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Optimizing CD45-Targeted Astatine-211-Radioimmunotherapy for Malignant and Non-Malignant Blood Disorders

ABSTRACT CD45 is expressed on almost all normal and neoplastic hematopoietic cells but not on non-blood cells and has, therefore, been pursued as a drug target. Initially centered on augmenting conditioning before hematopoietic cell transplantation (HCT) for blood cancers, there is increasing interest in expanding CD45-directed therapies into other settings, with radioimmunotherapy (RIT) being the major therapeutic modality so far. Investigators at our institution pioneered CD45 RIT with b-emitters such as iodine-131 (131I) using the murine monoclonal antibody (mAb), BC8. A phase 3 trial testing 131I-BC8 (131I-apamistamab [Iomab-B]) with allogeneic HCT in older adults with relapsed/refractory acute myeloid leukemia showed improved outcomes over conventional care, validating this approach. More recently, attention has shifted toward a-emitters that deliver substantially higher decay energies over much shorter distances than b-emitters, rendering them more suitable for precise and potent target cell killing. In our work, we focus on astatine-211 (211At) for its ideal half-life and decay without a-emitting daughters. For clinical application, mAbs are conjugated with the bifunctional boron cage molecule, isothiocyantophenethyl-ureido-closo-decaborate(2-) (B10-NCS), to enable stable protein astatination. Three early-phase trials testing 211At-BC8-B10 as augmentation of HCT conditioning for patients with malignant and non-malignant blood disorders are ongoing, with emerging data indicating significant anti-tumor efficacy. Nonetheless, relapses still occur. Other important limitations include marked infusion toxicities and human antimouse antibody (HAMA) responses related to the murine nature of BC8 and dimer formation after 211At labeling of mAb-B10 conjugates with tissue residualization from 211At atom oxidation. The latter may contribute to the risk of liver cell injury, the dose limiting extramedullary toxicity of CD45 RIT. As a first step toward our goal of optimizing CD45 RIT, we have raised new, fully human CD45 mAbs as basis for novel therapeutics. In preliminary in vivo studies in immunodeficient mice, we found some of these mAbs to have greater anti-tumor efficacy than a humanized version of BC8 (HuBC8) we generated as a reference mAb. We will now conduct comparative in vivo CD45+ cell targeting (“biodistribution”) and anti-tumor efficacy studies to select a lead candidate mAb for clinical application and use protein engineering to maximize the selectivity and efficacy of targeted radiation delivery. We will use immunodeficient mice xenotransplanted with human leukemia cells for this purpose as no human approaches are available and in vitro testing is inadequate to measure both the targeting and biologic RIT effects on human leukemia cells. Mice provide the in vivo milieu needed for comprehensive evaluation. Development of improved mAb astatination methodologies to minimize off-target toxicities of 211At-RIT will further increase therapy specificity and reduce toxicity. In parallel, we will conduct genome-scale, unbiased target identification/validation studies to identify partner drugs for rational combination therapies aimed at enhancing the anti-tumor efficacy of 211At-CD45 RIT.

Role of cellular physical interactions in pancreatic cancer progression

Pancreatic cancer, with a 5-year overall survival rate of 13%, has the lowest survival rate of all cancers. The goal of this project is to better understand the biological processes of pancreatic cancer progression and discover their potential as targets for efficient therapies. Pancreatic ductal adenocarcinoma (PDAC) underdoes epithelial architecture changes during its progression. However, the underlying mechanisms for these changes are largely unknown. Interestingly, our recent data demonstrate the recapitulation of the distinct epithelial architectures in the organoid culture of cells derived from the human normal pancreas, primary tumor, and metastatic lesions, thereby developing a unique organoid model for the in vitro studies of PDAC epithelial architecture changes. The primary objective of this project is to understand the regulation of the differential PDAC epithelial architectures as well as their contribution to PDAC progression. Our central hypothesis is that disruption in lumen structure drives PDAC epithelial architecture transition and promotes PDAC progression. We will combine experimental and computational approaches to test our central hypothesis by pursuing the following two specific aims: (Aim 1) define the regulators of PDAC epithelial architecture that drives PDAC progression and (Aim 2) determine the functional consequences of PDAC epithelial architecture on PDAC progression. With the completion of this aims, we expect: (Aim 1) to identify ion and water channels that are important for lumen structure as well as PDAC progression, revealing potential novel targets for therapeutic intervention, and (Aim 2) to uncover YAP’s role in PDAC progression and guide the development of YAP- targeted therapies.

BKCa Channel Contributions to Cerebellar Regulated TSC-Associated Neuropsychiatric Disorders

Project Summary TSC is associated with neurodevelopmental disability including cognitive disability and autism spectrum disorders (ASD) that make up part of TSC associated neuropsychiatric disorders (TAND). The mechanisms for TAND remain poorly understood but studies have increasingly implicated cerebellar dysfunction in the pathogenesis of cognitive and behavioral deficits in both TSC and other neurodevelopmental disorders. A shared feature is cerebellar Purkinje cell (PC) dysfunction. Changes in intrinsic properties of PCs results in both motor and cognitive/ behavioral changes in disease models and in individuals afflicted by these disorders. Mechanistic underpinnings of these altered properties remain unknown, but a significant emerging body of data implicate ion channel dysfunction as the primary etiology of these deficits. The current proposal seeks to delineate the ion channel contribution to PC dysfunction and to TAND-relevant behaviors. In doing so, these studies will produce significant both short- and long-term impact. Short-term: These proposed studies will provide a mechanistic understanding of the contribution of ion channels to the neuronal dysfunction in the cerebellum that has been demonstrated to be causally linked to abnormal TAND-relevant behaviors. In addition, we will target specific ion channels both genetically and pharmacologically to evaluate the benefits of ion channel restoration on both electrophysiological abnormalities but also the TAND-relevant behaviors observed in the model. Long-term: These studies, thus, provide a framework for subsequent clinically-relevant therapeutic development for TAND. First, these studies will uncover the ability for TAND-relevant behaviors to be improved upon targeting ion channel alterations in TSC. These studies will also define molecular targets on which therapeutic development can be targeted, thereby potentially providing a molecular-informed pipeline for therapeutic development. In addition, these studies will utilize clinically-available, FDA-approved pharmacological agents to target ion channel function and investigate the potential therapeutic benefits for these agents for TAND-relevant behaviors. Thus, these studies will address a core gap in knowledge to achieve a better mechanistic understanding of TAND and to develop therapeutic opportunities to address TAND. These studies will not only reveal previously understudied and novel mechanistic underpinnings for these behaviors but will provide pre-clinical insights into the therapeutic utility of clinically-utilized agents for the treatment of TAND-related behaviors, thus potentially providing both immediate and long-term opportunities for the treatment of TAND. Moreover, although these studies focus on TSC, these mechanisms may prove generalizable beyond TSC and provide a shared basis and therapeutic opportunity for other neuropsychiatric/developmental conditions.

Neuroinflammation in Cerebral Small Vessel Disease

Project Summary/Abstract Cerebral small vessel disease (cSVD) is a leading cause of vascular contributions to cognitive impairment and dementia (VCID), which is the 2nd leading cause of dementia and a significant contributor to Alzheimer’s disease (AD). Thus far, the underlying pathogenesis of cSVD is poorly understood. Several lines of evidence, including animal models, postmortem human brain pathology, and systemic inflammatory markers, demonstrated the damaging role of chronic neuroinflammation in cSVD. Direct evidence of neuroinflammation at the tissue level in patients with cSVD is still critically needed. The sphingosine-1-phosphate receptor 1 (S1PR1) regulates neuroinflammation through microglial and astrocyte activation and trafficking and has emerged as a promising target for neuroinflammation. In postmortem brains of patients with cSVD, we observed elevated S1PR1 expression and colocalization of S1PR1 with astrocytes and microglia. A novel 11C-CS1P1 PET radiotracer with high affinity and specificity targeting S1PR1 has been recently developed and validated in animal models and post-mortem human specimens. Under an FDA-approved eIND (IND 146548), we have successfully completed the safety and dosimetry study in healthy participants and performed preliminary studies in patients with cSVD. We found that 11C-CS1P1 PET uptake is significantly associated with WMH lesion burden in patients with cSVD after controlling for age, sex, race, vascular risk factors, and amyloid deposition. We hypothesize that 11C-CS1P1 PET uptake is a tissue-level biomarker of neuroinflammation to provide insight into cSVD severity, progression, and prognosis. We will 1) evaluate the relationship between 11C-CS1P1 PET uptake and cSVD neuroimaging abnormalities and cognitive impairment, 2) evaluate the test-retest repeatability and longitudinal evolution, and 3) determine whether 11C-CS1P1 PET uptake at baseline predict cSVD progression. The successful completion of this study will establish 11C-CS1P1 PET as an neuroinflammation imaging biomarker and investigate the role of neuroinflammation in cSVD pathogenesis and progression. It will lay a foundation for developing future therapies in modulating neuroinflammation.

Baby Toolbox Training and Certification Program

PROJECT SUMMARY Our objective is to improve early childhood outcomes and support the expansion of the NIH Infant and Toddler Toolbox (Baby Toolbox) by providing comprehensive training support to those interested in using it. The Baby Toolbox is a brand new, nationally-normed assessment for infants 1-42 months, commissioned by NICHD and released for public use in 2025. The Baby Toolbox is administered entirely on an iPad and includes 35 measures across six domains using novel technology (e.g., gaze tracking, automatic scoring, computerized adaptive testing). It has the potential to bring harmonization to the developmental fields, but in order for it to become a common currency for developmental research as envisioned, researchers need to know how to administer it and how to train others to administer it. We propose an education program that will include a week-long training workshop, certification activities, and post-workshop support to create expert cohorts of Baby Toolbox test administrators. Individuals who attend the workshops can become certified test trainers, capable of training others at their home institutions to administer the assessment thus creating a self-sufficient training model. Through the proposed educational program, we will provide funding to cover lodging, meals, and incidentals during the workshop, in addition to subsidizing transportation to/from the workshop and provide a one-year subscription to the Baby Toolbox. A portion of slots will also be set aside for those without current grant funding. Our team is highly qualified to complete these tasks because we have led the effort to develop the Baby Toolbox assessment and have already completed multiple training workshops for contract deliverables. This grant would continue the efforts started by the NICHD in funding the Baby Toolbox by helping support its rollout, implementation, and growth. To meet these goals, we have the following aims: Aim 1: Create cohorts of trained Baby Toolbox examiners who can catapult the Baby Toolbox into widespread use by hosting a comprehensive week-long education program (training workshop) yearly for individuals to learn how to administer and train others to administer the Baby Toolbox, Aim 2: Expand the use of the Baby Toolbox by recruiting and financially supporting individuals who will bring the Baby Toolbox into a variety of research and clinical settings. Aim 3: Build a virtual training resource of videos and materials to support ongoing fidelity checks with certified trainers, and future training efforts.

Targeting the Molecular Crosstalk Between EZHIP and PRC2 in PFA Ependymoma

Project Summary: PFA ependymoma is a rare and aggressive pediatric brain tumor with a poorly understood molecular mechanism. Unlike many cancers, PFA ependymoma exhibits very few genetic alterations. Instead, it is thought to be driven primarily by epigenetic dysregulation. A key player in this disease is the EZH1/2 inhibitory protein EZHIP, which is normally expressed only in germ cells. EZHIP is aberrantly expressed in PFA ependymoma, where it disrupts the function of Polycomb Repressive Complex 2 (PRC2), a master epigenetic regulator of developmental gene repression through deposition of the trimethylated histone H3 lysine 27 (H3K27me3) repressive histone mark. EZHIP-mediated dysregulation of PRC2 involves both enzymatic inhibition and physical stalling of PRC2 on CpG island (CGI) chromatin, leading to a global loss of H3K27me3 levels, an epigenetic hallmark of PFA ependymoma. PRC2 itself is a highly dynamic and intricate complex that assembles into two functional variants, PRC2.1 and PRC2.2. These two variants share a core composed of the catalytic subunits EZH1/2, along with EED, SUZ12, and RBBP4/7, and differ by incorporating distinct accessory subunits. PRC2.1 includes PHF1/MTF2/PHF19, EPOP, and PALI1/2, while PRC2.2 features AEBP2 and JARID2. Our preliminary data reveal intriguing molecular crosstalk between EZHIP and multiple PRC2 components, suggesting potential competitive or cooperative interplay. The ability of EZHIP to inhibit PRC2 partly stems from its mimicry of the oncohistone H3K27M, which harbors a lysine-to-methionine mutation that causes diffuse midline glioma, another devastating brain tumor in children, where PRC2 activity is also globally suppressed. However, the precise, EZHIP-specific mechanisms behind PRC2 dysregulation in PFA ependymoma remain largely unexplored. Our work aims to uncover these elusive mechanisms using a powerful combination of structural biology, biochemistry, and genomics approaches. Ultimately, we aim to identify therapeutic strategies that disrupt the pathogenic EZHIP–PRC2 crosstalk and restore the normal H3K27me3 epigenetic landscape. Specifically, in Aim 1, we will determine the structural and biochemical mechanisms underlying the enzymatic inhibition of the PRC2 core complex by EZHIP. In Aim 2, we will elucidate the molecular basis of EZHIP-mediated stalling of PRC2 on CGI chromatin, involving PRC2 functional variants. In Aim 3, we will explore an exciting mechanism-based therapeutic strategy to overcome PRC2 enzymatic inhibition and chromatin stalling induced by EZHIP.

Dissecting the role for astrocytes in mediating adverse outcomes of maternal immune activation.

Prenatal infections cause maternal immune activation (MIA), a major risk factor for several neurodevelopmental disorders, including schizophrenia, autism spectrum disorders (ASD), and attention deficit hyperactivity disorder (ADHD). Consequently, elucidating the mechanisms by which MIA alters brain function is critical for understanding the pathophysiology of these disorders and developing effective treatments. While the effects of MIA on neurons and microglia have been extensively studied, the impact of MIA on astrocytes, key regulators of brain physiology and homeostasis, remain unknown that significantly impedes our understanding the mechanisms of MIA-induced neurobehavioral abnormalities. To address this major knowledge gap, we conducted pilot studies that suggest that MIA increases impulsivity-like behaviors and amphetamine-induced hyperactivity and enhances extracellular levels of glutamate (GLU) and dopamine (DA) in the dorsal striatum (DS). MIA also increased pro-inflammatory signatures of astrocytes, including up- regulation of the Nuclear Factor kappa B (NF-κB) pathway and increased GFAP immunoreactivity in DS astrocytes. Collectively, these novel findings support our overarching hypothesis that MIA increases astrocyte reactivity, leading to increased gliotransmission (e.g., GLU), which in turn enhances DS DA release and DA- dependent behaviors. To test this hypothesis, we will leverage the expertise of the research team in molecular, physiological and neurobehavioral approaches and conduct the following Specific Aims: In Aim 1, we will identify the MIA-induced cellular and physiological changes characteristic of astrocyte reactivity. In Aim 2, we will determine the circuit mechanisms by which MIA increases DA signaling. In Aim 3, we will identify the molecular mechanisms whereby reactive astrocytes contribute to MIA-induced cellular and behavioral abnormalities. These studies will enhance the current understanding of the effects of MIA on brain functions and generate new insight into potential treatment strategies for MIA-associated neurodevelopmental disorders.

Clinical Trial Readiness of MEG Biomarkers in Children Across the Autism Spectrum

PROJECT SUMMARY Biological and phenotypic heterogeneity of autism spectrum disorder (ASD) poses a major challenge for clinically focused research and interventions. Brain electrophysiological phenotyping holds promise for parsing this heterogeneity. Using magnetoencephalography (MEG), findings of diminished and delayed auditory evoked responses (e.g. the ~50ms component, M50 and, specifically, its latency: M50L) have reproducibly been shown in ASD, with correlation to behavior. Additionally, abnormal resting state activity and network functional connectivity has been identified as an electrophysiological hallmark. Such passively-acquired signatures may serve as objective biomarkers in subtyping autistic individuals, including stratifying patients for inclusion in clinical trials according to biology, rather than behavior alone. However, despite their abundant promise, these measures are not yet permeating clinical trial design, nor being utilized in clinical practice, in part because of their lack of standardized implementation and analysis. This proposal seeks to remedy this by using rigorous and standardized, scalable and sharable methods with two leading MEG measures to determine their measurement- reliability as well as their sensitivity to inter-individual differences in clinically-relevant aspects of autism features, general cognitive ability and language and communication. Specifically adopting a 12-week repeated scanning design, mimicking the duration of a typical pharmaceutical trial or behavioral intervention, we will acquire each of these two MEG metrics at baseline and 12-week follow-up to assess interval change. Additionally, we will evaluate test-retest variability with an intermediate measurement point 4-weeks after baseline. As such we will characterize both intra-subject variability (measurement precision) and inter-subject variability which will be correlated with dimension axes of autism features, general cognitive ability and language skills, as well as major co-occurring condition confounds. These studies will recruit a broad range of 240 autistic children, paralleling the CDC’s prevalence data on intellectual ability and encompassing the group considered as having “profound autism”. This is enabled by our adoption of MEG-PLAN, a strategy developed over the last decade in our group and demonstrated to enhance inclusive participation in MEG scanning studies, even in non-verbal participants. Data will be compared to a control group of age-matched typically-developing peers. The two MEG measures will also be assessed for their ability to identify clusters of less heterogeneous neurophysiological phenotype as a novel basis for stratification or subtyping of the heterogeneous autism population. In culmination, this study addresses key “clinical readiness” aspects of utilization of MEG biomarkers for ASD including profound autism, for both stratification (inclusion/trial selection) and monitoring of response to intervention, and will, ultimately, pave the way for the adoption of such biomarkers as adjunctive tests in increasingly-routine clinical practice.

Airway Epithelial Defense Mechanisms in Combating STAT3-Deficiency-Related Lung Infections

Airway Epithelial Defense Mechanisms in Combating STAT3-Deficiency-Related Lung Infections Signal transducer and activator of transcription 3 (STAT3) regulates the expression of genes essential for various cellular processes, including survival, proliferation, differentiation, self-renewal, angiogenesis, and immune response. Abnormal and persistent STAT3 activation is detected in diverse human cancers, driving multiple pro- oncogenic functions. Multiple antitumor drug development targets the inhibition of STAT3 to treat various types of cancer. Unfortunately, downregulated STAT3 significantly increases host susceptibility to recurrent infections, especially pneumonia. Additionally, individuals with genetic polymorphisms associated with lower STAT3 expression are more susceptible to severe tuberculosis. Furthermore, patients with autosomal dominant hyper- IgE syndrome (AD-HIES), also known as Job Syndrome, which is caused by de novo STAT3 mutations and substantially decreased STAT3 expression, have a significantly increased susceptibility to bacterial and fungal infections, with high mortality rates and a shortened life span often associated with Pseudomonas aeruginosa infections. Gram-negative bacteria, particularly P. aeruginosa, are opportunistic pathogens that frequently cause hospital-acquired infections. The problems are worsened by the emerging P. aeruginosa with multidrug resistance (MDR), especially in patients with repeated antibiotic treatments, such as Job Syndrome sufferers. Notably, airway epithelial cell-derived proteins play a significant role in the antimicrobial milieu, promoting effective host defense against invading pathogens. One of the most critical STAT3-regulated antimicrobial molecules is bactericidal permeability-increasing protein fold A1 (BPIFA1, also known as SPLUNC1), a multifunctional innate immunity molecule and indispensable host defense protein that is abundantly secreted in the lungs. This application aims to elucidate how STAT3 deficiency impairs host epithelial defense against microbial infections and whether BPIFA1-mediated innate immune responses can sufficiently restore effective antimicrobial protection to prevent pneumonia. The long-term objective is to advance our understanding of the respiratory innate immune response, particularly in relation to epithelial cell-specific antimicrobial defense. We characterized BPIFA1 as an airway lining fluid protein secreted apically in the airway lumen and in primary human airway epithelial cultures. In this study, we hypothesize that mucosal BPIFA1 is an essential antimicrobial protein that plays a critical role in host defense against microbial infections in STAT3-deficiency- associated pneumonia. Our proposed studies will assess innate immunity mechanisms regulating the antimicrobial activity of the airway epithelium in STAT3 deficiency-associated lung infections. By focusing on the crucial epithelial-derived protein product, BPIFA1, our study will provide an alternative treatment for respiratory infections by augmenting native host defense mechanisms in high-risk individuals, including AD-HIES, cancer, and immunocompromised patients.

The Pyruvate-Lactate Metabolic Axis in Heart Failure and Recovery

PROJECT SUMMARY/ABSTRACT Heart failure (HF) is a leading cause of mortality worldwide. The metabolism of the failing heart is commonly characterized by increased glucose uptake, glycolytic dependence, and reduced oxidative phosphorylation. We previously demonstrated that blocking glucose oxidation is sufficient to cause hypertrophy and subsequent HF. Additionally, our preliminary data shows that an altered pyruvate-lactate metabolic axis may be pivotal in human HF. Research investigating both the mechanistic regulation and biological roles of the pyruvate-lactate metabolic axis in cardiac metabolism during HF and cardiac recovery is warranted and also has the potential to identify novel druggable pathways to target for future pharmacological approaches. The overall objective of this application is to test the hypothesis that impaired pyruvate oxidation is a cardinal feature of HF in humans and animal models and that myocardial recovery is tightly coupled to normalization of the pyruvate-lactate metabolic axis. We will quantify the pyruvate-lactate metabolic axis in human HF and myocardial recovery (Aim 1). Next, we will determine the essentiality of the pyruvate-lactate metabolic axis for HF and cardiac recovery (Aim 2). Lastly, we will define cell-autonomous mechanisms that regulate the pyruvate-lactate axis in HF and recovery (Aim 3). These experiments will allow us to identify patterns of metabolic alteration in the pyruvate-lactate axis and molecular pathways during HF and myocardial recovery. Understanding the role of pyruvate and lactate metabolism in HF and myocardial recovery is cutting-edge research. Our unique access to human HF myocardium from patients administered stable isotope-labeled glucose or lactate to quantitate pyruvate metabolism in HF and recovery is state-of-the-art and will likely help us reveal new fundamental mechanisms of cardiac metabolism and expedite the successful translation of therapeutics being validated in various models of HF and recovery.

Transposable element silencing as a regulator of salivary gland immune homeostasis

PROJECT SUMMARY/ABSTRACT Sjogren’s syndrome (SjS) is a chronic autoimmune disorder marked by salivary and lacrimal gland dysfunction, lymphocytic infiltration, and progressive secretory decline. While traditionally viewed as immune cell–driven, emerging evidence suggests that epithelial cells may initiate local inflammation. However, the molecular triggers originating from epithelial cells remain poorly defined. Transposable elements (TEs), including endogenous retroviruses (ERVs) and LINEs, are normally repressed through DNA methylation, histone modifications, and heterochromatin organization. Failure of TE silencing mechanisms due to aging, hormonal changes, or stress results in cytoplasmic dsRNA accumulation, nucleic acid sensor activation, and type I interferon signaling. These TE-derived nucleic acids are increasingly recognized as endogenous triggers of immunological stress that disrupt cellular homeostasis. Our preliminary data show widespread TE derepression and upregulation of interferon-stimulated genes in salivary glands from patients with SjS. To mimic this phenomenon, we will inducibly delete Setdb1, a key histone H3K9 methyltransferase, in defined epithelial compartments of the salivary gland. This will allow us to model compartment-specific TE derepression and assess its impact on both innate immune activation and adaptive immune responses. We will also test how aging and estrogen deficiency disrupt TE repression in basal/ductal versus acinar cells using lineage tracing and epigenomic profiling. Finally, we will evaluate the therapeutic potential of reverse transcriptase inhibitors and chromatin-modifying drugs in attenuating TE-driven inflammation. This exploratory study will uncover how failure of TE silencing contributes to epithelial-driven autoimmunity in SjS and will provide a foundation for future targeted epigenetic manipulations in human tissues and patients.

Pathogenic mechanisms of expanded ZFHX3 in SCA4 cerebellar organoids

Spinocerebellar ataxia type 4 (SCA4) is a disabling neurodegenerative disease characterized by progressive cerebellar ataxia, and the causative GGC-repeat expansion in ZFHX3 (ZHFX3-exp) was just discovered this year by our lab and others. Our research aims to understand how ZFHX3-exp causes SCA4 and to identify molecular therapeutic targets that can be quickly advanced into clinical trials. SCA4 is one of the four poly-glycine diseases that share the presence of neuronal intranuclear inclusion (NIIs) as a disease hallmark. In SCA4, NIIs are positive for ZFHX3, p62 and ubiquitin, indicating the loss of proteostasis as a mechanism of neurodegeneration. In addition, ZFHX3 RNA-gain-of-function may also contribute to neurodegeneration. Beyond this, knowledge of the disease mechanisms that underly SCA4 is extremely limited and there are currently no disease-modifying treatments for SCA4 or other polyG/NII diseases. There are no SCA4 mouse models and because of the high GC content in the repeat expansion complicates the production of SCA4 mouse models. We propose a novel approach to characterizing SCA4 Purkinje cell (PC) pathogenesis using human cerebellar organoids. Our approach allows for rapidly advancing the understanding of the pathogenesis and potential treatments of SCA4. Using cerebellar organoids will enable investigation on functional PCs, cerebellar neurodegeneration and the testing of potential therapeutic strategies. In aim 1, we will generate cerebellar organoids from five SCA4 patient-derived iPSC lines, and normal control iPSCs from individuals of the same family. These iPSC lines are already established in our laboratory. In aim 2, we will investigate PC viability, NII protein composition, proteostasis pathways, RNA gain-of-function and cell-type-specific dysregulated pathways by single nucleus RNA sequencing. In addition, we will study potential therapeutic targets by lentiviral knockdown and single nucleus RNA sequencing. SCA4 patient iPSCs express overabundant STAU1 and ATXN2. We will evaluate how lowering the abundance of these proteins modifies the PC molecular phenotype. Together, these experiments will establish a model to greatly enhance the understanding of human PC neurodegeneration, the pathological mechanisms of SCA4 and possible avenues of treatment.

Intrinsic and extrinsic mechanisms underlying trigeminal nerve deficits in familial dysautonomia

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

2-Deoxyglucose Therapy for Organophosphate Intoxication

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

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

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

Identifying host-interacting proteins of Sneathia vaginalis

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

Characterizing adipocyte heterogeneity in response to metabolic stress

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

Development of a multi-modal mouse model of cluster headache

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

Organization of thalamic networks and mechanisms of dysfunction in schizophrenia and autism

Thalamic networks, at the core of thalamocortical and thalamosubcortical communications, underlie processes of perception, attention, memory, emotions, and the sleep-wake cycle, and are disrupted in mental disorders, including schizophrenia and autism. However, the underlying mechanisms of pathology are unknown. I will present novel evidence on key organizational principles, structural, and molecular features of thalamocortical networks, as well as critical thalamic pathway interactions that are likely affected in disorders. This data can facilitate modeling typical and abnormal brain function and can provide the foundation to understand heterogeneous disruption of these networks in sleep disorders, attention deficits, and cognitive and affective impairments in schizophrenia and autism, with important implications for the design of targeted therapeutic interventions

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

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

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.

The synaptic functions of Alpha Synuclein and Lrrk2

Alpha synuclein and Lrrk2 are key players in Parkinson's disease and related disorders, but their normal role has been confusing and controversial. Data from acute gene-editing based knockdown, followed by functional assays, will be presented.

Dimensionality reduction beyond neural subspaces

Over the past decade, neural representations have been studied from the lens of low-dimensional subspaces defined by the co-activation of neurons. However, this view has overlooked other forms of covarying structure in neural activity, including i) condition-specific high-dimensional neural sequences, and ii) representations that change over time due to learning or drift. In this talk, I will present a new framework that extends the classic view towards additional types of covariability that are not constrained to a fixed, low-dimensional subspace. In addition, I will present sliceTCA, a new tensor decomposition that captures and demixes these different types of covariability to reveal task-relevant structure in neural activity. Finally, I will close with some thoughts regarding the circuit mechanisms that could generate mixed covariability. Together this work points to a need to consider new possibilities for how neural populations encode sensory, cognitive, and behavioral variables beyond neural subspaces.

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.

Learning and Memory

This webinar on learning and memory features three experts—Nicolas Brunel, Ashok Litwin-Kumar, and Julijana Gjorgieva—who present theoretical and computational approaches to understanding how neural circuits acquire and store information across different scales. Brunel discusses calcium-based plasticity and how standard “Hebbian-like” plasticity rules inferred from in vitro or in vivo datasets constrain synaptic dynamics, aligning with classical observations (e.g., STDP) and explaining how synaptic connectivity shapes memory. Litwin-Kumar explores insights from the fruit fly connectome, emphasizing how the mushroom body—a key site for associative learning—implements a high-dimensional, random representation of sensory features. Convergent dopaminergic inputs gate plasticity, reflecting a high-dimensional “critic” that refines behavior. Feedback loops within the mushroom body further reveal sophisticated interactions between learning signals and action selection. Gjorgieva examines how activity-dependent plasticity rules shape circuitry from the subcellular (e.g., synaptic clustering on dendrites) to the cortical network level. She demonstrates how spontaneous activity during development, Hebbian competition, and inhibitory-excitatory balance collectively establish connectivity motifs responsible for key computations such as response normalization.

Feedback-induced dispositional changes in risk preferences

Contrary to the original normative decision-making standpoint, empirical studies have repeatedly reported that risk preferences are affected by the disclosure of choice outcomes (feedback). Although no consensus has yet emerged regarding the properties and mechanisms of this effect, a widespread and intuitive hypothesis is that repeated feedback affects risk preferences by means of a learning effect, which alters the representation of subjective probabilities. Here, we ran a series of seven experiments (N= 538), tailored to decipher the effects of feedback on risk preferences. Our results indicate that the presence of feedback consistently increases risk-taking, even when the risky option is economically less advantageous. Crucially, risk-taking increases just after the instructions, before participants experience any feedback. These results challenge the learning account, and advocate for a dispositional effect, induced by the mere anticipation of feedback information. Epistemic curiosity and regret avoidance may drive this effect in partial and complete feedback conditions, respectively.

Beyond Homogeneity: Characterizing Brain Disorder Heterogeneity through EEG and Normative Modeling

Electroencephalography (EEG) has been thoroughly studied for decades in psychiatry research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patient's heterogeneity, overlooked in psychiatric EEG research relying on a case-control approach. We combine HD-EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity- across a cohort of 1674 patients with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, and 560 matched controls. Normative models showed that deviations from population norms among patients were highly heterogeneous and frequency-dependent. Deviation spatial overlap across patients did not exceed 40% and 24% for spectral and connectivity, respectively. Considering individual deviations in patients has significantly enhanced comparative analysis, and the identification of patient-specific markers has demonstrated a correlation with clinical assessments, representing a crucial step towards attaining precision psychiatry through EEG.

Deepfake Detection in Super-Recognizers and Police Officers

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

Piecing together the puzzle of emotional consciousness

Conscious emotional experiences are very rich in their nature, and can encompass anything ranging from the most intense panic when facing immediate threat, to the overwhelming love felt when meeting your newborn. It is then no surprise that capturing all aspects of emotional consciousness, such as intensity, valence, and bodily responses, into one theory has become the topic of much debate. Key questions in the field concern how we can actually measure emotions and which type of experiments can help us distill the neural correlates of emotional consciousness. In this talk I will give a brief overview of theories of emotional consciousness and where they disagree, after which I will dive into the evidence proposed to support these theories. Along the way I will discuss to what extent studying emotional consciousness is ‘special’ and will suggest several tools and experimental contrasts we have at our disposal to further our understanding on this intriguing topic.

The role of sub-population structure in computations through neural dynamics

Neural computations are currently conceptualised using two separate approaches: sorting neurons into functional sub-populations or examining distributed collective dynamics. Whether and how these two aspects interact to shape computations is currently unclear. Using a novel approach to extract computational mechanisms from recurrent networks trained on neuroscience tasks, we show that the collective dynamics and sub-population structure play fundamentally complementary roles. Although various tasks can be implemented in networks with fully random population structure, we found that flexible input–output mappings instead require a non-random population structure that can be described in terms of multiple sub-populations. Our analyses revealed that such a sub-population organisation enables flexible computations through a mechanism based on gain-controlled modulations that flexibly shape the collective dynamics.

Microbial modulation of zebrafish behavior and brain development

There is growing recognition that host-associated microbiotas modulate intrinsic neurodevelopmental programs including those underlying human social behavior. Despite this awareness, the fundamental processes are generally not understood. We discovered that the zebrafish microbiota is necessary for normal social behavior. By examining neuronal correlates of behavior, we found that the microbiota restrains neurite complexity and targeting of key forebrain neurons within the social behavior circuitry. The microbiota is also necessary for both localization and molecular functions of forebrain microglia, brain-resident phagocytes that remodel neuronal arbors. In particular, the microbiota promotes expression of complement signaling pathway components important for synapse remodeling. Our work provides evidence that the microbiota modulates zebrafish social behavior by stimulating microglial remodeling of forebrain circuits during early neurodevelopment and suggests molecular pathways for therapeutic interventions during atypical neurodevelopment.

Off the rails - how pathological patterns of whole brain activity emerge in epileptic seizures

In most brains across the animal kingdom, brain dynamics can enter pathological states that are recognisable as epileptic seizures. Yet usually, brain operate within certain constraints given through neuronal function and synaptic coupling, that will prevent epileptic seizure dynamics from emerging. In this talk, I will bring together different approaches to identifying how networks in the broadest sense shape brain dynamics. Using illustrative examples from intracranial EEG recordings, disorders characterised by molecular disruption of a single neurotransmitter receptor type, to single-cell recordings of whole-brain activity in the larval zebrafish, I will address three key questions - (1) how does the regionally specific composition of synaptic receptors shape ongoing physiological brain activity; (2) how can disruption of this regionally specific balance result in abnormal brain dynamics; and (3) which cellular patterns underly the transition into an epileptic seizure.

Integration of 3D human stem cell models derived from post-mortem tissue and statistical genomics to guide schizophrenia therapeutic development

Schizophrenia is a neuropsychiatric disorder characterized by positive symptoms (such as hallucinations and delusions), negative symptoms (such as avolition and withdrawal) and cognitive dysfunction1. Schizophrenia is highly heritable, and genetic studies are playing a pivotal role in identifying potential biomarkers and causal disease mechanisms with the hope of informing new treatments. Genome-wide association studies (GWAS) identified nearly 270 loci with a high statistical association with schizophrenia risk; however each locus confers only a small increase in risk therefore it is difficult to translate these findings into understanding disease biology that can lead to treatments. Induced pluripotent stem cell (iPSC) models are a tractable system to translate genetic findings and interrogate mechanisms of pathogenesis. Mounting research with patient-derived iPSCs has proposed several neurodevelopmental pathways altered in SCZ, such as neural progenitor cell (NPC) proliferation, imbalanced differentiation of excitatory and inhibitory cortical neurons. However, it is unclear what exactly these iPS models recapitulate, how potential perturbations of early brain development translates into illness in adults and how iPS models that represent fetal stages can be utilized to further drug development efforts to treat adult illness. I will present the largest transcriptome analysis of post-mortem caudate nucleus in schizophrenia where we discovered that decreased presynaptic DRD2 autoregulation is the causal dopamine risk factor for schizophrenia (Benjamin et al, Nature Neuroscience 2022 https://doi.org/10.1038/s41593-022-01182-7). We developed stem cell models from a subset of the postmortem cohort to better understand the molecular underpinnings of human psychiatric disorders (Sawada et al, Stem Cell Research 2020). We established a method for the differentiation of iPS cells into ventral forebrain organoids and performed single cell RNAseq and cellular phenotyping. To our knowledge, this is the first study to evaluate iPSC models of SZ from the same individuals with postmortem tissue. Our study establishes that striatal neurons in the patients with SCZ carry abnormalities that originated during early brain development. Differentiation of inhibitory neurons is accelerated whereas excitatory neuronal development is delayed, implicating an excitation and inhibition (E-I) imbalance during early brain development in SCZ. We found a significant overlap of genes upregulated in the inhibitory neurons in SCZ organoids with upregulated genes in postmortem caudate tissues from patients with SCZ compared with control individuals, including the donors of our iPS cell cohort. Altogether, we demonstrate that ventral forebrain organoids derived from postmortem tissue of individuals with schizophrenia recapitulate perturbed striatal gene expression dynamics of the donors’ brains (Sawada et al, biorxiv 2022 https://doi.org/10.1101/2022.05.26.493589).

Neuron-glial interactions in health and disease: from cognition to cancer

In the central nervous system, neuronal activity is a critical regulator of development and plasticity. Activity-dependent proliferation of healthy glial progenitors, oligodendrocyte precursor cells (OPCs), and the consequent generation of new oligodendrocytes contributes to adaptive myelination. This plasticity of myelin tunes neural circuit function and contributes to healthy cognition. The robust mitogenic effect of neuronal activity on normal oligodendroglial precursor cells, a putative cellular origin for many forms of glioma, suggests that dysregulated or “hijacked” mechanisms of myelin plasticity might similarly promote malignant cell proliferation in this devastating group of brain cancers. Indeed, neuronal activity promotes progression of both high-grade and low-grade glioma subtypes in preclinical models. Crucial mechanisms mediating activity-regulated glioma growth include paracrine secretion of BDNF and the synaptic protein neuroligin-3 (NLGN3). NLGN3 induces multiple oncogenic signaling pathways in the cancer cell, and also promotes glutamatergic synapse formation between neurons and glioma cells. Glioma cells integrate into neural circuits synaptically through neuron-to-glioma synapses, and electrically through potassium-evoked currents that are amplified through gap-junctional coupling between tumor cells This synaptic and electrical integration of glioma into neural circuits is central to tumor progression in preclinical models. Thus, neuron-glial interactions not only modulate neural circuit structure and function in the healthy brain, but paracrine and synaptic neuron-glioma interactions also play important roles in the pathogenesis of glial cancers. The mechanistic parallels between normal and malignant neuron-glial interactions underscores the extent to which mechanisms of neurodevelopment and plasticity are subverted by malignant gliomas, and the importance of understanding the neuroscience of cancer.

AI for Multi-centre Epilepsy Lesion Detection on MRI

Epilepsy surgery is a safe but underutilised treatment for drug-resistant focal epilepsy. One challenge in the presurgical evaluation of patients with drug-resistant epilepsy are patients considered “MRI negative”, i.e. where a structural brain abnormality has not been identified on MRI. A major pathology in “MRI negative” patients is focal cortical dysplasia (FCD), where lesions are often small or subtle and easily missed by visual inspection. In recent years, there has been an explosion in artificial intelligence (AI) research in the field of healthcare. Automated FCD detection is an area where the application of AI may translate into significant improvements in the presurgical evaluation of patients with focal epilepsy. I will provide an overview of our automated FCD detection work, the Multicentre Epilepsy Lesion Detection (MELD) project and how AI algorithms are beginning to be integrated into epilepsy presurgical planning at Great Ormond Street Hospital and elsewhere around the world. Finally, I will discuss the challenges and future work required to bring AI to the forefront of care for patients with epilepsy.

Myelin Formation and Oligodendrocyte Biology in Epilepsy

Epilepsy is one of the most common neurological diseases according to the World Health Organization (WHO) affecting around 70 million people worldwide [WHO]. Patients who suffer from epilepsy also suffer from a variety of neuro-psychiatric co-morbidities, which they can experience as crippling as the seizure condition itself. Adequate organization of cerebral white matter is utterly important for cognitive development. The failure of integration of neurologic function with cognition is reflected in neuro-psychiatric disease, such as autism spectrum disorder (ASD). However, in epilepsy we know little about the importance of white matter abnormalities in epilepsy-associated co-morbidities. Epilepsy surgery is an important therapy strategy in patients where conventional anti-epileptic drug treatment fails . On histology of the resected brain samples, malformations of cortical development (MCD) are common among the epilepsy surgery population, especially focal cortical dysplasia (FCD) and tuberous sclerosis complex (TSC). Both pathologies are associated with constitutive activation of the mTOR pathway. Interestingly, some type of FCD is morphological similar to TSC cortical tubers including the abnormalities of the white matter. Hypomyelination with lack of myelin-producing cells, the oligodendrocytes, within the lesional area is a striking phenomenon. Impairment of the complex myelination process can have a major impact on brain function. In the worst case leading to distorted or interrupted neurotransmissions. It is still unclear whether the observed myelin pathology in epilepsy surgical specimens is primarily related to the underlying malformation process or is just a secondary phenomenon of recurrent epileptic seizures creating a toxic micro-environment which hampers myelin formation. Interestingly, mTORC1 has been implicated as key signal for myelination, thus, promoting the maturation of oligodendrocytes . These results, however, remain controversial. Regardless of the underlying pathophysiologic mechanism, alterations of myelin dynamics, depending on their severity, are known to be linked to various kinds of developmental disorders or neuropsychiatric manifestations.

Brain mosaicism in epileptogenic cortical malformations

Focal Cortical Dysplasia (FCD) is the most common focal cortical malformation leading to intractable childhood focal epilepsy. In recent years, we and others have shown that FCD type II is caused by mosaic mutations in genes within the PI3K-AKT-mTOR-signaling pathway. Hyperactivation of the mTOR pathway accounts for neuropathological abnormalities and seizure occurrence in FCD. We further showed from human surgical FCDII tissue that epileptiform activity correlates with the density of mutated dysmorphic neurons, supporting their pro-epileptogenic role. The level of mosaicism, as defined by variant allele frequency (VAF) is thought to correlate with the size and regional brain distribution of the lesion such that when a somatic mutation occurs early during the cortical development, the dysplastic area is smaller than if it occurs later. Novel approaches based on the detection of cell-free DNA from the CSF and from trace tissue adherent to SEEG electrodes promise future opportunities for genetic testing during the presurgical evaluation of refractory epilepsy patients or in those that are not eligible for surgery. In utero-based electroporation mouse models allow to express somatic mutation during neurodevelopment and recapitulate most neuropathological and clinical features of FCDII, establishing relevant preclinical mouse models for developing precision medicine strategies.

Programmed axon death: from animal models into human disease

Programmed axon death is a widespread and completely preventable mechanism in injury and disease. Mouse and Drosophila studies define a molecular pathway involving activation of SARM1 NA Dase and its prevention by NAD synthesising enzyme NMNAT2 . Loss of axonal NMNAT2 causes its substrate, NMN , to accumulate and activate SARM1 , driving loss of NAD and changes in ATP , ROS and calcium. Animal models caused by genetic mutation, toxins, viruses or metabolic defects can be alleviated by blocking programmed axon death, for example models of CMT1B , chemotherapy-induced peripheral neuropathy (CIPN), rabies and diabetic peripheral neuropathy (DPN). The perinatal lethality of NMNAT2 null mice is completely rescued, restoring a normal, healthy lifespan. Animal models lack the genetic and environmental diversity present in human populations and this is problematic for modelling gene-environment combinations, for example in CIPN and DPN , and identifying rare, pathogenic mutations. Instead, by testing human gene variants in WGS datasets for loss- and gain-of-function, we identified enrichment of rare SARM1 gain-of-function variants in sporadic ALS , despite previous negative findings in SOD1 transgenic mice. We have shown in mice that heterozygous SARM1 loss-of-function is protective from a range of axonal stresses and that naturally-occurring SARM1 loss-of-function alleles are present in human populations. This enables new approaches to identify disorders where blocking SARM1 may be therapeutically useful, and the existence of two dominant negative human variants in healthy adults is some of the best evidence available that drugs blocking SARM1 are likely to be safe. Further loss- and gain-of-function variants in SARM1 and NMNAT2 are being identified and used to extend and strengthen the evidence of association with neurological disorders. We aim to identify diseases, and specific patients, in whom SARM1 -blocking drugs are most likely to be effective.

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.

Extracting computational mechanisms from neural data using low-rank RNNs

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

Searching for the algorithms of iterative motor learning involving the cerebellum

Flexible selection of task-relevant features through population gating

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

Myelin Formation and Oligodendrocyte Biology in Epilepsy

Epilepsy is one of the most common neurological diseases according to the World Health Organization (WHO) affecting around 70 million people worldwide [WHO]. Patients who suffer from epilepsy also suffer from a variety of neuro-psychiatric co-morbidities, which they can experience as crippling as the seizure condition itself. Adequate organization of cerebral white matter is utterly important for cognitive development. The failure of integration of neurologic function with cognition is reflected in neuro-psychiatric disease, such as autism spectrum disorder (ASD). However, in epilepsy we know little about the importance of white matter abnormalities in epilepsy-associated co-morbidities. Epilepsy surgery is an important therapy strategy in patients where conventional anti-epileptic drug treatment fails . On histology of the resected brain samples, malformations of cortical development (MCD) are common among the epilepsy surgery population, especially focal cortical dysplasia (FCD) and tuberous sclerosis complex (TSC). Both pathologies are associated with constitutive activation of the mTOR pathway. Interestingly, some type of FCD is morphological similar to TSC cortical tubers including the abnormalities of the white matter. Hypomyelination with lack of myelin-producing cells, the oligodendrocytes, within the lesional area is a striking phenomenon. Impairment of the complex myelination process can have a major impact on brain function. In the worst case leading to distorted or interrupted neurotransmissions. It is still unclear whether the observed myelin pathology in epilepsy surgical specimens is primarily related to the underlying malformation process or is just a secondary phenomenon of recurrent epileptic seizures creating a toxic micro-environment which hampers myelin formation. Interestingly, mTORC1 has been implicated as key signal for myelination, thus, promoting the maturation of oligodendrocytes . These results, however, remain controversial. Regardless of the underlying pathophysiologic mechanism, alterations of myelin dynamics, depending on their severity, are known to be linked to various kinds of developmental disorders or neuropsychiatric manifestations.

Hidden nature of seizures

How seizures emerge from the abnormal dynamics of neural networks within the epileptogenic tissue remains an enigma. Are seizures random events, or do detectable changes in brain dynamics precede them? Are mechanisms of seizure emergence identical at the onset and later stages of epilepsy? Is the risk of seizure occurrence stable, or does it change over time? A myriad of questions about seizure genesis remains to be answered to understand the core principles governing seizure genesis. The last decade has brought unprecedented insights into the complex nature of seizure emergence. It is now believed that seizure onset represents the product of the interactions between the process of a transition to seizure, long-term fluctuations in seizure susceptibility, epileptogenesis, and disease progression. During the lecture, we will review the latest observations about mechanisms of ictogenesis operating at multiple temporal scales. We will show how the latest observations contribute to the formation of a comprehensive theory of seizure genesis, and challenge the traditional perspectives on ictogenesis. Finally, we will discuss how combining conventional approaches with computational modeling, modern techniques of in vivo imaging, and genetic manipulation open prospects for exploration of yet hidden mechanisms of seizure genesis.

Development and evolution of neuronal connectivity

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

Redox and mitochondrial dysregulation in epilepsy

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

Epigenome regulation in neocortex expansion and generation of neuronal subtypes

Evolutionarily, the expansion of the human neocortex accounts for many of the unique cognitive abilities of humans. This expansion appears to reflect the increased proliferative potential of basal progenitors (BPs) in mammalian evolution. Further cortical progenitors generate both glutamatergic excitatory neurons (ENs) and GABAergic inhibitory interneurons (INs) in human cortex, whereas they produce exclusively ENs in rodents. The increased proliferative capacity and neuronal subtype generation of cortical progenitors in mammalian evolution may have evolved through epigenetic alterations. However, whether or how the epigenome in cortical progenitors differs between humans and other species is unknown. Here, we report that histone H3 acetylation is a key epigenetic regulation in BP profiling of sorted BPs, we show that H3K9 acetylation is low in murine BPs and high in amplification, neuronal subtype generation and cortical expansion. Through epigenetic profiling of sorted BPs, we show that H3K9 acetylation is low in murine BPs and high in human BPs. Elevated H3K9ac preferentially increases BP proliferation, increasing the size and folding of the normally smooth mouse neocortex. Furthermore, we found that the elevated H3 acetylation activates expression of IN genes in in developing mouse cortex and promote proliferation of IN progenitor-like cells in cortex of Pax6 mutant mouse models. Mechanistically, H3K9ac drives the BP amplification and proliferation of these IN progenitor-like cells by increasing expression of the evolutionarily regulated gene, TRNP1. Our findings demonstrate a previously unknown mechanism that controls neocortex expansion and generation of neuronal subtypes. Keywords: Cortical development, neurogenesis, basal progenitors, cortical size, gyrification, excitatory neuron, inhibitory interneuron, epigenetic profiling, epigenetic regulation, H3 acetylation, H3K9ac, TRNP1, PAX6

Binocular combination of light

The brain combines signals across the eyes. This process is well-characterized for the perceptual anatomical pathway through V1 that primarily codes contrast, where interocular normalization ensures that responses are approximately equal for monocular and binocular stimulation. But we have much less understanding of how luminance is combined binocularly, both in the cortex and in subcortical structures that govern pupil diameter. Here I will describe the results of experiments using a novel combined EEG and pupillometry paradigm to simultaneously index binocular combination of luminance flicker in parallel pathways. The results show evidence of a more linear process than for spatial contrast, that may reflect different operational constraints in distinct anatomical pathways.

The glymphatic system in motor neurone disease

Neurodegenerative diseases are chronic and inexorable conditions characterised by the presence of insoluble aggregates of abnormally ubiquinated and phosphorylated proteins. Recent evidence also suggests that protein misfolding can propagate throughout the body in a prion-like fashion via the interstitial or cerebrospinal fluids (CSF). As protein aggregation occurs well before the onset of brain damage and symptoms, new biomarkers sensitive to early pathology, together with therapeutic strategies that include eliminating seed proteins and blocking cell-to-cell spread, are of vital importance. The glymphatic system, which facilitates the continuous exchange of CSF and interstitial fluid to clear the brain of waste, presents as a potential biomarker of disease severity, therapeutic target, and drug delivery system. In this webinar, Associate Professor David Wright from the Department of Neuroscience, Monash University, will outline recent advances in using MRI to investigate the glymphatic system. He will also present some of his lab’s recent work investigating glymphatic clearance in preclinical models of motor neurone disease. Associate Professor David Wright is an NHMRC Emerging Leadership Fellow and the Director of Preclinical Imaging in the Department of Neuroscience, Monash University and the Alfred Research Alliance, Alfred Health. His research encompasses the development, application and analysis of advanced magnetic resonance imaging techniques for the study of disease, with a particular emphasis on neurodegenerative disorders. Although less than three years post PhD, he has published over 60 peer-reviewed journal articles in leading neuroscience journals such as Nature Medicine, Brain, and Cerebral Cortex.

Don't forget the gametes: Neurodevelopmental pathogenesis starts in the sperm and egg

Proper development of the nervous system depends not only on the inherited DNA sequence, but also on proper regulation of gene expression, as controlled in part by epigenetic mechanisms present in the parental gametes. In this presentation an internationally recognized research advocate explains why researchers concerned about the origins of increasingly prevalent neurodevelopmental disorders such as autism and attention deficit hyperactivity disorder should look beyond genetics in probing the origins of dysregulated transcription of brain-related genes. The culprit for a subset of cases, she contends, may lie in the exposure history of the parents, and thus their germ cells. To illustrate how environmentally informed, nongenetic dysfunction may occur, she focuses on the example of parents' histories of exposure to common agents of modern inhalational anesthesia, a highly toxic exposure that in mammalian models has been seen to induce heritable neurodevelopmental abnormality in offspring born of exposed germline.

From Computation to Large-scale Neural Circuitry in Human Belief Updating

Many decisions under uncertainty entail dynamic belief updating: multiple pieces of evidence informing about the state of the environment are accumulated across time to infer the environmental state, and choose a corresponding action. Traditionally, this process has been conceptualized as a linear and perfect (i.e., without loss) integration of sensory information along purely feedforward sensory-motor pathways. Yet, natural environments can undergo hidden changes in their state, which requires a non-linear accumulation of decision evidence that strikes a tradeoff between stability and flexibility in response to change. How this adaptive computation is implemented in the brain has remained unknown. In this talk, I will present an approach that my laboratory has developed to identify evidence accumulation signatures in human behavior and neural population activity (measured with magnetoencephalography, MEG), across a large number of cortical areas. Applying this approach to data recorded during visual evidence accumulation tasks with change-points, we find that behavior and neural activity in frontal and parietal regions involved in motor planning exhibit hallmarks signatures of adaptive evidence accumulation. The same signatures of adaptive behavior and neural activity emerge naturally from simulations of a biophysically detailed model of a recurrent cortical microcircuit. The MEG data further show that decision dynamics in parietal and frontal cortex are mirrored by a selective modulation of the state of early visual cortex. This state modulation is (i) specifically expressed in the alpha frequency-band, (ii) consistent with feedback of evolving belief states from frontal cortex, (iii) dependent on the environmental volatility, and (iv) amplified by pupil-linked arousal responses during evidence accumulation. Together, our findings link normative decision computations to recurrent cortical circuit dynamics and highlight the adaptive nature of decision-related long-range feedback processing in the brain.

Optimal information loading into working memory in prefrontal cortex

Working memory involves the short-term maintenance of information and is critical in many tasks. The neural circuit dynamics underlying working memory remain poorly understood, with different aspects of prefrontal cortical (PFC) responses explained by different putative mechanisms. By mathematical analysis, numerical simulations, and using recordings from monkey PFC, we investigate a critical but hitherto ignored aspect of working memory dynamics: information loading. We find that, contrary to common assumptions, optimal information loading involves inputs that are largely orthogonal, rather than similar, to the persistent activities observed during memory maintenance. Using a novel, theoretically principled metric, we show that PFC exhibits the hallmarks of optimal information loading and we find that such dynamics emerge naturally as a dynamical strategy in task-optimized recurrent neural networks. Our theory unifies previous, seemingly conflicting theories of memory maintenance based on attractor or purely sequential dynamics, and reveals a normative principle underlying the widely observed phenomenon of dynamic coding in PFC.

On biological and cognitive autonomy

In this talk I will introduce the central notions of the theory of autonomy, as it is being currently developed in biology and cognitive science. The theory of autonomy puts forward the capacity of self-determination of organisms as whole systems, and constitutes thereby an alternative to more reductionist and mechanistic approaches. I will discuss how the theory of autonomy provides a justification for the scientific use of notions as function, norm, agency and teleology, whose epistemological legitimacy is highly debated. I will conclude by describing the difficult challenges that poses the transition from biological to cognitive autonomy.

The Standard Model of the Retina

The science of the retina has reached an interesting stage of completion. There exists now a consensus standard model of this neural system - at least in the minds of many researchers - that serves as a baseline against which to evaluate new claims. The standard model links phenomena from molecular biophysics, cell biology, neuroanatomy, synaptic physiology, circuit function, and visual psychophysics. It is further supported by a normative theory explaining what the purpose is of processing visual information this way. Most new reports of retinal phenomena fit squarely within the standard model, and major revisions seem increasingly unlikely. Given that our understanding of other brain circuits with comparable complexity is much more rudimentary, it is worth considering an example of what success looks like. In this talk I will summarize what I think are the ingredients that led to this mature understanding of the retina. Equally important, a number of practices and concepts that are currently en vogue in neuroscience were not needed or indeed counterproductive. I look forward to debating how these lessons might extend to other areas of brain research.

Malignant synaptic plasticity in pediatric high-grade gliomas

Pediatric high-grade gliomas (pHGG) are a devastating group of diseases that urgently require novel therapeutic options. We have previously demonstrated that pHGGs directly synapse onto neurons and the subsequent tumor cell depolarization, mediated by calcium-permeable AMPA channels, promotes their proliferation. The regulatory mechanisms governing these postsynaptic connections are unknown. Here, we investigated the role of BDNF-TrkB signaling in modulating the plasticity of the malignant synapse. BDNF ligand activation of its canonical receptor, TrkB (which is encoded for by the gene NTRK2), has been shown to be one important modulator of synaptic regulation in the normal setting. Electrophysiological recordings of glioma cell membrane properties, in response to acute neurotransmitter stimulation, demonstrate in an inward current resembling AMPA receptor (AMPAR) mediated excitatory neurotransmission. Extracellular BDNF increases the amplitude of this glutamate-induced tumor cell depolarization and this effect is abrogated in NTRK2 knockout glioma cells. Upon examining tumor cell excitability using in situ calcium imaging, we found that BDNF increases the intensity of glutamate-evoked calcium transients in GCaMP6s expressing glioma cells. Western blot analysis indicates the tumors AMPAR properties are altered downstream of BDNF induced TrkB activation in glioma. Cell membrane protein capture (via biotinylation) and live imaging of pH sensitive GFP-tagged AMPAR subunits demonstrate an increase of calcium permeable channels at the tumors postsynaptic membrane in response to BDNF. We find that BDNF-TrkB signaling promotes neuron-to-glioma synaptogenesis as measured by high-resolution confocal and electron microscopy in culture and tumor xenografts. Our analysis of published pHGG transcriptomic datasets, together with brain slice conditioned medium experiments in culture, indicates the tumor microenvironment as the chief source of BDNF ligand. Disruption of the BDNF-TrkB pathway in patient-derived orthotopic glioma xenograft models, both genetically and pharmacologically, results in an increased overall survival and reduced tumor proliferation rate. These findings suggest that gliomas leverage normal mechanisms of plasticity to modulate the excitatory channels involved in synaptic neurotransmission and they reveal the potential to target the regulatory components of glioma circuit dynamics as a therapeutic strategy for these lethal cancers.

Dissecting subcircuits underlying hippocampal function

Liset M de la Prida is a Physicist (1994) and PhD in Neuroscience (1998), who leads the Laboratorio de Circuitos Neuronales at the Instituto Cajal, Madrid, Spain (http://www.hippo-circuitlab.es). The main focus of her lab is to understand the function of the hippocampal circuits in the normal and the diseased brain, in particular oscillations and neuronal representations. She is a leading international expert in the study of the basic mechanisms of physiological ripples and epileptic fast ripples, with strong visibility as developer of novel groundbreaking electrophysiological tools. Dr. de la Prida serves as an Editor for prestigious journals including eLife, Journal of Neuroscience Methods and eNeuro, and has commissioning duties in the American Epilepsy Society, FENS and the Spanish Society for Neurosciences.

The Synaptome Architecture of the Brain: Lifespan, disease, evolution and behavior

The overall aim of my research is to understand how the organisation of the synapse, with particular reference to the postsynaptic proteome (PSP) of excitatory synapses in the brain, informs the fundamental mechanisms of learning, memory and behaviour and how these mechanisms go awry in neurological dysfunction. The PSP indeed bears a remarkable burden of disease, with components being disrupted in disorders (synaptopathies) including schizophrenia, depression, autism and intellectual disability. Our work has been fundamental in revealing and then characterising the unprecedented complexity (>1000 highly conserved proteins) of the PSP in terms of the subsynaptic architecture of postsynaptic proteins such as PSD95 and how these proteins assemble into complexes and supercomplexes in different neurons and regions of the brain. Characterising the PSPs in multiple species, including human and mouse, has revealed differences in key sets of functionally important proteins, correlates with brain imaging and connectome data, and a differential distribution of disease-relevant proteins and pathways. Such studies have also provided important insight into synapse evolution, establishing that vertebrate behavioural complexity is a product of the evolutionary expansion in synapse proteomes that occurred ~500 million years ago. My lab has identified many mutations causing cognitive impairments in mice before they were found to cause human disorders. Our proteomic studies revealed that >130 brain diseases are caused by mutations affecting postsynaptic proteins. We uncovered mechanisms that explain the polygenic basis and age of onset of schizophrenia, with postsynaptic proteins, including PSD95 supercomplexes, carrying much of the polygenic burden. We discovered the “Genetic Lifespan Calendar”, a genomic programme controlling when genes are regulated. We showed that this could explain how schizophrenia susceptibility genes are timed to exert their effects in young adults. The Genes to Cognition programme is the largest genetic study so far undertaken into the synaptic molecular mechanisms underlying behaviour and physiology. We made important conceptual advances that inform how the repertoire of both innate and learned behaviours is built from unique combinations of postsynaptic proteins that either amplify or attenuate the behavioural response. This constitutes a key advance in understanding how the brain decodes information inherent in patterns of nerve impulses, and provides insight into why the PSP has evolved to be so complex, and consequently why the phenotypes of synaptopathies are so diverse. Our most recent work has opened a new phase, and scale, in understanding synapses with the first synaptome maps of the brain. We have developed next-generation methods (SYNMAP) that enable single-synapse resolution molecular mapping across the whole mouse brain and extensive regions of the human brain, revealing the molecular and morphological features of a billion synapses. This has already uncovered unprecedented spatiotemporal synapse diversity organised into an architecture that correlates with the structural and functional connectomes, and shown how mutations that cause cognitive disorders reorganise these synaptome maps; for example, by detecting vulnerable synapse subtypes and synapse loss in Alzheimer’s disease. This innovative synaptome mapping technology has huge potential to help characterise how the brain changes during normal development, including in specific cell types, and with degeneration, facilitating novel pathways to diagnosis and therapy.

The balance of excitation and inhibition and a canonical cortical computation

Excitatory and inhibitory (E & I) inputs to cortical neurons remain balanced across different conditions. The balanced network model provides a self-consistent account of this observation: population rates dynamically adjust to yield a state in which all neurons are active at biological levels, with their E & I inputs tightly balanced. But global tight E/I balance predicts population responses with linear stimulus-dependence and does not account for systematic cortical response nonlinearities such as divisive normalization, a canonical brain computation. However, when necessary connectivity conditions for global balance fail, states arise in which only a localized subset of neurons are active and have balanced inputs. We analytically show that in networks of neurons with different stimulus selectivities, the emergence of such localized balance states robustly leads to normalization, including sublinear integration and winner-take-all behavior. An alternative model that exhibits normalization is the Stabilized Supralinear Network (SSN), which predicts a regime of loose, rather than tight, E/I balance. However, an understanding of the causal relationship between E/I balance and normalization in SSN and conditions under which SSN yields significant sublinear integration are lacking. For weak inputs, SSN integrates inputs supralinearly, while for very strong inputs it approaches a regime of tight balance. We show that when this latter regime is globally balanced, SSN cannot exhibit strong normalization for any input strength; thus, in SSN too, significant normalization requires localized balance. In summary, we causally and quantitatively connect a fundamental feature of cortical dynamics with a canonical brain computation. Time allowing I will also cover our work extending a normative theoretical account of normalization which explains it as an example of efficient coding of natural stimuli. We show that when biological noise is accounted for, this theory makes the same prediction as the SSN: a transition to supralinear integration for weak stimuli.

Spatial uncertainty provides a unifying account of navigation behavior and grid field deformations

To localize ourselves in an environment for spatial navigation, we rely on vision and self-motion inputs, which only provide noisy and partial information. It is unknown how the resulting uncertainty affects navigation behavior and neural representations. Here we show that spatial uncertainty underlies key effects of environmental geometry on navigation behavior and grid field deformations. We develop an ideal observer model, which continually updates probabilistic beliefs about its allocentric location by optimally combining noisy egocentric visual and self-motion inputs via Bayesian filtering. This model directly yields predictions for navigation behavior and also predicts neural responses under population coding of location uncertainty. We simulate this model numerically under manipulations of a major source of uncertainty, environmental geometry, and support our simulations by analytic derivations for its most salient qualitative features. We show that our model correctly predicts a wide range of experimentally observed effects of the environmental geometry and its change on homing response distribution and grid field deformation. Thus, our model provides a unifying, normative account for the dependence of homing behavior and grid fields on environmental geometry, and identifies the unavoidable uncertainty in navigation as a key factor underlying these diverse phenomena.

Epileptogenesis in the developing brain:understanding a moving target

The origins, mechanisms and consequences of epilepsy in the developing brain are incompletely understood. Many developmental epilepsies have a genetic basis and their mechanisms stem from deficits in the function of one or numerous genes. Others, such as those that follow prolonged febrile seizures or severe birth asphyxia in a ‘normal’ brain may depend on the interaction of the insult with the rapidly evolving brain cells and circuits. Yet, how early-life insults may provoke epilepsy is unclear, and requires multiple levels of analysis: behavior, circuits, cells [neurons, glia] and molecules. Here we discuss developmental epileptogenesis, addressing some of its special features: the epilepsy phenotype, the effects insults on the maturation of brain circuits, the role of neuron-glia-neuron communication in cellular and circuit refinement, and how transient epileptogenic insults provoke enduring changes in the structure, connectivity and function of salient neuronal populations. We will highlight resolved questions- and the many unresolved issues that require tackling in 2022 and beyond.

An executive control approach to language production

Language production is a form of behavior and as such involves executive control and the prefrontal function. The cognitive architecture of prefrontal executive function thus certainly plays an important role in shaping language production. In this talk, I will review the main features of the prefrontal executive function we have uncovered during the last two decades and I will discuss how these features may help understanding language production.

Probabilistic computation in natural vision

A central goal of vision science is to understand the principles underlying the perception and neural coding of the complex visual environment of our everyday experience. In the visual cortex, foundational work with artificial stimuli, and more recent work combining natural images and deep convolutional neural networks, have revealed much about the tuning of cortical neurons to specific image features. However, a major limitation of this existing work is its focus on single-neuron response strength to isolated images. First, during natural vision, the inputs to cortical neurons are not isolated but rather embedded in a rich spatial and temporal context. Second, the full structure of population activity—including the substantial trial-to-trial variability that is shared among neurons—determines encoded information and, ultimately, perception. In the first part of this talk, I will argue for a normative approach to study encoding of natural images in primary visual cortex (V1), which combines a detailed understanding of the sensory inputs with a theory of how those inputs should be represented. Specifically, we hypothesize that V1 response structure serves to approximate a probabilistic representation optimized to the statistics of natural visual inputs, and that contextual modulation is an integral aspect of achieving this goal. I will present a concrete computational framework that instantiates this hypothesis, and data recorded using multielectrode arrays in macaque V1 to test its predictions. In the second part, I will discuss how we are leveraging this framework to develop deep probabilistic algorithms for natural image and video segmentation.

Dissecting the neural processes supporting perceptual learning

The brain and its inherent functions can be modified by various forms of learning. Learning-induced changes are seen even in basic perceptual functions. In particular, repeated training in a perceptual task can lead to a significant improvement in the trained task—a phenomenon known as perceptual learning. There has been a long-standing debate about the mechanisms of perceptual learning. In this talk, I will present results from our series of electrophysiological studies. These studies have consistently shown that perceptual learning is mediated by concerted changes in both perceptual and cognitive processes, resulting in improved sensory representation, enhanced top-down influences, and refined readout process.

Mutation targeted gene therapy approaches to alter rod degeneration and retain cones

My research uses electrophysiological techniques to evaluate normal retinal function, dysfunction caused by blinding retinal diseases and the restoration of function using a variety of therapeutic strategies. We can use our understanding or normal retinal function and disease-related changes to construct optimal therapeutic strategies and evaluate how they ameliorate the effects of disease. Retinitis pigmentosa (RP) is a family of blinding eye diseases caused by photoreceptor degeneration. The absence of the cells that for this primary signal leads to blindness. My interest in RP involves the evaluation of therapies to restore vision: replacing degenerated photoreceptors either with: (1) new stem or other embryonic cells, manipulated to become photoreceptors or (2) prosthetics devices that replace the photoreceptor signal with an electronic signal to light. Glaucoma is caused by increased intraocular pressure and leads to ganglion cell death, which eliminates the link between the retinal output and central visual processing. We are parsing out of the effects of increased intraocular pressure and aging on ganglion cells. Congenital Stationary Night Blindness (CSNB) is a family of diseases in which signaling is eliminated between rod photoreceptors and their postsynaptic targets, rod bipolar cells. This deafferents the retinal circuit that is responsible for vision under dim lighting. My interest in CSNB involves understanding the basic interplay between excitation and inhibition in the retinal circuit and its normal development. Because of the targeted nature of this disease, we are hopeful that a gene therapy approach can be developed to restore night vision. My work utilizes rodent disease models whose mutations mimic those found in human patients. While molecular manipulation of rodents is a fairly common approach, we have recently developed a mutant NIH miniature swine model of a common form of autosomal dominant RP (Pro23His rhodopsin mutation) in collaboration with the National Swine Resource Research Center at University of Missouri. More genetically modified mini-swine models are in the pipeline to examine other retinal diseases.

Mapping Individual Trajectories of Structural and Cognitive Decline in Mild Cognitive Impairment

The US has an aging population. For the first time in US history, the number of older adults is projected to outnumber that of children by 2034. This combined with the fact that the prevalence of Alzheimer's Disease increases exponentially with age makes for a worrying combination. Mild cognitive impairment (MCI) is an intermediate stage of cognitive decline between being cognitively normal and having full-blown Dementia, with every third person with MCI progressing to dementia of the Alzheimer's Type (DAT). While there is no known way to reverse symptoms once they begin, early prediction of disease can help stall its progression and help with early financial planning. While grey matter volume loss in the Hippocampus and Entorhinal Cortex (EC) are characteristic biomarkers of DAT, little is known about the rates of decrease of these volumes within individuals in MCI state across time. We used longitudinal growth curve models to map individual trajectories of volume loss in subjects with MCI. We then looked at whether these rates of volume decrease could predict progression to DAT right in the MCI stage. Finally, we evaluated whether these rates of Hippocampal and EC volume loss were correlated with individual rates of decline of episodic memory, visuospatial ability, and executive function.

Neuronal plasticity and neurotrophin signaling as the common mechanism for antidepressant effect

Neuronal plasticity has for a long time been considered important for the recovery from depression and for the antidepressant drug action, but how the drug action is translated to plasticity has remained unclear. Brain-derived neurotrophic factor (BDNF) and its receptor TRKB are critical regulators of neuronal plasticity and have been implicated in the antidepressant action. We have recently found that many, if not all, different antidepressants, including serotonin selective SSRIs, tricyclic as well as fast-acting ketamine, directly bind to TRKB, thereby promoting TRKB translocation to synaptic membranes, which increases BDNF signaling. We have previously shown that antidepressant treatment induces a juvenile-like state of activity in the cortex that facilitates beneficial rewiring of abnormal networks. We recently showed that activation of TRKB receptors in parvalbumin-containing interneurons orchestrates cortical activation states and is both necessary and sufficient for the antidepressantinduced cortical plasticity. Our findings open a new framework how the action of antidepressants act: rather than regulating brain monoamine concentrations, antidepressants directly bind to TRKB and allosterically promote BDNF signaling, thereby inducing a state of plasticity that allows re-wiring of abnormal networks for better functionality.

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

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

INTEGRATING GENETICS, PROTEOMICS, AND <EM>IN VITRO</EM> MODELING TO ELUCIDATE <EM>SLCO1A2</EM>-MEDIATED CEREBROSPINAL FLUID CLEARANCE IN IDIOPATHIC NORMAL PRESSURE HYDROCEPHALUS

FENS Forum 2026

THE CEREBROSPINAL FLUID AND PLASMA PROTEOMICS OF IDIOPATHIC NORMAL PRESSURE HYDROCEPHALUS

FENS Forum 2026

Inhibition-controlled Hebbian learning unifies phenomenological and normative models of plasticity

Bernstein Conference 2024

Localized balance of excitation and inhibition leads to normalization

COSYNE 2022

Localized balance of excitation and inhibition leads to normalization

COSYNE 2022

Normative models of spatio-spectral decorrelation in natural scenes predict experimentally observed ratio of PR types

COSYNE 2022

Normative Network Regularization for Neural System Identification

COSYNE 2022

Large scale neural dynamics that govern normal and disrupted breathing

COSYNE 2023

Normative Network Regularization for Neural System Identification

COSYNE 2022

Relating Divisive Normalization to Modulation of Correlated Variability in Primary Visual Cortex

COSYNE 2022

Relating Divisive Normalization to Modulation of Correlated Variability in Primary Visual Cortex

COSYNE 2022

Divisive normalization as a mechanism for hierarchical causal inference in motion perception

COSYNE 2023

Fitting normative neural sampling hypothesis models to neuronal response data

COSYNE 2023

Heterogeneity in normalization and attentional modulation in a circuit model

COSYNE 2023

Characterization of human Tau protein in yeast cells under normal and stress conditions

Cerebellar stimulation prevents Levodopa-induced dyskinesia in mice and normalizes brain activity in a wide motor network

Learning a divisive normalization model with a denoising objective

COSYNE 2023

A normative framework for balancing reward- and information-seeking behaviors in dynamic environments

COSYNE 2023

Normative modeling of auditory memory for natural sounds

COSYNE 2023

A normative theory of aggression

COSYNE 2023

Aeon: an open -source platform for testing normative models of natural behaviours and their neural implementations

COSYNE 2025

Computational benefits of normalization in a circuit model

COSYNE 2025

Divisive normalization underlying efficient inference in a deep generative model account of V1

COSYNE 2025

Abnormal changes in hippocampal synaptic plasticity are accompanied by parvalbumin reductions in the TgF344 rat model for Alzheimer’s disease

Abnormal functional connectivity in tectal circuit impairs decoding and behavior in mepc2 mutant zebrafish

Abnormal interneuron network configuration in a model of fragile X associated neuropsychiatric disorders

Abnormal patterns of sleep and waking behaviors are accompanied by increased slow gamma power in an Ank3 mouse model of epilepsy-mood disorder comorbidity

Area-specific abnormal development of cortical circuit in a 22q11 deletion mouse model

Behavioural abnormalities in DMSXL mice, a model of Myotonic Dystrophy type 1

Cell-type-specific profiling of microRNAs during epileptogenesis: Insights into neurons and microglia microRNA profiles in normal brain function and disease

Information correlations reduce the accuracy of pioneering normative decision makers

COSYNE 2023

Normative models of spatio-spectral decorrelation in natural scenes predict experimentally observed ratio of PR types

COSYNE 2022

The computational rules of value normalization in human reinforcement learning

The effect of altered normobaric oxygen manipulation on TMS induced corticospinal excitability

Electrophysiological fingerprinting of the abnormal brain cavity

Fear extinction impairments and sleep abnormalities in rats selected for blunted glucocorticoid responsiveness

Functional recovery caused by human adipose tissue mesenchymal stem cell-derived extracellular vesicles administered 24h after stroke in normotensive rats and some differences to hypertensive rats

FUSDelta14 mutation impairs normal neuronal development and causes systemic lipid metabolic alterations

Increased PKCgamma kinase activity causes abnormal Purkinje cell maturation and cerebellar ataxia

Divisive normalization shapes evidence accumulation during dynamic decision-making

COSYNE 2022