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Cartilage targeting exosomes for OA gene therapy and pain treatment

Project Summary Gene therapy has the potential to facilitate targeted expression of therapeutic proteins to promote cartilage regeneration in osteoarthritis (OA). The dense, avascular, aggrecan-glycosaminoglycan rich negatively charged cartilage, however, hinders their transport to reach chondrocytes in effective doses. While viral vector mediated gene delivery has shown promise, concerns over immunogenicity and tumorigenic side-effects persist. To address this, we have developed surface-modified cartilage-targeting MSC exosomes as non-viral carriers for gene therapy. MSC derived exosomes have intrinsic therapeutic potential as they can induce cartilage repair and are non-immunogenic, making them desirable for gene delivery. We have engineered charge-reversed cationic exosomes by anchoring cartilage targeting optimally charged arginine-rich cationic peptide (CPC) motifs into the anionic exosome bilayer (Exo-CPC) by using buffer pH as a charge-reversal switch. Exo-CPC use charge interactions to penetrate through the full thickness of arthritic cartilage (close to tidemark) and deliver the packaged genetic material cargo to chondrocytes residing in the deep tissue layers while native anionic exosomes cannot. They can also bind within the synovial joint, making them effective for OA pain relief gene therapy. Here we will engineer charge-reversed Exo-CPC for delivery of IL-1RA (receptor antagonist of interleukin-1) mRNA and NaV1.8 (voltage gated sodium channel 1.8) inhibitor siRNA to stimulate both disease modifying response and long-term pain relief with a one-time intra-articular dose. IL-1RA mRNA targets are in the chondrocytes and synovium cells; Nav1.8 expressing nerves innervate into synovium and subchondral bone in OA – sites that Exo-CPC can readily target. Aim 1 will engineer cartilage targeting Exo-CPC for delivery of IL- 1RA mRNA and Nav1.8 inhibitor siRNA. Their ability to deliver IL-1RA mRNA to chondrocytes and IL-1RA protein translation efficiency will be evaluated in-vitro. Exo-CPC-Na v1.8’s ability to reduce NaV1.8 bioactivity of sensory nerves will also be evaluated. In Aim 2, their distribution intra-articular (proximity to NaV1.8-positive nerves), extra-articular, and DRG and spinal cord using partial meniscectomy NaV1.8-tdTomato reporter mice OA models will be evaluated. Additionally, their dose dependent reduction on MMP activity, neuronal excitability and pain- related behaviors, and any immunogenicity will be assessed. Aim 3 will use the determined functional doses to study the long-term disease modifying and pain-relief effects of mono and combination therapy with Exo-CPC- IL-1RA and Exo-CPC-Nav1.8 in rescuing injury induced tissue structural damage as well as in reducing pain (weight bearing asymmetry) for up to one month following IA administration in early vs. late stages (intervention at 2 vs 6 weeks) of MMT (medial meniscectomy) induced OA rats. The project paves way for utilizing the intrinsic therapeutic potential of MSC Exosomes as viral-free, non-immunogenic carriers for OA gene therapy by employing cartilage as a drug depot. Cationic exosomes can be used to deliver other OA gene targets, and can be widely used for targeting other negatively charged tissues like meniscus, ligaments, discs, fracture callus etc.

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

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

TARGETING VAV1 SCAFFOLDING AND ENZYMATIC FUNCTIONS IN MULTIPLE SCLEROSIS VIA BRAIN-PENETRANT MOLECULAR GLUE DEGRADERS

Abstract Multiple Sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) with significant unmet medical needs, as current therapies offer limited efficacy against neurodegeneration and can have considerable side effects. VAV1, a key signaling protein predominantly expressed in hematopoietic cells, plays a crucial role in T and B lymphocyte activation and is genetically and functionally validated as a therapeutic target in MS. This project proposes an innovative approach to target VAV1 through the development of brain-penetrant molecular glue (MG) degraders. Distinct from Proteolysis Targeting Chimeras (PROTACs) that require a high- affinity ligand for the target protein, molecular glues can mediate degradation by engaging specific protein surface features, such as loops, without the necessity of a dedicated binder. These degraders aim to induce the proteasomal degradation of VAV1, thereby ablating both its enzymatic and scaffolding functions, which are implicated in neuroinflammation. The research strategy involves three primary aims: 1) To optimize lead VAV1 molecular glue degraders for enhanced potency, brain penetration, and favorable pharmacokinetic properties using advanced computational modeling and medicinal chemistry. 2) To evaluate the in vivo efficacy of the optimized VAV1 degraders in preclinical mouse models of MS (Experimental Autoimmune Encephalomyelitis - EAE), assessing their ability to ameliorate disease severity, reduce CNS inflammation and demyelination, and engage VAV1 in the CNS. 3) To investigate the Structure-Activity Relationship (SAR) of a novel non-canonical VAV1 degron motif, aiming to expand the understanding of molecular glue-mediated degradation and enable the rational design of degraders for other challenging therapeutic targets. Successful completion of this project is expected to deliver preclinical candidate VAV1 degraders with the potential for a novel, effective, and safer treatment paradigm for MS. Furthermore, the insights gained into non-canonical degron recognition will significantly advance the field of targeted protein degradation, broadening the scope of "undruggable" targets for therapeutic intervention in various diseases.

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.

Staphylococcus aureus metabolic requirements during skin colonization

Project Summary Staphylococcus aureus causes 76% of all skin infections, and yet simultaneously this pathogen asymptomatically colonizes the skin of 8-22% of healthy adults. Since the majority of S. aureus disease is the result of autoinfection from the colonizing strain, and invasive infections often originate from the skin, there is an urgent need to understand colonization mechanisms. In colonizing the skin, S. aureus encounters abundant levels of amino acid derivatives like urocanic acid and 5-oxoproline (OP) that contribute to the skin’s “acid mantle” and have reported anti-Staphylococcal properties. The central hypothesis of this project is that amino acid transport and catabolism is a critical feature of S. aureus skin colonization. To model this environment, we developed a skin-like media (SLM) to assess S. aureus physiology on the human skin surface. We determined the S. aureus transcriptional response using RNAseq and performed metabolomics in SLM, both of which demonstrated that amino acid catabolism genes are upregulated and that amino acids are rapidly consumed. These findings indicate that S. aureus has a skin expression program that enables survival and growth in this harsh environment. In Specific Aim 1, we are investigating S. aureus metabolism of serine, the second most abundant amino acid on human skin. We hypothesize that serine transport and catabolism is critical for S. aureus skin colonization. We will assess growth of mutant strains disrupted in serine pathways in the SLM and during mouse skin colonization. With 13C-tracing experiments we will investigate serine flux in S. aureus using metabolomics. We will determine serine transport mechanisms using bioinformatic guided targets and serine analogues. In Specific Aim 2, we will assess S. aureus resistance to toxic skin metabolites. OP is abundant on human skin and is known to be deleterious to bacteria. Our preliminary metabolomics studies indicate that S. aureus metabolizes OP in SLM, and we have identified a putative oxoprolinase (genes SAUSA300_1566-1561) that is upregulated on skin. We hypothesize that the detoxification of OP contributes to S. aureus survival on the skin. We will construct mutants in the 1566-1561 locus and test their contributions to OP metabolism in SLM with growth and metabolomics experiments. We will also investigate OP transport and test mutant strains in our mouse skin colonization model. In Specific Aim 3, we will identify new determinants of S. aureus skin colonization using TnSeq. We have developed an improved TnSeq library preparation and analysis protocol, and in our preliminary studies we performed TnSeq in SLM and in our mouse skin colonization model. We will evaluate pathway hits, such as respiration and fermentation, and aspartate metabolism targets by testing constructed mutants during SLM growth and in the mouse model. Novel hits will be validated with follow-up genetic experiments and 13C-tracing experiments. Collectively, the proposed studies will advance our knowledge of S. aureus colonization and adaptation to the skin environment.

Borrelia burgdorferi genotypic diversity, pathogenesis, and host cellular responses

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

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

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

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.

Multi-modal Micro Electrode Fluidic Array (MEFA) Shells for Brain Organoids

Abstract Brain organoids (BOs) derived from human stem cells bridge the gap between monolayer cell culture studies and animal models, which have well-documented limitations. Monolayer cell culture models fail to accurately replicate the 3D interconnectivity in the brain; animal models, while helpful, are limited due to interspecies differences, with most research focusing on rather phenotypical rather than mechanistic aspects. Concurrent with the advancement of BO models is the urgent need to develop 3D micro instrumentation supporting these organoids to investigate brain development and disease in their accurate physiological environment. Conventional microelectrode arrays (MEAs) used for neuronal cell culture studies are planar, which limits recording access to a small fraction of cells on the bottom side of the organoid. Also, conventional microfluidics is inherently planar, and while recent advances in 3D MEAs and 3D microfluidics have enabled electrical and chemical interrogation in 3D, combining both features with tunability and precision to allow independent and simultaneous control is challenging. Recently, we reported new 3D micro instrumentation in the form of 3D shell MEAs and demonstrated its applicability for electrical recording from BOs. They feature lithographically patterned and chip-integrated electrodes and self-folding polymer shells that can be triggered to wrap around BOs to measure electrical activity from the entire organoid surface. The 3D MEA shell system is modeled on and resembles a miniaturized electroencephalography (EEG) cap; the process used to make them is size-scalable, chip-integrated, and mass- producible. In the research, we aim to develop and validate 3D Micro Electrode Fluidic Array (MEFA) shells with multi-modal electrical recording and biochemical control capabilities, offering high spatiotemporal resolution, tunability, and scalability. Since 3D spatiotemporal patterns of neurochemicals play a critical role in molecular and cellular events of neural development and disease, we propose to apply and validate the MEFA shells in two studies that mimic neurodevelopment and monitor the spatiotemporal effects in neurological disorders and their treatments in vitro. We anticipate that the proposed 3D MEFAs would revolutionize brain sciences by permitting real-time, in-situ studies of electrical and chemical stimulation and interrogation of BOs in a high- throughput manner. The proposed 3D scalable, reproducible, and tunable 3D micro instrumentation for BOs has broad relevance to understanding brain development in utero and the development of anatomically accurate drug and toxicity screening platforms for brain sciences and neurological disorders.

Investigating the role of noncoding RNAs in malaria parasites through targeted Cas13-mediated degradation

Project Summary/Abstract One of the most significant sources of morbidity and mortality throughout large regions of the developing world continues to be malaria caused by infection with mosquito-borne parasites of the genus Plasmodium. The parasite species responsible for the most severe form of the disease is P. falciparum. To avoid antibodies produced by their host and thereby maintain lengthy infections, these parasites undergo a process called antigenic variation by which they can extend an infection for over a year. This results from changes in expression of a protein called PfEMP1, the primary antigenic and virulence determinant expressed on the surface of infected red blood cells. A large, multicopy gene family called var encodes different forms of PfEMP1, and switching expression between var genes enables parasites to evade antibody recognition and destruction by the immune system. The process requires precise and coordinated regulation of transcription of each var gene, however how this is accomplished is unknown. It was recently hypothesized that a family of noncoding RNAs (ncRNAs) plays a key role in controlling the expression of each var gene and in determining the likelihood of activation of any given gene. If correct, this would represent a significant advance in our understanding of how P. falciparum controls antigenic variation and avoids immune clearance. To test this hypothesis, we propose to adapt the CRISPR/Cas13 system of targeted RNA degradation for use in P. falciparum. Similar to the extensively used CRISPR/Cas9 system, CRISPR/Cas13 employes guide RNAs to target a nuclease to a sequence-specific target, however Cas13 targets single stranded RNA rather than DNA. By applying this system to the study of var-related ncRNAs, we will degrade specific ncRNAs and determine the effect on var gene expression. Two classes of ncRNAs previously proposed to regulate var gene expression will be targeted, one called ruf6 and a second encoded by the second exon of all var genes. This will enable us to alter ncRNA expression while leaving the underlying genomic DNA untouched, thereby allowing the unambiguous attribution of any resulting phenotypes to the ncRNAs. Aim 1 will optimize the Cas13 system for P. falciparum by testing different variants of the Cas13 endonuclease for their ability to degrade mRNAs encoding fluorescent reporter proteins. We will determine both the efficiency and sequence specificity of the system. Aim 2 will apply the system to var-associated ncRNAs and quantitatively measure changes in var gene expression and transcriptional switching. If successful, the adaptation of the Cas13 system to P. falciparum will provide the malaria research community with a powerful new tool for manipulating gene expression. In addition, we will gain valuable new insights into how malaria parasites regulate var gene expression, antigenic variation and immune evasion.

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.

Structure-Based Development of Nucleotide-Competing Inhibitors Against HIV-1 and LINE-1 Reverse Transcriptases

PROJECT SUMMARY Reverse transcriptases (RTs) from retroviruses and endogenous retroelements are essential polymerases that catalyze RNA- and DNA-dependent DNA synthesis. Nucleoside inhibitors (NIs) remain central to HIV-1 therapy and are also used against other viral infections and in cancer, but toxicity, limited selectivity, pharmacokinetic (PK) liabilities, and the emergence of drug resistance highlight the need for alternative RT inhibitor mechanisms. In contrast to NIs, nucleotide-competing inhibitors (NCIs) block the polymerase active site without requiring incorporation into nucleic acids. Structural studies by PI Ruiz have defined the NCI mechanism of action for HIV- 1 RT and revealed conserved binding modules shared across multiple polymerase families. These advances now enable rational discovery of improved NCIs. LINE-1 (L1) ORF2 RT is an emerging therapeutic target in cancer, autoimmunity, and aging, yet NIs are the only inhibitors known to act against L1 RT. Notably, the NCI-binding region is structurally similar between HIV-1 RT and L1 RT, suggesting that NCI recognition principles may extend across these two biologically distinct polymerases. This R21 seeks to establish proof-of-concept for NCI development against both enzymes. Aim 1 will discover and structurally optimize NCIs targeting HIV-1 RT by combining binding modules from known NCI chemotypes and determining their biochemical activity and co-crystal structures. Aim 2 will determine whether HIV-1 RT NCI principles translate to L1 RT by solving L1 RT/nucleic acid/NCI structures, evaluating enzymatic inhibition, and applying AI-based structure prediction and generative design to propose L1-specific NCI candidates. Cellular retrotransposition assays will test mechanism of action. Aim 3 will develop a fragment library tailored to protein–nucleic acid interfaces and perform fragment screening of HIV-1 and L1 RT/nucleic acid complexes to identify additional chemotypes that engage the NCI binding region. Successful completion will yield NCI scaffolds and mechanistic insights applicable to HIV-1 RT and L1 RT, define structural principles governing NCI recognition across two evolutionarily related polymerases, and establish new avenues for RT inhibitor development. The PI is highly qualified to lead this work, with extensive expertise in RT structural biology, drug design, and fragment-based discovery.

Engineering inducible morphotype switching control in Mycobacterium abscessus for investigating infection outcomes and discovering pathophysiological-targeted treatments

PROJECT SUMMARY Antibiotic-resistant nontuberculous mycobacteria (NTM) infections are rising at a rate of 8% each year and account for ~$1.7 billion in annual U.S. healthcare costs. Mycobacterium abscessus (Mabs), the most common rapidly growing NTM infection, is notoriously nicknamed the “antibiotic nightmare” for its extensive intrinsic and inducible broad-range multidrug resistance to antibiotic countermeasures. As part of its natural infection cycle, Mabs undergoes a morphotypical conversion from smooth to rough, characterized by irreversible genetic changes resulting in the loss of cell envelope glycopeptidolipids (GPLs). This morphotypic conversion is intimately associated with disease progression, ultimately leading to debilitating, refractory Mabs pulmonary disease. Specific stimuli triggering Mabs morphotypical conversion are unknown, thus preventing directed investigations into morphotype-specific immunological responses and the discovery of morphotype-specific therapeutic targets. This project leverages cutting-edge molecular genetic tools, including CRISPR (clustered regularly interspersed short palindromic repeats) interference (CRISPRi) and inducible knockdown control of CRISPRi via the anhydrotetracycline-inducible TetR-regulated promoter-operator system, to create six unique, reversible Mabs smooth to conditional rough morphotype strains. These molecular morphoswitchable strains allow precise investigator-mediated on-off control of Mabs surface GPLs, enabling investigations into Mabs morphological plasticity, unique pathophysiology traits associated with each morphotype, and the complex interplay between Mabs and morphotype-specific immunological responses. In Aim 1, we implement CRISPRi inducible knockdown tunable control of Mabs morphotype switching by targeting six, independent genetic targets directly involved in GPL biosynthesis (mps1, mps2) or transport (mmpS4, mmpL4a, mmpL4b, gap) and validate in vitro morphoswitching. In Aim 2, we establish and confirm Mabs morphoswitching and intracellular growth in infected THP-1 macrophages. Subsequently, we evaluate differential and distinct innate cellular immune responses elicited by Mabs smooth and Mabs conditional rough morphotypes during intracellular infection in human primary monocyte-derived macrophages. Collectively, these studies create a suite of characterized and reversible Mabs smooth and conditional rough morphoswitchable strains with controlled, regulated, and on- demand expression of Mabs surface GPLs. By enabling precisely timed and controlled induction of the Mabs conditional rough morphotype during intracellular growth, we can molecularly dissect and investigate fundamental Mabs host-pathogen interactions and immunological responses that so substantially influence negative clinical outcomes.

Structure-function and mechanistic studies of a specific glycosyltransferase complex in fusion-driven pediatric gliomas

Abstract Glycosylation is a co/post-translational modification involved in cell-matrix interactions, antigen-antibody interactions, tumor invasion, and cell motility. Abnormal glycosylation is a hallmark of cancer, with various glycosylation-related genes linked to glioma prognosis and tumor heterogeneity. Pediatric low-grade gliomas (pLGGs) stand as the most common childhood central nervous system tumor, accounting for 30%-40% of all CNS tumors in children. Despite its relatively low mortality rate, pLGGs are associated with devastating lifelong morbidity. The most common alteration found in 75% of tumors is the KIAA1549:BRAF fusion, causing an aberrant activation of the MAPK/ERK signaling pathway. Current treatments, such as traditional chemotherapies and targeted therapies, have limitations such as resistance, lack of specificity, toxicity and paradoxical activation of the MAPK pathway. This highlights the urgent need for novel therapeutic approaches. Investigations into KIAA1549:BRAF-driven pLGGs identified their dependency on the protein-O-mannosyl transferase (POMT) complex for survival. In contrast, BRAFV600E-mutant cells did not show dependency, suggesting the POMT complex as a vulnerability and promising target in KIAA1549:BRAF-driven pLGGs. Therefore, our goal is to characterize the POMT complex structurally and biochemically and study its roles in KIAA1549:BRAF-driven pLGGs. In this proposal, we aim to 1) determine the high-resolution structures of the complex in its unbound, substrate-bound, and inhibitor-bound forms and 2) elucidate the POMT complex mechanisms in KIAA1549:BRAF-driven pLGGs. We will define the critical functional domains, active sites, interaction interfaces and translational modifications crucial for enzymatic activity using cryo-EM techniques, mutagenesis, and functional studies. To study biological pathways and molecular events modulated by the POMT complex, we will implement global proteomics and transcriptomics analysis in well-characterized disease models. In parallel, we will assess the effect of the POMT complex on the MAPK/ERK signaling pathway. This study will guide the structure-based design of probes and drugs targeting the POMT complex and will unveil glycosylation-mediated oncogenesis in pediatric gliomas. It will aid in the development of new targeted therapies and the identification of new biomarkers for pLGGs harboring the KIAA1549:BRAF fusion. The research will be conducted in the Fischer lab at Dana-Farber Cancer Institute, which provides a collaborative and resource-rich environment. The career development plan includes training in scientific writing, mentoring, and presentation skills, as well as interdisciplinary networking with experts in structural biology and pediatric oncology. The candidate’s career goal is to establish an independent research laboratory focused on developing new therapeutic modalities for pediatric neurooncology. The training provided through this fellowship represents a critical step toward achieving this goal.

Identifying host-interacting proteins of Sneathia vaginalis

PROJECT SUMMARY AND ABSTRACT Sneathia vaginalis is a member of the human normal flora of the vagina. It is also a human pathogen that is associated with preterm birth and amniotic fluid infections as well as the most common bacterial species associated with HPV infection and cervical cancer. The identification of S. vaginalis as a human pathogen is recent and little is known about how this bacterium interacts with the host in either its commensal or pathogenic lifestyles. With the exception of a single toxin, no additional virulence factors have been identified. Our preliminary data demonstrates that S. vaginalis grows to high cell density in rich media; however, it fails to grow planktonically in other media unless host cells are present indicating that S. vaginalis relies on host cells for nutrients. This is consistent with its reduced genome. In addition, bacterial proliferation requires close proximity with the host cells and previous studies demonstrate that S. vaginalis can bind a variety of host cells. The proteins that mediate contact are unknown. We hypothesize that proteins on the surface of S. vaginalis are critical for host cell adhesion. We will use two Aims to examine this. Aim 1 will use mass spectrometry to identify S. vaginalis surface proteins. Aim 2 generates deletion strains of potential adhesins identified in Aim 1 as well as predicted host-interacting proteins that have already been identified bioinformatically based on those in other bacteria. The mutant bacteria are then tested in host-cell adhesion assays. Together, these aims will identify for the first time the proteins found on the surface of S. vaginalis while identifying proteins that interact with host cells that would be expected to contribute to either its commensal or pathogenic lifestyles or both. Moreover, these studies would be used to inform clinical lab practice as surface-expressed proteins could be used to identify identifying markers of S. vaginalis detection.

Intrinsic and extrinsic mechanisms underlying trigeminal nerve deficits in familial dysautonomia

PROJECT SUMMARY Rare diseases impose a significant burden on the US healthcare system, accounting for nearly half of all expenditures for their treatment. This statistic alone supports the need to invest in research to develop therapeutic interventions for rare diseases since the economic benefit outweighs the continued expense of financial resources. Familial dysautonomia (FD) is a rare, hereditary disease that arises from a splice site mutation in Elongator acetyltransferase complex subunit 1 (ELP1) and impacts the nervous system. To date, FD patients continue to face life-threatening complications involving basic involuntary functions like swallowing and somatosensation because there is no cure for this ultimately fatal neuropathy. FD patients exhibit symptoms due to defects in their somatosensory trigeminal nerves, whose cell bodies reside in the trigeminal ganglion (TG) and are derived from neural crest and placode cells. Recent studies from our lab using an FD mouse model (Elp1 deleted from neural crest cells) revealed TG axon outgrowth and target tissue innervation deficits, recapitulating phenotypes observed in FD patients. However, the mechanisms by which Elp1 mediates normal TG development, and how this goes awry in FD, remain largely elusive. To gain insight into Elp1 function, we performed mass spectrometry to evaluate the TG proteome of normal and FD mouse embryos. Our results uncovered statistically significant increases in extracellular matrix (ECM) and ECM binding proteins, pointing to altered TG biomechanical properties and, more broadly, changes in mechanotransduction, the process by which cells translate extrinsic cues into intrinsic signaling pathways that modulate gene expression. Importantly, proper axon outgrowth relies upon mechanotransduction as growth cones on axons sense and respond to their environment. In the head, this environment consists of ECM and cranial mesenchyme cells, but the impact of Elp1 loss from the latter is not known, including the potential for altered tissue biomechanics that could influence TG axon outgrowth. We hypothesize that loss of Elp1 induces changes in the biomechanical properties of both the TG/nerves and ECM/cranial mesenchyme, modifying mechanotransduction and leading to TG defects in FD, which we will interrogate in the following Specific Aims: 1) define the biomechanical properties of the TG/nerves and ECM/cranial mesenchyme and 2) determine the role of cranial mesenchyme Elp1 in mediating proper TG axon outgrowth. Our innovative research proposal takes a systems-level, multidisciplinary approach involving embryology, biomechanics, and high-resolution microscopy, with the goal of integrating molecular, cellular, and tissue data. These results will significantly advance our knowledge of the molecular mechanisms underscoring TG development and, collectively, inform treatment strategies for birth defects or disorders like FD with TG dysfunction, as well as nerve repair and/or regeneration after injury or disease.

Development of a multi-modal mouse model of cluster headache

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

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.

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

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

Expanding mechanisms and therapeutic targets for neurodegenerative disease

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

Contentopic mapping and object dimensionality - a novel understanding on the organization of object knowledge

Our ability to recognize an object amongst many others is one of the most important features of the human mind. However, object recognition requires tremendous computational effort, as we need to solve a complex and recursive environment with ease and proficiency. This challenging feat is dependent on the implementation of an effective organization of knowledge in the brain. Here I put forth a novel understanding of how object knowledge is organized in the brain, by proposing that the organization of object knowledge follows key object-related dimensions, analogously to how sensory information is organized in the brain. Moreover, I will also put forth that this knowledge is topographically laid out in the cortical surface according to these object-related dimensions that code for different types of representational content – I call this contentopic mapping. I will show a combination of fMRI and behavioral data to support these hypotheses and present a principled way to explore the multidimensionality of object processing.

SWEBAGS conference 2024: Shared network mechanisms of dopamine and deep brain stimulation for the treatment of Parkinson’s disease: From modulation of oscillatory cortex – basal ganglia communication to intelligent clinical brain computer interfaces

Screen Savers : Protecting adolescent mental health in a digital world

In our rapidly evolving digital world, there is increasing concern about the impact of digital technologies and social media on the mental health of young people. Policymakers and the public are nervous. Psychologists are facing mounting pressures to deliver evidence that can inform policies and practices to safeguard both young people and society at large. However, research progress is slow while technological change is accelerating.My talk will reflect on this, both as a question of psychological science and metascience. Digital companies have designed highly popular environments that differ in important ways from traditional offline spaces. By revisiting the foundations of psychology (e.g. development and cognition) and considering digital changes' impact on theories and findings, we gain deeper insights into questions such as the following. (1) How do digital environments exacerbate developmental vulnerabilities that predispose young people to mental health conditions? (2) How do digital designs interact with cognitive and learning processes, formalised through computational approaches such as reinforcement learning or Bayesian modelling?However, we also need to face deeper questions about what it means to do science about new technologies and the challenge of keeping pace with technological advancements. Therefore, I discuss the concept of ‘fast science’, where, during crises, scientists might lower their standards of evidence to come to conclusions quicker. Might psychologists want to take this approach in the face of technological change and looming concerns? The talk concludes with a discussion of such strategies for 21st-century psychology research in the era of digitalization.

Imagining and seeing: two faces of prosopagnosia

Vision Unveiled: Understanding Face Perception in Children Treated for Congenital Blindness

Combined electrophysiological and optical recording of multi-scale neural circuit dynamics

This webinar will showcase new approaches for electrophysiological recordings using our silicon neural probes and surface arrays combined with diverse optical methods such as wide-field or 2-photon imaging, fiber photometry, and optogenetic perturbations in awake, behaving mice. Multi-modal recording of single units and local field potentials across cortex, hippocampus and thalamus alongside calcium activity via GCaMP6F in cortical neurons in triple-transgenic animals or in hippocampal astrocytes via viral transduction are brought to bear to reveal hitherto inaccessible and under-appreciated aspects of coordinated dynamics in the brain.

Stability of visual processing in passive and active vision

The visual system faces a dual challenge. On the one hand, features of the natural visual environment should be stably processed - irrespective of ongoing wiring changes, representational drift, and behavior. On the other hand, eye, head, and body motion require a robust integration of pose and gaze shifts in visual computations for a stable perception of the world. We address these dimensions of stable visual processing by studying the circuit mechanism of long-term representational stability, focusing on the role of plasticity, network structure, experience, and behavioral state while recording large-scale neuronal activity with miniature two-photon microscopy.

Modeling idiosyncratic evaluation of faces

Deepfake Detection in Super-Recognizers and Police Officers

Using videos from the Deepfake Detection Challenge (cf. Groh et al., 2021), we investigated human deepfake detection performance (DDP) in two unique observer groups: Super-Recognizers (SRs) and "normal" officers from within the 18K members of the Berlin Police. SRs were identified either via previously proposed lab-based procedures (Ramon, 2021) or the only existing tool for SR identification involving increasingly challenging, authentic forensic material: beSure® (Berlin Test For Super-Recognizer Identification; Ramon & Rjosk, 2022). Across two experiments we examined deepfake detection performance (DDP) in participants who judged single videos and pairs of videos in a 2AFC decision setting. We explored speed-accuracy trade-offs in DDP, compared DDP between lab-identified SRs and non-SRs, and police officers whose face identity processing skills had been extensively tested using challenging. In this talk I will discuss our surprising findings and argue that further work is needed too determine whether face identity processing is related to DDP or not.

Recognizing Faces: Insights from Group and Individual Differences

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

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

Sensory Consequences of Visual Actions

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

State-of-the-Art Spike Sorting with SpikeInterface

This webinar will focus on spike sorting analysis with SpikeInterface, an open-source framework for the analysis of extracellular electrophysiology data. After a brief introduction of the project (~30 mins) highlighting the basics of the SpikeInterface software and advanced features (e.g., data compression, quality metrics, drift correction, cloud visualization), we will have an extensive hands-on tutorial (~90 mins) showing how to use SpikeInterface in a real-world scenario. After attending the webinar, you will: (1) have a global overview of the different steps involved in a processing pipeline; (2) know how to write a complete analysis pipeline with SpikeInterface.

Effect of nutrient sensing by microglia on mouse behavior

Microglia are the brain macrophages, eliciting multifaceted functions to maintain brain homeostasis across lifetime. To achieve this, microglia are able to sense a plethora of signals in their close environment. In the lab, we investigate the effect of nutrients on microglia function for several reasons: 1) Microglia express all the cellular machinery required to sense nutrients; 2) Eating habits have changed considerably over the last century, towards diets rich in fats and sugars; 3) This so-called "Western diet" is accompanied by an increase in the occurrence of neuropathologies, in which microglia are known to play a role. In my talk, I will present data showing how variations in nutrient intake alter microglia function, including exacerbation of synaptic pruning, with profound consequences for neuronal activity and behavior. I will also show unpublished data on the mechanisms underlying the effects of nutrients on microglia, notably through the regulation of their metabolic activity.

Vocal emotion perception at millisecond speed

The human voice is possibly the most important sound category in the social landscape. Compared to other non-verbal emotion signals, the voice is particularly effective in communicating emotions: it can carry information over large distances and independent of sight. However, the study of vocal emotion expression and perception is surprisingly far less developed than the study of emotion in faces. Thereby, its neural and functional correlates remain elusive. As the voice represents a dynamically changing auditory stimulus, temporally sensitive techniques such as the EEG are particularly informative. In this talk, the dynamic neurocognitive operations that take place when we listen to vocal emotions will be specified, with a focus on the effects of stimulus type, task demands, and speaker and listener characteristics (e.g., age). These studies suggest that emotional voice perception is not only a matter of how one speaks but also of who speaks and who listens. Implications of these findings for the understanding of psychiatric disorders such as schizophrenia will be discussed.

Workplace Experiences of LGBTQIA+ Academics in Psychology, Psychiatry, and Neuroscience

In this webinar, Dr David Pagliaccio discusses the findings of his recent pre-print on workplace bias and discrimination faced by LGBTQIA+ brain scientists in the US.

Vision Unveiled: Understanding Face Perception in Children Treated for Congenital Blindness

Despite her still poor visual acuity and minimal visual experience, a 2-3 month old baby will reliably respond to facial expressions, smiling back at her caretaker or older sibling. But what if that same baby had been deprived of her early visual experience? Will she be able to appropriately respond to seemingly mundane interactions, such as a peer’s facial expression, if she begins seeing at the age of 10? My work is part of Project Prakash, a dual humanitarian/scientific mission to identify and treat curably blind children in India and then study how their brain learns to make sense of the visual world when their visual journey begins late in life. In my talk, I will give a brief overview of Project Prakash, and present findings from one of my primary lines of research: plasticity of face perception with late sight onset. Specifically, I will discuss a mixed methods effort to probe and explain the differential windows of plasticity that we find across different aspects of distributed face recognition, from distinguishing a face from a nonface early in the developmental trajectory, to recognizing facial expressions, identifying individuals, and even identifying one’s own caretaker. I will draw connections between our empirical findings and our recent theoretical work hypothesizing that children with late sight onset may suffer persistent face identification difficulties because of the unusual acuity progression they experience relative to typically developing infants. Finally, time permitting, I will point to potential implications of our findings in supporting newly-sighted children as they transition back into society and school, given that their needs and possibilities significantly change upon the introduction of vision into their lives.

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

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

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

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

Euclidean coordinates are the wrong prior for primate vision

The mapping from the visual field to V1 can be approximated by a log-polar transform. In this domain, scale is a left-right shift, and rotation is an up-down shift. When fed into a standard shift-invariant convolutional network, this provides scale and rotation invariance. However, translation invariance is lost. In our model, this is compensated for by multiple fixations on an object. Due to the high concentration of cones in the fovea with the dropoff of resolution in the periphery, fully 10 degrees of visual angle take up about half of V1, with the remaining 170 degrees (or so) taking up the other half. This layout provides the basis for the central and peripheral pathways. Simulations with this model closely match human performance in scene classification, and competition between the pathways leads to the peripheral pathway being used for this task. Remarkably, in spite of the property of rotation invariance, this model can explain the inverted face effect. We suggest that the standard method of using image coordinates is the wrong prior for models of primate vision.

A sense without sensors: how non-temporal stimulus features influence the perception and the neural representation of time

Any sensory experience of the world, from the touch of a caress to the smile on our friend’s face, is embedded in time and it is often associated with the perception of the flow of it. The perception of time is therefore a peculiar sensory experience built without dedicated sensors. How the perception of time and the content of a sensory experience interact to give rise to this unique percept is unclear. A few empirical evidences show the existence of this interaction, for example the speed of a moving object or the number of items displayed on a computer screen can bias the perceived duration of those objects. However, to what extent the coding of time is embedded within the coding of the stimulus itself, is sustained by the activity of the same or distinct neural populations and subserved by similar or distinct neural mechanisms is far from clear. Addressing these puzzles represents a way to gain insight on the mechanism(s) through which the brain represents the passage of time. In my talk I will present behavioral and neuroimaging studies to show how concurrent changes of visual stimulus duration, speed, visual contrast and numerosity, shape and modulate brain’s and pupil’s responses and, in case of numerosity and time, influence the topographic organization of these features along the cortical visual hierarchy.

Learning to see stuff

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

When to stop immune checkpoint inhibitor for malignant melanoma? Challenges in emulating target trials

Observational data have become a popular source of evidence for causal effects when no randomized controlled trial exists, or to supplement information provided by those. In practice, a wide range of designs and analytical choices exist, and one recent approach relies on the target trial emulation framework. This framework is particularly well suited to mimic what could be obtained in a specific randomized controlled trial, while avoiding time-related selection biases. In this abstract, we present how this framework could be useful to emulate trials in malignant melanoma, and the challenges faced when planning such a study using longitudinal observational data from a cohort study. More specifically, two questions are envisaged: duration of immune checkpoint inhibitors, and trials comparing treatment strategies for BRAF V600-mutant patients (targeted therapy as 1st line, followed by immunotherapy as 2nd line, vs. immunotherapy as 2nd line followed by targeted therapy as 1st line). Using data from 1027 participants to the MELBASE cohort, we detail the results for the emulation of a trial where immune checkpoint inhibitor would be stopped at 6 months vs. continued, in patients in response or with stable disease.

Implications of Vector-space models of Relational Concepts

Vector-space models are used frequently to compare similarity and dimensionality among entity concepts. What happens when we apply these models to relational concepts? What is the evidence that such models do apply to relational concepts? If we use such a model, then one implication is that maximizing surface feature variation should improve relational concept learning. For example, in STEM instruction, the effectiveness of teaching by analogy is often limited by students’ focus on superficial features of the source and target exemplars. However, in contrast to the prediction of the vector-space computational model, the strategy of progressive alignment (moving from perceptually similar to different targets) has been suggested to address this issue (Gentner & Hoyos, 2017), and human behavioral evidence has shown benefits from progressive alignment. Here I will present some preliminary data that supports the computational approach. Participants were explicitly instructed to match stimuli based on relations while perceptual similarity of stimuli varied parametrically. We found that lower perceptual similarity reduced accurate relational matching. This finding demonstrates that perceptual similarity may interfere with relational judgements, but also hints at why progressive alignment maybe effective. These are preliminary, exploratory data and I to hope receive feedback on the framework and to start a discussion in a group on the utility of vector-space models for relational concepts in general.

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.

Representations of people in the brain

Faces and voices convey much of the non-verbal information that we use when communicating with other people. We look at faces and listen to voices to recognize others, understand how they are feeling, and decide how to act. Recent research in my lab aims to investigate whether there are similar coding mechanisms to represent faces and voices, and whether there are brain regions that integrate information across the visual and auditory modalities. In the first part of my talk, I will focus on an fMRI study in which we found that a region of the posterior STS exhibits modality-general representations of familiar people that can be similarly driven by someone’s face and their voice (Tsantani et al. 2019). In the second part of the talk, I will describe our recent attempts to shed light on the type of information that is represented in different face-responsive brain regions (Tsantani et al., 2021).

Intrinsic Geometry of a Combinatorial Sensory Neural Code for Birdsong

Understanding the nature of neural representation is a central challenge of neuroscience. One common approach to this challenge is to compute receptive fields by correlating neural activity with external variables drawn from sensory signals. But these receptive fields are only meaningful to the experimenter, not the organism, because only the experimenter has access to both the neural activity and knowledge of the external variables. To understand neural representation more directly, recent methodological advances have sought to capture the intrinsic geometry of sensory driven neural responses without external reference. To date, this approach has largely been restricted to low-dimensional stimuli as in spatial navigation. In this talk, I will discuss recent work from my lab examining the intrinsic geometry of sensory representations in a model vocal communication system, songbirds. From the assumption that sensory systems capture invariant relationships among stimulus features, we conceptualized the space of natural birdsongs to lie on the surface of an n-dimensional hypersphere. We computed composite receptive field models for large populations of simultaneously recorded single neurons in the auditory forebrain and show that solutions to these models define convex regions of response probability in the spherical stimulus space. We then define a combinatorial code over the set of receptive fields, realized in the moment-to-moment spiking and non-spiking patterns across the population, and show that this code can be used to reconstruct high-fidelity spectrographic representations of natural songs from evoked neural responses. Notably, we find that topological relationships among combinatorial codewords directly mirror acoustic relationships among songs in the spherical stimulus space. That is, the time-varying pattern of co-activity across the neural population expresses an intrinsic representational geometry that mirrors the natural, extrinsic stimulus space.  Combinatorial patterns across this intrinsic space directly represent complex vocal communication signals, do not require computation of receptive fields, and are in a form, spike time coincidences, amenable to biophysical mechanisms of neural information propagation.

NEW TREATMENTS FOR PAIN: Unmet needs and how to meet them

“Of pain you could wish only one thing: that it should stop. Nothing in the world was so bad as physical pain. In the face of pain there are no heroes.- George Orwell, ‘1984’ " "Neuroscience has revealed the secrets of the brain and nervous system to an extent that was beyond the realm of imagination just 10-20 years ago, let alone in 1949 when Orwell wrote his prophetic novel. Understanding pain, however, presents a unique challenge to academia, industry and medicine, being both a measurable physiological process as well as deeply personal and subjective. Given the millions of people who suffer from pain every day, wishing only, “that it should stop”, the need to find more effective treatments cannot be understated." "‘New treatments for pain’ will bring together approximately 120 people from the commercial, academic, and not-for-profit sectors to share current knowledge, identify future directions, and enable collaboration, providing delegates with meaningful and practical ways to accelerate their own work into developing treatments for pain.

What do neurons want?

Neuroscience of socioeconomic status and poverty: Is it actionable?

SES neuroscience, using imaging and other methods, has revealed generalizations of interest for population neuroscience and the study of individual differences. But beyond its scientific interest, SES is a topic of societal importance. Does neuroscience offer any useful insights for promoting socioeconomic justice and reducing the harms of poverty? In this talk I will use research from my own lab and others’ to argue that SES neuroscience has the potential to contribute to policy in this area, although its application is premature at present. I will also attempt to forecast the ways in which practical solutions to the problems of poverty may emerge from SES neuroscience. Bio: Martha Farah has conducted groundbreaking research on face and object recognition, visual attention, mental imagery, and semantic memory and - in more recent times - has been at the forefront of interdisciplinary research into neuroscience and society. This deals with topics such as using fMRI for lie detection, ethics of cognitive enhancement, and effects of social deprivation on brain development.

New Insights into the Neural Machinery of Face Recognition

How Children Discover Mathematical Structure through Relational Mapping

A core question in human development is how we bring meaning to conventional symbols. This question is deeply connected to understanding how children learn mathematics—a symbol system with unique vocabularies, syntaxes, and written forms. In this talk, I will present findings from a program of research focused on children’s acquisition of place value symbols (i.e., multidigit number meanings). The base-10 symbol system presents a variety of obstacles to children, particularly in English. Children who cannot overcome these obstacles face years of struggle as they progress through the mathematics curriculum of the upper elementary and middle school grades. Through a combination of longitudinal, cross-sectional, and pretest-training-posttest approaches, I aim to illuminate relational learning mechanisms by which children sometimes succeed in mastering the place value system, as well as instructional techniques we might use to help those who do not.

Peripersonal space (PPS) as a primary interface for self-environment interactions

Peripersonal space (PPS) defines the portion of space where interactions between our body and the external environment more likely occur. There is no physical boundary defining the PPS with respect to the extrapersonal space, but PPS is continuously constructed by a dedicated neural system integrating external stimuli and tactile stimuli on the body, as a function of their potential interaction. This mechanism represents a primary interface between the individual and the environment. In this talk, I will present most recent evidence and highlight the current debate about the neural and computational mechanisms of PPS, its main functions and properties. I will discuss novel data showing how PPS dynamically shapes to optimize body-environment interactions. I will describe a novel electrophysiological paradigm to study and measure PPS, and show how this has been used to search for a basic marker of potentials of self-environment interaction in newborns and patients with disorders of consciousness. Finally, I will discuss how PPS is also involved in, and in turn shaped by, social interactions. Under these acceptances, I will discuss how PPS plays a key role in self-consciousness.

Where do problem spaces come from? On metaphors and representational change

The challenges of problem solving do not exclusively lie in how to perform heuristic search, but they begin with how we understand a given task: How to cognitively represent the task domain and its components can determine how quickly someone is able to progress towards a solution, whether advanced strategies can be discovered, or even whether a solution is found at all. While this challenge of constructing and changing representations has been acknowledged early on in problem solving research, for the most part it has been sidestepped by focussing on simple, well-defined problems whose representation is almost fully determined by the task instructions. Thus, the established theory of problem solving as heuristic search in problem spaces has little to say on this. In this talk, I will present a study designed to explore this issue, by virtue of finding and refining an adequate problem representation being its main challenge. In this exploratory case study, it was investigated how pairs of participants acquaint themselves with a complex spatial transformation task in the domain of iterated mental paper folding over the course of several days. Participants have to understand the geometry of edges which occurs when repeatedly mentally folding a sheet of paper in alternating directions without the use of external aids. Faced with the difficulty of handling increasingly complex folds in light of limited cognitive capacity, participants are forced to look for ways in which to represent folds more efficiently. In a qualitative analysis of video recordings of the participants' behaviour, the development of their conceptualisation of the task domain was traced over the course of the study, focussing especially on their use of gesture and the spontaneous occurrence and use of metaphors in the construction of new representations. Based on these observations, I will conclude the talk with several theoretical speculations regarding the roles of metaphor and cognitive capacity in representational change.

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.

Adaptive neural network classifier for decoding finger movements

While non-invasive Brain-to-Computer interface can accurately classify the lateralization of hand moments, the distinction of fingers activation in the same hand is limited by their local and overlapping representation in the motor cortex. In particular, the low signal-to-noise ratio restrains the opportunity to identify meaningful patterns in a supervised fashion. Here we combined Magnetoencephalography (MEG) recordings with advanced decoding strategy to classify finger movements at single trial level. We recorded eight subjects performing a serial reaction time task, where they pressed four buttons with left and right index and middle fingers. We evaluated the classification performance of hand and finger movements with increasingly complex approaches: supervised common spatial patterns and logistic regression (CSP + LR) and unsupervised linear finite convolutional neural network (LF-CNN). The right vs left fingers classification performance was accurate above 90% for all methods. However, the classification of the single finger provided the following accuracy: CSP+SVM : – 68 ± 7%, LF-CNN : 71 ± 10%. CNN methods allowed the inspection of spatial and spectral patterns, which reflected activity in the motor cortex in the theta and alpha ranges. Thus, we have shown that the use of CNN in decoding MEG single trials with low signal to noise ratio is a promising approach that, in turn, could be extended to a manifold of problems in clinical and cognitive neuroscience.

Heterogeneity and non-random connectivity in reservoir computing

Reservoir computing is a promising framework to study cortical computation, as it is based on continuous, online processing and the requirements and operating principles are compatible with cortical circuit dynamics. However, the framework has issues that limit its scope as a generic model for cortical processing. The most obvious of these is that, in traditional models, learning is restricted to the output projections and takes place in a fully supervised manner. If such an output layer is interpreted at face value as downstream computation, this is biologically questionable. If it is interpreted merely as a demonstration that the network can accurately represent the information, this immediately raises the question of what would be biologically plausible mechanisms for transmitting the information represented by a reservoir and incorporating it in downstream computations. Another major issue is that we have as yet only modest insight into how the structural and dynamical features of a network influence its computational capacity, which is necessary not only for gaining an understanding of those features in biological brains, but also for exploiting reservoir computing as a neuromorphic application. In this talk, I will first demonstrate a method for quantifying the representational capacity of reservoirs without training them on tasks. Based on this technique, which allows systematic comparison of systems, I then present our recent work towards understanding the roles of heterogeneity and connectivity patterns in enhancing both the computational properties of a network and its ability to reliably transmit to downstream networks. Finally, I will give a brief taster of our current efforts to apply the reservoir computing framework to magnetic systems as an approach to neuromorphic computing.

In pursuit of a universal, biomimetic iBCI decoder: Exploring the manifold representations of action in the motor cortex

My group pioneered the development of a novel intracortical brain computer interface (iBCI) that decodes muscle activity (EMG) from signals recorded in the motor cortex of animals. We use these synthetic EMG signals to control Functional Electrical Stimulation (FES), which causes the muscles to contract and thereby restores rudimentary voluntary control of the paralyzed limb. In the past few years, there has been much interest in the fact that information from the millions of neurons active during movement can be reduced to a small number of “latent” signals in a low-dimensional manifold computed from the multiple neuron recordings. These signals can be used to provide a stable prediction of the animal’s behavior over many months-long periods, and they may also provide the means to implement methods of transfer learning across individuals, an application that could be of particular importance for paralyzed human users. We have begun to examine the representation within this latent space, of a broad range of behaviors, including well-learned, stereotyped movements in the lab, and more natural movements in the animal’s home cage, meant to better represent a person’s daily activities. We intend to develop an FES-based iBCI that will restore voluntary movement across a broad range of motor tasks without need for intermittent recalibration. However, the nonlinearities and context dependence within this low-dimensional manifold present significant challenges.

Faking emotions and a therapeutic role for robots and chatbots: Ethics of using AI in psychotherapy

In recent years, there has been a proliferation of social robots and chatbots that are designed so that users make an emotional attachment with them. This talk will start by presenting the first such chatbot, a program called Eliza designed by Joseph Weizenbaum in the mid 1960s. Then we will look at some recent robots and chatbots with Eliza-like interfaces and examine their benefits as well as various ethical issues raised by deploying such systems.

The Problem of Testimony

The talk will detail work drawing on behavioural results, formal analysis, and computational modelling with agent-based simulations to unpack the scale of the challenge humans face when trying to work out and factor in the reliability of their sources. In particular, it is shown how and why this task admits of no easy solution in the context of wider communication networks, and how this will affect the accuracy of our beliefs. The implications of this for the shift in the size and topology of our communication networks through the uncontrolled rise of social media are discussed.

The evolution and development of visual complexity: insights from stomatopod visual anatomy, physiology, behavior, and molecules

Bioluminescence, which is rare on land, is extremely common in the deep sea, being found in 80% of the animals living between 200 and 1000 m. These animals rely on bioluminescence for communication, feeding, and/or defense, so the generation and detection of light is essential to their survival. Our present knowledge of this phenomenon has been limited due to the difficulty in bringing up live deep-sea animals to the surface, and the lack of proper techniques needed to study this complex system. However, new genomic techniques are now available, and a team with extensive experience in deep-sea biology, vision, and genomics has been assembled to lead this project. This project is aimed to study three questions 1) What are the evolutionary patterns of different types of bioluminescence in deep-sea shrimp? 2) How are deep-sea organisms’ eyes adapted to detect bioluminescence? 3) Can bioluminescent organs (called photophores) detect light in addition to emitting light? Findings from this study will provide valuable insight into a complex system vital to communication, defense, camouflage, and species recognition. This study will bring monumental contributions to the fields of deep sea and evolutionary biology, and immediately improve our understanding of bioluminescence and light detection in the marine environment. In addition to scientific advancement, this project will reach K-college aged students through the development and dissemination of educational tools, a series of molecular and organismal-based workshops, museum exhibits, public seminars, and biodiversity initiatives.

Genetic-based brain machine interfaces for visual restoration

Visual restoration is certainly the greatest challenge for brain-machine interfaces with the high pixel number and high refreshing rate. In the recent year, we brought retinal prostheses and optogenetic therapy up to successful clinical trials. Concerning visual restoration at the cortical level, prostheses have shown efficacy for limited periods of time and limited pixel numbers. We are investigating the potential of sonogenetics to develop a non-contact brain machine interface allowing long-lasting activation of the visual cortex. The presentation will introduce our genetic-based brain machine interfaces for visual restoration at the retinal and cortical levels.

Inter-individual variability in reward seeking and decision making: role of social life and consequence for vulnerability to nicotine

Inter-individual variability refers to differences in the expression of behaviors between members of a population. For instance, some individuals take greater risks, are more attracted to immediate gains or are more susceptible to drugs of abuse than others. To probe the neural bases of inter-individual variability  we study reward seeking and decision-making in mice, and dissect the specific role of dopamine in the modulation of these behaviors. Using a spatial version of the multi-armed bandit task, in which mice are faced with consecutive binary choices, we could link modifications of midbrain dopamine cell dynamics with modulation of exploratory behaviors, a major component of individual characteristics in mice. By analyzing mouse behaviors in semi-naturalistic environments, we then explored the role of social relationships in the shaping of dopamine activity and associated beahviors. I will present recent data from the laboratory suggesting that changes in the activity of dopaminergic networks link social influences with variations in the expression of non-social behaviors: by acting on the dopamine system, the social context may indeed affect the capacity of individuals to make decisions, as well as their vulnerability to drugs of abuse, in particular nicotine.

Visualization and manipulation of our perception and imagery by BCI

We have been developing Brain-Computer Interface (BCI) using electrocorticography (ECoG) [1] , which is recorded by electrodes implanted on brain surface, and magnetoencephalography (MEG) [2] , which records the cortical activities non-invasively, for the clinical applications. The invasive BCI using ECoG has been applied for severely paralyzed patient to restore the communication and motor function. The non-invasive BCI using MEG has been applied as a neurofeedback tool to modulate some pathological neural activities to treat some neuropsychiatric disorders. Although these techniques have been developed for clinical application, BCI is also an important tool to investigate neural function. For example, motor BCI records some neural activities in a part of the motor cortex to generate some movements of external devices. Although our motor system consists of complex system including motor cortex, basal ganglia, cerebellum, spinal cord and muscles, the BCI affords us to simplify the motor system with exactly known inputs, outputs and the relation of them. We can investigate the motor system by manipulating the parameters in BCI system. Recently, we are developing some BCIs to visualize and manipulate our perception and mental imagery. Although these BCI has been developed for clinical application, the BCI will be useful to understand our neural system to generate the perception and imagery. In this talk, I will introduce our study of phantom limb pain [3] , that is controlled by MEG-BCI, and the development of a communication BCI using ECoG [4] , that enable the subject to visualize the contents of their mental imagery. And I would like to discuss how much we can control our cortical activities that represent our perception and mental imagery. These examples demonstrate that BCI is a promising tool to visualize and manipulate the perception and imagery and to understand our consciousness. References 1. Yanagisawa, T., Hirata, M., Saitoh, Y., Kishima, H., Matsushita, K., Goto, T., Fukuma, R., Yokoi, H., Kamitani, Y., and Yoshimine, T. (2012). Electrocorticographic control of a prosthetic arm in paralyzed patients. AnnNeurol 71, 353-361. 2. Yanagisawa, T., Fukuma, R., Seymour, B., Hosomi, K., Kishima, H., Shimizu, T., Yokoi, H., Hirata, M., Yoshimine, T., Kamitani, Y., et al. (2016). Induced sensorimotor brain plasticity controls pain in phantom limb patients. Nature communications 7, 13209. 3. Yanagisawa, T., Fukuma, R., Seymour, B., Tanaka, M., Hosomi, K., Yamashita, O., Kishima, H., Kamitani, Y., and Saitoh, Y. (2020). BCI training to move a virtual hand reduces phantom limb pain: A randomized crossover trial. Neurology 95, e417-e426. 4. Ryohei Fukuma, Takufumi Yanagisawa, Shinji Nishimoto, Hidenori Sugano, Kentaro Tamura, Shota Yamamoto, Yasushi Iimura, Yuya Fujita, Satoru Oshino, Naoki Tani, Naoko Koide-Majima, Yukiyasu Kamitani, Haruhiko Kishima (2022). Voluntary control of semantic neural representations by imagery with conflicting visual stimulation. arXiv arXiv:2112.01223.

Deception, ExoNETs, SmushWare & Organic Data: Tech-facilitated neurorehabilitation & human-machine training

Making use of visual display technology and human-robotic interfaces, many researchers have illustrated various opportunities to distort visual and physical realities. We have had success with interventions such as error augmentation, sensory crossover, and negative viscosity.  Judicial application of these techniques leads to training situations that enhance the learning process and can restore movement ability after neural injury. I will trace out clinical studies that have employed such technologies to improve the health and function, as well as share some leading-edge insights that include deceiving the patient, moving the "smarts" of software into the hardware, and examining clinical effectiveness

Keeping your Brain in Balance: the Ups and Downs of Homeostatic Plasticity (virtual)

Our brains must generate and maintain stable activity patterns over decades of life, despite the dramatic changes in circuit connectivity and function induced by learning and experience-dependent plasticity. How do our brains acheive this balance between opposing need for plasticity and stability? Over the past two decades, we and others have uncovered a family of “homeostatic” negative feedback mechanisms that are theorized to stabilize overall brain activity while allowing specific connections to be reconfigured by experience. Here I discuss recent work in which we demonstrate that individual neocortical neurons in freely behaving animals indeed have a homeostatic activity set-point, to which they return in the face of perturbations. Intriguingly, this firing rate homeostasis is gated by sleep/wake states in a manner that depends on the direction of homeostatic regulation: upward-firing rate homeostasis occurs selectively during periods of active wake, while downward-firing rate homeostasis occurs selectively during periods of sleep, suggesting that an important function of sleep is to temporally segregate bidirectional plasticity. Finally, we show that firing rate homeostasis is compromised in an animal model of autism spectrum disorder. Together our findings suggest that loss of homeostatic plasticity in some neurological disorders may render central circuits unable to compensate for the normal perturbations induced by development and learning.

ALBA-WWN Webinar: What it takes to succeed as a neuroscientist in Africa

In this webinar, the ALBA Network & World Women in Neuroscience partner to address equity, inclusion & diversity issues across the Sub-Saharan African neuroscience community. The panel discussion will explore the challenges and biases faced by African neuroscientists while establishing their careers - focusing on a lack of mentoring and networking but also on the difficulties to raise funding - as well as display the strengths present in the region, which can be exploited to find solutions. Registration is free but required: https://www.alba.network/alba-wwn-webinar-africa

An Attention-based Multimodal Decoder for Hybrid Brain-Computer Interface Control Systems

Bernstein Conference 2024

Calcium imaging-based brain-computer interface in freely behaving mice

Bernstein Conference 2024

Efficient cortical spike train decoding for brain-machine interface implants with recurrent spiking neural networks

Bernstein Conference 2024

Identifying cortical learning algorithms using Brain-Machine Interfaces

Bernstein Conference 2024

A brain-computer interface in prefrontal cortex that suppresses neural variability

COSYNE 2022

A closed-loop emulator that accurately predicts brain-machine interface decoder performance

COSYNE 2022

High-level prediction signals cascade through the macaque face-processing hierarchy

COSYNE 2022

High-level prediction signals cascade through the macaque face-processing hierarchy

COSYNE 2022

Learning static and motion cues to material by predicting moving surfaces

COSYNE 2022

Learning static and motion cues to material by predicting moving surfaces

COSYNE 2022

Stabilizing brain-computer interfaces through nonlinear manifold alignment with dynamics

COSYNE 2022

Stabilizing brain-computer interfaces through nonlinear manifold alignment with dynamics

COSYNE 2022

Calcium imaging-based brain-computer interface for investigating long-term neuronal code dynamics

COSYNE 2023

Compact neural representations in co-adaptive Brain-Computer Interfaces

COSYNE 2023

Thoughtful faces: Using facial features to infer naturalistic cognitive processing across species

COSYNE 2023

Activity exploration influences learning speeds in models of brain-computer interfaces

COSYNE 2025

An Anatomical Explanation of the Inverted Face Effect

COSYNE 2025

Cheese3D: sensitive detection and analysis of whole-face movement in mice

COSYNE 2025

Effect of surface material on whisker-surface interaction and mechanosensory neuron responses

COSYNE 2025

Non-invasive brain-machine interface control with artificial intelligence copilots

COSYNE 2025

Towards generalizable, real-time decoders for brain-computer interfaces

COSYNE 2025

Attention tracking using a novel digital interface in non-human primates

A brain-machine interface based on cotical mesoscale dynamics

Brain-machine interface learning is facilitated by distributed cortical feedback that is spatially and temporally structured

A Calcium Imaging Based Brain-Machine Interface for Virtual Navigation

Controlling a brain-computer interface to decode internally spoken syllables

Data processing tool for studying surface mobility of NMDARs

Dexamethasone improves cell surface trafficking of R451C Neuroligin3, an autism gene risk

Different faces of neurons expressing dopamine receptors in motor cortex – their laminar distribution, electrophysiological properties and role in skilled forelimb reaching

The effect of motion in the body and face patch systems of macaques

Embryonic exposure to valproic acid impairs visual preferences for Face-Like stimuli and alters dopaminergic distribution and signaling in domestic chicks

Engineering Toolset Platform for Neurobiological Interfaces

Face-body integration in anterior inferotemporal cortex

The fractal cortex: A multi-scale surface-preserving analysis suggests all cortices are approximations of a single universal shape

Functional parcellation of the human face-selective areas: a resting-state connectivity homogeneity analysis

Gold and silver nanoparticle-based Localized Surface Plasmon Resonance Sensor (LSPR) for the detection of histidine as a potential biomarker in Parkinson’s Disease

Increased surface P2X4 receptors by mutant SOD1 proteins contribute to ALS pathogenesis

Let’s face it: Lateralization of the face perception network is characterized by large interindividual variability and not by a clear right hemispheric dominance

Low-distortion and low-noise CMOS amplifier for high-channel-count neuroelectronic interfaces

Adaptive brain-computer interfaces based on error-related potentials and reinforcement learning

Bernstein Conference 2024