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From B-cell decisions to antibody repertoires

PROJECT SUMMARY/ABSTRACT Vaccine responses are highly variable across the population and not without risk for debilitating side-effects. Antibody-mediated immunity is generated by a Darwinian process to generate B-cells that contain B-cell receptors (BCR) that have high affinity for the pathogen-derived antigen, while also eliminating B-cells that happen to react to self-antigens. This process depends on cell fate decisions such as (i) death vs survival, (ii) entry into a proliferative program, (iii) differentiation into antibody-secreting plasma cells. According to clonal selection theory, B-cell fate decisions are made based on the genetically encoded affinity of the the BCR to the antigen (Signal 1) and the cognate T-cells’ TCR to the antigen peptide (Signal 2). However, single-cell resolution studies have revealed that fate decisions of genetically identical B-cells are remarkably heterogeneous. Our studies of the previous funding period revealed that B-cell epigenetic heterogeneity is in fact dynamically controlled: it is generated during the selection process but remains largely stable during the proliferative burst. This leads to our newly proposed Aim 1 to examine how the dynamic control of epigenetic state variability affects antibody responses. An innovative multi-scale model of Darwinian evolution directs and interprets experimental studies by life cell video microscopy in vitro and in immunization studies in vivo. Our previous studies also found that B-cells are capable of sensing the time gap between signal 1 and 2, suggesting a temporal proofreading mechanism for negative selection. This leads to newly proposed Aim 2 which seeks to identify the regulatory circuits that control the stringency of negative selection, as well as contextual germinal center (GC) cytokines that could be manipulable in vivo. These in silico and in vitro studies are followed by in vivo immunization to extend their physiological relevance. Finally, in Aim 3, we will ask what determines the time-gap of signal1 and signal 2, which occur in the immune- induced structure of the GC. We will develop a new model that simulates B-cell fate decisions as a function of their interactions with antigen-presenting stromal cells and T-cells that may be cognate or non-cognate. Model simulations will be used to interpret spatial transcriptomic data to test different adjuvants and predictions will be tested in in vivo immunization studies. With mouse models of inflammation and aging we will examine how adjuvants alter vaccine efficacy and risk.

HIV-1 Matrix and Envelope Protein Interactions

It is important to characterize how HIV-1 proteins fulfill their functions in order to develop new approaches for curtailing the AIDS epidemic. One of the remaining frontiers of HIV-1 research concerns the mechanisms by which the HIV-1 matrix (MA) and envelope (Env) proteins collaborate with each other to ensure the assembly of infectious viruses. The HIV-1 MA protein directs the delivery of precursor Gag (PrGag) proteins to the plasma membranes (PMs) of infected cells, and drives the formation of lipid raft-like, liquid ordered (Lo) membrane domains. This membrane reorganization attracts a number of proteins that favor lipid raft-type microdomains. Such proteins appear to assemble into virus particles as innocent bystanders, and this appears to be how Env proteins that carry cytoplasmic tail deletions (CT) can be incorporated into virions. In contrast, wild type (WT) Env proteins additionally require an interaction with MA proteins to assemble into viruses. This is most easily understood in the context of the lattice that MA proteins construct at the PMs of infected cells. In particular, multiple lines of evidence imply that the CTs of WT Env proteins are trapped by MA lattices in immature, assembling virus particles, and then are released after assembled viruses are processed into their mature forms. Despite a seeming consensus on the MA-Env interaction steps, there are a number of very significant unknowns. Using our recent and preliminary results as a foundation, and taking advantage of the unique expertise of our collaborators, we propose the characterization of WT and mutant MA lattices, and of interactions of MA and Env with each other, and with membrane lipids. Our results will help clarify how MA and Env cooperate; they will illuminate aspects of host cell protein-membrane interactions; and they will foster the development of new approaches to intefere with HIV-1 replication.

FIRE-PF: Developing and Testing a Trauma-Informed Alcohol Intervention to Enhance Mental Health in Firefighters

PROJECT SUMMARY Alcohol use and hazardous drinking are ubiquitous among firefighters in the United states and is associated with significant physical and mental health risks for this population. Due to the nature of their work, firefighters experience substantially higher rates of trauma exposure and are subsequently at greater risk of developing specific mental health conditions compared to the general population, particularly trauma-related psychopathology (e.g., posttraumatic stress). Hazardous drinking and posttraumatic stress frequently co-occur among firefighters, leading to poorer health outcomes compared to either condition alone. Despite this elevated risk, firefighters often lack access to tailored, empirically supported interventions, and no existing mental health interventions address hazardous drinking in a trauma-informed framework for this at-risk population. Personalized feedback interventions (PFIs) are a promising approach that could address this gap. By delivering brief, patient-centered feedback on drinking behaviors and perceptions within the context of trauma and occupational stress, PFIs aim to reduce problematic drinking behaviors and stigma related to coping-orientated drinking and improve stress management strategies. PFIs can be brief, cost-effective, and easily disseminated in a format accessible to large groups, making them a strong candidate for use with firefighters who face critical barriers to engaging in traditional mental health programs. This innovative study aims to develop a single-session, trauma-informed, online PFI tailored specifically for firefighters, using a comprehensive, three-phase approach to address three primary aims. The Development Phase involves developing, adapting, and enhancing a trauma-informed PFI by gathering qualitative feedback from firefighters (N = 45) and using an iterative, rapid user-centered design approach to ensure the intervention is engaging for firefighters as well as relevant and aligned with fire service culture. The Evaluation Phase will assess the feasibility, acceptability, and preliminary impact of the PFI in a mixed-methods longitudinal open trial with firefighters (N = 50), with a focus on the intervention's usability, delivery, and influence on drinking behaviors. The Implementation Planning Phase will involve qualitative and quantitative assessments with fire service leaders (N = 15) to identify implementation barriers and shape future research testing the implementation process for the intervention and inform future strategies for resource integration and fostering sustainable community partnerships. This proposal will equip Dr. Lebeaut with essential training for an independent research career, including training in (1) qualitative methodologies, (2) user-centered design, (3) developing, adapting, and enhancing trauma-informed alcohol interventions, and (4) developing collaborative relationships with community partners in the fire service. The proposed study will directly inform a future R01 to evaluate the intervention’s efficacy and scalability and support the development of a firefighter-focused research program.

Regulation of neutrophil endoplasmic reticulum stress response by IRE1a

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

Targeting disulfidptosis in cancer: mechanisms and preclinical translation

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

Th17 plasticity in rheumatoid arthritis

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

Causal mechanisms driving germline predisposition to myeloproliferative disorders

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

The role of GPR132 in regulating T cell responses in infection and cancer

PROJECT SUMMARY. CD8 T cells play a critical role in protection from a variety of infectious microorganisms, and pathogen-specific CD8 T cells undergo robust expansion, with an individual T cell clones expanding up to 10,000-fold in a matter of days. After infection is resolved, the majority of these T cells die, leaving a small population of memory cells to provide protective immunity from secondary challenge. T cell expansion and contraction are tightly orchestrated processes that involve a delicate balance between stimulatory and inhibitory signals to ensure proper immune function. Dysregulation of the T cell response can have detrimental effects; too little proliferation and the host fails to mount a successful immune response, while excessive proliferation and persistence of effector T cell populations can lead to tissue damage. This proposal aims to determine the role of the G protein coupled receptor GPR132 in the regulation of CD8 T cell responses during infection and tumorigenesis. GPR132 detects oxidized endogenous and microbial lipids, and this can lead to cell cycle arrest; however, the role of GPR132 in CD8 T cells remains unexplored. Here we identify GPR132 as a critical regulator of CD8 T cell expansion and memory differentiation. Completion of the proposed aims will: 1) uncover the temporal role of GPR132 in regulating T cell accumulation and function during infection and tumorigenesis, 2) examine the abundance of GPR132-activating ligands within the tissue during health and disease, and 3) determine how altering GPR132 ligand availability could be used to enhance/inhibit T cell responses. Overall, these studies will provide fundamental insights into the regulatory mechanisms that dictate the magnitude of T cell responses and how they can be modulated therapeutically, which would allow us to boost responses to pathogens/tumors or inhibit pathogenic responses in the context of autoimmune disease.

Transcriptional control of activation induced deaminase (AID) function

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

Behavioral, Implementation & Community Sciences Core

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

Neural circuits for disinhibition in the cerebellum

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

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

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

Hepatotoxicity of Legacy and Replacement PFAS: Role of BRUCE-Mitochondrial Interactions

Epidemiological studies have shown a strong association between exposure to PFAS (Per- and Poly- fluoroalkyl Substances) and liver toxicity. Particularly, legacy C8-PFAS members, PFOS (perfluorooctane sulfonate) and PFOA (perfluorooctanoic acid), are highly toxic, with PFOS estimated to be approximately 10 times more toxic than PFOA in ecotoxicity models. Consequently, PFAS replacements such as GenX and PFBS are marketed as safe alternatives, although growing evidence indicates that these substitutes also exhibit toxic effects. Lab animal model studies have shown hepatotoxic effects of both legacy and replacement PFAS members, characterized by Metabolic dysfunction-associated steatotic liver disease (MASLD) and its severe form Metabolic dysfunction- associated steatohepatitis (MASH), the two chronic liver diseases affecting an estimated 80-100 million Americans. The broader objective of this project is to understand the underlying mechanisms of PFAS hepatotoxicity in MASLD/MASH. In this context, our initial studies have shown that PFAS exposure of mice downregulates hepatic BRUCE, an autophagy inhibitor, resulting in development of MASLD in WT, and more severe MASLD and even progression to MASH in BRUCE liver-knockdown (BKO) mice. Using primary hepatocytes, we found PFAS-induced BRUCE reduction compromised mitochondrial (mt) functions (respiration, fatty acid oxidation/FAO, and ATP production) and suppressed mitophagy in WT and more so in BKO mice. Pharmacological restoration of mt function in mice prevented PFAS-induced MASLD/MASH. Guided by these compelling preliminary data and scientific premise, we hypothesize that PFAS degradation of BRUCE in hepatocytes induces excessive autophagy (resulting in cytotoxicity) and inhibits mitophagy (resulting in accumulation of damaged mitochondria), leading to release of mtDAMPs to activate inflammation/ fibrosis, thereby facilitating progression from MASLD to MASH. We will test this by three specific aims. Aim 1 (ex vivo) is to determine the human-relevant PFAS doses that modulate BRUCE levels for homeostatic vs cytotoxic autophagy and how BRUCE in turn regulates autophagy. Aim 2 (ex vivo) will investigate BRUCE-driven mitophagy pathway specific to PFAS exposure at human-relevant doses. Aim 3 (ex vivo and in vivo) will involve ex vivo simulation experiments to characterize the role of PFAS-induced, BRUCE-dependent hepatocyte- released mt DAMPs in activation of immune and fibrogenic cells using co-culture assays. Next, we will perform in vivo intervention to validate the role of PFAS-damaged mitochondria in driving MASH progression in mouse models. Furthermore, human relevance of the delineated mechanisms will be ascertained and validated using iPSC-derived human liver organoid system. Impact: This project will advance our understanding of autophagy/mitophagy-centric mechanisms with therapeutic potential in the context of PFAS-induced liver disease MASLD/MASH.

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.

Multiplex single-cell chemical genomics to identify small molecule modulators of tumor cell-intrinsic immunogenicity in glioblastoma

PROJECT SUMMARY/ABSTRACT Glioblastoma multiforme is the most common and aggressive primary brain cancer. Despite a multimodal treatment regimen of surgical resection, chemotherapy, radiotherapy, and tumor-treating fields, most patients succumb to the disease within two years of diagnosis. Cancer immunotherapy strategies have emerged as a powerful tool for treating aggressive solid tumors such as melanoma and non-small cell lung cancer. However, current strategies have led to low response rates in glioblastoma, resulting from its low immunogenicity. The proposed research program aims to identify small molecules capable of increasing the immunogenicity of glioblastoma cells, focusing on altering gene expression programs associated with recognition by the immune system and the ability of cytotoxic immune cells to target glioblastoma for destruction. We will use highly multiplex chemical transcriptomic profiling to determine the molecular consequence of exposing glioblastoma neurosphere models to 3,792 small molecules, targeting the majority of cellular activities and clinically relevant drug targets as well as a collection of previously identified immunomodulators. We will then determine how each exposure alters the expression of gene programs associated with tumor cell immunogenicity and response to therapy, including the expression of genes associated with the recognition by the immune system and those associated with immune checkpoints, as well as programs more broadly correlated with resistance to anti-cancer therapies. Chemical hits that meet specific criteria will be subjected to a medicinal chemistry review to further classify compounds by their suitability for treating malignancies in the brain. We will then screen chemical hits to determine their ability to modulate immune-mediated tumor cell killing using tumor- immune cell co-culture. Lastly, we will leverage gene editing and flow cytometry to validate hits based on on- target molecular effects and further refine the mechanism of action by inspecting the ability of drugs to modulate immunogenic programs at the protein level. Our chemical genomics screens aim to provide crucial information regarding the link between pathway activity and immunomodulation in GBM, a critical step to guide future efforts in GBM immunotherapy. More broadly, our study will establish single-cell chemical genomics as a scalable platform for phenotype-based screening for preclinical prioritization of chemical modulators of complex transcriptional phenotypes and provide a framework for hit prioritization, establishment of pipeline robustness and hit validation in the context of single- cell chemical genomics screens.

Temporomandibular Joint Disc Replacement: Biomechanical Characterization and Novel Implant Assessment

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

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

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

SUPPORT SERVICES FOR THE PREVENTION AND TREATMENT THROUGH A COMPREHENSIVE CARE CONTINUUM FOR HIV-AFFECTED ADOLESCENTS IN RESOURCE CONSTRAINED SETTINGS IMPLEMENTATION SCIENCE NETWORK

Support Services for the Prevention and Treatment through a Comprehensive Care Continuum for HIV-affected Adolescents in Resource Constrained Settings Implementation Science Network (PATC3H-IN) (UG1/UM2) Program The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) requires support for logistical and operational coordination, website and communication management, analytic and data management, infrastructure for emerging research, regulatory, and monitoring of research activities for the Prevention and Treatment through a Comprehensive Care Continuum for HIV-affected Adolescents in Resource Constrained Settings Implementation Science Network (PATC3H-IN) (UG1/UM2) Program. The NICHD and partner NIH Institutes anticipate funding 8 PATC3H-IN UG1 awards in Asia and throughout sub-Saharan Africa in 2023 through a cooperative agreement mechanism for interventions of high public health significance: The prevention of new HIV infections among adolescents at risk, and the identification of, linkage to and retention in care of, and long-term viral suppression among youth living with HIV in low-to-middle income countries with high HIV burden. The PATC3H-IN network will expand and/or improve on successes achieved by its predecessor, PATC3H, to new geographic settings and/or risk populations and stimulate much needed implementation science (IS) research in the prevention of new HIV infections among adolescents at risk and the identification of, and linkage and retention to care of and long-term viral suppression among youth living with HIV in low-to-middle income countries (LMICs). PATC3H-IN will establish a network of investigators with multidisciplinary expertise on the youth-specific PHCC and in IS research, whose mission will be to evaluate promising prevention innovations contextually and developmentally tailored for HIV uninfected at-risk youth, and treatment and care interventions for youth living with HIV which have demonstrated efficacy and/or effectiveness in adolescent or adult populations and to translate them into public health practices. The structure of PATC3H-IN will consist of multiple interdependent functional components: (1) Five Clinical Research Centers (CRC) awarded through the UG1 grant mechanism; (2) one Implementation Science Coordinating Center (ISCC) to be awarded through a UM2 grant mechanism in 2024; and (3) a Scientific Leadership Committee (SLC). The CRCs will conduct clinical research and clinical trials, including implementation, effectiveness, and hybrid implementation-effectiveness studies at their 8-or more participating Clinical Research Performance Sites (CRPS). The ISCC will establish infrastructure to support research education and capacity building across PATC3H-IN, as well as infrastructure for stakeholder engagement in and dissemination of findings from PATC3H-IN and advanced statistical modeling support across PATC3H-IN. The ISCC will also provide infrastructure for conducting foundational research to support the work of clinical sites, including possible modeling studies and translation projects, as well as national surveys, and/or systematic collection and analysis of relevant policies and laws. Lastly, the SLC will be responsible for PATC3H-IN governance, oversight, and coordination, and will develop and implement the network research agenda, convening working groups as needed, prioritizing emerging research projects, efficiently managing the development of clinical protocols, implementing and completing clinical trials, and ensuring timely publication and communication of results.

Stability in disrupted maternal representations over the perinatal period: Contributors and consequences

Abstract High-quality mother-infant relationships promote social, emotional, and cognitive development while protecting against poor child behavioral, health, and psychological adaptation that create risk for long- term negative outcomes. As mothers transition to parenthood, their own experiences of being cared for influence their emerging views of parenting and representations of their developing child. Evidence suggests that ‘disrupted’ maternal representations of the child, i.e., representations characterized by mixed communication, role merging, extreme withdrawal, and other unusual psychological processes, are tied to both poor child socioemotional adjustment and both insecure and disorganized attachment. However, it is unclear whether disrupted representations that emerge during pregnancy remain stable across the first several years of the child’s life. In addition, to date, research has not examined how change/stability in these representations may affect maternal caregiving and subsequent child adaptation. Using data from a longitudinal, multi-method study, this proposed project will examine the stability of maternal representations of the child for 99 women living in high risk contexts using the Working Model of the Child Interview during the third trimester and again when the child is two years of age. Mothers’ demographic characteristics (i.e. SES and relationship status), interpersonal violence experiences (i.e. child maltreatment or intimate violence exposure), psychological health (i.e. depressive, anxious, and PTSD symptoms), and parenting stress (i.e. perceptions of the child as difficult and parent-child interactions as dysfunctional) are measured as well to examine influences on representation stability. Finally, the observed quality of maternal caregiving and child adaptation are measured and examined in relation to stability in maternal representations of the child. Findings from this study have the potential to identify which mother-child dyads are at greatest risk for poor adaptation across the perinatal period and to delineate the contributors and consequences of maternal representational stability. These findings will serve as an important step towards informing the development or modification of existing prevention/intervention approaches that are targeted specifically towards mother-child dyads who are most at need.

Developing a novel technology for studying T cell differentiation in vivo

Summary CRISPR-based genetic screens have revolutionized our understanding of gene functions and molecular mechanisms across various biological processes. In the field of T cell biology, CRISPR screens have played a pivotal role in identifying genes that impact critical aspects, such as T cell development, differentiation, and function. However, traditional screens have struggled to distinguish genes with diverse mechanisms of action, necessitating further investigations. To address this challenge, researchers have harnessed the power of CRISPR screens combined with single-cell sequencing (scCRISPR-seq), enabling the simultaneous assessment of genetic perturbations and high-dimensional phenotypes at the single-cell level. While scCRISPR- seq has predominantly been performed in vitro using immortalized cell lines, its physiological relevance is limited due to oversimplified biological context and disparities compared to primary cells. This limitation highlights the urgent need for large-scale in vivo scCRISPR-seq with primary T cells. However, various challenges have discouraged its widespread adoption. The use of viral vectors for sgRNA delivery compromises physiological relevance, as the in vitro activation conditions fail to faithfully represent the intricate T cell priming process in vivo. Moreover, viral vector components and continuous Cas9 expression can trigger immunogenicity and cytotoxicity, leading to cell depletion and hindering long-term studies. Additionally, current scCRISPR-seq methods face technical limitations, including low editing efficiency and inadequate perturbation identity recovery rates, which impede efficient large-scale in vivo applications. Fortunately, recent advances in ribonucleoprotein complex (RNP) transfection have addressed many of these challenges. This cutting-edge technology enables efficient gene editing in primary T cells without the need for in vitro activation or permanent Cas9 expression. Leveraging the high editing efficiency of RNP transfection, the investigator’s team aims to develop a novel strategy for in vivo T cell CRISPR screens. This innovative approach involves arrayed RNP transfection and co- transfer of T cells that recognize the relevant antigens. Instead of traditional genetic barcodes, the strategy utilizes congenic markers (CD45.1/45.2 and CD90.1/CD90.2) from donor TCR transgenic T cells as "external barcodes." These markers facilitate the recovery of gene perturbation identity at the single-cell level through the application of CITE-seq. Importantly, this RNP-based strategy seamlessly integrates with existing single-cell sequencing protocols, enabling the comprehensive assessment of transcripts, epitopes, and chromatin accessibility simultaneously. To demonstrate the efficacy of this strategy, the team plans to develop two benchmarking approaches: RNP-CET-seq to investigate the role of TCR regulators in T cell exhaustion and RNP-CATE-seq to map the gene regulatory atlas of exhausted CD8 T cells. In summary, the proposed RNP- based scCRISPR-seq strategy overcomes the limitations of current approaches, enabling large-scale, multi- module in vivo genetic screens within a physiologically relevant context across various disease models.

Primary cilia protein IFT88 governs smooth muscle phenotype and vascular remodeling

Project Summary/Abstract Cardiovascular disease remains the leading cause of death in the United States, accounting for nearly 1 million deaths in 2022. Vascular diseases such as atherosclerosis, aneurysm, and coronary artery disease are regulated largely by smooth muscle cells (SMCs) residing in the blood vessel wall. The central dogma of vascular SMC biology is that differentiated cells can de-differentiate and give rise to a spectrum of alternative phenotypes promoting invasion, proliferation, fibrosis, and inflammation, but the mechanisms regulating SMC phenotypic transitions are poorly understood. Intraflagellar transport 88 (IFT88) is an essential protein for the formation of primary cilia, centriole-associated plasma membrane organelles that project into the extracellular milieu and regulate cell cycle reentry and responses to stimuli like growth factors and mechanical strain. Non- ciliary functions of IFT88 also include progression of the cell cycle checkpoint and polarized motility, both of which are functionally critical for SMC-mediated vascular remodeling. Little is known about the functional role of the primary cilia in SMCs and the role of the essential cilia protein IFT88 in regulating SMC phenotype. To address this gap in knowledge, my postdoctoral studies focus on the role of IFT88 in the context of intimal hyperplasia (K99). During the independent phase (R00), I will apply these findings to arteriovenous fistula (AVF) maturation, a surgical intervention often required for dialysis individuals with polycystic kidney disease (PKD), an IFT88 loss-of-function disease. I will test my central hypothesis that cilia are key regulators of SMC phenotype in three Specific Aims: 1) determine the role of IFT88-dependent SMC primary cilia in mechanotransduction of extracellular matrix (ECM) stiffness (K99), 2) determine the role of IFT88 in pathological intimal hyperplasia (K99), and 3) test whether SMC IFT88 expression is required for adaptive remodeling of grafted veins following AVF placement (R00). Overall, we propose that IFT88+ ciliated SMC represent an unidentified subclass of the SMC phenotype spectrum that is primarily responsible for vascular remodeling and is an attractive potential target for treatment of vascular diseases. Building on strong existing collaborations, we have formed a research and mentoring team with expertise in SMC pathophysiology, primary cilia biology, mechanobiology, AVF surgery, and PKD to complete the proposed aims. The additional training in cell-ECM interactions (Aim 1, K99), in vivo murine ligation injury and in vivo cilia imaging (Aim 2, K99), and AVF surgery and PKD pathology (Aim 3, R00) will be indispensable for preparing the PI, Dr. O’Brien, for his career as an independent investigator. Completion of the proposed aims will also contribute directly to an understanding of the function of IFT88-dependent primary cilia in SMCs and may likely identify novel therapeutic targets for treatment of vascular diseases.

2026 Thiol-Based Redox Regulation and Signaling Gordon Research Conference and Gordon Research Seminar

PROJECT SUMMARY This proposal requests support for the 10th meeting of the biennial Gordon Research Conference (GRC) and associated Gordon Research Seminar (GRS) on Thiol-Based Redox Regulation and Signaling to be held at the Rey Don Jaime Grand Hotel, Castelldefels, Spain on July 11-12 (GRS) and July 12-17 (GRC), 2026. Regulation of protein function through the post-translational modification of specific cysteine residues (thiol oxidation) plays an important role in cellular adaptation to local and global changes to endogenous and environmental oxidants. A key challenge for the redox-signaling field is to understand how thiol-based signaling mechanisms are integrated into cellular redox homeostasis and how these events facilitate communication between molecules, organelles, cells, and tissues to initiate and coordinate a specialized biological outcome. Significant emphasis for the 2026 meeting will be placed on an exploration of a wider range of cysteine thiol chemistry placed within a cellular context of other, often competing, oxidative or acyl modifications, some of which derive from environmental exposures, and contribute to cancer, aging and the progression of disease. In addition, we will discuss new insights into how cellular redox status impacts metabolic disease and new mathematical and analytical approaches to understand how redox gradients or “waves” impact the spatial and temporal aspects of signaling. A long-term objective is to use this new information to develop diagnostics and therapeutics for a wide range of redox-associated diseases that impact public health. This meeting provides a unique forum for extensive and immersive interaction among chemists, biologists, structural biologists and redox tool-builders, interested in a range of animal and cellular model systems, with clinical researchers and physicians focused on disease processes. While the thematic area of the conference is intentionally broad, its relevance to specialized NIH institutes is highly significant. Not only is redox toxicity proposed as a primary driver of chemically-induced pathology in humans, notably in aging and age-associated diseases, protection from these pathologies by “supersulfides” holds considerable promise. In keeping with the GRC tradition, the 2026 meeting will highlight presentations that emphasize unpublished work, creating a distinctive intellectual experience that enhances the excitement of the meeting. Investigators new to the meeting, junior investigators and graduate and post-graduate trainees will be welcomed. The associated GRS will provide a more intimate forum where graduate and postdoctoral trainees present their research to their peers, while receiving constructive comments from a few senior investigators who serve as mentors. We intend that the GRS/GRC meetings will attract and increase retention of junior scientists in the field of redox biology. We anticipate that the GRC will enhance the education of researchers at all career levels, generate new ideas and collaborations aimed at understanding thiol-based redox regulation and dysfunction, and enable future progress in the prevention, detection, and treatment of a wide-range of human diseases associated with perturbations in redox homeostasis.

Decoding stress vulnerability

Although stress can be considered as an ongoing process that helps an organism to cope with present and future challenges, when it is too intense or uncontrollable, it can lead to adverse consequences for physical and mental health. Social stress specifically, is a highly prevalent traumatic experience, present in multiple contexts, such as war, bullying and interpersonal violence, and it has been linked with increased risk for major depression and anxiety disorders. Nevertheless, not all individuals exposed to strong stressful events develop psychopathology, with the mechanisms of resilience and vulnerability being still under investigation. During this talk, I will identify key gaps in our knowledge about stress vulnerability and I will present our recent data from our contextual fear learning protocol based on social defeat stress in mice.

sensorimotor control, mouvement, touch, EEG

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

Consciousness at the edge of chaos

Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.

Memory Decoding Journal Club: Neocortical synaptic engrams for remote contextual memories

Neocortical synaptic engrams for remote contextual memories

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.

The representation of speech conversations in the human auditory cortex

Cognitive maps as expectations learned across episodes – a model of the two dentate gyrus blades

How can the hippocampal system transition from episodic one-shot learning to a multi-shot learning regime and what is the utility of the resultant neural representations? This talk will explore the role of the dentate gyrus (DG) anatomy in this context. The canonical DG model suggests it performs pattern separation. More recent experimental results challenge this standard model, suggesting DG function is more complex and also supports the precise binding of objects and events to space and the integration of information across episodes. Very recent studies attribute pattern separation and pattern integration to anatomically distinct parts of the DG (the suprapyramidal blade vs the infrapyramidal blade). We propose a computational model that investigates this distinction. In the model the two processing streams (potentially localized in separate blades) contribute to the storage of distinct episodic memories, and the integration of information across episodes, respectively. The latter forms generalized expectations across episodes, eventually forming a cognitive map. We train the model with two data sets, MNIST and plausible entorhinal cortex inputs. The comparison between the two streams allows for the calculation of a prediction error, which can drive the storage of poorly predicted memories and the forgetting of well-predicted memories. We suggest that differential processing across the DG aids in the iterative construction of spatial cognitive maps to serve the generation of location-dependent expectations, while at the same time preserving episodic memory traces of idiosyncratic events.

Principles of Cognitive Control over Task Focus and Task

2024 BACN Mid-Career Prize Lecture Adaptive behavior requires the ability to focus on a current task and protect it from distraction (cognitive stability), and to rapidly switch tasks when circumstances change (cognitive flexibility). How people control task focus and switch-readiness has therefore been the target of burgeoning research literatures. Here, I review and integrate these literatures to derive a cognitive architecture and functional rules underlying the regulation of stability and flexibility. I propose that task focus and switch-readiness are supported by independent mechanisms whose strategic regulation is nevertheless governed by shared principles: both stability and flexibility are matched to anticipated challenges via an incremental, online learner that nudges control up or down based on the recent history of task demands (a recency heuristic), as well as via episodic reinstatement when the current context matches a past experience (a recognition heuristic).

Influence of the context of administration in the antidepressant-like effects of the psychedelic 5-MeO-DMT

Psychedelics like psilocybin have shown rapid and long-lasting efficacy on depressive and anxiety symptoms. Other psychedelics with shorter half-lives, such as DMT and 5-MeO-DMT, have also shown promising preliminary outcomes in major depression, making them interesting candidates for clinical practice. Despite several promising clinical studies, the influence of the context on therapeutic responses or adverse effects remains poorly documented. To address this, we conducted preclinical studies evaluating the psychopharmacological profile of 5-MeO-DMT in contexts previously validated in mice as either pleasant (positive setting) or aversive (negative setting). Healthy C57BL/6J male mice received a single intraperitoneal (i.p.) injection of 5-MeO-DMT at doses of 0.5, 5, and 10 mg/kg, with assessments at 2 hours, 24 hours, and one week post-administration. In a corticosterone (CORT) mouse model of depression, 5-MeO-DMT was administered in different settings, and behavioral tests mimicking core symptoms of depression and anxiety were conducted. In CORT-exposed mice, an acute dose of 0.5 mg/kg administered in a neutral setting produced antidepressant-like effects at 24 hours, as observed by reduced immobility time in the Tail Suspension Test (TST). In a positive setting, the drug also reduced latency to first immobility and total immobility time in the TST. However, these beneficial effects were negated in a negative setting, where 5-MeO-DMT failed to produce antidepressant-like effects and instead elicited an anxiogenic response in the Elevated Plus Maze (EPM).Our results indicate a strong influence of setting on the psychopharmacological profile of 5-MeO-DMT. Future experiments will examine cortical markers of pre- and post-synaptic density to correlate neuroplasticity changes with the behavioral effects of 5-MeO-DMT in different settings.

Exploring the cerebral mechanisms of acoustically-challenging speech comprehension - successes, failures and hope

Comprehending speech under acoustically challenging conditions is an everyday task that we can often execute with ease. However, accomplishing this requires the engagement of cognitive resources, such as auditory attention and working memory. The mechanisms that contribute to the robustness of speech comprehension are of substantial interest in the context of hearing mild to moderate hearing impairment, in which affected individuals typically report specific difficulties in understanding speech in background noise. Although hearing aids can help to mitigate this, they do not represent a universal solution, thus, finding alternative interventions is necessary. Given that age-related hearing loss (“presbycusis”) is inevitable, developing new approaches is all the more important in the context of aging populations. Moreover, untreated hearing loss in middle age has been identified as the most significant potentially modifiable predictor of dementia in later life. I will present research that has used a multi-methodological approach (fMRI, EEG, MEG and non-invasive brain stimulation) to try to elucidate the mechanisms that comprise the cognitive “last mile” in speech acousticallychallenging speech comprehension and to find ways to enhance them.

Epileptic micronetworks and their clinical relevance

A core aspect of clinical epileptology revolves around relating epileptic field potentials to underlying neural sources (e.g. an “epileptogenic focus”). Yet still, how neural population activity relates to epileptic field potentials and ultimately clinical phenomenology, remains far from being understood. After a brief overview on this topic, this seminar will focus on unpublished work, with an emphasis on seizure-related focal spreading depression. The presented results will include hippocampal and neocortical chronic in vivo two-photon population imaging and local field potential recordings of epileptic micronetworks in mice, in the context of viral encephalitis or optogenetic stimulation. The findings are corroborated by invasive depth electrode recordings (macroelectrodes and BF microwires) in epilepsy patients during pre-surgical evaluation. The presented work carries general implications for clinical epileptology, and basic epilepsy research.

Dyslexia, Rhythm, Language and the Developing Brain

Recent insights from auditory neuroscience provide a new perspective on how the brain encodes speech. Using these recent insights, I will provide an overview of key factors underpinning individual differences in children’s development of language and phonology, providing a context for exploring atypical reading development (dyslexia). Children with dyslexia are relatively insensitive to acoustic cues related to speech rhythm patterns. This lack of rhythmic sensitivity is related to the atypical neural encoding of rhythm patterns in speech by the brain. I will describe our recent data from infants as well as children, demonstrating developmental continuity in the key neural variables.

The Role of Spatial and Contextual Relations of real world objects in Interval Timing

In the real world, object arrangement follows a number of rules. Some of the rules pertain to the spatial relations between objects and scenes (i.e., syntactic rules) and others about the contextual relations (i.e., semantic rules). Research has shown that violation of semantic rules influences interval timing with the duration of scenes containing such violations to be overestimated as compared to scenes with no violations. However, no study has yet investigated whether both semantic and syntactic violations can affect timing in the same way. Furthermore, it is unclear whether the effect of scene violations on timing is due to attentional or other cognitive accounts. Using an oddball paradigm and real-world scenes with or without semantic and syntactic violations, we conducted two experiments on whether time dilation will be obtained in the presence of any type of scene violation and the role of attention in any such effect. Our results from Experiment 1 showed that time dilation indeed occurred in the presence of syntactic violations, while time compression was observed for semantic violations. In Experiment 2, we further investigated whether these estimations were driven by attentional accounts, by utilizing a contrast manipulation of the target objects. The results showed that an increased contrast led to duration overestimation for both semantic and syntactic oddballs. Together, our results indicate that scene violations differentially affect timing due to violation processing differences and, moreover, their effect on timing seems to be sensitive to attentional manipulations such as target contrast.

Bayesian expectation in the perception of the timing of stimulus sequences

In the current virtual journal club Dr Di Luca will present findings from a series of psychophysical investigations where he measured sensitivity and bias in the perception of the timing of stimuli. He will present how improved detection with longer sequences and biases in reporting isochrony can be accounted for by optimal statistical predictions. Among his findings was also that the timing of stimuli that occasionally deviate from a regularly paced sequence is perceptually distorted to appear more regular. Such change depends on whether the context these sequences are presented is also regular. Dr Di Luca will present a Bayesian model for the combination of dynamically updated expectations, in the form of a priori probability, with incoming sensory information. These findings contribute to the understanding of how the brain processes temporal information to shape perceptual experiences.

Varying the Effectiveness of Scene Context

Neuromodulation of subjective experience

Many psychoactive substances are used with the aim of altering experience, e.g. as analgesics, antidepressants or antipsychotics. These drugs act on specific receptor systems in the brain, including the opioid, serotonergic and dopaminergic systems. In this talk, I will summarise human drug studies targeting opioid receptors and their role for human experience, with focus on the experience of pain, stress, mood, and social connection. Opioids are only indicated for analgesia, due to their potential to cause addiction. When these regulations occurred, other known effects were relegated to side effects. This may be the cause of the prevalent myth that opioids are the most potent painkillers, despite evidence from head-to-head trials, Cochrane reviews and network meta-analyses that opioids are not superior to non-opioid analgesics in the treatment of acute or chronic non-cancer pain. However, due to the variability and diversity of opioid effects across contexts and experiences, some people under some circumstances may indeed benefit from prolonged treatment. I will present data on individual differences in opioid effects due to participant sex and stress induction. Understanding the effects of these commonly used medications on other aspects of the human experience is important to ensure correct use and to prevent unnecessary pain and addiction risk.

Consolidation of remote contextual memory in the neocortical memory engram

Recent studies identified memory engram neurons, a neuronal population that is recruited by initial learning and is reactivated during memory recall.  Memory engram neurons are connected to one another through memory engram synapses in a distributed network of brain areas.  Our central hypothesis is that an associative memory is encoded and consolidated by selective strengthening of engram synapses.  We are testing this hypothesis, using a combination of engram cell labeling, optogenetic/chemogenetic, electrophysiological, and virus tracing approaches in rodent models of contextual fear conditioning.  In this talk, I will discuss our findings on how synaptic plasticity in memory engram synapses contributes to the acquisition and consolidation of contextual fear memory in a distributed network of the amygdala, hippocampus, and neocortex.

The role of CNS microglia in health and disease

Microglia are the resident CNS macrophages of the brain parenchyma. They have many and opposing roles in health and disease, ranging from inflammatory to anti-inflammatory and protective functions, depending on the developmental stage and the disease context. In Multiple Sclerosis, microglia are involved to important hallmarks of the disease, such as inflammation, demyelination, axonal damage and remyelination, however the exact mechanisms controlling their transformation towards a protective or devastating phenotype during the disease progression remains largely unknown until now. We wish to understand how brain microglia respond to demyelinating insults and how their behaviour changes in recovery. To do so we developed a novel histopathological analysis approach in 3D and a cell-based analysis tool that when applied in the cuprizone model of demyelination revealed region- and disease- dependent changes in microglial dynamics in the brain grey matter during demyelination and remyelination. We now use similar approaches with the aim to unravel sensitive changes in microglial dynamics during neuroinflammation in the EAE model. Furthermore, we employ constitutive knockout and tamoxifen-inducible gene-targeting approaches, immunological techniques, genetics and bioinformatics and currently seek to clarify the specific role of the brain resident microglial NF-κB molecular pathway versus other tissue macrophages in EAE.

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.

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.

The Geometry of Decision-Making

Running, swimming, or flying through the world, animals are constantly making decisions while on the move—decisions that allow them to choose where to eat, where to hide, and with whom to associate. Despite this most studies have considered only on the outcome of, and time taken to make, decisions. Motion is, however, crucial in terms of how space is represented by organisms during spatial decision-making. Employing a range of new technologies, including automated tracking, computational reconstruction of sensory information, and immersive ‘holographic’ virtual reality (VR) for animals, experiments with fruit flies, locusts and zebrafish (representing aerial, terrestrial and aquatic locomotion, respectively), I will demonstrate that this time-varying representation results in the emergence of new and fundamental geometric principles that considerably impact decision-making. Specifically, we find that the brain spontaneously reduces multi-choice decisions into a series of abrupt (‘critical’) binary decisions in space-time, a process that repeats until only one option—the one ultimately selected by the individual—remains. Due to the critical nature of these transitions (and the corresponding increase in ‘susceptibility’) even noisy brains are extremely sensitive to very small differences between remaining options (e.g., a very small difference in neuronal activity being in “favor” of one option) near these locations in space-time. This mechanism facilitates highly effective decision-making, and is shown to be robust both to the number of options available, and to context, such as whether options are static (e.g. refuges) or mobile (e.g. other animals). In addition, we find evidence that the same geometric principles of decision-making occur across scales of biological organisation, from neural dynamics to animal collectives, suggesting they are fundamental features of spatiotemporal computation.

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

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

Precise spatio-temporal spike patterns in cortex and model

The cell assembly hypothesis postulates that groups of coordinated neurons form the basis of information processing. Here, we test this hypothesis by analyzing massively parallel spiking activity recorded in monkey motor cortex during a reach-to-grasp experiment for the presence of significant ms-precise spatio-temporal spike patterns (STPs). For this purpose, the parallel spike trains were analyzed for STPs by the SPADE method (Stella et al, 2019, Biosystems), which detects, counts and evaluates spike patterns for their significance by the use of surrogates (Stella et al, 2022 eNeuro). As a result we find STPs in 19/20 data sets (each of 15min) from two monkeys, but only a small fraction of the recorded neurons are involved in STPs. To consider the different behavioral states during the task, we analyzed the data in a quasi time-resolved analysis by dividing the data into behaviorally relevant time epochs. The STPs that occur in the various epochs are specific to behavioral context - in terms of neurons involved and temporal lags between the spikes of the STP. Furthermore we find, that the STPs often share individual neurons across epochs. Since we interprete the occurrence of a particular STP as the signature of a particular active cell assembly, our interpretation is that the neurons multiplex their cell assembly membership. In a related study, we model these findings by networks with embedded synfire chains (Kleinjohann et al, 2022, bioRxiv 2022.08.02.502431).

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.

Autopoiesis and Enaction in the Game of Life

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

How Children Design by Analogy: The Role of Spatial Thinking

Analogical reasoning is a common reasoning tool for learning and problem-solving. Existing research has extensively studied children’s reasoning when comparing, or choosing from ready-made analogies. Relatively less is known about how children come up with analogies in authentic learning environments. Design education provides a suitable context to investigate how children generate analogies for creative learning purposes. Meanwhile, the frequent use of visual analogies in design provides an additional opportunity to understand the role of spatial reasoning in design-by-analogy. Spatial reasoning is one of the most studied human cognitive factors and is critical to the learning of science, technology, engineering, arts, and mathematics (STEAM). There is growing interest in exploring the interplay between analogical reasoning and spatial reasoning. In this talk, I will share qualitative findings from a case study, where a class of 11-to-12-year-olds in the Netherlands participated in a biomimicry design project. These findings illustrate (1) practical ways to support children’s analogical reasoning in the ideation process and (2) the potential role of spatial reasoning as seen in children mapping form-function relationships in nature analogically and adaptively to those in human designs.

Fidelity and Replication: Modelling the Impact of Protocol Deviations on Effect Size

Cognitive science and cognitive neuroscience researchers have agreed that the replication of findings is important for establishing which ideas (or theories) are integral to the study of cognition across the lifespan. Recently, high-profile papers have called into question findings that were once thought to be unassailable. Much attention has been paid to how p-hacking, publication bias, and sample size are responsible for failed replications. However, much less attention has been paid to the fidelity by which researchers enact study protocols. Researchers conducting education or clinical trials are aware of the importance in fidelity – or the extent to which the protocols are delivered in the same way across participants. Nevertheless, this idea has not been applied to cognitive contexts. This seminar discusses factors that impact the replicability of findings alongside recent models suggesting that even small fidelity deviations have real impacts on the data collected.

Multimodal Blending

In this talk, I’ll consider how new ideas emerge from old ones via the process of conceptual blending. I’ll start by considering analogical reasoning in problem solving and the role conceptual blending plays in these problem-solving contexts. Then I’ll consider blending in multi-modal contexts, including timelines, memes (viz. image macros), and, if time allows, zoom meetings. I suggest mappings analogy researchers have traditionally considered superficial are often important for the development of novel abstractions. Likewise, the analogue portion of multimodal blends anchors their generative capacity. Overall, these observations underscore the extent to which meaning is a socially distributed process whose intermediate products are stored in cognitive artifacts such as text and digital images.

Understanding Machine Learning via Exactly Solvable Statistical Physics Models

The affinity between statistical physics and machine learning has a long history. I will describe the main lines of this long-lasting friendship in the context of current theoretical challenges and open questions about deep learning. Theoretical physics often proceeds in terms of solvable synthetic models, I will describe the related line of work on solvable models of simple feed-forward neural networks. I will highlight a path forward to capture the subtle interplay between the structure of the data, the architecture of the network, and the optimization algorithms commonly used for learning.

Children-Agent Interaction For Assessment and Rehabilitation: From Linguistic Skills To Mental Well-being

Socially Assistive Robots (SARs) have shown great potential to help children in therapeutic and healthcare contexts. SARs have been used for companionship, learning enhancement, social and communication skills rehabilitation for children with special needs (e.g., autism), and mood improvement. Robots can be used as novel tools to assess and rehabilitate children’s communication skills and mental well-being by providing affordable and accessible therapeutic and mental health services. In this talk, I will present the various studies I have conducted during my PhD and at the Cambridge Affective Intelligence and Robotics Lab to explore how robots can help assess and rehabilitate children’s communication skills and mental well-being. More specifically, I will provide both quantitative and qualitative results and findings from (i) an exploratory study with children with autism and global developmental disorders to investigate the use of intelligent personal assistants in therapy; (ii) an empirical study involving children with and without language disorders interacting with a physical robot, a virtual agent, and a human counterpart to assess their linguistic skills; (iii) an 8-week longitudinal study involving children with autism and language disorders who interacted either with a physical or a virtual robot to rehabilitate their linguistic skills; and (iv) an empirical study to aid the assessment of mental well-being in children. These findings can inform and help the child-robot interaction community design and develop new adaptive robots to help assess and rehabilitate linguistic skills and mental well-being in children.

Extracting computational mechanisms from neural data using low-rank RNNs

An influential theory in systems neuroscience suggests that brain function can be understood through low-dimensional dynamics [Vyas et al 2020]. However, a challenge in this framework is that a single computational task may involve a range of dynamic processes. To understand which processes are at play in the brain, it is important to use data on neural activity to constrain models. In this study, we present a method for extracting low-dimensional dynamics from data using low-rank recurrent neural networks (lrRNNs), a highly expressive and understandable type of model [Mastrogiuseppe & Ostojic 2018, Dubreuil, Valente et al. 2022]. We first test our approach using synthetic data created from full-rank RNNs that have been trained on various brain tasks. We find that lrRNNs fitted to neural activity allow us to identify the collective computational processes and make new predictions for inactivations in the original RNNs. We then apply our method to data recorded from the prefrontal cortex of primates during a context-dependent decision-making task. Our approach enables us to assign computational roles to the different latent variables and provides a mechanistic model of the recorded dynamics, which can be used to perform in silico experiments like inactivations and provide testable predictions.

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.

Flexible selection of task-relevant features through population gating

Brains can gracefully weed out irrelevant stimuli to guide behavior. This feat is believed to rely on a progressive selection of task-relevant stimuli across the cortical hierarchy, but the specific across-area interactions enabling stimulus selection are still unclear. Here, we propose that population gating, occurring within A1 but controlled by top-down inputs from mPFC, can support across-area stimulus selection. Examining single-unit activity recorded while rats performed an auditory context-dependent task, we found that A1 encoded relevant and irrelevant stimuli along a common dimension of its neural space. Yet, the relevant stimulus encoding was enhanced along an extra dimension. In turn, mPFC encoded only the stimulus relevant to the ongoing context. To identify candidate mechanisms for stimulus selection within A1, we reverse-engineered low-rank RNNs trained on a similar task. Our analyses predicted that two context-modulated neural populations gated their preferred stimulus in opposite contexts, which we confirmed in further analyses of A1. Finally, we show in a two-region RNN how population gating within A1 could be controlled by top-down inputs from PFC, enabling flexible across-area communication despite fixed inter-areal connectivity.

Multisensory influences on vision: Sounds enhance and alter visual-perceptual processing

Visual perception is traditionally studied in isolation from other sensory systems, and while this approach has been exceptionally successful, in the real world, visual objects are often accompanied by sounds, smells, tactile information, or taste. How is visual processing influenced by these other sensory inputs? In this talk, I will review studies from our lab showing that a sound can influence the perception of a visual object in multiple ways. In the first part, I will focus on spatial interactions between sound and sight, demonstrating that co-localized sounds enhance visual perception. Then, I will show that these cross-modal interactions also occur at a higher contextual and semantic level, where naturalistic sounds facilitate the processing of real-world objects that match these sounds. Throughout my talk I will explore to what extent sounds not only improve visual processing but also alter perceptual representations of the objects we see. Most broadly, I will argue for the importance of considering multisensory influences on visual perception for a more complete understanding of our visual experience.

Modelling metaphor comprehension as a form of analogizing

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

Beyond Biologically Plausible Spiking Networks for Neuromorphic Computing

Biologically plausible spiking neural networks (SNNs) are an emerging architecture for deep learning tasks due to their energy efficiency when implemented on neuromorphic hardware. However, many of the biological features are at best irrelevant and at worst counterproductive when evaluated in the context of task performance and suitability for neuromorphic hardware. In this talk, I will present an alternative paradigm to design deep learning architectures with good task performance in real-world benchmarks while maintaining all the advantages of SNNs. We do this by focusing on two main features – event-based computation and activity sparsity. Starting from the performant gated recurrent unit (GRU) deep learning architecture, we modify it to make it event-based and activity-sparse. The resulting event-based GRU (EGRU) is extremely efficient for both training and inference. At the same time, it achieves performance close to conventional deep learning architectures in challenging tasks such as language modelling, gesture recognition and sequential MNIST.

Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity

Memory is a key component of biological neural systems that enables the retention of information over a huge range of temporal scales, ranging from hundreds of milliseconds up to years. While Hebbian plasticity is believed to play a pivotal role in biological memory, it has so far been analyzed mostly in the context of pattern completion and unsupervised learning. Here, we propose that Hebbian plasticity is fundamental for computations in biological neural systems. We introduce a novel spiking neural network (SNN) architecture that is enriched by Hebbian synaptic plasticity. We experimentally show that our memory-equipped SNN model outperforms state-of-the-art deep learning mechanisms in a sequential pattern-memorization task, as well as demonstrate superior out-of-distribution generalization capabilities compared to these models. We further show that our model can be successfully applied to one-shot learning and classification of handwritten characters, improving over the state-of-the-art SNN model. We also demonstrate the capability of our model to learn associations for audio to image synthesis from spoken and handwritten digits. Our SNN model further presents a novel solution to a variety of cognitive question answering tasks from a standard benchmark, achieving comparable performance to both memory-augmented ANN and SNN-based state-of-the-art solutions to this problem. Finally we demonstrate that our model is able to learn from rewards on an episodic reinforcement learning task and attain near-optimal strategy on a memory-based card game. Hence, our results show that Hebbian enrichment renders spiking neural networks surprisingly versatile in terms of their computational as well as learning capabilities. Since local Hebbian plasticity can easily be implemented in neuromorphic hardware, this also suggests that powerful cognitive neuromorphic systems can be build based on this principle.

Context-dependent selectivity to natural scenes in the retina

Restructuring cortical feedback circuits

We hardly notice when there is a speck on our glasses, the obstructed visual information seems to be magically filled in. The mechanistic basis for this fundamental perceptual phenomenon has, however, remained obscure. What enables neurons in the visual system to respond to context when the stimulus is not available? While feedforward information drives the activity in cortex, feedback information is thought to provide contextual signals that are merely modulatory. We have made the discovery that mouse primary visual cortical neurons are strongly driven by feedback projections from higher visual areas when their feedforward sensory input from the retina is missing. This drive is so strong that it makes visual cortical neurons fire as much as if they were receiving a direct sensory input. These signals are likely used to predict input from the feedforward pathway. Preliminary results show that these feedback projections are strongly influenced by experience and learning.

Pitch and Time Interact in Auditory Perception

Research into pitch perception and time perception has typically treated the two as independent processes. However, previous studies of music and speech perception have suggested that pitch and timing information may be processed in an integrated manner, such that the pitch of an auditory stimulus can influence a person’s perception, expectation, and memory of its duration and tempo. Typically, higher-pitched sounds are perceived as faster and longer in duration than lower-pitched sounds with identical timing. We conducted a series of experiments to better understand the limits of this pitch-time integrality. Across several experiments, we tested whether the higher-equals-faster illusion generalizes across the broader frequency range of human hearing by asking participants to compare the tempo of a repeating tone played in one of six octaves to a metronomic standard. When participants heard tones from all six octaves, we consistently found an inverted U-shaped effect of the tone’s pitch height, such that perceived tempo peaked between A4 (440 Hz) and A5 (880 Hz) and decreased at lower and higher octaves. However, we found that the decrease in perceived tempo at extremely high octaves could be abolished by exposing participants to high-pitched tones only, suggesting that pitch-induced timing biases are context sensitive. We additionally tested how the timing of an auditory stimulus influences the perception of its pitch, using a pitch discrimination task in which probe tones occurred early, late, or on the beat within a rhythmic context. Probe timing strongly biased participants to rate later tones as lower in pitch than earlier tones. Together, these results suggest that pitch and time exert a bidirectional influence on one another, providing evidence for integrated processing of pitch and timing information in auditory perception. Identifying the mechanisms behind this pitch-time interaction will be critical for integrating current models of pitch and tempo processing.

General purpose event-based architectures for deep learning

Biologically plausible spiking neural networks (SNNs) are an emerging architecture for deep learning tasks due to their energy efficiency when implemented on neuromorphic hardware. However, many of the biological features are at best irrelevant and at worst counterproductive when evaluated in the context of task performance and suitability for neuromorphic hardware. In this talk, I will present an alternative paradigm to design deep learning architectures with good task performance in real-world benchmarks while maintaining all the advantages of SNNs. We do this by focusing on two main features -- event-based computation and activity sparsity. Starting from the performant gated recurrent unit (GRU) deep learning architecture, we modify it to make it event-based and activity-sparse. The resulting event-based GRU (EGRU) is extremely efficient for both training and inference. At the same time, it achieves performance close to conventional deep learning architectures in challenging tasks such as language modelling, gesture recognition and sequential MNIST

Redox and mitochondrial dysregulation in epilepsy

Epileptic seizures render the brain uniquely dependent on energy producing pathways. Studies in our laboratory have been focused on the role of redox processes and mitochondria in the context of abnormal neuronal excitability associated with epilepsy. We have shown that that status epilepticus (SE) alters mitochondrial and cellular redox status, energetics and function and conversely, that reactive oxygen species and resultant dysfunction can lead to chronic epilepsy. Oxidative stress and neuroinflammatory pathways have considerable crosstalk and targeting redox processes has recently been shown to control neuroinflammation and excitability. Understanding the role of metabolic and redox processes can enable the development of novel therapeutics to control epilepsy and/or its comorbidities.

Learning static and dynamic mappings with local self-supervised plasticity

Animals exhibit remarkable learning capabilities with little direct supervision. Likewise, self-supervised learning is an emergent paradigm in artificial intelligence, closing the performance gap to supervised learning. In the context of biology, self-supervised learning corresponds to a setting where one sense or specific stimulus may serve as a supervisory signal for another. After learning, the latter can be used to predict the former. On the implementation level, it has been demonstrated that such predictive learning can occur at the single neuron level, in compartmentalized neurons that separate and associate information from different streams. We demonstrate the power such self-supervised learning over unsupervised (Hebb-like) learning rules, which depend heavily on stimulus statistics, in two examples: First, in the context of animal navigation where predictive learning can associate internal self-motion information always available to the animal with external visual landmark information, leading to accurate path-integration in the dark. We focus on the well-characterized fly head direction system and show that our setting learns a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading, and where the network remaps to integrate with different gains. Second, we show that incorporating global gating by reward prediction errors allows the same setting to learn conditioning at the neuronal level with mixed selectivity. At its core, conditioning entails associating a neural activity pattern induced by an unconditioned stimulus (US) with the pattern arising in response to a conditioned stimulus (CS). Solving the generic problem of pattern-to-pattern associations naturally leads to emergent cognitive phenomena like blocking, overshadowing, saliency effects, extinction, interstimulus interval effects etc. Surprisingly, we find that the same network offers a reductionist mechanism for causal inference by resolving the post hoc, ergo propter hoc fallacy.

Flexible multitask computation in recurrent networks utilizes shared dynamical motifs

Flexible computation is a hallmark of intelligent behavior. Yet, little is known about how neural networks contextually reconfigure for different computations. Humans are able to perform a new task without extensive training, presumably through the composition of elementary processes that were previously learned. Cognitive scientists have long hypothesized the possibility of a compositional neural code, where complex neural computations are made up of constituent components; however, the neural substrate underlying this structure remains elusive in biological and artificial neural networks. Here we identified an algorithmic neural substrate for compositional computation through the study of multitasking artificial recurrent neural networks. Dynamical systems analyses of networks revealed learned computational strategies that mirrored the modular subtask structure of the task-set used for training. Dynamical motifs such as attractors, decision boundaries and rotations were reused across different task computations. For example, tasks that required memory of a continuous circular variable repurposed the same ring attractor. We show that dynamical motifs are implemented by clusters of units and are reused across different contexts, allowing for flexibility and generalization of previously learned computation. Lesioning these clusters resulted in modular effects on network performance: a lesion that destroyed one dynamical motif only minimally perturbed the structure of other dynamical motifs. Finally, modular dynamical motifs could be reconfigured for fast transfer learning. After slow initial learning of dynamical motifs, a subsequent faster stage of learning reconfigured motifs to perform novel tasks. This work contributes to a more fundamental understanding of compositional computation underlying flexible general intelligence in neural systems. We present a conceptual framework that establishes dynamical motifs as a fundamental unit of computation, intermediate between the neuron and the network. As more whole brain imaging studies record neural activity from multiple specialized systems simultaneously, the framework of dynamical motifs will guide questions about specialization and generalization across brain regions.

At the nexus of genes, aging and environment: Understanding transcriptomic and epigenomic regulation in Parkinson's disease

Parkinson’s Disease (PD), the most common neurodegenerative movement disorder, is based on a complex interplay between genetic predispositions, aging processes, and environmental influences. In order to better understand the gene-environment axis in PD, we pursue a multi-omics approach to comprehensively interrogate genome-wide changes in histone modifications, DNA methylation, and hydroxymethylation, accompanied by transcriptomic profiling in cell and animal models of PD as well as large patient cohorts. Furthermore, we assess the plasticity of epigenomic modifications under influence of environmental factors using longitudinal cohorts of sporadic PD cases as well as mouse models exposed to specific environmental factors. Here, we present gene expression changes in PD mouse models in context of aging as well as environmental enrichment and high-fat diet.

A model of colour appearance based on efficient coding of natural images

An object’s colour, brightness and pattern are all influenced by its surroundings, and a number of visual phenomena and “illusions” have been discovered that highlight these often dramatic effects. Explanations for these phenomena range from low-level neural mechanisms to high-level processes that incorporate contextual information or prior knowledge. Importantly, few of these phenomena can currently be accounted for when measuring an object’s perceived colour. Here we ask to what extent colour appearance is predicted by a model based on the principle of coding efficiency. The model assumes that the image is encoded by noisy spatio-chromatic filters at one octave separations, which are either circularly symmetrical or oriented. Each spatial band’s lower threshold is set by the contrast sensitivity function, and the dynamic range of the band is a fixed multiple of this threshold, above which the response saturates. Filter outputs are then reweighted to give equal power in each channel for natural images. We demonstrate that the model fits human behavioural performance in psychophysics experiments, and also primate retinal ganglion responses. Next we systematically test the model’s ability to qualitatively predict over 35 brightness and colour phenomena, with almost complete success. This implies that contrary to high-level processing explanations, much of colour appearance is potentially attributable to simple mechanisms evolved for efficient coding of natural images, and is a basis for modelling the vision of humans and other animals.

Efficient Random Codes in a Shallow Neural Network

Efficient coding has served as a guiding principle in understanding the neural code. To date, however, it has been explored mainly in the context of peripheral sensory cells with simple tuning curves. By contrast, ‘deeper’ neurons such as grid cells come with more complex tuning properties which imply a different, yet highly efficient, strategy for representing information. I will show that a highly efficient code is not specific to a population of neurons with finely tuned response properties: it emerges robustly in a shallow network with random synapses. Here, the geometry of population responses implies that optimality obtains from a tradeoff between two qualitatively different types of error: ‘local’ errors (common to classical neural population codes) and ‘global’ (or ‘catastrophic’) errors. This tradeoff leads to efficient compression of information from a high-dimensional representation to a low-dimensional one. After describing the theoretical framework, I will use it to re-interpret recordings of motor cortex in behaving monkey. Our framework addresses the encoding of (sensory) information; if time allows, I will comment on ongoing work that focuses on decoding from the perspective of efficient coding.

Chemistry of the adaptive mind: lessons from dopamine

The human brain faces a variety of computational dilemmas, including the flexibility/stability, the speed/accuracy and the labor/leisure tradeoff. I will argue that striatal dopamine is particularly well suited to dynamically regulate these computational tradeoffs depending on constantly changing task demands. This working hypothesis is grounded in evidence from recent studies on learning, motivation and cognitive control in human volunteers, using chemical PET, psychopharmacology, and/or fMRI. These studies also begin to elucidate the mechanisms underlying the huge variability in catecholaminergic drug effects across different individuals and across different task contexts. For example, I will demonstrate how effects of the most commonly used psychostimulant methylphenidate on learning, Pavlovian and effortful instrumental control depend on fluctuations in current environmental volatility, on individual differences in working memory capacity and on opportunity cost respectively.

Predicting V1 contextual modulation and neural tuning using a convolutional neural network

Bernstein Conference 2024

Rhythm-structured predictive coding for contextualized speech processing

Bernstein Conference 2024

Contextual modulation of mesoscale functional connectivity

COSYNE 2022

Contextual motor learning in birdsong reflects two distinct neural processes

COSYNE 2022

Deliberation gated by opportunity cost adapts to context with urgency in non-human primates

COSYNE 2022

Differential encoding of temporal context and expectation across the visual hierarchy

COSYNE 2022

The emergence of gamma oscillations as a signature of gain control during context integration.

COSYNE 2022

Flexible circuit mechanisms for context-dependent song sequencing

COSYNE 2022

Flexible circuit mechanisms for context-dependent song sequencing

COSYNE 2022

Learning to combine sensory evidence and contextual priors under ambiguity

COSYNE 2022

Learning to combine sensory evidence and contextual priors under ambiguity

COSYNE 2022

Mind the gradient: context-dependent selectivity to natural images in the retina revealed with a novel perturbative approach

COSYNE 2022

Mind the gradient: context-dependent selectivity to natural images in the retina revealed with a novel perturbative approach

COSYNE 2022

Motor cortex isolates skill-specific dynamics in a context switching task

COSYNE 2022

Motor cortex isolates skill-specific dynamics in a context switching task

COSYNE 2022

A neural circuit model of hidden state inference for navigation and contextual memory

COSYNE 2022

A neural circuit model of hidden state inference for navigation and contextual memory

COSYNE 2022

Photoreceptor dynamics in the context of optimal chromatic codification

COSYNE 2022

Photoreceptor dynamics in the context of optimal chromatic codification

COSYNE 2022

The role of prior experience in the replay of both novel and familiar contexts

COSYNE 2022

The role of prior experience in the replay of both novel and familiar contexts

COSYNE 2022

A temporal context model of spatial memory

COSYNE 2022

A temporal context model of spatial memory

COSYNE 2022

Unifying model of contextual modulation with feedback from higher visual areas

COSYNE 2022

Unifying model of contextual modulation with feedback from higher visual areas

COSYNE 2022

Computation of abstract context in the midbrain reticular nucleus during perceptual decision-making

COSYNE 2023

On the Context-Dependent Efficient Coding of Olfactory Spaces

COSYNE 2023

Context-Dependent Epoch Codes in Association Cortex Shape Neural Computations

COSYNE 2023

Context-dependent sensory adaptation in cortical area MT as a substrate of flexible decision-making

COSYNE 2023

Differential effects of positive versus negative drug reinforcement on contextual coding

COSYNE 2023

Entorhinal grid-like signals reflect temporal context for human timing behavior

COSYNE 2023

Inferring the order of stable and context dependent perceptual biases in human vision

COSYNE 2023

Mechanisms of contextual fear memory suppression and extinction by the Nucleus Reuniens-CA1 pathway

COSYNE 2023

Mechanisms underlying flexible, context-dependent timing in medial entorhinal cortex

COSYNE 2023

Model-guided discovery of a retinal chromatic feature detector that signals visual context changes

COSYNE 2023

Modularity emerges in neural networks trained to perform context-dependent behavior

COSYNE 2023

Neural-astrocyte interaction enables contextually guided circuit dynamics

COSYNE 2023

Neural network dynamics underlying context-dependent perceptual decision making

COSYNE 2023

Variable syllable context depth in Bengalese finch songs: A Bayesian sequence model

COSYNE 2023

Effect of experience on context-dependent learning in recurrent networks

Bernstein Conference 2024