheral nerve stimulation (PNS). This project first aims to examine the effects of a single PCMS session on corticospinal transmission and hand motor function in PwMS. Using a randomized, crossover design, 25 PwMS will complete two sessions: (1) PCMS and (2) sham-PCMS. Each session will deliver 180 paired TMS-PNS stimuli over 30 minutes. The primary outcome is performance on the 9-Hole Peg Test (9HPT). Secondary outcomes include pinch grip force, maximal voluntary contraction (MVC), MEP amplitude and latency, F-wave parameters, and M- max amplitude. It is hypothesized that PCMS will enhance corticospinal transmission and improve hand motor performance compared to sham stimulation. Second, this project will examine the effects of PCMS combined with hand motor training in PwMS. Forty-eight PwMS will be randomized to receive either PCMS or sham-PCMS combined with motor training over 10 sessions in 3–4 weeks. Outcomes will be assessed at baseline, post- intervention, and one-month follow-up. It is hypothesized that PCMS participants receiving PCMS with motor training to show greater functional gains than those receiving sham-PCMS with motor training and the functional gains will be better maintained in the PCMS with motor training group at follow-up. This project is the first to apply PCMS in PwMS, leveraging a noninvasive neuromodulation strategy to specifically enhance corticospinal output for improving manual dexterity. Findings will establish proof-of-concept for this intervention in PwMS and guide future studies optimizing stimulation protocols and evaluating clinical efficacy on a larger scale. Ultimately, this work may lead to a new therapeutic approach to improve dexterity, independence, and quality of life for people living with MS.
2026 Thiol-Based Redox Regulation and Signaling Gordon Research Conference and Gordon Research Seminar
PROJECT SUMMARY This proposal requests support for the 10th meeting of the biennial Gordon Research Conference (GRC) and associated Gordon Research Seminar (GRS) on Thiol-Based Redox Regulation and Signaling to be held at the Rey Don Jaime Grand Hotel, Castelldefels, Spain on July 11-12 (GRS) and July 12-17 (GRC), 2026. Regulation of protein function through the post-translational modification of specific cysteine residues (thiol oxidation) plays an important role in cellular adaptation to local and global changes to endogenous and environmental oxidants. A key challenge for the redox-signaling field is to understand how thiol-based signaling mechanisms are integrated into cellular redox homeostasis and how these events facilitate communication between molecules, organelles, cells, and tissues to initiate and coordinate a specialized biological outcome. Significant emphasis for the 2026 meeting will be placed on an exploration of a wider range of cysteine thiol chemistry placed within a cellular context of other, often competing, oxidative or acyl modifications, some of which derive from environmental exposures, and contribute to cancer, aging and the progression of disease. In addition, we will discuss new insights into how cellular redox status impacts metabolic disease and new mathematical and analytical approaches to understand how redox gradients or “waves” impact the spatial and temporal aspects of signaling. A long-term objective is to use this new information to develop diagnostics and therapeutics for a wide range of redox-associated diseases that impact public health. This meeting provides a unique forum for extensive and immersive interaction among chemists, biologists, structural biologists and redox tool-builders, interested in a range of animal and cellular model systems, with clinical researchers and physicians focused on disease processes. While the thematic area of the conference is intentionally broad, its relevance to specialized NIH institutes is highly significant. Not only is redox toxicity proposed as a primary driver of chemically-induced pathology in humans, notably in aging and age-associated diseases, protection from these pathologies by “supersulfides” holds considerable promise. In keeping with the GRC tradition, the 2026 meeting will highlight presentations that emphasize unpublished work, creating a distinctive intellectual experience that enhances the excitement of the meeting. Investigators new to the meeting, junior investigators and graduate and post-graduate trainees will be welcomed. The associated GRS will provide a more intimate forum where graduate and postdoctoral trainees present their research to their peers, while receiving constructive comments from a few senior investigators who serve as mentors. We intend that the GRS/GRC meetings will attract and increase retention of junior scientists in the field of redox biology. We anticipate that the GRC will enhance the education of researchers at all career levels, generate new ideas and collaborations aimed at understanding thiol-based redox regulation and dysfunction, and enable future progress in the prevention, detection, and treatment of a wide-range of human diseases associated with perturbations in redox homeostasis.
Decoding stress vulnerability
Although stress can be considered as an ongoing process that helps an organism to cope with present and future challenges, when it is too intense or uncontrollable, it can lead to adverse consequences for physical and mental health. Social stress specifically, is a highly prevalent traumatic experience, present in multiple contexts, such as war, bullying and interpersonal violence, and it has been linked with increased risk for major depression and anxiety disorders. Nevertheless, not all individuals exposed to strong stressful events develop psychopathology, with the mechanisms of resilience and vulnerability being still under investigation. During this talk, I will identify key gaps in our knowledge about stress vulnerability and I will present our recent data from our contextual fear learning protocol based on social defeat stress in mice.
Enhancing Real-World Event Memory
Memory is essential for shaping how we interpret the world, plan for the future, and understand ourselves, yet effective cognitive interventions for real-world episodic memory loss remain scarce. This talk introduces HippoCamera, a smartphone-based intervention inspired by how the brain supports memory, designed to enhance real-world episodic recollection by replaying high-fidelity autobiographical cues. It will showcase how our approach improves memory, mood, and hippocampal activity while uncovering links between memory distinctiveness, well-being, and the perception of time.
Mapping the neural dynamics of dominance and defeat
Social experiences can have lasting changes on behavior and affective state. In particular, repeated wins and losses during fighting can facilitate and suppress future aggressive behavior, leading to persistent high aggression or low aggression states. We use a combination of techniques for multi-region neural recording, perturbation, behavioral analysis, and modeling to understand how nodes in the brain’s subcortical “social decision-making network” encode and transform aggressive motivation into action, and how these circuits change following social experience.
Localisation of Seizure Onset Zone in Epilepsy Using Time Series Analysis of Intracranial Data
There are over 30 million people with drug-resistant epilepsy worldwide. When neuroimaging and non-invasive neural recordings fail to localise seizure onset zones (SOZ), intracranial recordings become the best chance for localisation and seizure-freedom in those patients. However, intracranial neural activities remain hard to visually discriminate across recording channels, which limits the success of intracranial visual investigations. In this presentation, I present methods which quantify intracranial neural time series and combine them with explainable machine learning algorithms to localise the SOZ in the epileptic brain. I present the potentials and limitations of our methods in the localisation of SOZ in epilepsy providing insights for future research in this area.
Influence of the context of administration in the antidepressant-like effects of the psychedelic 5-MeO-DMT
Psychedelics like psilocybin have shown rapid and long-lasting efficacy on depressive and anxiety symptoms. Other psychedelics with shorter half-lives, such as DMT and 5-MeO-DMT, have also shown promising preliminary outcomes in major depression, making them interesting candidates for clinical practice. Despite several promising clinical studies, the influence of the context on therapeutic responses or adverse effects remains poorly documented. To address this, we conducted preclinical studies evaluating the psychopharmacological profile of 5-MeO-DMT in contexts previously validated in mice as either pleasant (positive setting) or aversive (negative setting). Healthy C57BL/6J male mice received a single intraperitoneal (i.p.) injection of 5-MeO-DMT at doses of 0.5, 5, and 10 mg/kg, with assessments at 2 hours, 24 hours, and one week post-administration. In a corticosterone (CORT) mouse model of depression, 5-MeO-DMT was administered in different settings, and behavioral tests mimicking core symptoms of depression and anxiety were conducted. In CORT-exposed mice, an acute dose of 0.5 mg/kg administered in a neutral setting produced antidepressant-like effects at 24 hours, as observed by reduced immobility time in the Tail Suspension Test (TST). In a positive setting, the drug also reduced latency to first immobility and total immobility time in the TST. However, these beneficial effects were negated in a negative setting, where 5-MeO-DMT failed to produce antidepressant-like effects and instead elicited an anxiogenic response in the Elevated Plus Maze (EPM).Our results indicate a strong influence of setting on the psychopharmacological profile of 5-MeO-DMT. Future experiments will examine cortical markers of pre- and post-synaptic density to correlate neuroplasticity changes with the behavioral effects of 5-MeO-DMT in different settings.
Neural mechanisms governing the learning and execution of avoidance behavior
The nervous system orchestrates adaptive behaviors by intricately coordinating responses to internal cues and environmental stimuli. This involves integrating sensory input, managing competing motivational states, and drawing on past experiences to anticipate future outcomes. While traditional models attribute this complexity to interactions between the mesocorticolimbic system and hypothalamic centers, the specific nodes of integration have remained elusive. Recent research, including our own, sheds light on the midline thalamus's overlooked role in this process. We propose that the midline thalamus integrates internal states with memory and emotional signals to guide adaptive behaviors. Our investigations into midline thalamic neuronal circuits have provided crucial insights into the neural mechanisms behind flexibility and adaptability. Understanding these processes is essential for deciphering human behavior and conditions marked by impaired motivation and emotional processing. Our research aims to contribute to this understanding, paving the way for targeted interventions and therapies to address such impairments.
The multi-phase plasticity supporting winner effect
Aggression is an innate behavior across animal species. It is essential for competing for food, defending territory, securing mates, and protecting families and oneself. Since initiating an attack requires no explicit learning, the neural circuit underlying aggression is believed to be genetically and developmentally hardwired. Despite being innate, aggression is highly plastic. It is influenced by a wide variety of experiences, particularly winning and losing previous encounters. Numerous studies have shown that winning leads to an increased tendency to fight while losing leads to flight in future encounters. In the talk, I will present our recent findings regarding the neural mechanisms underlying the behavioral changes caused by winning.
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.
The quest for brain identification
In the 17th century, physician Marcello Malpighi observed the existence of distinctive patterns of ridges and sweat glands on fingertips. This was a major breakthrough, and originated a long and continuing quest for ways to uniquely identify individuals based on fingerprints, a technique massively used until today. It is only in the past few years that technologies and methodologies have achieved high-quality measures of an individual’s brain to the extent that personality traits and behavior can be characterized. The concept of “fingerprints of the brain” is very novel and has been boosted thanks to a seminal publication by Finn et al. in 2015. They were among the firsts to show that an individual’s functional brain connectivity profile is both unique and reliable, similarly to a fingerprint, and that it is possible to identify an individual among a large group of subjects solely on the basis of her or his connectivity profile. Yet, the discovery of brain fingerprints opened up a plethora of new questions. In particular, what exactly is the information encoded in brain connectivity patterns that ultimately leads to correctly differentiating someone’s connectome from anybody else’s? In other words, what makes our brains unique? In this talk I am going to partially address these open questions while keeping a personal viewpoint on the subject. I will outline the main findings, discuss potential issues, and propose future directions in the quest for identifiability of human brain networks.
Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities; Spatial filtering to enhance signal processing in invasive neurophysiology
On Thursday February 15th, we will host Victoria Peterson and Julian Neumann. Victoria will tell us about “Spatial filtering to enhance signal processing in invasive neurophysiology”. Besides his scientific presentation on “Closed-loop deep brain stimulation as a neuroprosthetic of dopaminergic circuits – Current evidence and future opportunities”, Julian will give us a glimpse at the person behind the science. The talks will be followed by a shared discussion. Note: The talks will exceptionally be held at 10 ET / 4PM CET. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
Reimagining the neuron as a controller: A novel model for Neuroscience and AI
We build upon and expand the efficient coding and predictive information models of neurons, presenting a novel perspective that neurons not only predict but also actively influence their future inputs through their outputs. We introduce the concept of neurons as feedback controllers of their environments, a role traditionally considered computationally demanding, particularly when the dynamical system characterizing the environment is unknown. By harnessing a novel data-driven control framework, we illustrate the feasibility of biological neurons functioning as effective feedback controllers. This innovative approach enables us to coherently explain various experimental findings that previously seemed unrelated. Our research has profound implications, potentially revolutionizing the modeling of neuronal circuits and paving the way for the creation of alternative, biologically inspired artificial neural networks.
Current and future trends in neuroimaging
With the advent of several different fMRI analysis tools and packages outside of the established ones (i.e., SPM, AFNI, and FSL), today's researcher may wonder what the best practices are for fMRI analysis. This talk will discuss some of the recent trends in neuroimaging, including design optimization and power analysis, standardized analysis pipelines such as fMRIPrep, and an overview of current recommendations for how to present neuroimaging results. Along the way we will discuss the balance between Type I and Type II errors with different correction mechanisms (e.g., Threshold-Free Cluster Enhancement and Equitable Thresholding and Clustering), as well as considerations for working with large open-access databases.
Connectome-based models of neurodegenerative disease
Neurodegenerative diseases involve accumulation of aberrant proteins in the brain, leading to brain damage and progressive cognitive and behavioral dysfunction. Many gaps exist in our understanding of how these diseases initiate and how they progress through the brain. However, evidence has accumulated supporting the hypothesis that aberrant proteins can be transported using the brain’s intrinsic network architecture — in other words, using the brain’s natural communication pathways. This theory forms the basis of connectome-based computational models, which combine real human data and theoretical disease mechanisms to simulate the progression of neurodegenerative diseases through the brain. In this talk, I will first review work leading to the development of connectome-based models, and work from my lab and others that have used these models to test hypothetical modes of disease progression. Second, I will discuss the future and potential of connectome-based models to achieve clinically useful individual-level predictions, as well as to generate novel biological insights into disease progression. Along the way, I will highlight recent work by my lab and others that is already moving the needle toward these lofty goals.
A recurrent network model of planning predicts hippocampal replay and human behavior
When interacting with complex environments, humans can rapidly adapt their behavior to changes in task or context. To facilitate this adaptation, we often spend substantial periods of time contemplating possible futures before acting. For such planning to be rational, the benefits of planning to future behavior must at least compensate for the time spent thinking. Here we capture these features of human behavior by developing a neural network model where not only actions, but also planning, are controlled by prefrontal cortex. This model consists of a meta-reinforcement learning agent augmented with the ability to plan by sampling imagined action sequences drawn from its own policy, which we refer to as `rollouts'. Our results demonstrate that this agent learns to plan when planning is beneficial, explaining the empirical variability in human thinking times. Additionally, the patterns of policy rollouts employed by the artificial agent closely resemble patterns of rodent hippocampal replays recently recorded in a spatial navigation task, in terms of both their spatial statistics and their relationship to subsequent behavior. Our work provides a new theory of how the brain could implement planning through prefrontal-hippocampal interactions, where hippocampal replays are triggered by -- and in turn adaptively affect -- prefrontal dynamics.
How Intermittent Bioenergetic Challenges Enhance Brain and Body Health
Humans and other animals evolved in habitats fraught with a range of environmental challenges to their bodies and brains. Accordingly, cells and organ systems possess adaptive stress-responsive signaling pathways that enable them to not only withstand environmental challenges, but also to prepare for future challenges and function more efficiently. These phylogenetically conserved processes are the foundation of the hormesis principle in which repeated exposures to low to moderate amounts of an environmental challenge improve cellular and organismal fitness. Here I describe cellular and molecular mechanisms by which cells in the brain and body respond to intermittent fasting and exercise in ways that enhance performance and counteract aging and disease processes. Switching back and forth between adaptive stress response (during fasting and exercise) and growth and plasticity (eating, resting, sleeping) modes enhances the performance and resilience of various organ systems. While pharmacological interventions that engage a particular hormetic mechanism are being developed, it seems unlikely that any will prove superior to fasting and exercise.
Anticipating behaviour through working memory (BACN Early Career Prize Lecture 2023)
Working memory is about the past but for the future. Adopting such a future-focused perspective shifts the narrative of working memory as a limited-capacity storage system to working memory as an anticipatory buffer that helps us prepare for potential and sequential upcoming behaviour. In my talk, I will present a series of our recent studies that have started to reveal emerging principles of a working memory that looks forward – highlighting, amongst others, how selective attention plays a vital role in prioritising internal contents for behaviour, and the bi-directional links between visual working memory and action. These studies show how studying the dynamics of working memory, selective attention, and action together paves way for an integrated understanding of how mind serves behaviour.
Brain network communication: concepts, models and applications
Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models.
Decoding mental conflict between reward and curiosity in decision-making
Humans and animals are not always rational. They not only rationally exploit rewards but also explore an environment owing to their curiosity. However, the mechanism of such curiosity-driven irrational behavior is largely unknown. Here, we developed a decision-making model for a two-choice task based on the free energy principle, which is a theory integrating recognition and action selection. The model describes irrational behaviors depending on the curiosity level. We also proposed a machine learning method to decode temporal curiosity from behavioral data. By applying it to rat behavioral data, we found that the rat had negative curiosity, reflecting conservative selection sticking to more certain options and that the level of curiosity was upregulated by the expected future information obtained from an uncertain environment. Our decoding approach can be a fundamental tool for identifying the neural basis for reward–curiosity conflicts. Furthermore, it could be effective in diagnosing mental disorders.
Attending to the ups and downs of Lewy body dementia: An exploration of cognitive fluctuations
Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD) share similarities in pathology and clinical presentation and come under the umbrella term of Lewy body dementias (LBD). Fluctuating cognition is a key symptom in LBD and manifests as altered levels of alertness and attention, with a marked difference between best and worst performance. Cognition and alertness can change over seconds or minutes to hours and days of obtundation. Cognitive fluctuations can have significant impacts on the quality of life of people with LBD as well as potentially contribute to the exacerbation of other transient symptoms including, for example, hallucinations and psychosis as well as making it difficult to measure cognitive effect size benefits in clinical trials of LBD. However, this significant symptom in LBD is poorly understood. In my presentation I will discuss the phenomenology of cognitive fluctuations, how we can measure it clinically and limitations of these approaches. I will then outline the work of our group and others which has been focussed on unpicking the aetiological basis of cognitive fluctuations in LBD using a variety of imaging approaches (e.g. SPECT, sMRI, fMRI and EEG). I will then briefly explore future research directions.
Present and Future of the diagnostic work-up multiple sclerosis: the imaging perspective
Computational models of spinal locomotor circuitry
To effectively move in complex and changing environments, animals must control locomotor speed and gait, while precisely coordinating and adapting limb movements to the terrain. The underlying neuronal control is facilitated by circuits in the spinal cord, which integrate supraspinal commands and afferent feedback signals to produce coordinated rhythmic muscle activations necessary for stable locomotion. I will present a series of computational models investigating dynamics of central neuronal interactions as well as a neuromechanical model that integrates neuronal circuits with a model of the musculoskeletal system. These models closely reproduce speed-dependent gait expression and experimentally observed changes following manipulation of multiple classes of genetically-identified neuronal populations. I will discuss the utility of these models in providing experimentally testable predictions for future studies.
Learning to Express Reward Prediction Error-like Dopaminergic Activity Requires Plastic Representations of Time
The dominant theoretical framework to account for reinforcement learning in the brain is temporal difference (TD) reinforcement learning. The TD framework predicts that some neuronal elements should represent the reward prediction error (RPE), which means they signal the difference between the expected future rewards and the actual rewards. The prominence of the TD theory arises from the observation that firing properties of dopaminergic neurons in the ventral tegmental area appear similar to those of RPE model-neurons in TD learning. Previous implementations of TD learning assume a fixed temporal basis for each stimulus that might eventually predict a reward. Here we show that such a fixed temporal basis is implausible and that certain predictions of TD learning are inconsistent with experiments. We propose instead an alternative theoretical framework, coined FLEX (Flexibly Learned Errors in Expected Reward). In FLEX, feature specific representations of time are learned, allowing for neural representations of stimuli to adjust their timing and relation to rewards in an online manner. In FLEX dopamine acts as an instructive signal which helps build temporal models of the environment. FLEX is a general theoretical framework that has many possible biophysical implementations. In order to show that FLEX is a feasible approach, we present a specific biophysically plausible model which implements the principles of FLEX. We show that this implementation can account for various reinforcement learning paradigms, and that its results and predictions are consistent with a preponderance of both existing and reanalyzed experimental data.
A recurrent network model of planning explains hippocampal replay and human behavior
When interacting with complex environments, humans can rapidly adapt their behavior to changes in task or context. To facilitate this adaptation, we often spend substantial periods of time contemplating possible futures before acting. For such planning to be rational, the benefits of planning to future behavior must at least compensate for the time spent thinking. Here we capture these features of human behavior by developing a neural network model where not only actions, but also planning, are controlled by prefrontal cortex. This model consists of a meta-reinforcement learning agent augmented with the ability to plan by sampling imagined action sequences drawn from its own policy, which we refer to as 'rollouts'. Our results demonstrate that this agent learns to plan when planning is beneficial, explaining the empirical variability in human thinking times. Additionally, the patterns of policy rollouts employed by the artificial agent closely resemble patterns of rodent hippocampal replays recently recorded in a spatial navigation task, in terms of both their spatial statistics and their relationship to subsequent behavior. Our work provides a new theory of how the brain could implement planning through prefrontal-hippocampal interactions, where hippocampal replays are triggered by - and in turn adaptively affect - prefrontal dynamics.
Preliminary Research Colloquium of Neuroscience and Neurology of future advancement
A specialized role for entorhinal attractor dynamics in combining path integration and landmarks during navigation
During navigation, animals estimate their position using path integration and landmarks. In a series of two studies, we used virtual reality and electrophysiology to dissect how these inputs combine to generate the brain’s spatial representations. In the first study (Campbell et al., 2018), we focused on the medial entorhinal cortex (MEC) and its set of navigationally-relevant cell types, including grid cells, border cells, and speed cells. We discovered that attractor dynamics could explain an array of initially puzzling MEC responses to virtual reality manipulations. This theoretical framework successfully predicted both MEC grid cell responses to additional virtual reality manipulations, as well as mouse behavior in a virtual path integration task. In the second study (Campbell*, Attinger* et al., 2021), we asked whether these principles generalize to other navigationally-relevant brain regions. We used Neuropixels probes to record thousands of neurons from MEC, primary visual cortex (V1), and retrosplenial cortex (RSC). In contrast to the prevailing view that “everything is everywhere all at once,” we identified a unique population of MEC neurons, overlapping with grid cells, that became active with striking spatial periodicity while head-fixed mice ran on a treadmill in darkness. These neurons exhibited unique cue-integration properties compared to other MEC, V1, or RSC neurons: they remapped more readily in response to conflicts between path integration and landmarks; they coded position prospectively as opposed to retrospectively; they upweighted path integration relative to landmarks in conditions of low visual contrast; and as a population, they exhibited a lower-dimensional activity structure. Based on these results, our current view is that MEC attractor dynamics play a privileged role in resolving conflicts between path integration and landmarks during navigation. Future work should include carefully designed causal manipulations to rigorously test this idea, and expand the theoretical framework to incorporate notions of uncertainty and optimality.
AI for Multi-centre Epilepsy Lesion Detection on MRI
Epilepsy surgery is a safe but underutilised treatment for drug-resistant focal epilepsy. One challenge in the presurgical evaluation of patients with drug-resistant epilepsy are patients considered “MRI negative”, i.e. where a structural brain abnormality has not been identified on MRI. A major pathology in “MRI negative” patients is focal cortical dysplasia (FCD), where lesions are often small or subtle and easily missed by visual inspection. In recent years, there has been an explosion in artificial intelligence (AI) research in the field of healthcare. Automated FCD detection is an area where the application of AI may translate into significant improvements in the presurgical evaluation of patients with focal epilepsy. I will provide an overview of our automated FCD detection work, the Multicentre Epilepsy Lesion Detection (MELD) project and how AI algorithms are beginning to be integrated into epilepsy presurgical planning at Great Ormond Street Hospital and elsewhere around the world. Finally, I will discuss the challenges and future work required to bring AI to the forefront of care for patients with epilepsy.
PIEZO2 in somatosensory neurons coordinates gastrointestinal transit
The transit of food through the gastrointestinal tract is critical for nutrient absorption and survival, and the gastrointestinal tract has the ability to initiate motility reflexes triggered by luminal distention. This complex function depends on the crosstalk between extrinsic and intrinsic neuronal innervation within the intestine, as well as local specialized enteroendocrine cells. However, the molecular mechanisms and the subset of sensory neurons underlying the initiation and regulation of intestinal motility remain largely unknown. Here, we show that humans lacking PIEZO2 exhibit impaired bowel sensation and motility. Piezo2 in mouse dorsal root but not nodose ganglia is required to sense gut content, and this activity slows down food transit rates in the stomach, small intestine, and colon. Indeed, Piezo2 is directly required to detect colon distension in vivo. Our study unveils the mechanosensory mechanisms that regulate the transit of luminal contents throughout the gut, which is a critical process to ensure proper digestion, nutrient absorption, and waste removal. These findings set the foundation of future work to identify the highly regulated interactions between sensory neurons, enteric neurons and non- neuronal cells that control gastrointestinal motility.
Brain mosaicism in epileptogenic cortical malformations
Focal Cortical Dysplasia (FCD) is the most common focal cortical malformation leading to intractable childhood focal epilepsy. In recent years, we and others have shown that FCD type II is caused by mosaic mutations in genes within the PI3K-AKT-mTOR-signaling pathway. Hyperactivation of the mTOR pathway accounts for neuropathological abnormalities and seizure occurrence in FCD. We further showed from human surgical FCDII tissue that epileptiform activity correlates with the density of mutated dysmorphic neurons, supporting their pro-epileptogenic role. The level of mosaicism, as defined by variant allele frequency (VAF) is thought to correlate with the size and regional brain distribution of the lesion such that when a somatic mutation occurs early during the cortical development, the dysplastic area is smaller than if it occurs later. Novel approaches based on the detection of cell-free DNA from the CSF and from trace tissue adherent to SEEG electrodes promise future opportunities for genetic testing during the presurgical evaluation of refractory epilepsy patients or in those that are not eligible for surgery. In utero-based electroporation mouse models allow to express somatic mutation during neurodevelopment and recapitulate most neuropathological and clinical features of FCDII, establishing relevant preclinical mouse models for developing precision medicine strategies.
Beta oscillations in the basal ganglia: Past, Present and Future; Oscillatory signatures of motor symptoms across movement disorders
On Wednesday, January 25th, at noon ET / 6PM CET, we will host Roxanne Lofredi and Hagai Bergman. Roxanne Lofredi, MD, is a research fellow in the Movement Disorders and Neuromodulation Unit at Charité Universitätsmedizin Berlin. Hagai Bergman, MD, PhD, is a Professor of Physiology in the Edmond and Lily Safra Center for Brain Research and Faculty of Medicine at the Hebrew University of Jerusalem, and is Simone and Bernard Guttman Chair in Brain Research. Beside his scientific presentation on “Beta oscillations in the basal ganglia: Past, Present and Future”, he will also give us a glimpse at the “Person behind the science”. The talks will be followed by a shared discussion. You can register via talks.stimulatingbrains.org to receive the (free) Zoom link!
Can we have jam today and jam tomorrow ?Improving outcomes for older people living with mental illness using applied and translational research
This talk will examine how approaches such as ‘big data’ and new ways of delivering clinical trials can improve current services for older people with mental illness (jam today) and identify and deliver new treatments in the future (jam tomorrow).
NEW TREATMENTS FOR PAIN: Unmet needs and how to meet them
“Of pain you could wish only one thing: that it should stop. Nothing in the world was so bad as physical pain. In the face of pain there are no heroes.- George Orwell, ‘1984’ " "Neuroscience has revealed the secrets of the brain and nervous system to an extent that was beyond the realm of imagination just 10-20 years ago, let alone in 1949 when Orwell wrote his prophetic novel. Understanding pain, however, presents a unique challenge to academia, industry and medicine, being both a measurable physiological process as well as deeply personal and subjective. Given the millions of people who suffer from pain every day, wishing only, “that it should stop”, the need to find more effective treatments cannot be understated." "‘New treatments for pain’ will bring together approximately 120 people from the commercial, academic, and not-for-profit sectors to share current knowledge, identify future directions, and enable collaboration, providing delegates with meaningful and practical ways to accelerate their own work into developing treatments for pain.
Learning Relational Rules from Rewards
Humans perceive the world in terms of objects and relations between them. In fact, for any given pair of objects, there is a myriad of relations that apply to them. How does the cognitive system learn which relations are useful to characterize the task at hand? And how can it use these representations to build a relational policy to interact effectively with the environment? In this paper we propose that this problem can be understood through the lens of a sub-field of symbolic machine learning called relational reinforcement learning (RRL). To demonstrate the potential of our approach, we build a simple model of relational policy learning based on a function approximator developed in RRL. We trained and tested our model in three Atari games that required to consider an increasingly number of potential relations: Breakout, Pong and Demon Attack. In each game, our model was able to select adequate relational representations and build a relational policy incrementally. We discuss the relationship between our model with models of relational and analogical reasoning, as well as its limitations and future directions of research.
Controlling the present while planning the future: How the brain learns and produces fast motor sequences
Motor sequencing is one of the fundamental components of human motor skill. In this talk I will show evidence that the fast and smooth production of motor sequences relies on the ability to plan upcoming movements while simultaneously controlling the ongoing movement. I will argue that this ability relies heavily on planning-related areas in premotor and parietal cortex.
Semantic Distance and Beyond: Interacting Predictors of Verbal Analogy Performance
Prior studies of A:B::C:D verbal analogies have identified several factors that affect performance, including the semantic similarity between source and target domains (semantic distance), the semantic association between the C-term and incorrect answers (distracter salience), and the type of relations between word pairs (e.g., categorical, compositional, and causal). However, it is unclear how these stimulus properties affect performance when utilized together. Moreover, how do these item factors interact with individual differences such as crystallized intelligence and creative thinking? Several studies reveal interactions among these item and individual difference factors impacting verbal analogy performance. For example, a three-way interaction demonstrated that the effects of semantic distance and distracter salience had a greater impact on performance for compositional and causal relations than for categorical ones (Jones, Kmiecik, Irwin, & Morrison, 2022). Implications for analogy theories and future directions are discussed.
The 15th David Smith Lecture in Anatomical Neuropharmacology: Professor Tim Bliss, "Memories of long term potentiation
The David Smith Lectures in Anatomical Neuropharmacology, Part of the 'Pharmacology, Anatomical Neuropharmacology and Drug Discovery Seminars Series', Department of Pharmacology, University of Oxford. The 15th David Smith Award Lecture in Anatomical Neuropharmacology will be delivered by Professor Tim Bliss, Visiting Professor at UCL and the Frontier Institutes of Science and Technology, Xi’an Jiaotong University, China, and is hosted by Professor Nigel Emptage. This award lecture was set up to celebrate the vision of Professor A David Smith, namely, that explanations of the action of drugs on the brain requires the definition of neuronal circuits, the location and interactions of molecules. Tim Bliss gained his PhD at McGill University in Canada. He joined the MRC National Institute for Medical Research in Mill Hill, London in 1967, where he remained throughout his career. His work with Terje Lømo in the late 1960’s established the phenomenon of long-term potentiation (LTP) as the dominant synaptic model of how the mammalian brain stores memories. He was elected as a Fellow of the Royal Society in 1994 and is a founding fellow of the Academy of Medical Sciences. He shared the Bristol Myers Squibb award for Neuroscience with Eric Kandel in 1991, the Ipsen Prize for Neural Plasticity with Richard Morris and Yadin Dudai in 2013. In May 2012 he gave the annual Croonian Lecture at the Royal Society on ‘The Mechanics of Memory’. In 2016 Tim, with Graham Collingridge and Richard Morris shared the Brain Prize, one of the world's most coveted science prizes. Abstract: In 1966 there appeared in Acta Physiologica Scandinavica an abstract of a talk given by Terje Lømo, a PhD student in Per Andersen’s laboratory at the University of Oslo. In it Lømo described the long-lasting potentiation of synaptic responses in the dentate gyrus of the anaesthetised rabbit that followed repeated episodes of 10-20Hz stimulation of the perforant path. Thus, heralded and almost entirely unnoticed, one of the most consequential discoveries of 20th century neuroscience was ushered into the world. Two years later I arrived in Oslo as a visiting post-doc from the National Institute for Medical Research in Mill Hill, London. In this talk I recall the events that led us to embark on a systematic reinvestigation of the phenomenon now known as long-term potentiation (LTP) and will then go on to describe the discoveries and controversies that enlivened the early decades of research into synaptic plasticity in the mammalian brain. I will end with an observer’s view of the current state of research in the field, and what we might expect from it in the future.
Social immunity in ants: disease defense of the colony
Social insects fight disease as a collective. Their colonies are protected against disease by the combination of the individual immune defenses of all colony members and their jointly performed nest- and colony-hygiene. This social immunity is achieved by cooperative behaviors to reduce pathogen load of the colony and to prevent transmission along the social interaction networks of colony members. Individual and social immunity interact: performance of sanitary care can affect future disease susceptibility, yet also vice versa, individuals differing in susceptibility adjust their sanitary care performance to their individual risk of infection. I present the integrated approach we use to understand how colony protection arises from the individual and collective actions of colony members and how it affects pathogen communities and hence disease ecology.
Visualising time in the human brain
We all have a sense of time. Yet it is a particularly intangible sensation. So how is our “sense” of time represented in the brain? Functional neuroimaging studies have consistently identified a network of regions, including Supplementary Motor Area and basal ganglia, that are activated when participants make judgements about the duration of currently unfolding events. In parallel, left parietal cortex and cerebellum are activated when participants predict when future events are likely to occur. These structures are activated by temporal processing even when task goals are purely perceptual. So why should the perception of time be represented in regions of the brain that have more traditionally been implicated in motor function? One possibility is that we learn about time through action. In other words, action could provide the functional scaffolding for learning about time in childhood, explaining why it has come to be represented in motor circuits of the adult brain.
Foraging for the future: Food caching in squirrels and birds
Optimization at the Single Neuron Level: Prediction of Spike Sequences and Emergence of Synaptic Plasticity Mechanisms
Intelligent behavior depends on the brain’s ability to anticipate future events. However, the learning rules that enable neurons to predict and fire ahead of sensory inputs remain largely unknown. We propose a plasticity rule based on pre-dictive processing, where the neuron learns a low-rank model of the synaptic input dynamics in its membrane potential. Neurons thereby amplify those synapses that maximally predict other synaptic inputs based on their temporal relations, which provide a solution to an optimization problem that can be implemented at the single-neuron level using only local information. Consequently, neurons learn sequences over long timescales and shift their spikes towards the first inputs in a sequence. We show that this mechanism can explain the development of anticipatory motion signaling and recall in the visual system. Furthermore, we demonstrate that the learning rule gives rise to several experimentally observed STDP (spike-timing-dependent plasticity) mechanisms. These findings suggest prediction as a guiding principle to orchestrate learning and synaptic plasticity in single neurons.
Transcriptional adaptation couples past experience and future sensory responses
Animals traversing different environments encounter both stable background stimuli and novel cues, which are generally thought to be detected by primary sensory neurons and then distinguished by downstream brain circuits. Sensory adaptation is a neural mechanism that filters background by minimizing responses to stable sensory stimuli, and a fundamental feature of sensory systems. Adaptation over relatively fast timescales (milliseconds to minutes) have been reported in many sensory systems. However, adaptation to persistent environmental stimuli over longer timescales (hours to days) have been largely unexplored, even though those timescales are ethologically important since animals typically stay in one environment for hours. I showed that each of the ~1,000 olfactory sensory neuron (OSN) subtypes in the mouse harbors a distinct transcriptome whose content is precisely determined by interactions between its odorant receptor and the environment. This transcriptional variation is systematically organized to support sensory adaptation: expression levels of many genes relevant to transforming odors into spikes continuously vary across OSN subtypes, dynamically adjust to new environments over hours, and accurately predict acute OSN-specific odor responses. The sensory periphery therefore separates salient signals from predictable background via a transcriptional mechanism whose moment-to-moment state reflects the past and constrains the future; these findings suggest a general model in which structured transcriptional variation within a cell type reflects individual experience.
Multi-modal biomarkers improve prediction of memory function in cognitively unimpaired older adults
Identifying biomarkers that predict current and future cognition may improve estimates of Alzheimer’s disease risk among cognitively unimpaired older adults (CU). In vivo measures of amyloid and tau protein burden and task-based functional MRI measures of core memory mechanisms, such as the strength of cortical reinstatement during remembering, have each been linked to individual differences in memory in CU. This study assesses whether combining CSF biomarkers with fMRI indices of cortical reinstatement improves estimation of memory function in CU, assayed using three unique tests of hippocampal-dependent memory. Participants were 158 CU (90F, aged 60-88 years, CDR=0) enrolled in the Stanford Aging and Memory Study (SAMS). Cortical reinstatement was quantified using multivoxel pattern analysis of fMRI data collected during completion of a paired associate cued recall task. Memory was assayed by associative cued recall, a delayed recall composite, and a mnemonic discrimination task that involved discrimination between studied ‘target’ objects, novel ‘foil’ objects, and perceptually similar ‘lure’ objects. CSF Aβ42, Aβ40, and p-tau181 were measured with the automated Lumipulse G system (N=115). Regression analyses examined cross-sectional relationships between memory performance in each task and a) the strength of cortical reinstatement in the Default Network (comprised of posterior medial, medial frontal, and lateral parietal regions) during associative cued recall and b) CSF Aβ42/Aβ40 and p-tau181, controlling for age, sex, and education. For mnemonic discrimination, linear mixed effects models were used to examine the relationship between discrimination (d’) and each predictor as a function of target-lure similarity. Stronger cortical reinstatement was associated with better performance across all three memory assays. Age and higher CSF p-tau181 were each associated with poorer associative memory and a diminished improvement in mnemonic discrimination as target-lure similarity decreased. When combined in a single model, CSF p-tau181 and Default Network reinstatement strength, but not age, explained unique variance in associative memory and mnemonic discrimination performance, outperforming the single-modality models. Combining fMRI measures of core memory functions with protein biomarkers of Alzheimer’s disease significantly improved prediction of individual differences in memory performance in CU. Leveraging multimodal biomarkers may enhance future prediction of risk for cognitive decline.
Towards the optimal protocol for investigation of the mirror neuron system
The study of mirror neurons (MN) has a long way since its discovery on monkeys and later on humans. However, in literature there are inconsistencies on the ways stimuli are presented and on the time of presentation. Which is the best way to present motor movement stimuli? Is it possible to estimate when the mirror neurons effect take place by using Transcranial Magnetic Stimulation at specific time windows? In the current study we test different ways of stimuli presentation (photo and video of hand movements) and brain stimulation (e.g. TMS) delivered on the dominant primary motor cortex (M1) at different time windows. Our aim is to solve this void still present on the field and create a standardized protocol that will generate the strongest mirror neurons response in order to have the way for future studies on the field.
Do we reason differently about affectively charged analogies? Insights from EEG research
Affectively charged analogies are commonly used in literature and art, but also in politics and argumentation. There are reasons to think we may process these analogies differently. Notably, analogical reasoning is a complex process that requires the use of cognitive resources, which are limited. In the presence of affectively charged content, some of these resources might be directed towards affective processing and away from analogical reasoning. To investigate this idea, I investigated effects of affective charge on differences in brain activity evoked by sound versus unsound analogies. The presentation will detail the methods and results for two such experiments, one in which participants saw analogies formed of neutral and negative words and one in which they were created by combining conditioned symbols. I will also briefly discuss future research aiming to investigate the effects of analogical reasoning on brain activity related to affective processing.
Dissecting the role of accumbal D1 and D2 medium spiny neurons in information encoding
Nearly all motivated behaviors require the ability to associate outcomes with specific actions and make adaptive decisions about future behavior. The nucleus accumbens (NAc) is integrally involved in these processes. The NAc is a heterogeneous population primarily composed of D1 and D2 medium spiny projection (MSN) neurons that are thought to have opposed roles in behavior, with D1 MSNs promoting reward and D2 MSNs promoting aversion. Here we examined what types of information are encoded by the D1 and D2 MSNs using optogenetics, fiber photometry, and cellular resolution calcium imaging. First, we showed that mice responded for optical self-stimulation of both cell types, suggesting D2-MSN activation is not inherently aversive. Next, we recorded population and single cell activity patterns of D1 and D2 MSNs during reinforcement as well as Pavlovian learning paradigms that allow dissociation of stimulus value, outcome, cue learning, and action. We demonstrated that D1 MSNs respond to the presence and intensity of unconditioned stimuli – regardless of value. Conversely, D2 MSNs responded to the prediction of these outcomes during specific cues. Overall, these results provide foundational evidence for the discrete aspects of information that are encoded within the NAc D1 and D2 MSN populations. These results will significantly enhance our understanding of the involvement of the NAc MSNs in learning and memory as well as how these neurons contribute to the development and maintenance of substance use disorders.
Epilepsy Genetics – From Family Studies to Polygenic Risk Scores
Whilst epilepsy may be a consequence of an acquired insult including trauma, stroke, and brain tumours, the genetic component to epilepsies has been greatly under-estimated. Considerable progress has recently occurred in the understanding of epilepsy genetics, both at a clinical genetic level and in the basic science of epilepsies. The clinical evidence for genetic components will be first briefly discussed including data from population studies, twin analyses and multiplex family studies. Initial molecular discoveries occurred via classical methods of linkage and gene identification. Recent large-scale hypothesis-free whole exome studies searching for rare variants and genome-wide association studies detecting common variants have been very rewarding. These discoveries have now impacted on clinical practice, especially in severe childhood epilepsies but increasingly so in adult patients. The “genetic background” of patients has long been posited as part of the reason that some patients have epilepsy, or perhaps why some have more severe epilepsy. This has been unmeasurable but now, with the development of polygenic risk scores, the “background” is now in the research foreground. The current and future impact of polygenic risk scores will be explored.
Brain chart for the human lifespan
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure.
Mechanisms of Axon Growth and Regeneration
Almost everybody that has seen neurons under a microscope for the first time is fascinated by their beauty and their complex shape. Early on during development, however, there are hardly any signs of their future complexity, but the neurons look round and simple. How do neurons develop their sophisticated structure? How do they initially generate domains that later have distinct function within neuronal circuits, such as the axon? And, can a better understanding of the underlying developmental mechanisms help us in pathological conditions, such as a spinal cord injury, to induce axons to regenerate? Here, I will talk about the cytoskeleton as a driving force for neuronal polarization. We will then explore how cytoskeletal changes help to reactivate the growth program of injured CNS axons to elicit axon regeneration after a spinal cord injury. Finally, we will discuss whether axon growth and synapse formation may be processes in neurons that might exclude each other. Following this developmental hypothesis, it will help us to generate a novel perspective on regeneration failure in the adult CNS, and how we can overcome this failure to induce axon regeneration. Thus, this talk will describe how we can exploit developmental mechanisms to induce axon regeneration after a spinal cord injury.
Adaptive Deep Brain Stimulation: Investigational System Development at the Edge of Clinical Brain Computer Interfacing
Over the last few decades, the use of deep brain stimulation (DBS) to improve the treatment of those with neurological movement disorders represents a critical success story in the development of invasive neurotechnology and the promise of brain-computer interfaces (BCI) to improve the lives of those suffering from incurable neurological disorders. In the last decade, investigational devices capable of recording and streaming neural activity from chronically implanted therapeutic electrodes has supercharged research into clinical applications of BCI, enabling in-human studies investigating the use of adaptive stimulation algorithms to further enhance therapeutic outcomes and improve future device performance. In this talk, Dr. Herron will review ongoing clinical research efforts in the field of adaptive DBS systems and algorithms. This will include an overview of DBS in current clinical practice, the development of bidirectional clinical-use research platforms, ongoing algorithm evaluation efforts, a discussion of current adoption barriers to be addressed in future work.
Inferring informational structures in neural recordings of drosophila with epsilon-machines
Measuring the degree of consciousness an organism possesses has remained a longstanding challenge in Neuroscience. In part, this is due to the difficulty of finding the appropriate mathematical tools for describing such a subjective phenomenon. Current methods relate the level of consciousness to the complexity of neural activity, i.e., using the information contained in a stream of recorded signals they can tell whether the subject might be awake, asleep, or anaesthetised. Usually, the signals stemming from a complex system are correlated in time; the behaviour of the future depends on the patterns in the neural activity of the past. However these past-future relationships remain either hidden to, or not taken into account in the current measures of consciousness. These past-future correlations are likely to contain more information and thus can reveal a richer understanding about the behaviour of complex systems like a brain. Our work employs the "epsilon-machines” framework to account for the time correlations in neural recordings. In a nutshell, epsilon-machines reveal how much of the past neural activity is needed in order to accurately predict how the activity in the future will behave, and this is summarised in a single number called "statistical complexity". If a lot of past neural activity is required to predict the future behaviour, then can we say that the brain was more “awake" at the time of recording? Furthermore, if we read the recordings in reverse, does the difference between forward and reverse-time statistical complexity allow us to quantify the level of time asymmetry in the brain? Neuroscience predicts that there should be a degree of time asymmetry in the brain. However, this has never been measured. To test this, we used neural recordings measured from the brains of fruit flies and inferred the epsilon-machines. We found that the nature of the past and future correlations of neural activity in the brain, drastically changes depending on whether the fly was awake or anaesthetised. Not only does our study find that wakeful and anaesthetised fly brains are distinguished by how statistically complex they are, but that the amount of correlations in wakeful fly brains was much more sensitive to whether the neural recordings were read forward vs. backwards in time, compared to anaesthetised brains. In other words, wakeful fly brains were more complex, and time asymmetric than anaesthetised ones.
Scaffolding up from Social Interactions: A proposal of how social interactions might shape learning across development
Social learning and analogical reasoning both provide exponential opportunities for learning. These skills have largely been studied independently, but my future research asks how combining skills across previously independent domains could add up to more than the sum of their parts. Analogical reasoning allows individuals to transfer learning between contexts and opens up infinite opportunities for innovation and knowledge creation. Its origins and development, so far, have largely been studied in purely cognitive domains. Constraining analogical development to non-social domains may mistakenly lead researchers to overlook its early roots and limit ideas about its potential scope. Building a bridge between social learning and analogy could facilitate identification of the origins of analogical reasoning and broaden its far-reaching potential. In this talk, I propose that the early emergence of social learning, its saliency, and its meaningful context for young children provides a springboard for learning. In addition to providing a strong foundation for early analogical reasoning, the social domain provides an avenue for scaling up analogies in order to learn to learn from others via increasingly complex and broad routes.
Future data services sandpit: transforming discovery and access
PREDICTIVE COGNITION PRIORITIZES FUTURE INTERACTIONS IN DYNAMIC ENVIRONMENTS
FENS Forum 2026
Dopamine neurons reveal an efficient code for a multidimensional, distributional map of the future
COSYNE 2023
Prioritizing experience replay when future goals are unknown
COSYNE 2023
Dopamine ramps encode discounted future value on a moment-by-moment basis
COSYNE 2025
The big, the fast and the blue: towards the optimal channelrhodopsin for the future optical cochlear implant
Feasibility and future role of high-density transcranial magnetic stimulation (HD-TMS) in Amyotrophic Lateral Sclerosis (ALS): A pilot study in healthy volunteers
Present and future: dual information processing modes in the hippocampal-medial entorhinal circuitry
Cracking the code: How early brain asymmetry foretells neurodevelopmental futures
FENS Forum 2024
Dynamic perception in volatile environments: How relevant is the past when predicting the future?
FENS Forum 2024
Eyes on the future: Unveiling mental simulations as a deliberative decision-making mechanism
FENS Forum 2024
Future encoding mechanisms in visual working memory
FENS Forum 2024
Grid representation for future spatial information in the medial entorhinal cortex
FENS Forum 2024
Kinematic data predict risk of future falls in patients with Parkinson’s disease without a history of falls: A five-year prospective study
FENS Forum 2024
Microglial activation in the anterior cingulate cortex: A biological marker of early adverse events and future vulnerability to develop alcohol use disorder
FENS Forum 2024
Optogenetic stimulation in the visual thalamus for future brain vision prostheses
FENS Forum 2024
Serotonin neurons in the dorsal raphe nucleus encode probability rather than value of future rewards
FENS Forum 2024
Cortical reactivations predict future sensory responses
COSYNE 2023
Perceptual adaptation leads to changes in encoding accuracy that match those of a recurrent neural network optimized to predict the future
Neuromatch 5
future coverage
97 items
Add content
Have a seminar, talk, or paper on future? Post it so others working in this area can find it.
Post content