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Multimodal computational models for early prediction of peritoneal recurrence in gastric cancer

ABSTRACT Gastric cancer represents a significant disease burden and is a leading cause of cancer-related deaths in the United States and globally. Approximately 80% of gastric cancer patients are diagnosed at an advanced stage, with the peritoneum being the most common site of relapse (peritoneal recurrence) after radical surgery. Nearly 50% of patients with advanced-stage gastric cancer develop peritoneal recurrence post-surgery, resulting in a median survival of only 3–6 months and a markedly reduced quality of life. Early peritoneal recurrence is primarily characterized by micro-metastasis, which traditional imaging techniques struggle to detect due to the small size of metastatic nodules. Predicting the likelihood and timing of peritoneal recurrence is crucial for identifying at- risk patients, enabling timely interventions that could improve survival rates and quality of life. Unfortunately, reliable predictive biomarkers and models for peritoneal recurrence in gastric cancer are lacking in clinical practice, highlighting an urgent need for innovative predictive tools. This proposal aims to develop and validate novel predictive models for early peritoneal recurrence in gastric cancer, leveraging advanced deep learning techniques and multimodal integration of clinical, radiological (CT), and histopathological (hematoxylin and eosin, H&E) data. In Aim 1, we will develop a rational approach for predicting peritoneal recurrence by creating a novel deep learning multimodal method guided by genomics knowledge. Additionally, we will integrate both deep learning-extracted features and traditional hand-crafted radiomics features with clinical data to improve prediction accuracy. Aim 2 focuses on developing a robust prediction model of peritoneal recurrence utilizing a pre-trained foundation model from large-scale H&E image data. Aim 3 will combine CT, H&E, and clinical data to further enhance predictive capabilities, employing an innovative cross-modal collaborative optimization approach for multimodal data integration. All models will be trained and internally validated using a retrospective cohort from Atrium Health Wake Forest Baptist Comprehensive Cancer Center and externally validated in two independent cohorts from additional institutions to ensure robustness across populations and imaging protocols. Additionally, we will compare our models with existing methods, including clinical staging and alternative fusion strategies. If successful, these models will enhance risk stratification and prediction of peritoneal recurrence in gastric cancer patients, significantly improving survival rates and quality of life by identifying those likely to develop peritoneal recurrence post-surgery and facilitating timely intervention. Furthermore, they can help avoid the risk of complications and extra medical costs associated with overtreatment. Since the information is derived from routinely examined CT, H&E and clinical data, they could be seamlessly integrated into current clinical workflows. The AI technology developed through this project has the potential to benefit underserved populations in low- resource settings and reduce healthcare disparities in the U.S.

Cardiorespiratory and autonomic impacts of coolants in e-cigarette aerosols

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

Short-wave infrared Cerenkov imaging to better visualize targeted radiotherapy and diagnostic radiotracers

SUMMARY. The problem: Cerenkov luminescence (CL) imaging (CLI) is a new imaging method that utilizes light emitted during decay of radiotracers. CLI merges optical and nuclear imaging by utilizing affordable yet highly sensitive optical cameras with clinical radiotracers. It provides fast and cheap clinical optical imaging to explore radiotracer distribution in patients. While not tomographic, CLI systems have a lower price, smaller footprint and higher resolution than nuclear imaging scanners. Yet, due to the very low signal intensity of CL its versatility remains limited since CLI requires strict exclusion of ambient light with an enclosure. Therefore, CLI requires novel approaches to make clinical imaging more feasible. We hypothesized that we could explore the short-wave infrared (SWIR) part of CL to enable CLI under ambient light without enclosure, providing improved and facile CLI, particularly of isotopes used for therapy that cannot be imaged otherwise. SWIR imaging (900- 1300 nm) has almost no autofluorescence, absorption or scatter but provides significantly higher depth penetration, yielding images with higher contrast and resolution compared to the visible range. Since typical LEDs do not emit light beyond 850 nm, they do not interfere with the SWIR camera. We can therefore perform CLI in the SWIR range (SWIR-CLI) without the limiting light-tight box and under ambient LED light and also achieve better signal penetration and accuracy. We will investigate if SWIR-CLI can be used to monitor distribution of therapeutic isotopes for targeted radiotherapy (TRT), a fast-expanding field as highlighted by Novartis’ acquisition of Lutathera and Pluvicto for the price of $6 bn. These agents are targeting 177Lu as therapy to neuroendocrine and prostate cancers. For TRT α-emitting isotopes are particularly attractive due to the α- particle’s short path length with high linear energy transfer. However, α-emitters are very difficult to image with conventional equipment. The α-emitter could be swapped with an imaging isotope, but this can alter the agent’s biodistribution. The α-particle itself does not have sufficient energy to produce CL but several daughters in the decay chains of most α-emitters produce electrons with sufficient energy to create CL. We have already imaged the α-emitter 223Ra in patients and have recently shown that CLI of α-emitters in the SWIR is possible. SWIR- CLI could therefore provide a facile imaging approach for α-emitters. We will answer with our three independent Aims the following questions: (1) Can we image diagnostic isotopes with SWIR-CLI? (2) Can we image therapeutic emitters with SWIR-CLI? (3) Can we use SWIR-CLI to image patients undergoing PET and/or TRT? Animal studies will employ established mouse cancer models to optimize imaging parameters and validate findings, directly informing the co-clinical Aim 3 trial. By eliminating the requirement for a light-tight enclosure and enabling CLI under ambient light, SWIR-CLI represents a significant shift in the practical deployment of CLI rather than an incremental improvement. Our study will broaden the reach of CLI by enabling imaging under ambient lighting, unlocking innovative new opportunities for CLI (monitoring TRT) in research & clinical settings.

Communication and Hospice Online with Optimal Support and Engagement (CHOOSE)

Abstract Drawing upon the principles of social identity theory, existing literature, and our initial findings from family caregiver (FCG) online support groups (OSGs), our objective is to identify fundamental facilitator communication strategies that promote safe communication engage participants, and strengthen mechanisms of action (MOAs) within OSGs, ultimately enhancing health outcomes for hospice FCGs. Our pioneering initiative, Communication and Hospice Online with Optimal Support and Engagement (CHOOSE) is backed by compelling evidence highlighting the critical role of facilitator communication in reinforcing MOAs (a shared identity, social support, and social networks) in OSGs. Preliminary research underscores the transformative power of these MOAs in improving health outcomes for FCGs, yet current studies lack generalizability and statistical robustness. CHOOSE represents the first major, multisite, rigorously designed, and theoretically informed OSG intervention explicitly tailored for hospice FCGs of cancer patients. We aim to strengthen MOAs to enhance FCG well-being, reduce depression and anxiety, improve quality of life, and diminish loneliness. By advancing this critical research, we seek to provide a well-founded, evidence-based solution to the urgent needs of FCGs, making a significant impact on their health and well-being. We have outlined the following study aims: Aim 1. Determine the effect of the CHOOSE intervention on FCGs’ health outcomes compared to usual OSGs and usual hospice care. Aim 2. Examine direct and mediational relationships between CHOOSE participation, MOAs, and health outcomes. Aim 3. Explore the relationship between facilitator communication strategies and the FCG experience of the MOA to allow for future calibration of the intervention 1

Causal mechanisms driving germline predisposition to myeloproliferative disorders

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

Factory-treated, long-lasting permethrin baby wraps for the prevention of malaria: A phase III randomized controlled trial

PROJECT SUMMARY/ABSTRACT Progress against malaria has stalled. Novel interventions – particularly those targeting outdoor and daytime biting – are needed. In a randomized, placebo-controlled trial of permethrin- vs. sham-treated baby wraps in Uganda, we found a significant reduction in clinical malaria incidence among children carried in permethrin- as compared to sham-treated wraps (Boyce et al, NEJM, 2025). Despite these promising results, our trial incorporated a monthly re-treatment strategy that would be difficult to operationalize at scale. Furthermore, we only followed participants for 6 months, which is shorter than the expected period of use. Therefore, implementation studies - and specifically trials of long-lasting, factory-treated textiles - are now needed. Factory-treated materials would not only eliminate the need for retreatment for up to 12 months, but because the chemicals are more tightly bound, result in less absorption across the skin. Therefore, we now propose to conduct a randomized, double-blind trial of factory-treated, long-lasting (FTLL) wraps. AIM 1: Determine the effectiveness of FTLL permethrin wraps in combination with existing interventions for the prevention of malaria in children. We will enroll 750 mother-infant pairs from routine immunization visits (~3 months of age) at 3 sites of varying transmission intensity across Uganda. All participants will receive new dual active ingredient (AI) bed nets and be randomized (1:1) to either FTLL or untreated wraps. The primary outcome will be clinical malaria incidence during the period of wrap use, defined as fever a positive malaria rapid diagnostic test (RDT) between the FTLL and untreated arms. AIM 2: Confirm the safety of extended exposure to FTLL permethrin wraps for use in young children. Although a review of factory-treated clothing by the US Environmental Protection Agency, including clothing for children and toddlers, did not identify scenarios of concern, the frequency of use envisioned here may be beyond that modeled. To accomplish this, we will perform semi-annual assessments of growth (e.g., height-for-weight) and neurodevelopment (ND) during the period of use and 12-months after discontinuation. AIM 3: Assess the effect of FTLL permethrin wraps on Anopheles mosquito indices and blood-meal seeking behaviors. We will conduct longitudinal entomological surveillance, including CDC-light trap and aspirator collections, supplemented by human landing catches at sentinel households (~10-15%) from both the FTLL and untreated arms. This work tests a novel intervention, which leverages technology developed by the US military, to reduce the burden of malaria in endemic countries. Addressing malaria in these countries minimizes the risk of importation into the US. If successful, the project will provide additional evidence for treated textiles, which may be used to protect American travelers and deployed military servicemembers. The project will be conducted in Uganda, where malaria is highly endemic and it will be possible to enroll at-risk women-infant pairs.

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

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

Eosinophils promote persistence and transmission during Bordetella spp. infections

ABSTRACT Despite widespread vaccination, Bordetella spp., the causative agents of whooping cough, continue to circulate globally. Resurgent outbreaks contribute to significant healthcare burdens and costs estimated up to $79 million annually. This persistence and reemergence highlight a critical need for new therapies and prevention methods. Our laboratory investigates bacterial and host drivers that enable Bordetella success, defined as enhanced persistence, reinfection, and transmission. We have identified the Bordetella sigma factor BtrS as a regulator of immunosuppressive pathways that modulate eosinophil function. Leveraging genetically tractable Bordetella strains, advanced murine models, and immunological tools, we are uniquely positioned to dissect how eosinophils contribute to respiratory bacterial infections. Our preliminary data reveal that eosinophils promote Bordetella persistence. Our results also show that the anti-inflammatory cytokine IL1 receptor antagonist (IL1Ra) also contribute to persistence. However, the contribution of eosinophil-derived immunosuppressors remains unclear and will be investigated in Specific Aim 1. Moreover, we have evidence that eosinophils are required for nasal shedding, through mucus enhancement, and paroxysmal coughing, via exacerbation of bronchoconstriction, during Bordetella spp. infection, two key metrics of transmission. The eosinophil-effectors that promote shedding, coughing, and transmission, will be investigated in Specific Aim 2. Based on our data, we hypothesize that eosinophils contribute to Bordetella pathogenesis by (1) promoting persistent infection and (2) enhancing transmission through mucus-driven shedding and cough reflex induction. This proposal will test this hypothesis through two specific aims: Aim 1: Delineate the immunosuppressive role of eosinophils in modulating host responses and enabling Bordetella persistence. Aim 2: Define the mechanisms by which eosinophils facilitate Bordetella spp. transmission. By reframing eosinophils as active modulators of bacterial pathogenesis, this research challenges traditional views of eosinophils as terminal effector cells and positions them as novel targets for therapeutic intervention, that might be applicable to other mucosal pathogens. The outcomes will contribute to our understanding of eosinophil biology in infection and may lead to innovative strategies to halt bacterial persistence and transmission.

Specific Affinity Requirements for Antibody Somatic Hypermutation

PROJECT SUMMARY Antibodies diversify through two distinct pathways. The first involves the combinatorial assembly of immunoglobulin (Ig) heavy and light chain variable region (V) exons, forming the antigen recognition domains of the B cell receptor (BCR), which is initially expressed as IgM on immature B cells. The second diversification pathway is somatic hypermutation (SHM) of V exons in germinal centers (GCs). In this setting, B cells that acquire mutations enhancing affinity for antigen receive limited cognate T cell help and are selected for clonal expansion, leading to affinity maturation. These primary and secondary diversification systems work together to generate protective antibody responses. The primary, or pre-immune, repertoire provides the foundation for initial antigen recognition. SHM and affinity maturation refine these baseline specificities. While it is well established that SHM improves affinities already present in the primary repertoire, this project explores the hypothesis that SHM can also generate new specificities in B cells that initially lack measurable antigen recognition. This process, termed affinity birth, may enable access to otherwise excluded V gene segments and expand the landscape of antibody evolution. This hypothesis will be tested through two specific aims: (i) To elucidate the extent of SHM-mediated Ig diversification in non-specific or bystander B cells. And, (ii) to define parameters that influence SHM-mediated antibody affinity birth. The significance of this work lies in its potential to reveal previously unappreciated flexibility in the antibody diversification process and to uncover modifiable factors that influence the emergence of new specificities. The proposed studies are innovative in suggesting that B cells possess intrinsic capacity to undergo SHM and selection regardless of their initial antigen specificity. This research may advance understanding of how germinal centers support antibody evolution and inform strategies to design vaccines that anticipate emerging pathogens.

Improving Disease-Modifying Therapy Uptake among Patients with Multiple Sclerosis

Project Summary/Abstract Recent advances in the epidemiology of multiple sclerosis (MS) indicate that its prevalence is similar among White (238 per 100,000) and Black (226 per 100,000) populations. These data challenge historic assumptions about individuals with northern European heritage having higher risk and prevalence of MS. Evidence also suggests that MS incidence may be higher than previously recognized in the United States and increasing over time with more individuals identified and diagnosed year over year. MS continues to impose significant and growing burden on patients, healthcare systems and society. These health differences in the diagnosis, treatment and symptom management of MS in light of the increasing prevalence of MS in the US are an important public health issue that requires broader urgent research and policy attention to reduce the overall disease burden. In this study, we will use real-world data derived from the electronic health records (EHR) from four large academic medical centers (University of Kentucky, University of Virginia, Virginia Commonwealth University, and University of Southern California). Extracted EHR data from these four medical centers will be deidentified, combined, and harmonized. We will use this combined data set to examine (1) whether there are any differences in the timely treatment of disease modifying therapy (DMT) among different MS populations, (2) any disparities in the management of symptoms and comorbidities, (3) how non-medical factors of health such as income, education, and health insurance status (patientlevel), linguistically appropriate care provision (provider-level), and neighborhood factors (system-level) affect these outcomes and influence disparities across populations, and (4) assess whether disparities exist in the risks of cardiovascular disease CVD and mortality in MS subgroups and examine if these disparities can be reduced with improved treatment of MS and vascular comorbidities. In pursuing these objectives, we will identify clinical solutions (e.g., optimal DMT sequences) and non-medical factors such as neighborhood factors such as poverty, educational achievement, crime rates, civic participation, and housing quality, access to care factors, and cultural and linguistic match between providers and patients that substantially contribute to health disparities. For actionable solutions, we will rank-order these factors by their relative importance in addressing disparities, which will guide decision-making at the policy, system, and provider level. Our long-term objective is to develop public health strategies and scalable solutions to reduce overall burden in the management of MS. This project is expected to help policy makers and health system administrators in prioritizing interventions and to have implications for clinical practice in improving care of all patients with MS in neurology clinics, at the healthcare system level, and for national health policy.

Molecular Mechanism of Immunoglobulin Class Switch Recombination

Antibodies produced by B cells are a critical component of the adaptive immune system in mammals that can respond to and clear a plethora of different pathogens. A key property of B cells is their ability to alter the coding sequence of the immunoglobulin heavy and light chain genes, via VDJ-recombination, somatic hypermutation (SHM) and class switch recombination (CSR). While VDJ-recombination and SHM alter the variable regions of antibodies that directly contact pathogen antigens, CSR changes the constant region of the antibody, which dictates its effector function to optimally respond to the antigen recognized by the antibody. CSR occurs via targeted DNA double strand break (DSB) induction in the switch regions preceding the distinct constant region coding sequences. DSB induction requires active transcription of the switch regions and is initiated by activation-induced cytidine deaminase (AID) induced cytosine deamination (converting cytosine to uracil) within the switch regions. Fusion of the DSBs in the switch regions results in deletion of intervening genomic sequence, completing CSR. Since AID is inherently a mutagenic enzyme that can trigger both point mutations and genomic translocations, its activity has to be tightly controlled, and aberrant AID activity has been directly implicated in the genetic changes that lead to B cell lymphoma formation. Thus, define the molecular mechanism of CSR is critical to understand our adaptive immune system and B cell cancer development, both highly relevant to human health. To study CSR in living B cells, cellular models have been developed to analyze AID function and switch region transcription at the single molecule level. With this new methodology, the critical unanswered question of how AID is specifically recruited to the immunoglobulin heavy chain locus and not other genomic locations will be addressed. In addition, the overall kinetics of CSR will be determined and how transcription controls specific DSB induction in switch regions will be defined. The results of these works will significantly advance our understanding of CSR and provide new insights on how AID contributes to B cell lymphoma formation.

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

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

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.

A novel MRI method for noninvasive imaging of bone quality in type 2 diabetes

ABSTRACT: Type 2 diabetes mellitus (T2DM) affects 500 million of the global population, which is expected to increase to 800 million in 20 years. One of the multiple complications involved with T2DM is the significantly increased bone fracture risk and post-fracture mortality. Dual-energy X-ray absorptiometry (DXA) scans are routinely performed to measure bone mineral density (BMD) and associated fracture risk. However, T2DM patients often show preserved or even elevated BMD despite the significantly increased fracture risk. This mismatch between the BMD measurement and actual fracture risk hampers the accurate assessment of fracture risk and the appropriate treatment of T2DM that considers patient bone health. The lack of an accurate fracture risk assessment tool also confounds the evaluation of the bone health effect of antidiabetic drugs, including recently highlighted glucagon-like peptide-1 receptor agonists (e.g., semaglutide) and sodium-glucose cotransporter-2 inhibitors. Previous studies have suggested that bone quality, rather than bone quantity, as represented by BMD, is a crucial factor contributing to fracture risk in T2DM settings. Collagen crosslinking via advanced glycation end-products (AGEs) in cortical bone has been identified as a distinctive bone quality characteristic of T2DM patients, which explains the increased bone fragility. Although this finding is highly promising for improving the bone health management of T2DM patients, currently, no non-invasive method can monitor collagen crosslinking in the bones. This proposal aims to develop an ultrashort echo time (UTE) MRI-based method for measuring the degree of bone collagen crosslinking by quantifying magnetization transfer between water and collagen in the bone. This method, termed UTE-quantitative magnetization transfer (UTE-qMT) MRI, measures not only the quantity of macromolecules (e.g., collagen) in the bone but also the rates of exchange between water and macromolecular protons, which are related to the degree of collagen crosslinking. The proposal will develop and optimize the accelerated UTE-qMT method for reliably measuring the exchange rate in Aim 1. The optimized technique will be validated by correlating exchange rates with AGE-driven collagen crosslinking and subsequent compromise of bone mechanical properties in Aim 2. Finally, the optimized UTE-qMT MRI method will be translated to animal and human studies to demonstrate its clinical feasibility for investigating the effect of antidiabetic drugs on bone health in patients with T2DM in Aim 3. The successful completion of these aims will enable rapid and accurate assessment of bone fracture risk in patients with T2DM. Furthermore, noninvasively probing bone quality can also accurately assess the effect of antidiabetic drugs on bone health and aid in screening novel T2DM therapeutics for their impact on bone health.

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.

Autoreactive T cells in lupus

The autoimmune disease systemic lupus erythematosus (SLE) is characterized by loss of adaptive immune tolerance in conjunction with innate immune system hyperactivity. Autoantibodies, produced by plasma cells derived from activated B cells, form proinflammatory immune complexes. These immune complexes drive feed forward loops that sustain a systemic inflammatory environment and deposit in tissues leading to potentially fatal organ damage. B cells receive help from T cells to produce antibodies. They also contribute to disease by shaping T cell responses and secreting cytokines. Recent case reports in which SLE patients were treated with anti-CD19 CAR-T cell therapy to deplete B cells highlight the pathogenic role of B cells in lupus and their value as a therapeutic target. However, a better understanding of how autoreactive B cells interact with autoreactive T cells may reveal more targeted points of therapeutic intervention that specifically block autoreactive responses while sparing protective ones. Antigen specific interactions between CD4+ T cells and B cells are required for the development of autoimmune disease in lupus. However, whether these critical interactions occur in germinal centers, where competition for CD4+ T cell help selects high affinity B cells, or in extrafollicular responses, where B cells may avoid peripheral tolerance checkpoints, is unclear. Gene expression profiles and pathways specific to autoreactive CD4+ T cells, and how they are shaped by their interaction with autoreactive B cells, are also ill defined. CD8+ T cells, which recognize antigen presented on MHC Class I, have also been suggested to modulate the fate of autoreactive B cells. They can directly kill autoreactive B cells as a means of tolerance, and a subset of CD8+ T cells has recently been shown to have B cell helper function. Whether and how such interactions between B and CD8+ T cells enhance or suppress the development of lupus is unknown. Here, we will use genetic and in vivo proximity labeling approaches to address these knowledge gaps. In Aim 1, we will test the hypothesis that antigen specific interactions between B and CD8+ T cells promote B cell activation and autoantibody production in lupus. We will prevent B cells, but not other cells, from undergoing cognate interactions with CD8+ T cells via B cell-specific deletion of B2M, a component of the MHC Class I complex, in two lupus models. In Aim 2, will use the uLIPSTIC in vivo proximity system to label all T cells interacting with B cells in lupus models compared to wild type controls. Features specific to these autoreactive T cells will be defined by flow cytometry, scRNA Seq, and scTCR-Seq. These studies will provide valuable molecular and cellular insight into the mutual activation of B and T cells in lupus. They will set the stage for future mechanistic studies defining the role of autoreactive T cell specific genes and pathways and potentially highlight new therapeutic targets specific to autoreactive B/T interactions.

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.

Neutralizing persistent IFN-I to improve HIV-specific CAR T cell therapy

PROJECT SUMMARY A critical hurdle to further improving the quality of life for people living with HIV (PLWH) is the need to resolve the residual immune activation and inflammation that persists even in those taking effective antiretroviral therapy (ART), which suppresses HIV replication. This unresolved and persistent immune activation is associated with increased type-I interferon (IFN-I) signaling, and increased incidence of comorbidities. Encouragingly, reports demonstrate that blocking IFN-I signaling in animal models of HIV infection can reduce HIV reservoirs and restore T cell immune function. We hypothesize that blocking IFN-I would likewise augment engineered T cell-based therapies against HIV, such as chimeric antigen receptor (CAR) T cells. Our prior work has demonstrated that when engineered to express both the 4-1BB and CD28 costimulatory domains and protected from HIV infection, HIV-specific CD4 ectodomain CAR T cells can reduce acute viremia, prevent CD4+ T cell loss, and reduce viral burden in the tissues of HIV-infected humanized mice. However, the reduction of plasma viral loads was ultimately transient, suggesting that the potency of HIV-specific CAR T cells should be further optimized for clinical translation. Our preliminary data highlights interferon-beta (IFNb) as a key immunosuppressive IFN-I negatively regulating CAR T cell proliferation, and we demonstrate that neutralizing IFNb in vivo enhanced the engraftment and persistence of HIV-specific CAR T cells adoptively transferred into HIV-infected ART- suppressed humanized mice. This proposal will interrogate whether IFNb neutralization augments CAR T cell therapy through 1) identifying the mechanism(s) by which chronic IFNb exposure mediates HIV-specific CAR T cell dysfunction, and 2) determining the effect of neutralizing IFNb on CAR T cell function and persistence in HIV infection in vivo. The proposed aims seek to develop the neutralization of IFNb as a novel immunotherapy approach to maximize the potency of HIV-specific CAR T cells aimed at achieving a functional HIV cure.

Engineering of a temperate Burkholderia cepacia complex phage to improve efficacy as a potential therapeutic

Project Summary Bacteria in the Burkholderia cepacia complex (Bcc) cause difficult to treat infections in patients with compromised respiratory systems, such as those with cystic fibrosis (CF). Alternative treatment options are needed, since antibiotics often fail these patients. Bacteriophage (phage) therapy is a promising strategy, yet therapeutically ideal phages are difficult to find and narrow in their range of use due to host specificity. In the proposed study, we continue development of a potential phage therapeutic sourced from Burkholderia itself. We have isolated a phage, called BCC02, that was present within the genome of a Burkholderia bacteria (a prophage) and have shown that it can kill other bacteria within the same genus. However, this phage still has the potential to integrate into other bacterial genomes, which is an undesirable trait for phage therapy. By engineering changes to the BCC02 genome using synthetic biology techniques, we hypothesize that we can increase its range of therapeutic potential by disabling its ability to integrate into the bacterial genome, and that this change will increase the number of bacteria that it can lyse. The specific aims of this project are to (1) engineer this phage to lose the ability to lysogenize (integrate into bacterial genomes) then test the effects of these modifications on bacterial host range and (2) test activity of our originally isolated phage, BCC02 as well as our engineered variant on a clinically relevant panel of patho-adapted isolates from patients with CF. We propose to use transformation-associated recombination (TAR) cloning methods to target the lysogeny control region of the BCC02 genome for removal. We hypothesize that loss of integration ability will force this phage into an obligately lytic lifestyle, where it will lyse all bacteria it is able to infect. Successful completion of this project will determine the feasibility of engineering obligately lytic Burkholderia-targeting phages from Burkholderia spp. prophages, shed light on the effects of lytic lifestyle on host range, and establish the utility of these phages for tackling particularly problematic clinical infections. In addition, this study may produce a Bcc- targeting phage that is primed for development to be used for phage therapy.

A PROTAC Strategy to Combat Botulinum Neurotoxicity

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

Bacterial ferrous iron sensing via the BqsRS (CarRS) two-component system

Project Summary Pseudomonas aeruginosa (Pa) is an opportunistic and increasingly antibiotic resistant Gram-negative bacterium that is one of the major causes of chronic nosocomial infections in the United States. The colonization of Pa within a host is often linked to the bioavailability of nutrients, such as iron, and Pa has multiple iron acquisition pathways that allow it to adapt readily to the variety of environments it may encounter within a human host. Pa responds to these dynamic environments commonly through the use of two-component signal transduction systems (TCSs) that are important mediators of signal transduction and allow pathogens to detect chemical and/or physical changes in the environment in order to control basic cellular processes. Previous studies have identified a biofilm and quorum sensing TCS known as BqsRS (also known as CarRS) that regulates biofilm formation and decay in Pa through the sensing of extracytoplasmic Fe2+ and Ca2+. Among its targets, the BqsRS TCS is known to regulate rhlAB and rhlC, critical genes for rhamnolipid production and biofilm formation that are also known to be connected to iron homeostasis and antibiotic resistance. Moreover, the deletion of either bqsR or bqsS in PAO1 results in a significant increase in biofilm formation but reduced biofilm dispersion, the latter of which is important for downstream infections. These observations highlight the importance of the BqsRS TCS to Pa virulence, but there is a foundational lack of understanding regarding the structure, the selectivity, and the mechanism of this system. The ultimate goal of this proposal is to generate a mechanistic and functional understanding of BqsRS at atomic, molecular, and organismal levels in order to exploit this system as a means of reducing or stemming the virulence of opportunistic pathogens such as Pa. The objectives of this exploratory grant are to determine the structural and molecular characteristics of BqsRS, to define how these properties govern BqsRS metal selectivity and function, and to examine a new role of the BqsRS system in regulating the Feo system in P. aeruginosa. Ultimately, the accomplishment of this exploratory grant will deliver fundamental mechanistic insight into a critical metal-sensing TCS and lay the groundwork for future studies that may be designed to target this system and its homologs for additional bacterial exploits.

A Novel Mitochondrial-Targeted Inhibitor of NLRP3 Inflammasome Activation

PROJECT ABSTRACT Inflammasomes are multiprotein complexes of the innate immune system that assemble upon detecting specific molecular patterns associated with pathogens and cellular damage. Once assembled, activated inflammasomes trigger a cascade of downstream events that culminate in cell death and inflammation. Aberrant activation of the NLRP3 inflammasome contributes to the pathogenesis of numerous inflammatory and degenerative diseases, including gout, atherosclerosis, type 2 diabetes, and Alzheimer’s disease. Despite its central role in innate immunity and inflammation, there are no FDA-approved therapies that directly target the NLRP3 inflammasome. Current strategies rely on biologics that inhibit downstream pro-inflammatory cytokines produced from inflammasome activation, such as interleukin-1β (IL-1β), but do not block upstream inflammasome assembly or pyroptotic cell death, highlighting a critical unmet need for selective small-molecule inhibitors with novel mechanisms of action. To address this gap, we identified a covalent small molecule, Compound-2 (C-2), that robustly inhibits NLRP3 inflammasome activation in murine and human immune cells. C-2 suppresses multiple downstream events triggered by inflammasome activation, including IL-1β secretion and pyroptosis, with no apparent toxicity. Chemoproteomic profiling revealed that C-2 interacts with SLC25A3, a mitochondrial phosphate and copper transporter, suggesting a previously unrecognized regulatory node in inflammasome signaling. This R21 project aims to (1) elucidate the mechanism by which C-2 suppresses NLRP3 activation and (2) define the molecular interaction between C-2 and SLC25A3 and its functional consequences. Our studies will integrate biochemical, cellular, and in vivo approaches to uncover a novel mitochondrial mechanism of inflammasome regulation and validate C-2 as a first-in-class inflammasome inhibitor. Successful completion of this project will lay the foundation for future therapeutic development targeting mitochondrial- inflammasome crosstalk in inflammatory disease.

Programming Offspring Metabolism: The Role of Milk Extracellular Vesicles in Fat Development

SUMMARY Obesity is a global health crisis, contributing significantly to the prevalence of metabolic disorders, cardiovascular diseases, and various chronic conditions. A growing body of evidence suggests that maternal obesity during pregnancy and lactation can predispose offspring to obesity and metabolic dysfunction later in life. However, the mechanisms by which maternal obesity programs these adverse outcomes in offspring remain poorly understood. Breast milk is not only a source of essential nutrients but also contains bioactive components, including extracellular vesicles (EVs), which play crucial roles in cellular communication and development. Recent studies have shown that EVs can survive digestion and enter the infant’s circulation, influencing immune and metabolic development. Despite the established link between maternal obesity and altered breast milk composition, no study has investigated the role of milk-derived EVs (mEVs) in programming offspring fat development and metabolism. Understanding this novel pathway could revolutionize our approach to preventing intergenerational transmission of obesity. Our preliminary studies using a mouse model of maternal high-fat diet-induced obesity revealed significant alterations in mEV biogenesis and cargo composition, including changes in specific miRNAs. Oral administration of mEVs from obese dams to neonatal mice increased adiposity and impaired lipid metabolism, indicating that mEVs are crucial in modulating fat development and metabolic pathways in offspring. Several key miRNAs found in mouse mEVs are conserved in human milk EVs, highlighting the potential translational relevance of our findings to human health. We hypothesize that mEVs are critical mediators of maternal obesity’s programming effects on offspring metabolism and adiposity. In specific aim 1, we will use mouse models and advanced molecular techniques (miRNA sequencing, proteomics, and lipidomics) to characterize how maternal obesity affects mEV biogenesis and the composition of their bioactive cargo. We will also evaluate how maternal dietary intake, independent of obesity, influences mEV composition. Specific aim 2 will define the programming effects of mEVs on offspring energy metabolism and obesity. In addition, we will explore whether human milk EVs from lean and obese mothers exert similar programming effects on fat development and metabolism in a mouse model. This R21 application embodies a high-risk, high-reward approach to obesity research. It ventures into uncharted territory by proposing that mEVs are novel regulators of metabolic programming, a concept that has not been explored in prior studies. The potential reward is substantial: discovering a new mechanism by which maternal obesity influences offspring health could fundamentally shift our understanding of early-life metabolic programming and lead to innovative strategies for obesity prevention. If successful, this research could open a new field of study with broad implications for maternal and child health.

Spatial Mapping to Detail the Role of Biomolecules in Governing Biofilm Organization and Resiliency to Stress in Pseudomonas aeruginosa Biofilms

PROJECT SUMMARY The bacterium Pseudomonas aeruginosa is a leading cause of hospital acquired infections, exhibiting substantial antibiotic tolerance due to growth in biofilms. Our previous work shows how biofilm fitness is increased by alkyl quinolones (AQs), a class of molecules produced by the Pseudomonas Quinolone Signal (PQS) pathway of Pseudomonas aeruginosa. AQs form aggregates that spatially limit regions of cell death and reduce overall cell death in biofilms. Spatial studies build on ”what” molecules are doing by revealing when, where, and with whom they are found. Others have shown that AQs transiently bind amyloids and our preliminary results find that amyloid localization is shifted in the absence of AQs. However, the spatial relationships of these molecules have not been investigated. Our research combines multiple spatial analytical techniques, such as fluorescence microscopy, polarized light microscopy, confocal Raman microscopy to assemble detailed maps of AQ and amyloid localization during biofilm development. Using transgenic strains we will also determine amyloid distribution as a function of AQ abundance. This work will build on previous findings that AQ concentrations are able to shift locally in response to stress. We hypothesize that this can impact the localization of amyloids and allow biofilms to respond locally to stress, shielding the greater biofilm from damage. We will map biomolecular distribution of entire colony biofilms in response to stress to determine if local responses have the ability to shield more distal regions of the biofilm. The capacity of spatial biomolecular organization to increase bacterial resilience and infection virulence is an understudied area that has the potential to bring to light to novel targets for therapeutics to fight biofilm infections.

Noninvasive Neuromodulation to Improve Hand Motor Function in Multiple Sclerosis

Project Summary/Abstract Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating, and degenerative disease that affects nearly one million Americans. Although more than 75% of persons with MS (PwMS) experience hand motor impairments that reduce independence and quality of life, current treatments primarily aim to slow disease progression through pharmacological approaches and rehabilitation and often do not improve motor function. Recent evidence shows that reduced corticospinal transmission is strongly associated with motor impairment severity in PwMS, highlighting the need for targeted strategies to strengthen residual corticospinal pathways. Therefore, this project aims to evaluate the therapeutic potential of paired corticospinal-motoneuronal stimulation (PCMS) in improving hand dexterity in PwMS. PCMS, a noninvasive mechanism-driven neuromodulation approach, enhances corticospinal transmission by producing long-term potentiation-like effects at the corticospinal-motoneuronal synapse by precisely pairing transcranial magnetic stimulation (TMS) with peripheral nerve stimulation (PNS). This project first aims to examine the effects of a single PCMS session on corticospinal transmission and hand motor function in PwMS. Using a randomized, crossover design, 25 PwMS will complete two sessions: (1) PCMS and (2) sham-PCMS. Each session will deliver 180 paired TMS-PNS stimuli over 30 minutes. The primary outcome is performance on the 9-Hole Peg Test (9HPT). Secondary outcomes include pinch grip force, maximal voluntary contraction (MVC), MEP amplitude and latency, F-wave parameters, and M- max amplitude. It is hypothesized that PCMS will enhance corticospinal transmission and improve hand motor performance compared to sham stimulation. Second, this project will examine the effects of PCMS combined with hand motor training in PwMS. Forty-eight PwMS will be randomized to receive either PCMS or sham-PCMS combined with motor training over 10 sessions in 3–4 weeks. Outcomes will be assessed at baseline, post- intervention, and one-month follow-up. It is hypothesized that PCMS participants receiving PCMS with motor training to show greater functional gains than those receiving sham-PCMS with motor training and the functional gains will be better maintained in the PCMS with motor training group at follow-up. This project is the first to apply PCMS in PwMS, leveraging a noninvasive neuromodulation strategy to specifically enhance corticospinal output for improving manual dexterity. Findings will establish proof-of-concept for this intervention in PwMS and guide future studies optimizing stimulation protocols and evaluating clinical efficacy on a larger scale. Ultimately, this work may lead to a new therapeutic approach to improve dexterity, independence, and quality of life for people living with MS.

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

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

Predictive Coding Light

Current machine learning systems consume vastly more energy than biological brains. Neuromorphic systems aim to overcome this difference by mimicking the brain’s information coding via discrete voltage spikes. However, it remains unclear how both artificial and natural networks of spiking neurons can learn energy-efficient information processing strategies. Here we propose Predictive Coding Light (PCL), a recurrent hierarchical spiking neural network for unsupervised representation learning. In contrast to previous predictive coding approaches, PCL does not transmit prediction errors to higher processing stages. Instead, it suppresses the most predictable spikes and transmits a compressed representation of the input. Using only biologically plausible spike-timing based learning rules, PCL reproduces a wealth of findings on information processing in visual cortex and permits strong performance in downstream classification tasks. Overall, PCL offers a new approach to predictive coding and its implementation in natural and artificial spiking neural networks

From Spiking Predictive Coding to Learning Abstract Object Representation

In a first part of the talk, I will present Predictive Coding Light (PCL), a novel unsupervised learning architecture for spiking neural networks. In contrast to conventional predictive coding approaches, which only transmit prediction errors to higher processing stages, PCL learns inhibitory lateral and top-down connectivity to suppress the most predictable spikes and passes a compressed representation of the input to higher processing stages. We show that PCL reproduces a range of biological findings and exhibits a favorable tradeoff between energy consumption and downstream classification performance on challenging benchmarks. A second part of the talk will feature our lab’s efforts to explain how infants and toddlers might learn abstract object representations without supervision. I will present deep learning models that exploit the temporal and multimodal structure of their sensory inputs to learn representations of individual objects, object categories, or abstract super-categories such as „kitchen object“ in a fully unsupervised fashion. These models offer a parsimonious account of how abstract semantic knowledge may be rooted in children's embodied first-person experiences.

Rethinking brain mechanisms in the light of evolution

Relating circuit dynamics to computation: robustness and dimension-specific computation in cortical dynamics

Neural dynamics represent the hard-to-interpret substrate of circuit computations. Advances in large-scale recordings have highlighted the sheer spatiotemporal complexity of circuit dynamics within and across circuits, portraying in detail the difficulty of interpreting such dynamics and relating it to computation. Indeed, even in extremely simplified experimental conditions, one observes high-dimensional temporal dynamics in the relevant circuits. This complexity can be potentially addressed by the notion that not all changes in population activity have equal meaning, i.e., a small change in the evolution of activity along a particular dimension may have a bigger effect on a given computation than a large change in another. We term such conditions dimension-specific computation. Considering motor preparatory activity in a delayed response task we utilized neural recordings performed simultaneously with optogenetic perturbations to probe circuit dynamics. First, we revealed a remarkable robustness in the detailed evolution of certain dimensions of the population activity, beyond what was thought to be the case experimentally and theoretically. Second, the robust dimension in activity space carries nearly all of the decodable behavioral information whereas other non-robust dimensions contained nearly no decodable information, as if the circuit was setup to make informative dimensions stiff, i.e., resistive to perturbations, leaving uninformative dimensions sloppy, i.e., sensitive to perturbations. Third, we show that this robustness can be achieved by a modular organization of circuitry, whereby modules whose dynamics normally evolve independently can correct each other’s dynamics when an individual module is perturbed, a common design feature in robust systems engineering. Finally, we will recent work extending this framework to understanding the neural dynamics underlying preparation of speech.

Impact of High Fat Diet on Central Cardiac Circuits: When The Wanderer is Lost

Cardiac vagal motor drive originates in the brainstem's cardiac vagal motor neurons (CVNs). Despite well-established cardioinhibitory functions in health, our understanding of CVNs in disease is limited. There is a clear connection of cardiovascular regulation with metabolic and energy expenditure systems. Using high fat diet as a model, this talk will explore how metabolic dysfunction impacts the regulation of cardiac tissue through robust inhibition of CVNs. Specifically, it will present an often overlooked modality of inhibition, tonic gamma-aminobuytric acid (GABA) A-type neurotransmission using an array of techniques from single cell patch clamp electrophysiology to transgenic in vivo whole animal physiology. It also will highlight a unique interaction with the delta isoform of protein kinase C to facilitate GABA A-type receptor expression.

The Brain Prize winners' webinar

This webinar brings together three leaders in theoretical and computational neuroscience—Larry Abbott, Haim Sompolinsky, and Terry Sejnowski—to discuss how neural circuits generate fundamental aspects of the mind. Abbott illustrates mechanisms in electric fish that differentiate self-generated electric signals from external sensory cues, showing how predictive plasticity and two-stage signal cancellation mediate a sense of self. Sompolinsky explores attractor networks, revealing how discrete and continuous attractors can stabilize activity patterns, enable working memory, and incorporate chaotic dynamics underlying spontaneous behaviors. He further highlights the concept of object manifolds in high-level sensory representations and raises open questions on integrating connectomics with theoretical frameworks. Sejnowski bridges these motifs with modern artificial intelligence, demonstrating how large-scale neural networks capture language structures through distributed representations that parallel biological coding. Together, their presentations emphasize the synergy between empirical data, computational modeling, and connectomics in explaining the neural basis of cognition—offering insights into perception, memory, language, and the emergence of mind-like processes.

Decision and Behavior

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

LLMs and Human Language Processing

This webinar convened researchers at the intersection of Artificial Intelligence and Neuroscience to investigate how large language models (LLMs) can serve as valuable “model organisms” for understanding human language processing. Presenters showcased evidence that brain recordings (fMRI, MEG, ECoG) acquired while participants read or listened to unconstrained speech can be predicted by representations extracted from state-of-the-art text- and speech-based LLMs. In particular, text-based LLMs tend to align better with higher-level language regions, capturing more semantic aspects, while speech-based LLMs excel at explaining early auditory cortical responses. However, purely low-level features can drive part of these alignments, complicating interpretations. New methods, including perturbation analyses, highlight which linguistic variables matter for each cortical area and time scale. Further, “brain tuning” of LLMs—fine-tuning on measured neural signals—can improve semantic representations and downstream language tasks. Despite open questions about interpretability and exact neural mechanisms, these results demonstrate that LLMs provide a promising framework for probing the computations underlying human language comprehension and production at multiple spatiotemporal scales.

Clonal analysis at single cell level helps to understand neural crest development

Recent research on the neural crest has revealed the multipotency and plasticity of nerve-associated Schwann cell precursors, which can differentiate into diverse cell types, including parasympathetic neurons, neuroendocrine cells, and mesenchymal stem cells. These findings challenge the traditional view of peripheral nerves, highlighting their role as niches for migratory progenitor cells that contribute to tissue formation and regeneration.

Light-gated membrane channels: Discovery and creation of diversity, principles from protein structure, and cell-function access to biology

Neural mechanisms governing the learning and execution of avoidance behavior

The nervous system orchestrates adaptive behaviors by intricately coordinating responses to internal cues and environmental stimuli. This involves integrating sensory input, managing competing motivational states, and drawing on past experiences to anticipate future outcomes. While traditional models attribute this complexity to interactions between the mesocorticolimbic system and hypothalamic centers, the specific nodes of integration have remained elusive. Recent research, including our own, sheds light on the midline thalamus's overlooked role in this process. We propose that the midline thalamus integrates internal states with memory and emotional signals to guide adaptive behaviors. Our investigations into midline thalamic neuronal circuits have provided crucial insights into the neural mechanisms behind flexibility and adaptability. Understanding these processes is essential for deciphering human behavior and conditions marked by impaired motivation and emotional processing. Our research aims to contribute to this understanding, paving the way for targeted interventions and therapies to address such impairments.

Modelling the fruit fly brain and body

Through recent advances in microscopy, we now have an unprecedented view of the brain and body of the fruit fly Drosophila melanogaster. We now know the connectivity at single neuron resolution across the whole brain. How do we translate these new measurements into a deeper understanding of how the brain processes sensory information and produces behavior? I will describe two computational efforts to model the brain and the body of the fruit fly. First, I will describe a new modeling method which makes highly accurate predictions of neural activity in the fly visual system as measured in the living brain, using only measurements of its connectivity from a dead brain [1], joint work with Jakob Macke. Second, I will describe a whole body physics simulation of the fruit fly which can accurately reproduce its locomotion behaviors, both flight and walking [2], joint work with Google DeepMind.

The multi-phase plasticity supporting winner effect

Aggression is an innate behavior across animal species. It is essential for competing for food, defending territory, securing mates, and protecting families and oneself. Since initiating an attack requires no explicit learning, the neural circuit underlying aggression is believed to be genetically and developmentally hardwired. Despite being innate, aggression is highly plastic. It is influenced by a wide variety of experiences, particularly winning and losing previous encounters. Numerous studies have shown that winning leads to an increased tendency to fight while losing leads to flight in future encounters. In the talk, I will present our recent findings regarding the neural mechanisms underlying the behavioral changes caused by winning.

There’s more to timing than time: P-centers, beat bins and groove in musical microrhythm

How does the dynamic shape of a sound affect its perceived microtiming? In the TIME project, we studied basic aspects of musical microrhythm, exploring both stimulus features and the participants’ enculturated expertise via perception experiments, observational studies of how musicians produce particular microrhythms, and ethnographic studies of musicians’ descriptions of microrhythm. Collectively, we show that altering the microstructure of a sound (“what” the sound is) changes its perceived temporal location (“when” it occurs). Specifically, there are systematic effects of core acoustic factors (duration, attack) on perceived timing. Microrhythmic features in longer and more complex sounds can also give rise to different perceptions of the same sound. Our results shed light on conflicting results regarding the effect of microtiming on the “grooviness” of a rhythm.

Modeling human brain development and disease: the role of primary cilia

Neurodevelopmental disorders (NDDs) impose a global burden, affecting an increasing number of individuals. While some causative genes have been identified, understanding the human-specific mechanisms involved in these disorders remains limited. Traditional gene-driven approaches for modeling brain diseases have failed to capture the diverse and convergent mechanisms at play. Centrosomes and cilia act as intermediaries between environmental and intrinsic signals, regulating cellular behavior. Mutations or dosage variations disrupting their function have been linked to brain formation deficits, highlighting their importance, yet their precise contributions remain largely unknown. Hence, we aim to investigate whether the centrosome/cilia axis is crucial for brain development and serves as a hub for human-specific mechanisms disrupted in NDDs. Towards this direction, we first demonstrated species-specific and cell-type-specific differences in the cilia-genes expression during mouse and human corticogenesis. Then, to dissect their role, we provoked their ectopic overexpression or silencing in the developing mouse cortex or in human brain organoids. Our findings suggest that cilia genes manipulation alters both the numbers and the position of NPCs and neurons in the developing cortex. Interestingly, primary cilium morphology is disrupted, as we find changes in their length, orientation and number that lead to disruption of the apical belt and altered delamination profiles during development. Our results give insight into the role of primary cilia in human cortical development and address fundamental questions regarding the diversity and convergence of gene function in development and disease manifestation. It has the potential to uncover novel pharmacological targets, facilitate personalized medicine, and improve the lives of individuals affected by NDDs through targeted cilia-based therapies.

Roles of inhibition in stabilizing and shaping the response of cortical networks

Inhibition has long been thought to stabilize the activity of cortical networks at low rates, and to shape significantly their response to sensory inputs. In this talk, I will describe three recent collaborative projects that shed light on these issues. (1) I will show how optogenetic excitation of inhibition neurons is consistent with cortex being inhibition stabilized even in the absence of sensory inputs, and how this data can constrain the coupling strengths of E-I cortical network models. (2) Recent analysis of the effects of optogenetic excitation of pyramidal cells in V1 of mice and monkeys shows that in some cases this optogenetic input reshuffles the firing rates of neurons of the network, leaving the distribution of rates unaffected. I will show how this surprising effect can be reproduced in sufficiently strongly coupled E-I networks. (3) Another puzzle has been to understand the respective roles of different inhibitory subtypes in network stabilization. Recent data reveal a novel, state dependent, paradoxical effect of weakening AMPAR mediated synaptic currents onto SST cells. Mathematical analysis of a network model with multiple inhibitory cell types shows that this effect tells us in which conditions SST cells are required for network stabilization.

Executive functions in the brain of deaf individuals – sensory and language effects

Executive functions are cognitive processes that allow us to plan, monitor and execute our goals. Using fMRI, we investigated how early deafness influences crossmodal plasticity and the organisation of executive functions in the adult human brain. Results from a range of visual executive function tasks (working memory, task switching, planning, inhibition) show that deaf individuals specifically recruit superior temporal “auditory” regions during task switching. Neural activity in auditory regions predicts behavioural performance during task switching in deaf individuals, highlighting the functional relevance of the observed cortical reorganisation. Furthermore, language grammatical skills were correlated with the level of activation and functional connectivity of fronto-parietal networks. Together, these findings show the interplay between sensory and language experience in the organisation of executive processing in the brain.

Maintaining Plasticity in Neural Networks

Nonstationarity presents a variety of challenges for machine learning systems. One surprising pathology which can arise in nonstationary learning problems is plasticity loss, whereby making progress on new learning objectives becomes more difficult as training progresses. Networks which are unable to adapt in response to changes in their environment experience plateaus or even declines in performance in highly non-stationary domains such as reinforcement learning, where the learner must quickly adapt to new information even after hundreds of millions of optimization steps. The loss of plasticity manifests in a cluster of related empirical phenomena which have been identified by a number of recent works, including the primacy bias, implicit under-parameterization, rank collapse, and capacity loss. While this phenomenon is widely observed, it is still not fully understood. This talk will present exciting recent results which shed light on the mechanisms driving the loss of plasticity in a variety of learning problems and survey methods to maintain network plasticity in non-stationary tasks, with a particular focus on deep reinforcement learning.

Learning produces a hippocampal cognitive map in the form of an orthogonalized state machine

Cognitive maps confer animals with flexible intelligence by representing spatial, temporal, and abstract relationships that can be used to shape thought, planning, and behavior. Cognitive maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. Here, we employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different versions of linear tracks in virtual reality. The results provide a detailed view of the formation of a cognitive map in the hippocampus. Throughout learning, both the animal behavior and hippocampal neural activity progressed through multiple intermediate stages, gradually revealing improved task representation that mirrored improved behavioral efficiency. The learning process led to progressive decorrelations in initially similar hippocampal neural activity within and across tracks, ultimately resulting in orthogonalized representations resembling a state machine capturing the inherent struture of the task. We show that a Hidden Markov Model (HMM) and a biologically plausible recurrent neural network trained using Hebbian learning can both capture core aspects of the learning dynamics and the orthogonalized representational structure in neural activity. In contrast, we show that gradient-based learning of sequence models such as Long Short-Term Memory networks (LSTMs) and Transformers do not naturally produce such orthogonalized representations. We further demonstrate that mice exhibited adaptive behavior in novel task settings, with neural activity reflecting flexible deployment of the state machine. These findings shed light on the mathematical form of cognitive maps, the learning rules that sculpt them, and the algorithms that promote adaptive behavior in animals. The work thus charts a course toward a deeper understanding of biological intelligence and offers insights toward developing more robust learning algorithms in artificial intelligence.

Using Adversarial Collaboration to Harness Collective Intelligence

There are many mysteries in the universe. One of the most significant, often considered the final frontier in science, is understanding how our subjective experience, or consciousness, emerges from the collective action of neurons in biological systems. While substantial progress has been made over the past decades, a unified and widely accepted explanation of the neural mechanisms underpinning consciousness remains elusive. The field is rife with theories that frequently provide contradictory explanations of the phenomenon. To accelerate progress, we have adopted a new model of science: adversarial collaboration in team science. Our goal is to test theories of consciousness in an adversarial setting. Adversarial collaboration offers a unique way to bolster creativity and rigor in scientific research by merging the expertise of teams with diverse viewpoints. Ideally, we aim to harness collective intelligence, embracing various perspectives, to expedite the uncovering of scientific truths. In this talk, I will highlight the effectiveness (and challenges) of this approach using selected case studies, showcasing its potential to counter biases, challenge traditional viewpoints, and foster innovative thought. Through the joint design of experiments, teams incorporate a competitive aspect, ensuring comprehensive exploration of problems. This method underscores the importance of structured conflict and diversity in propelling scientific advancement and innovation.

Connectome-based models of neurodegenerative disease

Neurodegenerative diseases involve accumulation of aberrant proteins in the brain, leading to brain damage and progressive cognitive and behavioral dysfunction. Many gaps exist in our understanding of how these diseases initiate and how they progress through the brain. However, evidence has accumulated supporting the hypothesis that aberrant proteins can be transported using the brain’s intrinsic network architecture — in other words, using the brain’s natural communication pathways. This theory forms the basis of connectome-based computational models, which combine real human data and theoretical disease mechanisms to simulate the progression of neurodegenerative diseases through the brain. In this talk, I will first review work leading to the development of connectome-based models, and work from my lab and others that have used these models to test hypothetical modes of disease progression. Second, I will discuss the future and potential of connectome-based models to achieve clinically useful individual-level predictions, as well as to generate novel biological insights into disease progression. Along the way, I will highlight recent work by my lab and others that is already moving the needle toward these lofty goals.

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.

Neuroinflammation in Epilepsy: what have we learned from human brain tissue specimens ?

Epileptogenesis is a gradual and dynamic process leading to difficult-to-treat seizures. Several cellular, molecular, and pathophysiologic mechanisms, including the activation of inflammatory processes.  The use of human brain tissue represents a crucial strategy to advance our understanding of the underlying neuropathology and the molecular and cellular basis of epilepsy and related cognitive and behavioral comorbidities,  The mounting evidence obtained during the past decade has emphasized the critical role of inflammation  in the pathophysiological processes implicated in a large spectrum of genetic and acquired forms of  focal epilepsies. Dissecting the cellular and molecular mediators of  the pathological immune responses and their convergent and divergent mechanisms, is a major requisite for delineating their role in the establishment of epileptogenic networks. The role of small regulatory molecules involved in the regulation of  specific pro- and anti-inflammatory pathways  and the crosstalk between neuroinflammation and oxidative stress will be addressed.    The observations supporting the activation of both innate and adaptive immune responses in human focal epilepsy will be discussed and elaborated, highlighting specific inflammatory pathways as potential targets for antiepileptic, disease-modifying therapeutic strategies.

Diffuse coupling in the brain - A temperature dial for computation

The neurobiological mechanisms of arousal and anesthesia remain poorly understood. Recent evidence highlights the key role of interactions between the cerebral cortex and the diffusely projecting matrix thalamic nuclei. Here, we interrogate these processes in a whole-brain corticothalamic neural mass model endowed with targeted and diffusely projecting thalamocortical nuclei inferred from empirical data. This model captures key features seen in propofol anesthesia, including diminished network integration, lowered state diversity, impaired susceptibility to perturbation, and decreased corticocortical coherence. Collectively, these signatures reflect a suppression of information transfer across the cerebral cortex. We recover these signatures of conscious arousal by selectively stimulating the matrix thalamus, recapitulating empirical results in macaque, as well as wake-like information processing states that reflect the thalamic modulation of largescale cortical attractor dynamics. Our results highlight the role of matrix thalamocortical projections in shaping many features of complex cortical dynamics to facilitate the unique communication states supporting conscious awareness.

NII Methods (journal club): NeuroQuery, comprehensive meta-analysis of human brain mapping

We will discuss a recent paper by Taylor et al. (2023): https://www.sciencedirect.com/science/article/pii/S1053811923002896. They discuss the merits of highlighting results instead of hiding them; that is, clearly marking which voxels and clusters pass a given significance threshold, but still highlighting sub-threshold results, with opacity proportional to the strength of the effect. They use this to illustrate how there in fact may be more agreement between researchers than previously thought, using the NARPS dataset as an example. By adopting a continuous, "highlighted" approach, it becomes clear that the majority of effects are in the same location and that the effect size is in the same direction, compared to an approach that only permits rejecting or not rejecting the null hypothesis. We will also talk about the implications of this approach for creating figures, detecting artifacts, and aiding reproducibility.

Brain Connectivity Workshop

Founded in 2002, the Brain Connectivity Workshop (BCW) is an annual international meeting for in-depth discussions of all aspects of brain connectivity research. By bringing together experts in computational neuroscience, neuroscience methodology and experimental neuroscience, it aims to improve the understanding of the relationship between anatomical connectivity, brain dynamics and cognitive function. These workshops have a unique format, featuring only short presentations followed by intense discussion. This year’s workshop is co-organised by Wellcome, putting the spotlight on brain connectivity in mental health disorders. We look forward to having you join us for this exciting, thought-provoking and inclusive event.

Anticipating behaviour through working memory (BACN Early Career Prize Lecture 2023)

Working memory is about the past but for the future. Adopting such a future-focused perspective shifts the narrative of working memory as a limited-capacity storage system to working memory as an anticipatory buffer that helps us prepare for potential and sequential upcoming behaviour. In my talk, I will present a series of our recent studies that have started to reveal emerging principles of a working memory that looks forward – highlighting, amongst others, how selective attention plays a vital role in prioritising internal contents for behaviour, and the bi-directional links between visual working memory and action. These studies show how studying the dynamics of working memory, selective attention, and action together paves way for an integrated understanding of how mind serves behaviour.

Brain network communication: concepts, models and applications

Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models.

Light-driven dopamine release in the adult and developing retina

Freeze or flee ? New insights from rodent models of autism

Individuals afflicted with certain types of autism spectrum disorder often exhibit impaired cognitive function alongside enhanced emotional symptoms and mood lability. However, current understanding of the pathogenesis of autism and intellectual disabilities is based primarily on studies in the hippocampus and cortex, brain areas involved in cognitive function. But, these disorders are also associated with strong emotional symptoms, which are likely to involve changes in the amygdala and other brain areas. In this talk I will highlight these issues by presenting analyses in rat models of ASD/ID lacking Nlgn3 and Frm1 (causing Fragile X Syndrome). In addition to identifying new circuit and cellular alterations underlying divergent patterns of fear expression, these findings also suggest novel therapeutic strategies.

From pecking order to ketamine - neural mechanism of social and emotional behavior

Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.

From pecking order to ketamine - neural mechanism of social and emotional behavior

Emotions and social interactions color our lives and shape our behaviors. Using animal models and engineered manipulations, we aim to understand how social and emotional behaviors are encoded in the brain, focusing on the neural circuits underlying dominance hierarchy and depression. This lecture will highlight our recent discoveries on how downward social mobility leads to depression; how ketamine tames depression by blocking burst firing in the brain’s antireward center; and, how glia-neuron interaction plays a surprising role in this process. I will also present our recent work on the mechanism underlying the sustained antidepressant activity of ketamine and its brain region specificity. With these results, we hope to illuminate on a more unified theory on ketamine’s mode of action and inspire new treatment strategies for depression.

How curiosity affects learning and information seeking via the dopaminergic circuit

Over the last decade, research on curiosity – the desire to seek new information – has been rapidly growing. Several studies have shown that curiosity elicits activity within the dopaminergic circuit and thereby enhances hippocampus-dependent learning. However, given this new field of research, we do not have a good understanding yet of (i) how curiosity-based learning changes across the lifespan, (ii) why some people show better learning improvements due to curiosity than others, and (iii) whether lab-based research on curiosity translates to how curiosity affects information seeking in real life. In this talk, I will present a series of behavioural and neuroimaging studies that address these three questions about curiosity. First, I will present findings on how curiosity and interest affect learning differently in childhood and adolescence. Second, I will show data on how inter-individual differences in the magnitude of curiosity-based learning depend on the strength of resting-state functional connectivity within the cortico-mesolimbic dopaminergic circuit. Third, I will present findings on how the level of resting-state functional connectivity within this circuit is also associated with the frequency of real-life information seeking (i.e., about Covid-19-related news). Together, our findings help to refine our recently proposed framework – the Prediction, Appraisal, Curiosity, and Exploration (PACE) framework – that attempts to integrate theoretical ideas on the neurocognitive mechanisms of how curiosity is elicited, and how curiosity enhances learning and information seeking. Furthermore, our findings highlight the importance of curiosity research to better understand how curiosity can be harnessed to improve learning and information seeking in real life.

Walk the talk: concrete actions to promote diversity in neuroscience in Latin America

Building upon the webinar "What are the main barriers to succeed in brain sciences in Latin America?" (February 2021) and the paper "Addressing the opportunity gap in the Latin American neuroscience community" (Silva, A., Iyer, K., Cirulli, F. et al. Nat Neurosci August 2022), this ALBA-IBRO Webinar is the next chapter in our journey towards fostering inclusivity and diversity in neuroscience in Latin America. The webinar is designed to go beyond theoretical discussions and provide tangible solutions. We will showcase 3-4 best practice case studies, shining a spotlight on real-life actions and campaigns implemented at the institutional level, be it within government bodies, universities, or other organisations. Our goal is to empower neuroscientists across Latin America by equipping them with practical knowledge they can apply in their own institutions and countries.

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

The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks

Neural activity is often described in terms of population-level factors extracted from the responses of many neurons. Factors provide a lower-dimensional description with the aim of shedding light on network computations. Yet, mechanistically, computations are performed not by continuously valued factors but by interactions among neurons that spike discretely and variably. Models provide a means of bridging these levels of description. We developed a general method for training model networks of spiking neurons by leveraging factors extracted from either data or firing-rate-based networks. In addition to providing a useful model-building framework, this formalism illustrates how reliable and continuously valued factors can arise from seemingly stochastic spiking. Our framework establishes procedures for embedding this property in network models with different levels of realism. The relationship between spikes and factors in such networks provides a foundation for interpreting (and subtly redefining) commonly used quantities such as firing rates.

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

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

Dynamic endocrine modulation of the nervous system

Sex hormones are powerful neuromodulators of learning and memory. In rodents and nonhuman primates estrogen and progesterone influence the central nervous system across a range of spatiotemporal scales. Yet, their influence on the structural and functional architecture of the human brain is largely unknown. Here, I highlight findings from a series of dense-sampling neuroimaging studies from my laboratory designed to probe the dynamic interplay between the nervous and endocrine systems. Individuals underwent brain imaging and venipuncture every 12-24 hours for 30 consecutive days. These procedures were carried out under freely cycling conditions and again under a pharmacological regimen that chronically suppresses sex hormone production. First, resting state fMRI evidence suggests that transient increases in estrogen drive robust increases in functional connectivity across the brain. Time-lagged methods from dynamical systems analysis further reveals that these transient changes in estrogen enhance within-network integration (i.e. global efficiency) in several large-scale brain networks, particularly Default Mode and Dorsal Attention Networks. Next, using high-resolution hippocampal subfield imaging, we found that intrinsic hormone fluctuations and exogenous hormone manipulations can rapidly and dynamically shape medial temporal lobe morphology. Together, these findings suggest that neuroendocrine factors influence the brain over short and protracted timescales.

The Neural Race Reduction: Dynamics of nonlinear representation learning in deep architectures

What is the relationship between task, network architecture, and population activity in nonlinear deep networks? I will describe the Gated Deep Linear Network framework, which schematizes how pathways of information flow impact learning dynamics within an architecture. Because of the gating, these networks can compute nonlinear functions of their input. We derive an exact reduction and, for certain cases, exact solutions to the dynamics of learning. The reduction takes the form of a neural race with an implicit bias towards shared representations, which then govern the model’s ability to systematically generalize, multi-task, and transfer. We show how appropriate network architectures can help factorize and abstract knowledge. Together, these results begin to shed light on the links between architecture, learning dynamics and network performance.

Retinal and brain circuits underlying the effects of light on behavior

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.

Integrative Neuromodulation: from biomarker identification to optimizing neuromodulation

Why do we make decisions impulsively blinded in an emotionally rash moment? Or caught in the same repetitive suboptimal loop, avoiding fears or rushing headlong towards illusory rewards? These cognitive constructs underlying self-control and compulsive behaviours and their influence by emotion or incentives are relevant dimensionally across healthy individuals and hijacked across disorders of addiction, compulsivity and mood. My lab focuses on identifying theory-driven modifiable biomarkers focusing on these cognitive constructs with the ultimate goal to optimize and develop novel means of neuromodulation. Here I will provide a few examples of my group’s recent work to illustrate this approach. I describe a series of recent studies on intracranial physiology and acute stimulation focusing on risk taking and emotional processing. This talk highlights the subthalamic nucleus, a common target for deep brain stimulation for Parkinson’s disease and obsessive-compulsive disorder. I further describe recent translational work in non-invasive neuromodulation. Together these examples illustrate the approach of the lab highlighting modifiable biomarkers and optimizing neuromodulation.

Cognitive supports for analogical reasoning in rational number understanding

In cognitive development, learning more than the input provides is a central challenge. This challenge is especially evident in learning the meaning of numbers. Integers – and the quantities they denote – are potentially infinite, as are the fractional values between every integer. Yet children’s experiences of numbers are necessarily finite. Analogy is a powerful learning mechanism for children to learn novel, abstract concepts from only limited input. However, retrieving proper analogy requires cognitive supports. In this talk, I seek to propose and examine number lines as a mathematical schema of the number system to facilitate both the development of rational number understanding and analogical reasoning. To examine these hypotheses, I will present a series of educational intervention studies with third-to-fifth graders. Results showed that a short, unsupervised intervention of spatial alignment between integers and fractions on number lines produced broad and durable gains in fractional magnitudes. Additionally, training on conceptual knowledge of fractions – that fractions denote magnitude and can be placed on number lines – facilitates explicit analogical reasoning. Together, these studies indicate that analogies can play an important role in rational number learning with the help of number lines as schemas. These studies shed light on helpful practices in STEM education curricula and instructions.

Interplay between circuits that mediate spontaneous retinal waves and early light responses during retinal development

Understanding Machine Learning via Exactly Solvable Statistical Physics Models

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

Private oxytocin supply and its receptors in the hypothalamus for social avoidance learning

Many animals live in complex social groups. To survive, it is essential to know who to avoid and who to interact. Although naïve mice are naturally attracted to any adult conspecifics, a single defeat experience could elicit social avoidance towards the aggressor for days. The neural mechanisms underlying the behavior switch from social approach to social avoidance remains incompletely understood. Here, we identify oxytocin neurons in the retrochiasmatic supraoptic nucleus (SOROXT) and oxytocin receptor (OXTR) expressing cells in the anterior subdivision of ventromedial hypothalamus, ventrolateral part (aVMHvlOXTR) as a key circuit motif for defeat-induced social avoidance learning. After defeat, aVMHvlOXTR cells drastically increase their responses to aggressor cues. This response change is functionally important as optogenetic activation of aVMHvlOXTR cells elicits time-locked social avoidance towards a benign social target whereas inactivating the cells suppresses defeat-induced social avoidance. Furthermore, OXTR in the aVMHvl is itself essential for the behavior change. Knocking out OXTR in the aVMHvl or antagonizing the receptor during defeat, but not during post-defeat social interaction, impairs defeat-induced social avoidance. aVMHvlOXTR receives its private supply of oxytocin from SOROXT cells. SOROXT is highly activated by the noxious somatosensory inputs associated with defeat. Oxytocin released from SOROXT depolarizes aVMHvlOXTR cells and facilitates their synaptic potentiation, and hence, increases aVMHvlOXTR cell responses to aggressor cues. Ablating SOROXT cells impairs defeat-induced social avoidance learning whereas activating the cells promotes social avoidance after a subthreshold defeat experience. Altogether, our study reveals an essential role of SOROXT-aVMHvlOXTR circuit in defeat-induced social learning and highlights the importance of hypothalamic oxytocin system in social ranking and its plasticity.

Direction-selective ganglion cells in primate retina: a subcortical substrate for reflexive gaze stabilization?

To maintain a stable and clear image of the world, our eyes reflexively follow the direction in which a visual scene is moving. Such gaze stabilization mechanisms reduce image blur as we move in the environment. In non-primate mammals, this behavior is initiated by ON-type direction-selective ganglion cells (ON-DSGCs), which detect the direction of image motion and transmit signals to brainstem nuclei that drive compensatory eye movements. However, ON-DSGCs have not yet been functionally identified in primates, raising the possibility that the visual inputs that drive this behavior instead arise in the cortex. In this talk, I will present molecular, morphological and functional evidence for identification of an ON-DSGC in macaque retina. The presence of ON-DSGCs highlights the need to examine the contribution of subcortical retinal mechanisms to normal and aberrant gaze stabilization in the developing and mature visual system. More generally, our findings demonstrate the power of a multimodal approach to study sparsely represented primate RGC types.

LifePerceives

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

Microglial efferocytosis: Diving into the Alzheimer's Disease gene pool

Genome-wide association studies and functional genomics studies have linked specific cell types, genes, and pathways to Alzheimer’s disease (AD) risk. In particular, AD risk alleles primarily affect the abundance or structure, and thus the activity, of genes expressed in macrophages, strongly implicating microglia (the brain-resident macrophages) in the etiology of AD. These genes converge on pathways (endocytosis/phagocytosis, cholesterol metabolism, and immune response) with critical roles in core macrophage functions such as efferocytosis. Here, we review these pathways, highlighting relevant genes identified in the latest AD genetics and genomics studies, and describe how they may contribute to AD pathogenesis. Investigating the functional impact of AD-associated variants and genes in microglia is essential for elucidating disease risk mechanisms and developing effective therapeutic approaches." https://doi.org/10.1016/j.neuron.2022.10.015

Indispensable for generating epileptic seizures: where, when, how?

In epilepsy research, a holy grail has been the identification and understanding of the "epileptogenic zone" - operationally defined as the (minimal) area or region of the brain is indispensible for the generation of epileptic seizures. The identification of the epileptogenic zone is particularly important for surgical treatments of focal epilepsy patients, but I will highlight some recent clinical, experimental and theoretical work showing that it is also fundamentally linked with our understanding of epilepsy and seizures. I will conclude with a proposal for an updated understanding of the epileptogenic zone and ictogenesis.

An insect vision-based flight control model with a plastic efference copy

COSYNE 2022

Moving bar of light evokes vectorial spatial selectivity in hippocampal place cells

COSYNE 2022

Moving bar of light evokes vectorial spatial selectivity in hippocampal place cells

COSYNE 2022

Exploring a neural circuit for estimating ambient wind direction in flight

COSYNE 2023

A computational map of flight control in Drosophila melanogaster

COSYNE 2025

40Hz-transcranial Alternating Current Stimulation (tACS) modulates illusory perception: shedding light on Pareidolia

Analyses of circRNA expression throughout circadian rhythm reveal a strong link between Cdr1as and light-induced phase shifts in the SCN

Blue light modulates task-dependent subcortico-cortical connectivity during an auditory attentional task

A certain type of Photoreceptor contributes to the immediate effect of light on eclosion behaviour

Comparing clearing methods and imaging procedures in light sheet microscopy

A Complexin-Transducin-Complex in Light Adaptation in Mammalian Retina

Custom Light-Sheet Microscopy setups for large-scale human and mouse brain mapping

How does optogenetic restoration of retinal light sensitivity affect visual processing in mice?

Enlightening the Glycine Receptor α2 as a Key Regulator in the Brain Reward Pathway

Exposure to blue light at night during adolescence induces neurotransmitter plasticity in the amygdala affecting emotional responses in mice

Green light exposure elicits anti-inflammation, endogenous opioid release and lessens synaptic potentiation to relieve post-surgical pain in rats

Green light-induced antinociception involves descending modulation of mechanical sensitivity

The impact of light source properties, neural morphology and the distribution of light-gated ion channels on the effective spatial resolution of optogenetic stimulation

In-vivo fast non-linear microscopy reveals intraneuronal transport impairment induced by slight molecular motor imbalances in the brain of zebrafish larvae

Light as an inverse agonist inhibits constitutive G protein signalling of the zebrafish non-visual opsin Opn7b

Light sheet imaging of behaviourally activated amygdala neurons in the Fragile-X knockout rat model of autism spectrum disorders

Light on the spinal projections and roles of medullary V2a reticulospinal neurons in locomotion

Light-induced stress response is impaired in the Retinitis Pigmentosa mouse model CerklKD/KO

Lightweight, reusable chronic implants for Neuropixels 2.0 probes

Linking plasma amyloid beta and neurofilament light chain to intracortical myelin content in cognitively normal older adults

Local thermal modulation of optogenetically induced epileptic activity by infrared laser light

Manipulation of network activity in 3D spinal explants by single cell light-activation

Mathematical simulation enlightenment and experimental improvement of tDCS in a model of psychotic transition: a translational study

Membrane-targeted light-sensitive compound for opto-poration

Moonlighting Regulation of Neuronal Cell Fate Determination by Endocytic Adaptor AP-2

neurofilamant light chain (nfl) immunoassay for the smcxpro™ assay platform: development and applications

A novel membrane-targeted photoswitch restores physiological light-responses in the degenerated Rd10 mouse retina

Physiologically relevant light stimulation leads to local signatures of sleep pressure in the contralateral visual cortex in freely moving mice

How the use of dim red-light during preparation affects ERG responses of mice with long-wavelength shifted opsin

Responsibility issues raised by neurotechnologies in light of ethics and philosophy

Role of the Ferritin light-chain in the logic of sound coding

Searchlight analysis for intracranial EEG recordings

Serum Neurofilament Light As A Biomarker Of Vulnerability To Repeated Mild Traumatic Brain Injury In Adolescent Male Rats

Single pulse electrical stimulation evoked responses: a pioneering preclinical tool to highlight new specific EEG signatures

An insect vision-based flight control model with a plastic efference copy

COSYNE 2022