humans

Borrelia burgdorferi genotypic diversity, pathogenesis, and host cellular responses

PROJECT SUMMARY Lyme disease is the most common tick-borne illness in the United States, with an estimated 476,000 cases annually, and Pennsylvania (PA) consistently reports one of the highest case numbers nationwide. Borrelia burgdorferi sensu stricto (Bb) is a causative agent of Lyme disease in the US and is transmitted by Ixodes spp. ticks. Bb produces various outer surface proteins (Osp) and other mechanisms to survive in vectors, evade host immune systems, and to propagate infection within a host. Over 35 OspC genotypes have been characterized, which fluctuate in abundance in natural vector and host populations, suggesting host adaptation. While many Lyme-infected patients recover following antibiotic treatment, some may experience neurological symptoms, Lyme neuroborreliosis (LNB), which may be associated with specific genotypes. While previous studies focused on clinical manifestations, pathogenicity, genetic variations, and host immune responses using mouse models or patient samples, the genotype-specific immune responses that contribute to disease progression in humans remain poorly understood. Our central hypothesis is that certain Bb OspC genotypes, maintained in natural populations, are associated with distinct host immune responses that influence disease severity, progression, and persistence. Aim 1 will define the dynamics of OspC genotypes in tick and small mammal populations over time in Western PA to establish a 16-year longitudinal tick study and an 8-year longitudinal small mammal study. Using deep amplicon sequencing, we will quantify genotype diversity, detect low-abundance genotypes, and identify potential host-adapted genotypes. These empirical data will inform a compartmental mathematical model to evaluate OspC genotype prevalence, distribution, and public health risks, including LNB, across space and time. Aim 2 will assess how distinct Bb OspC genotypes affect the host immune landscape and cellular responses using human samples. To determine how Bb genotype contributes to disease phenotype, we will perform immune profiling studies which will include microscopy-based assessment of infected cell cultures, flow cytometric analysis of immune cell phenotypes, and measurement of genotype-specific cytokine, chemokine, and antigen production (sub-Aim2a). We will also employ multi-omics approaches that integrate single cell RNA sequencing with antibody-based protein profiling (scRNA-seq/Ab-seq) to characterize transcriptional and functional changes in immune cell populations exposed to different Bb genotypes (sub-Aim2b). This work is innovative in its integration of long-term ecological data with advanced immune profiling and single cell multi- omics to uncover genotype-specific mechanisms of Bb pathogenicity and human immune response—an approach not previously applied in Lyme disease research. These studies will clarify how specific genotypes influence immune responses and disease severity. Together, the proposed aims will identify critical genetic and immunological mechanisms that drive Bb pathogenicity and human susceptibility, informing the development of improved diagnostics, targeted therapies, and public health interventions to reduce the burden of Lyme disease.

Weak Cell Adhesion is a Prognostic Signature of Invasive Cancer

Project Summary Despite early detection, low-grade and localized breast cancers such as ductal carcinoma in situ (DCIS) can relapse in up to 20% of cases despite standard of care. For DCIS, relapse affects over 12,000 U.S. women annually and has increased 60% in the last 40 years. Current diagnostic assessments including histopathological markers often miss early disseminating cells, lack specificity, or cannot distinguish cancer from non-cancer cells in the stroma. Hence there is an unmet need for cancer diagnostic technologies that employ radically different characterization methods. For example, significant physical differences exist between metastasizing and benign breast cancer cells, owing to metastasizing cells detaching from the primary tumor, migrating through the surrounding stroma, intravasating and extravasating, and ultimately engrafting in distant tissues. We recently demonstrated that cancer cells with weaker adhesion migrate faster and metastasize more frequently in murine breast cancer models than strongly adherent cells. In a small pilot study of human breast tumors, we also observed that the abundance of weakly adherent (WA) cells scales with disease severity; subpopulations from invasive carcinomas were the least adherent. However, a subset of DCIS cases displayed much less adhesion, suggesting that these patients may have a tumor subpopulation that progresses to metastatic disease despite standard-of-care treatment. Weak adhesion is a defining physical characteristic of tumors, but to establish their role in initiation, metastasis, and patient outcomes, we will leverage model systems and our newly patented adhesion technology to answer these fundamental questions of cancer biology and clinical translation. To understand the impact of adhesion on cancer progression, we will evaluate the tumor-initiating potential of WA versus strongly adherent (SA) tumor cells in a murine breast cancer model before confirming how weak adhesion advantages cells to cause secondary disease using bioengineered in vitro models. In dissecting the stages of metastasis where WA cells exhibit advantages, e.g., recapitulating stromal niche, transendothelial migration, and tissue-specific colonization, we will identify mechanisms that enable WA cells to thrive and evaluate therapeutic targets that disrupt these pathways. Finally, we will analyze the adhesion profiles of resected tumors and stroma from 80 breast cancer patients with DCIS or invasive disease. Adhesion data will be correlated with conventional assessment methods and ultimately with patient outcomes, e.g., disease-free and progression-free intervals. We anticipate that the DCIS subpopulation that aligns with the adhesion signature of invasive carcinomas will have shorter intervals and survival time. This integrated study design bridges mouse models, mechanistic bioengineering assays, and human samples to clarify the metastatic potential and prognostic value of WA breast cancer cells. Our use of mouse models in this grant is required to study the interactions among tumor cells, immune cells, vasculature, and stromal tissues that drive tumor formation in vivo. Bioengineered in vitro systems lack the complexity to ask such questions and using injected tumor cells is not possible in humans.

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

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

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.

Bridging Local and System-Wide Autoreactive, Extrafollicular B Cell Signatures in a TLR7-Driven Model

Project Summary A substantial body of literature has described the development of autoreactive humoral responses in the context of autoimmune disease and recently discerned an exciting new avenue for investigation. While early work focused on canonical mechanisms of activation through the germinal center (GC) response, recent studies have found GC infrastructure to be dispensable for the onset of chronic autoimmunity. It has become clear that an alternative pathway of B cell activation, the extrafollicular (EF) pathway, can drive the onset of new autoreactivity in multiple human disorders including rheumatoid arthritis and systemic lupus erythematosus (SLE). In comparison to the GC pathway, the EF pathway represents a less stringent method for B cell activation, leads to accelerated antibody-secreting cell (ASC) formation, and thus has a higher propensity for the production of autoreactive B cell effectors and ASCs. Recently, our group has identified a similar skew toward the EF response in the context of severe viral infection, tied to acute tolerance loss, increased disease severity, and complicated recovery from infection. These findings highlight how further study of the EF response is crucial to our understanding of autoimmune induction across multiple areas of disease. Toll-like receptor 7 (TLR7) stimulation has been identified as a key contributor to EF B cell development in SLE, and several studies have now linked TLR7 overstimulation to chronic autoimmune disease. While EF effector B cell populations have now been identified in both murine models and humans, substantial gaps in our knowledge remain to be answered concerning i) the origins of these cells and ii) the system-wide and microenvironmental signaling and organization that drive this differentiation pathway. We propose to address these gaps, here, by utilizing a TLR7 agonist (R848) in a murine model to characterize the autoreactive response within the blood and draining lymph node through innovative high-throughput analytical techniques. Systemic shifts in proteomic signatures and immune cell phenotype will be monitored in the blood throughout the induction of autoreactivity, using novel applications of machine-learning based classification. These signatures will then be connected to developing inflammatory microenvironments identified within the draining lymph node by applying a customized set of software tools to spatial transcriptomic data. This work will deepen our understanding of the immunologic mechanisms by which the EF pathway can lead to “run-away” autoreactive B cell development, with the added potential for identification of early blood-based biomarkers for this developing autoreactivity. The above proposed work will provide an ideal training opportunity for the candidate to develop experience with advanced immunologic laboratory techniques, rigorous bioinformatic analysis, a systems-level view of immunology, and scientific communication. The Woodruff and Sanz Labs are highly experienced within the autoimmune disease space with extensive experience with the required techniques and established routes for clinical collaboration to act on these findings.

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

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

2-Deoxyglucose Therapy for Organophosphate Intoxication

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

Characterization of biofilm formation in shigellosis

Abstract The intestinal pathogen Shigella flexneri is the causative agent of bacillary dysentery and is responsible for more than 250 million cases of dysentery annually, resulting in more than 200,000 deaths. S. flexneri is an intracellular pathogen that invade epithelial cells in the colon and spread from cell to cell. The dissemination process relies on a bacterial adaptor termed IcsA that recruits key components of the actin cytoskeleton and supports actin-based motility. We have recently discovered that in addition of its intracellular role in dissemination, IcsA also support bile salt-dependent biofilm formation. Here, we propose to characterize the structural determinants that support IcsA-mediated bile salts-dependent biofilm formation (Aim1) and the role of IcsA in extracellular and intracellular colonization in an infant rabbit model of shigellosis (Aim2). The characterization of the dual functions of IcsA will provide novel insights into the mechanisms supporting bacillary dysentery in humans.

Breaking Tolerance: Trichloroethylene Provides Survival Signals to Autoreactive CD4s in the Liver

PROJECT SUMMARY The industrial solvent and widespread environmental contaminant, trichloroethylene (TCE) has been linked to autoimmune disease in humans. How TCE impairs tolerance (i.e., unresponsiveness) to self-antigens leading to autoimmunity has not been explored. Autoimmune diseases (ADs) are a class of disorders that affect many different organs and tissues. However, all autoimmune diseases share a feature in common which is the ability of potentially pathogenic autoreactive cells to evade deletion. During early life, peripheral CD4+ cells are primarily comprised of recent thymic emigrants (RTE) which home to the liver. The liver is known to efficiently retain and tolerize self-reactive CD4s to where they are functionally unresponsive to their antigen. Thus, the liver is the first checkpoint in the periphery to filter, retain, and enforce tolerance to autoreactive CD4+ RTEs. The liver is also the site of TCE metabolism. Our Aims are designed to test the hypothesis that TCE, through its metabolite TCAH, delivers costimulatory signals to liver CD4 RTEs via CD28, thereby overriding inhibitory CTLA-4 signaling. This disruption promotes the survival of self-reactive CD4 RTEs by impairing CTLA-4-dependent tolerance mechanisms contributing to the development of ADs. This research will significantly advance the fields of toxicology and autoimmunity, where the origins of environmentally induced AD remain poorly understood. Aim 1 will assess TCE’s effects on RTE migration patterns in real-time in transgenic mice. Aim 2 will investigate TCAH-mediated costimulatory signaling in CD4 RTEs in vitro. Successful completion of these studies will determine how TCE alters key tolerance pathways in the liver resulting in a greater proportion of self-reactive effector memory (EM) peripheral CD4s capable of promoting AD.

Directing the Evolution of Common Human Precursors into HIV-1 Broadly Neutralizing Antibodies

Project Summary An effective HIV vaccine will likely elicit broadly neutralizing antibodies (bnAbs). Doing so, however, remains a major challenge because bnAbs usually require multiple rare and unusual changes that emerge after years of active infection. It is not clear that a practical number of immunizations can consistently recapitulate this process. Although investigators have successfully expanded defined precursors of known bnAbs, they have not moved these diversified precursors to a specific target in humans. Importantly here, the severity of this problem increases rapidly with the number changes needed. The problem further deepens if the required changes are in slow-to-mutate antibody framework regions or require specific indels. The need to move from precursor to bnAb in the fewest steps motivates our focus on the V2 apex epitope of the HIV-1 envelope glycoprotein (Env). Apex bnAbs are qualitatively different from other bnAb classes. They require far fewer mutations, located in their rapidly evolving heavy-chain CDR3 (HCDR3) regions. These HCDR3s are unusually important to their ability to neutralize virus. For example, we have shown that a diverse repertoire of mouse B cell receptors can be modified with apex bnAb HCDR3s, and the resulting mouse B cells generated potent neutralizing sera. Thus, apex precursors can largely be defined by their HCDR3s alone and are far more common than other defined bnAb precursors. Interestingly, these HCDR3 are very similar to those of another class of antibodies that recognize the CD4-induced co-receptor-binding site (CoRBS). Both antibody classes have unusually long HCDR3s with sulfated tyrosines at their tips. Unlike apex bnAbs, these non-neutralizing CoRBS antibodies are readily elicited through vaccination. We have recently shown that apex precursors also bind the CoRBS, suggesting that some apex bnAbs emerge from CoRBS antibodies. Thus, the first step of sequential vaccine strategies, expanding and diversifying a defined precursor pool, is straightforward. Here we divide the remaining goals into two: moving from a precursor that does not bind Env to one that does so and then broaden it to recognize the majority of circulating isolates. We have already made significant progress in the first step: we have shown in our original mouse vaccine model that we can generate potent apex- specific neutralizing antisera. However the breadth of this sera remains limited. Building on these studies, we will pursue three goals: (1) Define the essential mutations that transform a CoRBS antibody into one that binds the Env apex and then generate antigens that select for these mutations. (2) Define mutations and generate antigens that expand the breadth of these antibodies, transforming them to bnAbs, and (3) Evaluate these antigens in a novel system that models key features of the human apex response in mice, and iteratively refine this process using antibodies and HCDR3s drawn from a wide panel of HIV-naïve persons. In short, these studies develop original concepts and tools that can accelerate development of an HIV-1 vaccine and deepen our understanding of the antibody response to vaccines and pathogens.

Characterizing adipocyte heterogeneity in response to metabolic stress

Project Summary Adipose tissue is a central player in metabolism, storing energy healthily under normal conditions but becoming dysfunctional when overloaded. This can lead to the development of metabolic disease, most notably insulin resistance and type 2 diabetes (T2D). Understanding the contribution of adipose tissue to these complications requires knowledge of the individual cell types within adipose tissue and how they respond to different metabolic conditions. My previous work used single nucleus RNA sequencing to profile the cell types in adipose tissue and identified a number of subpopulations of white adipocytes that are differentially associated with clinical characteristics such as body mass index. In this grant, I now aim to better understand how a diverse array of stimuli influences adipocyte development and specification, the role that intra-individual variation plays in the response to these stimuli, and a better understanding of the relationship of adipocyte state to the development of metabolic disease. To do this, I propose using a model in which I can study human adipocyte development and function in mice to perform experiments such as high fat diet and cold exposure that are well-characterized in mice but not in humans. By performing experiments using cells from humans with a range of starting clinical characteristics, I can determine what changes will happen in response to a stimuli in all individuals verses those that only occur in specific populations. The experience that I have in characterizing adipocytes and adipose tissue both at the bench and computationally make me uniquely positioned to answer these questions. Taken together, these studies can test the behavior of adipocyte subpopulations from different people and under different conditions, ultimately leading to a better understanding of how subpopulations develop and, eventually, how we can target these populations to treat metabolic disease.

A PROTAC Strategy to Combat Botulinum Neurotoxicity

PROJECT SUMMARY/ABSTRACT Botulinum neurotoxin (BoNT), the causative agent of botulism, is the most potent toxin known to humans. While BoNTs are widely recognized for their therapeutic and cosmetic applications, such as Botox™, their increasing use has raised concerns about iatrogenic botulism. Due to their extreme lethality, ease of production, and history of weaponization, the Centers for Disease Control and Prevention (CDC) classifies BoNTs as a Category A bioterrorism threat. Among the seven major serotypes (A-G), BoNT/A, BoNT/B, and BoNT/E account for over 95% of human botulism cases with A being the most prevalent. Despite the severity of botulism, no approved therapeutic exists to rescue intoxicated neurons. The current treatment, a heptavalent antitoxin, can only slow disease progression and requires early administration and prolonged hospitalization due to the inability of antibodies to penetrate infected cells. In the field of small- molecule inhibitors (SMIs), promising scaffolds targeting BoNT/A have been discovered, offering opportunities for further derivatization to incorporate bifunctional approaches. Developing a clinically viable therapeutic requires inhibiting the zinc (Zn2+) metalloprotease light chain (LC) as well as addressing toxin persistence. Through extensive inhibitor screening, we have identified two classes of small molecules that inhibit BoNT/A with submicromolar affinity and demonstrate efficacy in both cellular and animal models. However, the transient nature of these inhibitors necessitates the need of a sustained clearance approach. To achieve this, we propose integrating our previously identified BoNT/A LC SMIs with a targeted protein degradation (TPD) technology for toxin elimination. Based upon the background outlined, vide supra, our research strategy for the ablation of BoNT/A will be focused upon the following three specific objectives: 1) Structural Optimization – Utilize molecular docking, and structure-activity relationship (SAR) analysis to modify inhibitors for TPD ligand attachment. 2) Degrader Design – Development of ubiquitin-protease system (UPS)-based proteolysis-targeting chimeras (PROTACs) and autophagy-targeting chimeras to enhance degradation efficiency. 3) Cellular Evaluation – Assess enzyme inhibition, toxin clearance, degradation kinetics in cells.

Avian influenza virus prevention in the domestic host by a deactivated vaccine

Abstract Influenza viruses, which affect both birds and mammals, pose a substantial public health concern. An estimated 10% of the global population annually becomes infected, resulting in 300,000 to 600,000 deaths worldwide. Our research objectives are to develop a Hemagglutinin (HA) and Neuraminidase (NA) based rabies-vectored vaccine against highly pathogenic Avian Influenza (HPAI) A virus H5N1. We have already demonstrated the vaccine’s immunogenicity and protective efficacy against HPAI H5N1 Vietnam 1203. To advance this research, we propose to utilize a novel RAVB-based deactivated vaccine that harbors the H5 antigens of the current homologous circulation (clade 2.3.4.4b) and a construct expressing N1. Our first aim will involve comparing the H5 or H5/N1 RABV-based vaccines against challenges by PR8 recombinants carrying H5N1 proteins in mice. We will employ a single immunization and a prime/boost approach, either with or without an adjuvant approved for use in animals and humans (SEPIVAC SWE™). We will assess the role of T cells in the vaccine-induced protection by performing CD4/CD8 depletion before challenge Our second aim will utilize the vaccine approach identified to protect our mouse system in dairy cows. Subsequently, we will assess the vaccine’s efficacy against challenges administered intranasally and intramammary. We will verify the role of the vaccine-induced antibodies in protection against H5N1 by performing passive transfer studies of purified IgG from vaccinated cows before challenge. In summary, this study will evaluate the efficacy and delineate the mechanism of protection of a safe and well- established vaccine platform to protect against HPAI H5 and explore its potential as an animal and human vaccine.

Glycoengineering core a(1,3)-fucose motifs to enhance HIV-1 envelope vaccine immunogenicity

Project Summary The HIV-1 envelope glycoprotein (Env) is the sole target of neutralizing antibodies (NAbs). We previously developed a vaccine platform integrating three innovations: (1) the uncleaved prefusion-optimized (UFO) trimer design to stabilize Env; (2) multilayered single-component self-assembling protein nanoparticles (1c-SApNPs) for multivalent trimer display; and (3) enzymatic trimming of oligomannose glycans on CHO cell-produced Env immunogens. Glycan trimming substantially improved Env immunogenicity by enhancing tier 2 NAb elicitation, reducing off-target responses to immunodominant glycan sites, and increasing responder rates. These vaccine candidates are now in phase 1 clinical trials (NCT06541093; NCT06905275). Building on this foundation, we propose a novel strategy to enhance immunogenicity by incorporating core α(1,3)-fucose into HIV-1 Env. Core α(1,3)-fucose, a key allergenic epitope in many plant and insect glycoproteins, is highly immunogenic in humans and other mammals. Our central hypothesis is that the targeted introduction of core α(1,3)-fucose will convert the glycan shield from an immune-evasive barrier into an immunogenic trigger that promotes NAb induction. Glycoengineered cell lines expressing α(1,3)-fucose will enable production of highly immunogenic Env vaccines suitable for preclinical and clinical testing. Importantly, particulate display of these Env trimers on 1c-SApNPs can suppress IgE-mediated allergic pathways by inducing high-affinity protective IgGs, ensuring vaccine safety. Aim 1 will focus on producing core α(1,3)-fucosylated HIV-1 Env immunogens. We will begin by developing a transient insect cell expression system using BTI-TN-5B1-4 (“High Five” or Hi5) cells to produce Env with short paucimannose glycans bearing native α(1,3)-fucose. To further enhance α(1,3)-fucosylation, we will co-express exogenous core α(1,3)-fucosyltransferases in insect and CHO cells. We will validate glycan profiles and characterize the biochemical, biophysical, structural, and antigenic properties of the resulting immunogens. Aim 2 will assess the immunogenicity of these glycoengineered HIV-1 Env immunogens. Using our previously established glycan-trimmed Env immunogens as benchmarks, we will immunize mice, rabbits, and nonhuman primates (NHPs). Mice will be used for early-stage immunogen and adjuvant screening; rabbits to evaluate glycan hole-targeting NAb responses; and key vaccine formulations will advance to NHP studies. We will assess autologous and heterologous tier 2 NAb responses and vaccine responder rates. Aim 3 will elucidate the functional, structural, repertoire, and mechanistic basis of vaccine-induced immunity. We will isolate NAbs via Env-specific single-cell sorting and antibody cloning, map epitopes by electron microscopy (EM) and X-ray crystallography, perform next-generation sequencing (NGS) of B-cell repertoires, and trace NAb lineages. Finally, we will investigate antigen trafficking, retention, presentation, and germinal center (GC) reactions in lymph nodes. Together, these studies will define a new class of glycoengineered HIV-1 vaccines and establish core α(1,3)-fucose as a novel immunomodulatory tool to overcome glycan shield-mediated immune evasion.

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.

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

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

Neural circuits underlying sleep structure and functions

Sleep is an active state critical for processing emotional memories encoded during waking in both humans and animals. There is a remarkable overlap between the brain structures and circuits active during sleep, particularly rapid eye-movement (REM) sleep, and the those encoding emotions. Accordingly, disruptions in sleep quality or quantity, including REM sleep, are often associated with, and precede the onset of, nearly all affective psychiatric and mood disorders. In this context, a major biomedical challenge is to better understand the underlying mechanisms of the relationship between (REM) sleep and emotion encoding to improve treatments for mental health. This lecture will summarize our investigation of the cellular and circuit mechanisms underlying sleep architecture, sleep oscillations, and local brain dynamics across sleep-wake states using electrophysiological recordings combined with single-cell calcium imaging or optogenetics. The presentation will detail the discovery of a 'somato-dendritic decoupling'in prefrontal cortex pyramidal neurons underlying REM sleep-dependent stabilization of optimal emotional memory traces. This decoupling reflects a tonic inhibition at the somas of pyramidal cells, occurring simultaneously with a selective disinhibition of their dendritic arbors selectively during REM sleep. Recent findings on REM sleep-dependent subcortical inputs and neuromodulation of this decoupling will be discussed in the context of synaptic plasticity and the optimization of emotional responses in the maintenance of mental health.

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

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

Expanding mechanisms and therapeutic targets for neurodegenerative disease

A hallmark pathological feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion of RNA-binding protein TDP-43 from the nucleus of neurons in the brain and spinal cord. A major function of TDP-43 is as a repressor of cryptic exon inclusion during RNA splicing. By re-analyzing RNA-sequencing datasets from human FTD/ALS brains, we discovered dozens of novel cryptic splicing events in important neuronal genes. Single nucleotide polymorphisms in UNC13A are among the strongest hits associated with FTD and ALS in human genome-wide association studies, but how those variants increase risk for disease is unknown. We discovered that TDP-43 represses a cryptic exon-splicing event in UNC13A. Loss of TDP-43 from the nucleus in human brain, neuronal cell lines and motor neurons derived from induced pluripotent stem cells resulted in the inclusion of a cryptic exon in UNC13A mRNA and reduced UNC13A protein expression. The top variants associated with FTD or ALS risk in humans are located in the intron harboring the cryptic exon, and we show that they increase UNC13A cryptic exon splicing in the face of TDP-43 dysfunction. Together, our data provide a direct functional link between one of the strongest genetic risk factors for FTD and ALS (UNC13A genetic variants), and loss of TDP-43 function. Recent analyses have revealed even further changes in TDP-43 target genes, including widespread changes in alternative polyadenylation, impacting expression of disease-relevant genes (e.g., ELP1, NEFL, and TMEM106B) and providing evidence that alternative polyadenylation is a new facet of TDP-43 pathology.

Neurobiological Pathways to Tau-dependent Pathology: Perspectives from flies to humans

Gene regulatory mechanisms of neocortex development and evolution

The neocortex is considered to be the seat of higher cognitive functions in humans. During its evolution, most notably in humans, the neocortex has undergone considerable expansion, which is reflected by an increase in the number of neurons. Neocortical neurons are generated during development by neural stem and progenitor cells. Epigenetic mechanisms play a pivotal role in orchestrating the behaviour of stem cells during development. We are interested in the mechanisms that regulate gene expression in neural stem cells, which have implications for our understanding of neocortex development and evolution, neural stem cell regulation and neurodevelopmental disorders.

Decision and Behavior

This webinar addressed computational perspectives on how animals and humans make decisions, spanning normative, descriptive, and mechanistic models. Sam Gershman (Harvard) presented a capacity-limited reinforcement learning framework in which policies are compressed under an information bottleneck constraint. This approach predicts pervasive perseveration, stimulus‐independent “default” actions, and trade-offs between complexity and reward. Such policy compression reconciles observed action stochasticity and response time patterns with an optimal balance between learning capacity and performance. Jonathan Pillow (Princeton) discussed flexible descriptive models for tracking time-varying policies in animals. He introduced dynamic Generalized Linear Models (Sidetrack) and hidden Markov models (GLM-HMMs) that capture day-to-day and trial-to-trial fluctuations in choice behavior, including abrupt switches between “engaged” and “disengaged” states. These models provide new insights into how animals’ strategies evolve under learning. Finally, Kenji Doya (OIST) highlighted the importance of unifying reinforcement learning with Bayesian inference, exploring how cortical-basal ganglia networks might implement model-based and model-free strategies. He also described Japan’s Brain/MINDS 2.0 and Digital Brain initiatives, aiming to integrate multimodal data and computational principles into cohesive “digital brains.”

Dynamic neurochemistry in conscious humans during stereoEEG monitoring

Brain-Wide Compositionality and Learning Dynamics in Biological Agents

Biological agents continually reconcile the internal states of their brain circuits with incoming sensory and environmental evidence to evaluate when and how to act. The brains of biological agents, including animals and humans, exploit many evolutionary innovations, chiefly modularity—observable at the level of anatomically-defined brain regions, cortical layers, and cell types among others—that can be repurposed in a compositional manner to endow the animal with a highly flexible behavioral repertoire. Accordingly, their behaviors show their own modularity, yet such behavioral modules seldom correspond directly to traditional notions of modularity in brains. It remains unclear how to link neural and behavioral modularity in a compositional manner. We propose a comprehensive framework—compositional modes—to identify overarching compositionality spanning specialized submodules, such as brain regions. Our framework directly links the behavioral repertoire with distributed patterns of population activity, brain-wide, at multiple concurrent spatial and temporal scales. Using whole-brain recordings of zebrafish brains, we introduce an unsupervised pipeline based on neural network models, constrained by biological data, to reveal highly conserved compositional modes across individuals despite the naturalistic (spontaneous or task-independent) nature of their behaviors. These modes provided a scaffolding for other modes that account for the idiosyncratic behavior of each fish. We then demonstrate experimentally that compositional modes can be manipulated in a consistent manner by behavioral and pharmacological perturbations. Our results demonstrate that even natural behavior in different individuals can be decomposed and understood using a relatively small number of neurobehavioral modules—the compositional modes—and elucidate a compositional neural basis of behavior. This approach aligns with recent progress in understanding how reasoning capabilities and internal representational structures develop over the course of learning or training, offering insights into the modularity and flexibility in artificial and biological agents.

Decomposing motivation into value and salience

Humans and other animals approach reward and avoid punishment and pay attention to cues predicting these events. Such motivated behavior thus appears to be guided by value, which directs behavior towards or away from positively or negatively valenced outcomes. Moreover, it is facilitated by (top-down) salience, which enhances attention to behaviorally relevant learned cues predicting the occurrence of valenced outcomes. Using human neuroimaging, we recently separated value (ventral striatum, posterior ventromedial prefrontal cortex) from salience (anterior ventromedial cortex, occipital cortex) in the domain of liquid reward and punishment. Moreover, we investigated potential drivers of learned salience: the probability and uncertainty with which valenced and non-valenced outcomes occur. We find that the brain dissociates valenced from non-valenced probability and uncertainty, which indicates that reinforcement matters for the brain, in addition to information provided by probability and uncertainty alone, regardless of valence. Finally, we assessed learning signals (unsigned prediction errors) that may underpin the acquisition of salience. Particularly the insula appears to be central for this function, encoding a subjective salience prediction error, similarly at the time of positively and negatively valenced outcomes. However, it appears to employ domain-specific time constants, leading to stronger salience signals in the aversive than the appetitive domain at the time of cues. These findings explain why previous research associated the insula with both valence-independent salience processing and with preferential encoding of the aversive domain. More generally, the distinction of value and salience appears to provide a useful framework for capturing the neural basis of motivated behavior.

Navigating semantic spaces: recycling the brain GPS for higher-level cognition

Humans share with other animals a complex neuronal machinery that evolved to support navigation in the physical space and that supports wayfinding and path integration. In my talk I will present a series of recent neuroimaging studies in humans performed in my Lab aimed at investigating the idea that this same neural navigation system (the “brain GPS”) is also used to organize and navigate concepts and memories, and that abstract and spatial representations rely on a common neural fabric. I will argue that this might represent a novel example of “cortical recycling”, where the neuronal machinery that primarily evolved, in lower level animals, to represent relationships between spatial locations and navigate space, in humans are reused to encode relationships between concepts in an internal abstract representational space of meaning.

This decision matters: Sorting out the variables that lead to a single choice

Towards Human Systems Biology of Sleep/Wake Cycles: Phosphorylation Hypothesis of Sleep

The field of human biology faces three major technological challenges. Firstly, the causation problem is difficult to address in humans compared to model animals. Secondly, the complexity problem arises due to the lack of a comprehensive cell atlas for the human body, despite its cellular composition. Lastly, the heterogeneity problem arises from significant variations in both genetic and environmental factors among individuals. To tackle these challenges, we have developed innovative approaches. These include 1) mammalian next-generation genetics, such as Triple CRISPR for knockout (KO) mice and ES mice for knock-in (KI) mice, which enables causation studies without traditional breeding methods; 2) whole-body/brain cell profiling techniques, such as CUBIC, to unravel the complexity of cellular composition; and 3) accurate and user-friendly technologies for measuring sleep and awake states, exemplified by ACCEL, to facilitate the monitoring of fundamental brain states in real-world settings and thus address heterogeneity in human.

Inducing short to medium neuroplastic effects with Transcranial Ultrasound Stimulation

Sound waves can be used to modify brain activity safely and transiently with unprecedented precision even deep in the brain - unlike traditional brain stimulation methods. In a series of studies in humans and non-human primates, I will show that Transcranial Ultrasound Stimulation (TUS) can have medium- to long-lasting effects. Multiple read-outs allow us to conclude that TUS can perturb neuronal tissues up to 2h after intervention, including changes in local and distributed brain network configurations, behavioural changes, task-related neuronal changes and chemical changes in the sonicated focal volume. Combined with multiple neuroimaging techniques (resting state functional Magnetic Resonance Imaging [rsfMRI], Spectroscopy [MRS] and task-related fMRI changes), this talk will focus on recent human TUS studies.

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.

Rodents to Investigate the Neural Basis of Audiovisual Temporal Processing and Perception

To form a coherent perception of the world around us, we are constantly processing and integrating sensory information from multiple modalities. In fact, when auditory and visual stimuli occur within ~100 ms of each other, individuals tend to perceive the stimuli as a single event, even though they occurred separately. In recent years, our lab, and others, have developed rat models of audiovisual temporal perception using behavioural tasks such as temporal order judgments (TOJs) and synchrony judgments (SJs). While these rodent models demonstrate metrics that are consistent with humans (e.g., perceived simultaneity, temporal acuity), we have sought to confirm whether rodents demonstrate the hallmarks of audiovisual temporal perception, such as predictable shifts in their perception based on experience and sensitivity to alterations in neurochemistry. Ultimately, our findings indicate that rats serve as an excellent model to study the neural mechanisms underlying audiovisual temporal perception, which to date remains relativity unknown. Using our validated translational audiovisual behavioural tasks, in combination with optogenetics, neuropharmacology and in vivo electrophysiology, we aim to uncover the mechanisms by which inhibitory neurotransmission and top-down circuits finely control ones’ perception. This research will significantly advance our understanding of the neuronal circuitry underlying audiovisual temporal perception, and will be the first to establish the role of interneurons in regulating the synchronized neural activity that is thought to contribute to the precise binding of audiovisual stimuli.

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.

Social and non-social learning: Common, or specialised, mechanisms? (BACN Early Career Prize Lecture 2022)

The last decade has seen a burgeoning interest in studying the neural and computational mechanisms that underpin social learning (learning from others). Many findings support the view that learning from other people is underpinned by the same, ‘domain-general’, mechanisms underpinning learning from non-social stimuli. Despite this, the idea that humans possess social-specific learning mechanisms - adaptive specializations moulded by natural selection to cope with the pressures of group living - persists. In this talk I explore the persistence of this idea. First, I present dissociations between social and non-social learning - patterns of data which are difficult to explain under the domain-general thesis and which therefore support the idea that we have evolved special mechanisms for social learning. Subsequently, I argue that most studies that have dissociated social and non-social learning have employed paradigms in which social information comprises a secondary, additional, source of information that can be used to supplement learning from non-social stimuli. Thus, in most extant paradigms, social and non-social learning differ both in terms of social nature (social or non-social) and status (primary or secondary). I conclude that status is an important driver of apparent differences between social and non-social learning. When we account for differences in status, we see that social and non-social learning share common (dopamine-mediated) mechanisms.

Doubting the neurofeedback double-blind do participants have residual awareness of experimental purposes in neurofeedback studies?

Neurofeedback provides a feedback display which is linked with on-going brain activity and thus allows self-regulation of neural activity in specific brain regions associated with certain cognitive functions and is considered a promising tool for clinical interventions. Recent reviews of neurofeedback have stressed the importance of applying the “double-blind” experimental design where critically the patient is unaware of the neurofeedback treatment condition. An important question then becomes; is double-blind even possible? Or are subjects aware of the purposes of the neurofeedback experiment? – this question is related to the issue of how we assess awareness or the absence of awareness to certain information in human subjects. Fortunately, methods have been developed which employ neurofeedback implicitly, where the subject is claimed to have no awareness of experimental purposes when performing the neurofeedback. Implicit neurofeedback is intriguing and controversial because it runs counter to the first neurofeedback study, which showed a link between awareness of being in a certain brain state and control of the neurofeedback-derived brain activity. Claiming that humans are unaware of a specific type of mental content is a notoriously difficult endeavor. For instance, what was long held as wholly unconscious phenomena, such as dreams or subliminal perception, have been overturned by more sensitive measures which show that degrees of awareness can be detected. In this talk, I will discuss whether we will critically examine the claim that we can know for certain that a neurofeedback experiment was performed in an unconscious manner. I will present evidence that in certain neurofeedback experiments such as manipulations of attention, participants display residual degrees of awareness of experimental contingencies to alter their cognition.

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.

Movement planning as a window into hierarchical motor control

The ability to organise one's body for action without having to think about it is taken for granted, whether it is handwriting, typing on a smartphone or computer keyboard, tying a shoelace or playing the piano. When compromised, e.g. in stroke, neurodegenerative and developmental disorders, the individuals’ study, work and day-to-day living are impacted with high societal costs. Until recently, indirect methods such as invasive recordings in animal models, computer simulations, and behavioural markers during sequence execution have been used to study covert motor sequence planning in humans. In this talk, I will demonstrate how multivariate pattern analyses of non-invasive neurophysiological recordings (MEG/EEG), fMRI, and muscular recordings, combined with a new behavioural paradigm, can help us investigate the structure and dynamics of motor sequence control before and after movement execution. Across paradigms, participants learned to retrieve and produce sequences of finger presses from long-term memory. Our findings suggest that sequence planning involves parallel pre-ordering of serial elements of the upcoming sequence, rather than a preparation of a serial trajectory of activation states. Additionally, we observed that the human neocortex automatically reorganizes the order and timing of well-trained movement sequences retrieved from memory into lower and higher-level representations on a trial-by-trial basis. This echoes behavioural transfer across task contexts and flexibility in the final hundreds of milliseconds before movement execution. These findings strongly support a hierarchical and dynamic model of skilled sequence control across the peri-movement phase, which may have implications for clinical interventions.

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.

Internal representation of musical rhythm: transformation from sound to periodic beat

When listening to music, humans readily perceive and move along with a periodic beat. Critically, perception of a periodic beat is commonly elicited by rhythmic stimuli with physical features arranged in a way that is not strictly periodic. Hence, beat perception must capitalize on mechanisms that transform stimulus features into a temporally recurrent format with emphasized beat periodicity. Here, I will present a line of work that aims to clarify the nature and neural basis of this transformation. In these studies, electrophysiological activity was recorded as participants listened to rhythms known to induce perception of a consistent beat across healthy Western adults. The results show that the human brain selectively emphasizes beat representation when it is not acoustically prominent in the stimulus, and this transformation (i) can be captured non-invasively using surface EEG in adult participants, (ii) is already in place in 5- to 6-month-old infants, and (iii) cannot be fully explained by subcortical auditory nonlinearities. Moreover, as revealed by human intracerebral recordings, a prominent beat representation emerges already in the primary auditory cortex. Finally, electrophysiological recordings from the auditory cortex of a rhesus monkey show a significant enhancement of beat periodicities in this area, similar to humans. Taken together, these findings indicate an early, general auditory cortical stage of processing by which rhythmic inputs are rendered more temporally recurrent than they are in reality. Already present in non-human primates and human infants, this "periodized" default format could then be shaped by higher-level associative sensory-motor areas and guide movement in individuals with strongly coupled auditory and motor systems. Together, this highlights the multiplicity of neural processes supporting coordinated musical behaviors widely observed across human cultures.The experiments herein include: a motor timing task comparing the effects of movement vs non-movement with and without feedback (Exp. 1A & 1B), a transcranial magnetic stimulation (TMS) study on the role of the supplementary motor area (SMA) in transforming temporal information (Exp. 2), and a perceptual timing task investigating the effect of noisy movement on time perception with both visual and auditory modalities (Exp. 3A & 3B). Together, the results of these studies support the Bayesian cue combination framework, in that: movement improves the precision of time perception not only in perceptual timing tasks but also motor timing tasks (Exp. 1A & 1B), stimulating the SMA appears to disrupt the transformation of temporal information (Exp. 2), and when movement becomes unreliable or noisy there is no longer an improvement in precision of time perception (Exp. 3A & 3B). Although there is support for the proposed framework, more studies (i.e., fMRI, TMS, EEG, etc.) need to be conducted in order to better understand where and how this may be instantiated in the brain; however, this work provides a starting point to better understanding the intrinsic connection between time and movement

Seeing slowly - how inner retinal photoreceptors support vision and circadian rhythms in mice and humans

Epigenomic (re)programming of the brain and behavior by ovarian hormones

Rhythmic changes in sex hormone levels across the ovarian cycle exert powerful effects on the brain and behavior, and confer female-specific risks for neuropsychiatric conditions. In this talk, Dr. Kundakovic will discuss the role of fluctuating ovarian hormones as a critical biological factor contributing to the increased depression and anxiety risk in women. Cycling ovarian hormones drive brain and behavioral plasticity in both humans and rodents, and the talk will focus on animal studies in Dr. Kundakovic’s lab that are revealing the molecular and receptor mechanisms that underlie this female-specific brain dynamic. She will highlight the lab’s discovery of sex hormone-driven epigenetic mechanisms, namely chromatin accessibility and 3D genome changes, that dynamically regulate neuronal gene expression and brain plasticity but may also prime the (epi)genome for psychopathology. She will then describe functional studies, including hormone replacement experiments and the overexpression of an estrous cycle stage-dependent transcription factor, which provide the causal link(s) between hormone-driven chromatin dynamics and sex-specific anxiety behavior. Dr. Kundakovic will also highlight an unconventional role that chromatin dynamics may have in regulating neuronal function across the ovarian cycle, including in sex hormone-driven X chromosome plasticity and hormonally-induced epigenetic priming. In summary, these studies provide a molecular framework to understand ovarian hormone-driven brain plasticity and increased female risk for anxiety and depression, opening new avenues for sex- and gender-informed treatments for brain disorders.

The sense of agency as an explorative role in our perception and action

The sense of agency refers to the subjective feeling of controlling one's own behavior and, through them, external events. Why is this subjective feeling important for humans? Is it just a by-product of our actions? Previous studies have shown that the sense of agency can affect the intensity of sensory input because we predict the input from our motor intention. However, my research has found that the sense of agency plays more roles than just predictions. It enhances perceptual processes of sensory input and potentially helps to harvest more information about the link between the external world and the self. Furthermore, our recent research found both indirect and direct evidence that the sense of agency is important for people's exploratory behaviors, and this may be linked to proximal exploitations of one's control in the environment. In this talk, I will also introduce the paradigms we use to study the sense of agency as a result of perceptual processes, and our findings of individual differences in this sense and the implications.

Obesity and Brain – Bidirectional Influences

The regulation of body weight relies on homeostatic mechanisms that use a combination of internal signals and external cues to initiate and terminate food intake. Homeostasis depends on intricate communication between the body and the hypothalamus involving numerous neural and hormonal signals. However, there is growing evidence that higher-level cognitive function may also influence energy balance. For instance, research has shown that BMI is consistently linked to various brain, cognitive, and personality measures, implicating executive, reward, and attentional systems. Moreover, the rise in obesity rates over the past half-century is attributed to the affordability and widespread availability of highly processed foods, a phenomenon that contradicts the idea that food intake is solely regulated by homeostasis. I will suggest that prefrontal systems involved in value computation and motivation act to limit food overconsumption when food is scarce or expensive, but promote over-eating when food is abundant, an optimum strategy from an economic standpoint. I will review the genetic and neuroscience literature on the CNS control of body weight. I will present recent studies supporting a role of prefrontal systems in weight control. I will also present contradictory evidence showing that frontal executive and cognitive findings in obesity may be a consequence not a cause of increased hunger. Finally I will review the effects of obesity on brain anatomy and function. Chronic adiposity leads to cerebrovascular dysfunction, cortical thinning, and cognitive impairment. As the most common preventable risk factor for dementia, obesity poses a significant threat to brain health. I will conclude by reviewing evidence for treatment of obesity in adults to prevent brain disease.

Relations and Predictions in Brains and Machines

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

Spatial matching tasks for insect minds: relational similarity in bumblebees

Understanding what makes human unique is a fundamental research drive for comparative psychologists. Cognitive abilities such as theory of mind, cooperation or mental time travel have been considered uniquely human. Despite empirical evidence showing that animals other than humans are able (to some extent) of these cognitive achievements, findings are still heavily contested. In this context, being able to abstract relations of similarity has also been considered one of the hallmarks of human cognition. While previous research has shown that other animals (e.g., primates) can attend to relational similarity, less is known about what invertebrates can do. In this talk, I will present a series of spatial matching tasks that previously were used with children and great apes and that I adapted for use with wild-caught bumblebees. The findings from these studies suggest striking similarities between vertebrates and invertebrates in their abilities to attend to relational similarity.

Analogical Reasoning and Generalization for Interactive Task Learning in Physical Machines

Humans are natural teachers; learning through instruction is one of the most fundamental ways that we learn. Interactive Task Learning (ITL) is an emerging research agenda that studies the design of complex intelligent robots that can acquire new knowledge through natural human teacher-robot learner interactions. ITL methods are particularly useful for designing intelligent robots whose behavior can be adapted by humans collaborating with them. In this talk, I will summarize our recent findings on the structure that human instruction naturally has and motivate an intelligent system design that can exploit their structure. The system – AILEEN – is being developed using the common model of cognition. Architectures that implement the Common Model of Cognition - Soar, ACT-R, and Sigma - have a prominent place in research on cognitive modeling as well as on designing complex intelligent agents. However, they miss a critical piece of intelligent behavior – analogical reasoning and generalization. I will introduce a new memory – concept memory – that integrates with a common model of cognition architecture and supports ITL.

Effect of Different Influences on Temporal Error Monitoring

Metacognition has long been defined as “cognition about cognition”. One of its aspects is the error monitoring ability, which includes being aware of one’s own errors without external feedback. This ability is mostly investigated in two-alternative forced choice tasks, where the performance has all or none nature in terms of accuracy. The previous literature documents the effect of different influences on the error monitoring ability, such as working memory, feedback and sensorimotor involvement. However, these demonstrations fall short of generalizing to the real life scenarios where the errors often have a magnitude and a direction. To bridge this gap, recent studies showed that humans could keep track of the magnitude and the direction of their errors in temporal, spatial and numerical domains in two metrics: confidence and short-long/few-more judgements. This talk will cover how the documented effects that are obtained in the two alternative forced choices tasks apply to the temporal error monitoring ability. Finally, how magnitude and direction monitoring (i.e., confidence and short-long judgements) can be differentiated as the two indices of temporal error monitoring ability will be discussed.

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

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

Learning to see stuff

Humans are very good at visually recognizing materials and inferring their properties. Without touching surfaces, we can usually tell what they would feel like, and we enjoy vivid visual intuitions about how they typically behave. This is impressive because the retinal image that the visual system receives as input is the result of complex interactions between many physical processes. Somehow the brain has to disentangle these different factors. I will present some recent work in which we show that an unsupervised neural network trained on images of surfaces spontaneously learns to disentangle reflectance, lighting and shape. However, the disentanglement is not perfect, and we find that as a result the network not only predicts the broad successes of human gloss perception, but also the specific pattern of errors that humans exhibit on an image-by-image basis. I will argue this has important implications for thinking about appearance and vision more broadly.

Toward the neural basis of joint attention: studies in humans and monkeys

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.

Sampling the environment with body-brain rhythms

Since Darwin, comparative research has shown that most animals share basic timing capacities, such as the ability to process temporal regularities and produce rhythmic behaviors. What seems to be more exclusive, however, are the capacities to generate temporal predictions and to display anticipatory behavior at salient time points. These abilities are associated with subcortical structures like basal ganglia (BG) and cerebellum (CE), which are more developed in humans as compared to nonhuman animals. In the first research line, we investigated the basic capacities to extract temporal regularities from the acoustic environment and produce temporal predictions. We did so by adopting a comparative and translational approach, thus making use of a unique EEG dataset including 2 macaque monkeys, 20 healthy young, 11 healthy old participants and 22 stroke patients, 11 with focal lesions in the BG and 11 in the CE. In the second research line, we holistically explore the functional relevance of body-brain physiological interactions in human behavior. Thus, a series of planned studies investigate the functional mechanisms by which body signals (e.g., respiratory and cardiac rhythms) interact with and modulate neurocognitive functions from rest and sleep states to action and perception. This project supports the effort towards individual profiling: are individuals’ timing capacities (e.g., rhythm perception and production), and general behavior (e.g., individual walking and speaking rates) influenced / shaped by body-brain interactions?

LifePerceives

Life Perceives is a symposium bringing together scientists and artists for an open exploration of how “perception” can be understood as a phenomenon that does not only belong to humans, or even the so-called “higher organisms”, but exists across the entire spectrum of life in a myriad of forms. The symposium invites leading practitioners from the arts and sciences to present unique insights through short talks, open discussions, and artistic interventions that bring us slightly closer to the life worlds of plants and fungi, microbial communities and immune systems, cuttlefish and crows. What do we mean when we talk about perception in other species? Do other organisms have an experience of the world? Or does our human-centred perspective make understanding other forms of life on their own terms an impossible dream? Whatever your answers to these questions may be, we hope to unsettle them, and leave you more curious than when you arrived.

Roots of Analogy

Can nonhuman animals perceive the relation-between-relations? This intriguing question has been studied over the last 40 years; nonetheless, the extent to which nonhuman species can do so remains controversial. Here, I review empirical evidence suggesting that pigeons, parrots, crows, and baboons join humans in reliably acquiring and transferring relational matching-to-sample (RMTS). Many theorists consider that RMTS captures the essence of analogy, because basic to analogy is appreciating the ‘relation between relations.’ Factors affecting RMTS performance include: prior training experience, the entropy of the sample stimulus, and whether the items that serve as sample stimuli can also serve as choice stimuli.

Analyzing artificial neural networks to understand the brain

In the first part of this talk I will present work showing that recurrent neural networks can replicate broad behavioral patterns associated with dynamic visual object recognition in humans. An analysis of these networks shows that different types of recurrence use different strategies to solve the object recognition problem. The similarities between artificial neural networks and the brain presents another opportunity, beyond using them just as models of biological processing. In the second part of this talk, I will discuss—and solicit feedback on—a proposed research plan for testing a wide range of analysis tools frequently applied to neural data on artificial neural networks. I will present the motivation for this approach as well as the form the results could take and how this would benefit neuroscience.

Motor contribution to auditory temporal predictions

Temporal predictions are fundamental instruments for facilitating sensory selection, allowing humans to exploit regularities in the world. Recent evidence indicates that the motor system instantiates predictive timing mechanisms, helping to synchronize temporal fluctuations of attention with the timing of events in a task-relevant stream, thus facilitating sensory selection. Accordingly, in the auditory domain auditory-motor interactions are observed during perception of speech and music, two temporally structured sensory streams. I will present a behavioral and neurophysiological account for this theory and will detail the parameters governing the emergence of this auditory-motor coupling, through a set of behavioral and magnetoencephalography (MEG) experiments.

Prefrontal top-down projections control context-dependent strategy selection

The rules governing behavior often vary with behavioral contexts. As a result, an action rewarded in one context may be discouraged in another. Animals and humans are capable of switching between behavioral strategies under different contexts and acting adaptively according to the variable rules, a flexibility that is thought to be mediated by the prefrontal cortex (PFC). However, how the PFC orchestrates the context-dependent switch of strategies remains unclear. Here we show that pathway-specific projection neurons in the medial PFC (mPFC) differentially contribute to context-instructed strategy selection. In mice trained in a decision-making task in which a previously established rule and a newly learned rule are associated with distinct contexts, the activity of mPFC neurons projecting to the dorsomedial striatum (mPFC-DMS) encodes the contexts and further represents decision strategies conforming to the old and new rules. Moreover, mPFC-DMS neuron activity is required for the context-instructed strategy selection. In contrast, the activity of mPFC neurons projecting to the ventral midline thalamus (mPFC-VMT) does not discriminate between the contexts, and represents the old rule even if mice have adopted the new one. Furthermore, these neurons act to prevent the strategy switch under the new rule. Our results suggest that mPFC-DMS neurons promote flexible strategy selection guided by contexts, whereas mPFC-VMT neurons favor fixed strategy selection by preserving old rules.

On the link between conscious function and general intelligence in humans and machines

In popular media, there is often a connection drawn between the advent of awareness in artificial agents and those same agents simultaneously achieving human or superhuman level intelligence. In this talk, I will examine the validity and potential application of this seemingly intuitive link between consciousness and intelligence. I will do so by examining the cognitive abilities associated with three contemporary theories of conscious function: Global Workspace Theory (GWT), Information Generation Theory (IGT), and Attention Schema Theory (AST), and demonstrating that all three theories specifically relate conscious function to some aspect of domain-general intelligence in humans. With this insight, we will turn to the field of Artificial Intelligence (AI) and find that, while still far from demonstrating general intelligence, many state-of-the-art deep learning methods have begun to incorporate key aspects of each of the three functional theories. Given this apparent trend, I will use the motivating example of mental time travel in humans to propose ways in which insights from each of the three theories may be combined into a unified model. I believe that doing so can enable the development of artificial agents which are not only more generally intelligent but are also consistent with multiple current theories of conscious function.

It’s All About Motion: Functional organization of the multisensory motion system at 7T

The human middle temporal complex (hMT+) has a crucial biological relevance for the processing and detection of direction and speed of motion in visual stimuli. In both humans and monkeys, it has been extensively investigated in terms of its retinotopic properties and selectivity for direction of moving stimuli; however, only in recent years there has been an increasing interest in how neurons in MT encode the speed of motion. In this talk, I will explore the proposed mechanism of speed encoding questioning whether hMT+ neuronal populations encode the stimulus speed directly, or whether they separate motion into its spatial and temporal components. I will characterize how neuronal populations in hMT+ encode the speed of moving visual stimuli using electrocorticography ECoG and 7T fMRI. I will illustrate that the neuronal populations measured in hMT+ are not directly tuned to stimulus speed, but instead encode speed through separate and independent spatial and temporal frequency tuning. Finally, I will suggest that this mechanism may play a role in evaluating multisensory responses for visual, tactile and auditory stimuli in hMT+.

Exploring emotion in the expression of ape gesture

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

The multimodal number sense: spanning space, time, sensory modality, and action

Humans and other animals can estimate rapidly the number of items in a scene, flashes or tones in a sequence and motor actions. Adaptation techniques provide clear evidence in humans for the existence of specialized numerosity mechanisms that make up the numbersense. This sense of number is truly general, encoding the numerosity of both spatial arrays and sequential sets, in vision and audition, and interacting strongly with action. The adaptation (cross-sensory and cross-format) acts on sensory mechanisms rather than decisional processes, pointing to a truly general sense.

From Machine Learning to Autonomous Intelligence

How could machines learn as efficiently as humans and animals? How could machines learn to reason and plan? How could machines learn representations of percepts and action plans at multiple levels of abstraction, enabling them to reason, predict, and plan at multiple time horizons? I will propose a possible path towards autonomous intelligent agents, based on a new modular cognitive architecture and a somewhat new self supervised training paradigm. The centerpiece of the proposed architecture is a configurable predictive world model that allows the agent to plan. Behavior and learning are driven by a set of differentiable intrinsic cost functions. The world model uses a new type of energy-based model architecture called H-JEPA (Hierarchical Joint Embedding Predictive Architecture). H-JEPA learns hierarchical abstract representations of the world that are simultaneously maximally informative and maximally predictable.

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.

Learning predictive maps in the brain for spatial navigation

The predictive map hypothesis provides a promising framework to model representations in the hippocampal formation. I will introduce a tractable implementation of a predictive map called the successor representation (SR), before presenting data showing that rats and humans display SR-like navigational choices on a novel open-field maze. Next, I will show how such a predictive map could be implemented using spatial representations found in the hippocampal formation, before finally presenting how such learning might be well approximated by phenomena that exist in the spatial memory system - namely spike-timing dependent plasticity and theta phase precession.

From Machine Learning to Autonomous Intelligence

How could machines learn as efficiently as humans and animals? How could machines learn to reason and plan? How could machines learn representations of percepts and action plans at multiple levels of abstraction, enabling them to reason, predict, and plan at multiple time horizons? I will propose a possible path towards autonomous intelligent agents, based on a new modular cognitive architecture and a somewhat new self-supervised training paradigm. The centerpiece of the proposed architecture is a configurable predictive world model that allows the agent to plan. Behavior and learning are driven by a set of differentiable intrinsic cost functions. The world model uses a new type of energy-based model architecture called H-JEPA (Hierarchical Joint Embedding Predictive Architecture). H-JEPA learns hierarchical abstract representations of the world that are simultaneously maximally informative and maximally predictable. The corresponding working paper is available here:https://openreview.net/forum?id=BZ5a1r-kVsf

Development and evolution of neuronal connectivity

In most animal species including humans, commissural axons connect neurons on the left and right side of the nervous system. In humans, abnormal axon midline crossing during development causes a whole range of neurological disorders ranging from congenital mirror movements, horizontal gaze palsy, scoliosis or binocular vision deficits. The mechanisms which guide axons across the CNS midline were thought to be evolutionary conserved but our recent results suggesting that they differ across vertebrates.  I will discuss the evolution of visual projection laterality during vertebrate evolution.  In most vertebrates, camera-style eyes contain retinal ganglion cell (RGC) neurons projecting to visual centers on both sides of the brain. However, in fish, RGCs are thought to only innervate the contralateral side. Using 3D imaging and tissue clearing we found that bilateral visual projections exist in non-teleost fishes. We also found that the developmental program specifying visual system laterality differs between fishes and mammals. We are currently using various strategies to discover genes controlling the development of visual projections. I will also present ongoing work using 3D imaging techniques to study the development of the visual system in human embryo.

Behavioural probing of learned statistical structure in humans

COSYNE 2022

Identifying the control strategies of monkeys and humans in a virtual balancing task

COSYNE 2022

Identifying the control strategies of monkeys and humans in a virtual balancing task

COSYNE 2022

Insight moments in neural networks and humans

COSYNE 2022

Insight moments in neural networks and humans

COSYNE 2022

Integrating information and reward into subjective value: humans, monkeys, and the lateral habenula

COSYNE 2022

Integrating information and reward into subjective value: humans, monkeys, and the lateral habenula

COSYNE 2022

Near-optimal time investments under uncertainty in humans, rats, and mice

COSYNE 2022

Near-optimal time investments under uncertainty in humans, rats, and mice

COSYNE 2022

The timescale and magnitude of 1/f aperiodic activity decrease with cortical depth in humans, macaques, and mice

COSYNE 2022

The timescale and magnitude of 1/f aperiodic activity decrease with cortical depth in humans, macaques, and mice

COSYNE 2022

Alignment of ANN Language Models with Humans After a Developmentally Realistic Amount of Training

COSYNE 2023

Biased AI systems produce biased humans

COSYNE 2023

Intracranial electrophysiological evidence for a novel neuro-computational mechanism of cognitive flexibility in humans

COSYNE 2023

Spatial-frequency channels for object recognition by neural networks are twice as wide as those of humans

COSYNE 2023

Violations of transitivity disrupt relational inference in humans and reinforcement learning models

COSYNE 2023

Expectation management in humans and LLMs

COSYNE 2025

Humans forage for reward in classic reinforcement learning tasks

COSYNE 2025

Humans can use positive and negative spectrotemporal correlations to detect rising and falling pitch

COSYNE 2025

Persistent decision-making in mice, monkeys, and humans

COSYNE 2025

3D-imaging reveals conserved cerebrospinal fluid drainage via meningeal lymphatic vasculature in mice and humans

Accuracy in self-monitoring of temporal errors in humans and rodents

Characterisation of the neural correlates of central sensitisation induced by the high frequency stimulation (HFS) model in healthy humans using functional magnetic resonance imaging (fMRI)

A common mechanism for saliency detection and motor reactivity in humans and rhesus monkeys

Cyclicity of cerebral glutamate and glutamine levels across sleep-wake states in humans

The development of corneal innervation; a 3D analysis in mice and humans

FOXP2 in the mammalian thalamus: humans, including patients with schizophrenia, and animal models

Hippocampal neurons sparsely code individual episodic memories in humans

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

Impaired processing of amplitude-modulated tones in the inferior colliculus in Cacna2d3 mice - a risk gene for autism spectrum disorders in humans

Increasing cortico-subcortical connectivity predicts a bursting event during sevoflurane-induced burst suppression state in humans

In mice and humans, brain vascular barrier homeostasis and contractility are acquired postnatally

Motivational performance in humans as a function of the neurochemical composition of anterior insula and dorsomedial prefrontal cortex/dorsal anterior cingulate cortex

Multiple stimulus-stimulus associations during multi-step reinforcement learning in humans in spatially structured and unstructured frames

Neural correlates of symmetric and asymmetric bimanual control of pinch force in humans

Preferential Decisions by Association: The Interplay of Internal Preference on Humans' External Perception

Pre-movement spinal cord activity in humans: a simultaneous brain-spinal cord fMRI study

Probing cortical excitability under GABAergic modulation in humans with Epilepsy

Pupil size during sleep indicates distinct brain states in humans

A role of parahippocampal cortex in forward-looking choices during multi-step reinforcement learning in humans