interest

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.

Pilot and Feasibility Program

PILOT AND FEASIBILITY PROGRAM: PROJECT SUMMARY The goal of the Cedars-Sinai Digestive Diseases Research Center (CSDDRC) Pilot and Feasibility (P&F) Program is to provide monetary support, expertise, and technical support to advance innovative basic, translational, and clinical research that matches the overall goal and themes of the Center. The central theme of the CSDDRC is mechanisms and measurements of the fibroinflammatory response in gastrointestinal (GI) tissues, which reflects Center members’ research in three subthemes: 1) Gut Microbiome, 2) Gastrointestinal (GI) and Liver Metabolism, and 3) GI and Liver Injury. The mission of CSDDRC P&F Program is to support new investigators, established investigators who are new to digestive and liver disease research, and established digestive and liver disease investigators who want to start new or collaborative research that promises to lead to a paradigm shift in the digestive diseases field. In partnership with the Enrichment Program, we will provide guidance for P&F awardees in the form of mentorship and collaboration opportunities. The CSDDRC Biomedical Research Cores will also support P&F awardees, facilitating rapid progress of their new and collaborative digestive and liver disease research. The P&F Program’s outcome measures will include the number of high-impact research publications, grant applications, and subsequent extramural funding for P&F awardees. We will accomplish our goals through the following three specific aims. Aim 1 will solicit research proposals from P&F candidates whose proposed research aligns with the central theme and the subthemes of the CSDDRC. We will advertise P&F support widely across campuses, in addition to contacting department/institute directors to solicit their recommendations for promising young and established investigators who are interested in working in digestive and liver diseases. Aim 2 will select pilot project applications that meet CSDDRC P&F Program goals using rigorous review criteria. Each year, the P&F Program will select four pilot projects to be funded by the P30 grant and matched by institutional support. Submitted applications will be peer- reviewed and preliminarily scored based on the NIH review format by three local expert reviewers. Subsequently, after oral presentations by the P&F applicants, the External Advisory Board (EAB) members will undertake a second round of review, scoring, and discussion at the P&F Program Review meeting following the CSDDRC Annual Symposium. Funding decisions will be made during the P&F Program Review meeting. Aim 3 will assist P&F project investigators with career development and obtaining extramural funding for digestive disease research. P&F awardees will benefit from the Enrichment Program’s well-organized mentoring structure, led by experienced members of the CSDDRC, which includes the Grants-in-Progress Mentoring Program, Gastrointestinal Research-in-Progress meetings, and grant application workshops. P&F awardees will also be mentored through direct interactions with P&F Program Directors, Core Directors, members of the Internal Advisory Board and EAB, and individual or collaborative mentor teams.

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.

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.

Development of an at-home weight-shifting balance game with musical biofeedback for older adults

Reducing fall risk is a dire societal need that requires interventions that over-prepare individuals to perform maneuvers important to daily mobility. Falling is often caused by improper weight shifting, and interventions that focus on developing weight-shifting abilities have shown improvements in clinical balance outcomes, including reduced fall incidence. Interventions that combine challenges to the cognitive and motor systems may be necessary to reduce fall-risk. Our central hypothesis is that leveraging gamification and “musical biofeedback” will improve balance abilities through practicing weight-shifting skills with increased cognitive and physical demands. Musical biofeedback conveys biological sensor data from the participant through specific musical sound parameters in real-time. Of particular interest in the proposal is the applicability to use musical biofeedback to train weight-shifting skills in a musical game. The goal is to develop a wearable sensor system that can be used at-home to practice and develop balance skills, while supporting cognitive engagement and motivation to adhere to exercise goals. To start, we are focusing on older adult end-users who typically have home exercise programs focused on weight-shifting. However, in the future, many other populations can benefit from this technology. In this Trailblazer award, the PI is leveraging her background in studying complex human maneuvers, developing musical biofeedback for older adults, and in algorithm development for mHealth sensors. The transdisciplinary team includes expertise in engineering, gamified rehabilitation technologies, home exercise programs, psychology of aging, and music. In the proposed research, our goals are to evaluate responses to the musical biofeedback game (Aim 1), validate the mHealth sensor system (Aim 2), and phenotype the gameplay behavior of fallers vs. non-fallers (Aim 3), relative to their baseline characteristics (Sub-Aim 3). Our long-term goal is for a variety of people to improve their balance control patterns while supporting and building their self-efficacy. We envision users, including older adults, training with musical biofeedback to safely (and enjoyably) prepare themselves to ambulate in their community – improving and preserving their mobility. The proposed research will pioneer using an emerging clinical technology – musical biofeedback – to train balance during weight-shifting tasks. The proposed research innovates how musical biofeedback, gamification, and focusing on weight-shifting and turns in balance training can be leveraged to challenge cognitive and physical body systems in fall-risk populations. By developing new therapy options and better understanding responses relative to baseline characteristics, this research improves clinical practices to reduce fall risk and deepens our understanding of dynamic balance control. Finally, the results of the proposed research will have translational impacts to help other fall-risk groups.

Mechanisms of age-related inflammatory dysregulation in the pathogenesis of periodontal disease

Periodontal disease is a chronic inflammatory condition that affects the supporting tissues of the dentition. Similar to other chronic inflammatory conditions, the prevalence of periodontal disease increases with age. Dysregulation of the host inflammatory response is central to the pathogenesis of periodontal disease and other age-related diseases. Therefore, an improved understanding of the pathologic mechanisms that contribute to age-related inflammatory dysregulation is needed to better manage periodontal disease in older adults. Towards understanding a mechanism of age-related inflammatory dysregulation in periodontal disease, we will investigate the role of triggering receptor expressed on myeloid cells 2 (TREM2). TREM2 is a potent immunoregulator expressed on macrophages. Signaling through TREM2 downregulates inflammation, in part, through inhibition of inflammatory cytokine expression. Dysregulation of TREM2 has been implicated in chronic inflammatory disease and age-related conditions, such as Alzheimer’s disease, liver disease, and osteoarthritis. However, the role of TREM2 in periodontal disease is understudied. Therefore, we propose to study TREM2 in the pathogenesis of periodontal disease and age-related inflammatory dysregulation. Our preliminary work has demonstrated that TREM2 is critical in macrophage immunoregulatory processes in the periodontium and TREM2 dysregulation contributes to periodontal disease in mice. We have shown that Trem2 is expressed in macrophages isolated form the periodontium in mice. We demonstrated that old mice expressed less Trem2 in the periodontium compared to young, which was associated with local inflammatory dysregulation and increased periodontal disease severity. Interestingly, Trem2 depletion in young mice resulted in increased inflammatory dysregulation and periodontal disease severity, similar to what is observed in old mice. From the preliminary data, we hypothesize that TREM2 modulates macrophage activity in the periodontium and age-related dysregulation of TREM2 drives a pathologic inflammatory response in periodontal disease. In Aim 1, we will demonstrate the extent to which TREM2 modulates inflammation and periodontal disease severity using old, young, and Trem2-/- mouse models of periodontal disease. In Aim 2, we will develop tissue-specific, single cell map of the immune cells in the periodontium and understand the effect of age and Trem2 on immune cell phenotypes and subpopulations. Findings from this proposal will elucidate a novel mechanism in age-related inflammatory dysregulation in the pathogenesis of periodontal disease and further advance our understanding of the role of TREM2 within oral tissues. This proposal was designed to generate a novel body of work that will be used to develop the independent research program of an early stage investigator and to support an R01 proposal to be submitted at the completion of this project period.

RECONJOINT: A Preference Elicitation Tool to Improve Shared Decision Making for Breast Reconstruction Surgery

PROJECT SUMMARY/ABSTRACT Breast reconstruction is a critical component of comprehensive breast cancer care, offering physical and emotional restoration after mastectomy. However, 40% of women undergoing breast reconstruction report dissatisfaction and decisional regret due to low involvement with treatment decisions and poor alignment between treatment preferences and the chosen reconstructive technique. Current approaches to shared decision-making (SDM) often fail to elicit and integrate individual-level preferences into treatment planning. This serves as a barrier to effective SDM and patient-centered care. To address this gap, we developed a web- based decision tool that uses adaptive choice–based conjoint (ACBC) analysis to elicit patient-level preferences for breast reconstruction. Preliminary studies indicate that the decision tool is acceptable and usable; patients wanted to view their results and use the tool in clinic, which we could not accommodate at the time because the decision tool currently lacks a structured method for clinical integration. We propose to develop an implementation toolkit for the decision tool to facilitate clinical integration and then test the feasibility, acceptability, and implementation of the intervention, RECONJOINT (decision tool and toolkit). In Aim 1, we will design an implementation toolkit informed by focus groups and developed with input from key partners, including patients, providers, and patient advocates. Candidate elements for the implementation toolkit include components developed for site-level implementation: treatment preferences report, video introducing the tool and existing evidence, and recommendations for patients and providers to incorporate preferences into SDM. In Aim 2, we will evaluate the feasibility, acceptability, and preliminary efficacy of the intervention in a pilot cluster-randomized hybrid type 1 trial conducted at two cancer centers (Memorial Sloan Kettering and Duke University). Our primary outcome of interest is the feasibility of the intervention. Secondary outcomes include acceptability and preliminary efficacy. Using a hybrid design, we will simultaneously evaluate facilitators, barriers, and strategies to implementation and how these factors influence the feasibility and acceptability of the intervention. The Consolidated Framework for Implementation Research and the Theoretical Domains Framework will serve as conceptual frameworks. This study is innovative as it leverages ACBC analysis to elicit patient preferences, designs an intervention with multilevel input from clinical and community partners, and uses a hybrid trial design to simultaneously evaluate feasibility, acceptability, preliminary efficacy, and implementation. By addressing critical barriers to SDM and enhancing patient–provider communication, this research aligns with the goals of PA-25-253 and the National Cancer Plan to deliver high quality, patient-centered cancer care. Findings from this study will inform a full-scale multi-site trial to evaluate the efficacy of the intervention and implementation outcomes (e.g., reach).

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

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

Environmental sampling for the fungal pathogen Coccidioides spp. in New Mexico

PROJECT SUMMARY/ABSTRACT Coccidioidomycosis (also known as Valley fever) is a fungal disease endemic to the arid and semi-arid portions of the United States. Due to its alarming health impacts, it has recently been deemed as one of the fungal diseases of highest concern by the World Health Organization. Disease cases continue to rise, causing increasing concern and warranting further understanding of this disease. Though New Mexico has been considered endemic to the disease since the 1940s, few cases are reported in the state each year, suggesting cases may be going vastly underreported. Indeed, recent epidemiologic models suggest New Mexico is likely underreporting cases, which may be a result of low disease awareness in the state or a lack of understanding what populations are at risk. Meanwhile, the neighboring state of Arizona reports the highest number of cases in the country, despite similarities in climate and ecology to New Mexico. In general, very little is known about the health burden of coccidioidomycosis and the geographical distribution of the causative fungal pathogen, Coccidioides spp., in New Mexico. Interestingly, both species of Coccidioides are likely endemic to New Mexico and hybridization of the species may occur. This, in combination with a variety of different ecosystems across the state, makes New Mexico an ideal location for studying the ecology of Coccidioides spp. The objective of our proposal is to generate preliminary data to gain a better understanding of the geographical distribution of Coccidioides spp. in New Mexico, including any regions where hybridization of the species may be occurring. To achieve this, we will collect soil samples throughout New Mexico to: (1) identify what ecosystems are conducive for the growth of Coccidioides and each Coccidioides species in New Mexico and (2) assess whether locations directly surrounding New Mexico’s five largest population centers (Albuquerque, Las Cruces, Rio Rancho, Santa Fe, and Roswell) are endemic to Coccidioides spp. The positive impacts of our proposal are an understanding of what populations are at risk for contracting this disease, where future disease surveillance efforts should be targeted in the state, and where future soil samples should be collected to further explore the genomics and phenotypes of Coccidioides spp. and potential for hybridization. This will help us achieve our long-term goal: to understand the ecology and endemicity of Coccidioides spp. to increase disease awareness, mitigate the negative health impacts from coccidioidomycosis, and ultimately protect the health of all Americans.

Post-diagnosis changes in body composition and renal cell cancer survival

ABSTRACT Significance. Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer and most lethal subtype, and there is great interest in the identification of potentially modifiable prognostic factors. Although weight status seems to be relevant, the relationship between body mass index (BMI) at diagnosis and survival among ccRCC patients indicates that mortality is lowest among those classified as overweight or obese at the time of diagnosis by BMI. This has resulted in confusion in clinical guidance for weight management among ccRCC patients. Recent work involving body composition features (adipose and muscle tissue) has provided some insight, but we do not understand how weight or body composition changes after diagnosis relate to survival, nor how these changes relate to pathological and molecular tumor features— information which is needed to resolve this controversy. Rigorous analytical approaches are further required to accurately address these questions. Innovation. Our study is highly innovative in that 1) we will be the first to leverage a large-scale cohort of ccRCC patients with multiple assessments of weight and body composition from diagnosis onward; 2) we will examine tumor characteristics, including molecular features, as potential drivers of these changes; and 3) we will use a rigorous joint modeling approach to simultaneously model the post-diagnosis trajectories of weight and body composition and their relationships with cancer outcomes in the most statistically sound manner. Our findings will inform clinical management of, and identify modifiable body composition features to improve survival for the growing number of ccRCC patients. Approach. We will use available data from the RESOLVE cohort, an NCI-funded retrospective cohort of 1,239 Stage I-III clear-cell renal cell carcinoma (ccRCC) patients diagnosed between 2000-2020 at Memorial Sloan Kettering Cancer Center. These data include clinical and patient-level factors collected from the medical record, including repeated height and weight assessments, body composition measures from existing computed tomography scans, pathological and molecular tumor characteristics, and overall survival (OS) and disease-free survival (DFS). We will use a joint modeling approach to simultaneously model changes in post-diagnosis body weight (Aim 1) and OS and DFS, as well as post-diagnosis changes in muscle and adipose tissue features (Aim 2) and OS and DFS. Models will include molecular tumor characteristics as predictors of these longitudinal trajectories. Impact. These results will provide crucial insight into the relationship between body composition changes and outcomes among ccRCC patients, and potentially identify tumor-related characteristics driving these associations. These results will resolve apparent paradoxes around the relationship between obesity and ccRCC mortality and identify potential targets for nutrition and physical activity interventions on body composition.

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

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

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

The Systems Vision Science Summer School & Symposium, August 11 – 22, 2025, Tuebingen, Germany

Applications are invited for our third edition of Systems Vision Science (SVS) summer school since 2023, designed for everyone interested in gaining a systems level understanding of biological vision. We plan a coherent, graduate-level, syllabus on the integration of experimental data with theory and models, featuring lectures, guided exercises and discussion sessions. The summer school will end with a Systems Vision Science symposium on frontier topics on August 20-22, with additional invited and contributed presentations and posters. Call for contributions and participations to the symposium will be sent out spring of 2025. All summer school participants are invited to attend, and welcome to submit contributions to the symposium.

Mouse Motor Cortex Circuits and Roles in Oromanual Behavior

I’m interested in structure-function relationships in neural circuits and behavior, with a focus on motor and somatosensory areas of the mouse’s cortex involved in controlling forelimb movements. In one line of investigation, we take a bottom-up, cellularly oriented approach and use optogenetics, electrophysiology, and related slice-based methods to dissect cell-type-specific circuits of corticospinal and other neurons in forelimb motor cortex. In another, we take a top-down ethologically oriented approach and analyze the kinematics and cortical correlates of “oromanual” dexterity as mice handle food. I'll discuss recent progress on both fronts.

Gene regulatory mechanisms of neocortex development and evolution

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

On finding what you’re (not) looking for: prospects and challenges for AI-driven discovery

Recent high-profile scientific achievements by machine learning (ML) and especially deep learning (DL) systems have reinvigorated interest in ML for automated scientific discovery (eg, Wang et al. 2023). Much of this work is motivated by the thought that DL methods might facilitate the efficient discovery of phenomena, hypotheses, or even models or theories more efficiently than traditional, theory-driven approaches to discovery. This talk considers some of the more specific obstacles to automated, DL-driven discovery in frontier science, focusing on gravitational-wave astrophysics (GWA) as a representative case study. In the first part of the talk, we argue that despite these efforts, prospects for DL-driven discovery in GWA remain uncertain. In the second part, we advocate a shift in focus towards the ways DL can be used to augment or enhance existing discovery methods, and the epistemic virtues and vices associated with these uses. We argue that the primary epistemic virtue of many such uses is to decrease opportunity costs associated with investigating puzzling or anomalous signals, and that the right framework for evaluating these uses comes from philosophical work on pursuitworthiness.

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

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

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

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

Characterizing the causal role of large-scale network interactions in supporting complex cognition

Neuroimaging has greatly extended our capacity to study the workings of the human brain. Despite the wealth of knowledge this tool has generated however, there are still critical gaps in our understanding. While tremendous progress has been made in mapping areas of the brain that are specialized for particular stimuli, or cognitive processes, we still know very little about how large-scale interactions between different cortical networks facilitate the integration of information and the execution of complex tasks. Yet even the simplest behavioral tasks are complex, requiring integration over multiple cognitive domains. Our knowledge falls short not only in understanding how this integration takes place, but also in what drives the profound variation in behavior that can be observed on almost every task, even within the typically developing (TD) population. The search for the neural underpinnings of individual differences is important not only philosophically, but also in the service of precision medicine. We approach these questions using a three-pronged approach. First, we create a battery of behavioral tasks from which we can calculate objective measures for different aspects of the behaviors of interest, with sufficient variance across the TD population. Second, using these individual differences in behavior, we identify the neural variance which explains the behavioral variance at the network level. Finally, using covert neurofeedback, we perturb the networks hypothesized to correspond to each of these components, thus directly testing their casual contribution. I will discuss our overall approach, as well as a few of the new directions we are currently pursuing.

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

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

Of glia and macrophages, signaling hubs in development and homeostasis

We are interested in the biology of macrophages, which represent the first line of defense against pathogens. In Drosophila, the embryonic hemocytes arise from the mesoderm whereas glial cells arise from multipotent precursors in the neurogenic region. These cell types represent, respectively, the macrophages located outside and within the nervous system (similar to vertebrate microglia). Thus, despite their different origin, hemocytes and glia display common functions. In addition, both cell types express the Glide/Gcm transcription factor, which plays an evolutionarily conserved role as an anti-inflammatory factor. Moreover, embryonic hemocytes play an evolutionarily conserved and fundamental role in development. The ability to migrate and to contact different tissues/organs most likely allow macrophages to function as signaling hubs. The function of macrophages beyond the recognition of the non-self calls for revisiting the biology of these heterogeneous and plastic cells in physiological and pathological conditions across evolution.

Trends in NeuroAI - Meta's MEG-to-image reconstruction

Trends in NeuroAI is a reading group hosted by the MedARC Neuroimaging & AI lab (https://medarc.ai/fmri). Title: Brain-optimized inference improves reconstructions of fMRI brain activity Abstract: The release of large datasets and developments in AI have led to dramatic improvements in decoding methods that reconstruct seen images from human brain activity. We evaluate the prospect of further improving recent decoding methods by optimizing for consistency between reconstructions and brain activity during inference. We sample seed reconstructions from a base decoding method, then iteratively refine these reconstructions using a brain-optimized encoding model that maps images to brain activity. At each iteration, we sample a small library of images from an image distribution (a diffusion model) conditioned on a seed reconstruction from the previous iteration. We select those that best approximate the measured brain activity when passed through our encoding model, and use these images for structural guidance during the generation of the small library in the next iteration. We reduce the stochasticity of the image distribution at each iteration, and stop when a criterion on the "width" of the image distribution is met. We show that when this process is applied to recent decoding methods, it outperforms the base decoding method as measured by human raters, a variety of image feature metrics, and alignment to brain activity. These results demonstrate that reconstruction quality can be significantly improved by explicitly aligning decoding distributions to brain activity distributions, even when the seed reconstruction is output from a state-of-the-art decoding algorithm. Interestingly, the rate of refinement varies systematically across visual cortex, with earlier visual areas generally converging more slowly and preferring narrower image distributions, relative to higher-level brain areas. Brain-optimized inference thus offers a succinct and novel method for improving reconstructions and exploring the diversity of representations across visual brain areas. Speaker: Reese Kneeland is a Ph.D. student at the University of Minnesota working in the Naselaris lab. Paper link: https://arxiv.org/abs/2312.07705

Event-related frequency adjustment (ERFA): A methodology for investigating neural entrainment

Neural entrainment has become a phenomenon of exceptional interest to neuroscience, given its involvement in rhythm perception, production, and overt synchronized behavior. Yet, traditional methods fail to quantify neural entrainment due to a misalignment with its fundamental definition (e.g., see Novembre and Iannetti, 2018; Rajandran and Schupp, 2019). The definition of entrainment assumes that endogenous oscillatory brain activity undergoes dynamic frequency adjustments to synchronize with environmental rhythms (Lakatos et al., 2019). Following this definition, we recently developed a method sensitive to this process. Our aim was to isolate from the electroencephalographic (EEG) signal an oscillatory component that is attuned to the frequency of a rhythmic stimulation, hypothesizing that the oscillation would adaptively speed up and slow down to achieve stable synchronization over time. To induce and measure these adaptive changes in a controlled fashion, we developed the event-related frequency adjustment (ERFA) paradigm (Rosso et al., 2023). A total of twenty healthy participants took part in our study. They were instructed to tap their finger synchronously with an isochronous auditory metronome, which was unpredictably perturbed by phase-shifts and tempo-changes in both positive and negative directions across different experimental conditions. EEG was recorded during the task, and ERFA responses were quantified as changes in instantaneous frequency of the entrained component. Our results indicate that ERFAs track the stimulus dynamics in accordance with the perturbation type and direction, preferentially for a sensorimotor component. The clear and consistent patterns confirm that our method is sensitive to the process of frequency adjustment that defines neural entrainment. In this Virtual Journal Club, the discussion of our findings will be complemented by methodological insights beneficial to researchers in the fields of rhythm perception and production, as well as timing in general. We discuss the dos and don’ts of using instantaneous frequency to quantify oscillatory dynamics, the advantages of adopting a multivariate approach to source separation, the robustness against the confounder of responses evoked by periodic stimulation, and provide an overview of domains and concrete examples where the methodological framework can be applied.

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

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

How curiosity affects learning and information seeking via the dopaminergic circuit

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

Signatures of criticality in efficient coding networks

The critical brain hypothesis states that the brain can benefit from operating close to a second-order phase transition. While it has been shown that several computational aspects of sensory information processing (e.g., sensitivity to input) are optimal in this regime, it is still unclear whether these computational benefits of criticality can be leveraged by neural systems performing behaviorally relevant computations. To address this question, we investigate signatures of criticality in networks optimized to perform efficient encoding. We consider a network of leaky integrate-and-fire neurons with synaptic transmission delays and input noise. Previously, it was shown that the performance of such networks varies non-monotonically with the noise amplitude. Interestingly, we find that in the vicinity of the optimal noise level for efficient coding, the network dynamics exhibits signatures of criticality, namely, the distribution of avalanche sizes follows a power law. When the noise amplitude is too low or too high for efficient coding, the network appears either super-critical or sub-critical, respectively. This result suggests that two influential, and previously disparate theories of neural processing optimization—efficient coding, and criticality—may be intimately related

How Children Design by Analogy: The Role of Spatial Thinking

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

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.

Can a single neuron solve MNIST? Neural computation of machine learning tasks emerges from the interaction of dendritic properties

Physiological experiments have highlighted how the dendrites of biological neurons can nonlinearly process distributed synaptic inputs. However, it is unclear how qualitative aspects of a dendritic tree, such as its branched morphology, its repetition of presynaptic inputs, voltage-gated ion channels, electrical properties and complex synapses, determine neural computation beyond this apparent nonlinearity. While it has been speculated that the dendritic tree of a neuron can be seen as a multi-layer neural network and it has been shown that such an architecture could be computationally strong, we do not know if that computational strength is preserved under these qualitative biological constraints. Here we simulate multi-layer neural network models of dendritic computation with and without these constraints. We find that dendritic model performance on interesting machine learning tasks is not hurt by most of these constraints and may synergistically benefit from all of them combined. Our results suggest that single real dendritic trees may be able to learn a surprisingly broad range of tasks through the emergent capabilities afforded by their properties.

Neural networks in the replica-mean field limits

In this talk, we propose to decipher the activity of neural networks via a “multiply and conquer” approach. This approach considers limit networks made of infinitely many replicas with the same basic neural structure. The key point is that these so-called replica-mean-field networks are in fact simplified, tractable versions of neural networks that retain important features of the finite network structure of interest. The finite size of neuronal populations and synaptic interactions is a core determinant of neural dynamics, being responsible for non-zero correlation in the spiking activity and for finite transition rates between metastable neural states. Theoretically, we develop our replica framework by expanding on ideas from the theory of communication networks rather than from statistical physics to establish Poissonian mean-field limits for spiking networks. Computationally, we leverage our original replica approach to characterize the stationary spiking activity of various network models via reduction to tractable functional equations. We conclude by discussing perspectives about how to use our replica framework to probe nontrivial regimes of spiking correlations and transition rates between metastable neural states.

Do large language models solve verbal analogies like children do?

Analogical reasoning –learning about new things by relating it to previous knowledge– lies at the heart of human intelligence and creativity and forms the core of educational practice. Children start creating and using analogies early on, making incredible progress moving from associative processes to successful analogical reasoning. For example, if we ask a four-year-old “Horse belongs to stable like chicken belongs to …?” they may use association and reply “egg”, whereas older children will likely give the intended relational response “chicken coop” (or other term to refer to a chicken’s home). Interestingly, despite state-of-the-art AI-language models having superhuman encyclopedic knowledge and superior memory and computational power, our pilot studies show that these large language models often make mistakes providing associative rather than relational responses to verbal analogies. For example, when we asked four- to eight-year-olds to solve the analogy “body is to feet as tree is to …?” they responded “roots” without hesitation, but large language models tend to provide more associative responses such as “leaves”. In this study we examine the similarities and differences between children's and six large language models' (Dutch/multilingual models: RobBERT, BERT-je, M-BERT, GPT-2, M-GPT, Word2Vec and Fasttext) responses to verbal analogies extracted from an online adaptive learning environment, where >14,000 7-12 year-olds from the Netherlands solved 20 or more items from a database of 900 Dutch language verbal analogies.

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

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

Nonlinear computations in spiking neural networks through multiplicative synapses

The brain efficiently performs nonlinear computations through its intricate networks of spiking neurons, but how this is done remains elusive. While recurrent spiking networks implementing linear computations can be directly derived and easily understood (e.g., in the spike coding network (SCN) framework), the connectivity required for nonlinear computations can be harder to interpret, as they require additional non-linearities (e.g., dendritic or synaptic) weighted through supervised training. Here we extend the SCN framework to directly implement any polynomial dynamical system. This results in networks requiring multiplicative synapses, which we term the multiplicative spike coding network (mSCN). We demonstrate how the required connectivity for several nonlinear dynamical systems can be directly derived and implemented in mSCNs, without training. We also show how to precisely carry out higher-order polynomials with coupled networks that use only pair-wise multiplicative synapses, and provide expected numbers of connections for each synapse type. Overall, our work provides an alternative method for implementing nonlinear computations in spiking neural networks, while keeping all the attractive features of standard SCNs such as robustness, irregular and sparse firing, and interpretable connectivity. Finally, we discuss the biological plausibility of mSCNs, and how the high accuracy and robustness of the approach may be of interest for neuromorphic computing.

Brian2CUDA: Generating Efficient CUDA Code for Spiking Neural Networks

Graphics processing units (GPUs) are widely available and have been used with great success to accelerate scientific computing in the last decade. These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. Here, we present Brian2CUDA, an open-source software that extends the Brian simulator with a GPU backend. Our implementation generates efficient code for the numerical integration of neuronal states and for the propagation of synaptic events on GPUs, making use of their massively parallel arithmetic capabilities. We benchmark the performance improvements of our software for several model types and find that it can accelerate simulations by up to three orders of magnitude compared to Brian’s CPU backend. Currently, Brian2CUDA is the only package that supports Brian’s full feature set on GPUs, including arbitrary neuron and synapse models, plasticity rules, and heterogeneous delays. When comparing its performance with Brian2GeNN, another GPU-based backend for the Brian simulator with fewer features, we find that Brian2CUDA gives comparable speedups, while being typically slower for small and faster for large networks. By combining the flexibility of the Brian simulator with the simulation speed of GPUs, Brian2CUDA enables researchers to efficiently simulate spiking neural networks with minimal effort and thereby makes the advancements of GPU computing available to a larger audience of neuroscientists.

A predictive-processing account of psychosis

There has been increasing interest in the neurocomputational mechanisms underlying psychotic disorders in recent years. One promising approach is based on the theoretical framework of predictive processing, which proposes that inferences regarding the state of the world are made by combining prior beliefs with sensory signals. Delusions and hallucinations are the core symptoms of psychosis and often co-occur. Yet, different predictive-processing alterations have been proposed for these two symptom dimensions, according to which the relative weighting of prior beliefs in perceptual inference is decreased or increased, respectively. I will present recent behavioural, neuroimaging, and computational work that investigated perceptual decision-making under uncertainty and ambiguity to elucidate the changes in predictive processing that may give rise to psychotic experiences. Based on the empirical findings presented, I will provide a more nuanced predictive-processing account that suggests a common mechanism for delusions and hallucinations at low levels of the predictive-processing hierarchy, but still has the potential to reconcile apparently contradictory findings in the literature. This account may help to understand the heterogeneity of psychotic phenomenology and explain changes in symptomatology over time.

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.

Designing the BEARS (Both Ears) Virtual Reality Training Package to Improve Spatial Hearing in Young People with Bilateral Cochlear Implant

Results: the main areas which were modified based on participatory feedback were the variety of immersive scenarios to cover a range of ages and interests, the number of levels of complexity to ensure small improvements were measured, the feedback and reward schemes to ensure positive reinforcement, and specific provision for participants with balance issues, who had difficulties when using head-mounted displays. The effectiveness of the finalised BEARS suite will be evaluated in a large-scale clinical trial. We have added in additional login options for other members of the family and based on patient feedback we have improved the accompanying reward schemes. Conclusions: Through participatory design we have developed a training package (BEARS) for young people with bilateral cochlear implants. The training games are appropriate for use by the study population and ultimately should lead to patients taking control of their own management and reducing the reliance upon outpatient-based rehabilitation programmes. Virtual reality training provides a more relevant and engaging approach to rehabilitation for young people.

Setting network states via the dynamics of action potential generation

To understand neural computation and the dynamics in the brain, we usually focus on the connectivity among neurons. In contrast, the properties of single neurons are often thought to be negligible, at least as far as the activity of networks is concerned. In this talk, I will contradict this notion and demonstrate how the biophysics of action-potential generation can have a decisive impact on network behaviour. Our recent theoretical work shows that, among regularly firing neurons, the somewhat unattended homoclinic type (characterized by a spike onset via a saddle homoclinic orbit bifurcation) particularly stands out: First, spikes of this type foster specific network states - synchronization in inhibitory and splayed-out/frustrated states in excitatory networks. Second, homoclinic spikes can easily be induced by changes in a variety of physiological parameters (like temperature, extracellular potassium, or dendritic morphology). As a consequence, such parameter changes can even induce switches in network states, solely based on a modification of cellular voltage dynamics. I will provide first experimental evidence and discuss functional consequences of homoclinic spikes for the design of efficient pattern-generating motor circuits in insects as well as for mammalian pathologies like febrile seizures. Our analysis predicts an interesting role for homoclinic action potentials as an integral part of brain dynamics in both health and disease.

Spontaneous Emergence of Computation in Network Cascades

Neuronal network computation and computation by avalanche supporting networks are of interest to the fields of physics, computer science (computation theory as well as statistical or machine learning) and neuroscience. Here we show that computation of complex Boolean functions arises spontaneously in threshold networks as a function of connectivity and antagonism (inhibition), computed by logic automata (motifs) in the form of computational cascades. We explain the emergent inverse relationship between the computational complexity of the motifs and their rank-ordering by function probabilities due to motifs, and its relationship to symmetry in function space. We also show that the optimal fraction of inhibition observed here supports results in computational neuroscience, relating to optimal information processing.

ISAM-NIG Webinars

Optimized Non-Invasive Brain Stimulation for Addiction Treatment

Neuroscience of socioeconomic status and poverty: Is it actionable?

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

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.

Careers for neuroscience in Artificial Intelligence

The purpose of this event is twofold: to raise awareness of careers in AI to neuroscience postgraduate and Early Career Researchers (ECRs), and to give the chance for commercial organisations to acquire and diversify their talent pool.  We know that our early career members are highly motivated and interested in different career pathways, and wish to help them fulfil their ambitions. This will be a hybrid event held in person at Arca Blanca, Covent Garden, London and also available online. FREE for BNA members!

From the Didactic to the Heuristic Use of Analogies in Science Teaching

Extensive research on science teaching has shown the effectiveness of analogies as a didactic tool which, when appropriately and effectively used, facilitates the learning process of abstract concepts. This seminar does not contradict the efficacy of such a didactic use of analogies in this seminar but switches attention and interest on their heuristic use in approaching and understanding of what previously unknown. Such a use of analogies derives from research with 10 to 17 year-olds, who, when asked to make predictions in novel situations and to then provide explanations about these predictions, they self-generated analogies and used them by reasoning on their basis. This heuristic use of analogies can be used in science teaching in revealing how students approach situations they have not considered before as well as the sources they draw upon in doing so.

What the fly’s eye tells the fly’s brain…and beyond

Fly Escape Behaviors: Flexible and Modular We have identified a set of escape maneuvers performed by a fly when confronted by a looming object. These escape responses can be divided into distinct behavioral modules. Some of the modules are very stereotyped, as when the fly rapidly extends its middle legs to jump off the ground. Other modules are more complex and require the fly to combine information about both the location of the threat and its own body posture. In response to an approaching object, a fly chooses some varying subset of these behaviors to perform. We would like to understand the neural process by which a fly chooses when to perform a given escape behavior. Beyond an appealing set of behaviors, this system has two other distinct advantages for probing neural circuitry. First, the fly will perform escape behaviors even when tethered such that its head is fixed and neural activity can be imaged or monitored using electrophysiology. Second, using Drosophila as an experimental animal makes available a rich suite of genetic tools to activate, silence, or image small numbers of cells potentially involved in the behaviors. Neural Circuits for Escape Until recently, visually induced escape responses have been considered a hardwired reflex in Drosophila. White-eyed flies with deficient visual pigment will perform a stereotyped middle-leg jump in response to a light-off stimulus, and this reflexive response is known to be coordinated by the well-studied giant fiber (GF) pathway. The GFs are a pair of electrically connected, large-diameter interneurons that traverse the cervical connective. A single GF spike results in a stereotyped pattern of muscle potentials on both sides of the body that extends the fly's middle pair of legs and starts the flight motor. Recently, we have found that a fly escaping a looming object displays many more behaviors than just leg extension. Most of these behaviors could not possibly be coordinated by the known anatomy of the GF pathway. Response to a looming threat thus appears to involve activation of numerous different neural pathways, which the fly may decide if and when to employ. Our goal is to identify the descending pathways involved in coordinating these escape behaviors as well as the central brain circuits, if any, that govern their activation. Automated Single-Fly Screening We have developed a new kind of high-throughput genetic screen to automatically capture fly escape sequences and quantify individual behaviors. We use this system to perform a high-throughput genetic silencing screen to identify cell types of interest. Automation permits analysis at the level of individual fly movements, while retaining the capacity to screen through thousands of GAL4 promoter lines. Single-fly behavioral analysis is essential to detect more subtle changes in behavior during the silencing screen, and thus to identify more specific components of the contributing circuits than previously possible when screening populations of flies. Our goal is to identify candidate neurons involved in coordination and choice of escape behaviors. Measuring Neural Activity During Behavior We use whole-cell patch-clamp electrophysiology to determine the functional roles of any identified candidate neurons. Flies perform escape behaviors even when their head and thorax are immobilized for physiological recording. This allows us to link a neuron's responses directly to an action.

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.

Learning in/about/from the basal ganglia

The basal ganglia are a collection of brain areas that are connected by a variety of synaptic pathways and are a site of significant reward-related dopamine release. These properties suggest a possible role for the basal ganglia in action selection, guided by reinforcement learning. In this talk, I will discuss a framework for how this function might be performed and computational results using an upward mapping to identify putative low-dimensional control ensembles that may be involved in tuning decision policy. I will also present some recent experimental results and theory – related to effects of extracellular ion dynamics -- that run counter to the classical view of basal ganglia pathways and suggest a new interpretation of certain aspects of this framework. For those not so interested in the basal ganglia, I hope that the upward mapping approach and impact of extracellular ion dynamics will nonetheless be of interest!

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

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

Neural Representations of Social Homeostasis

How does our brain rapidly determine if something is good or bad? How do we know our place within a social group? How do we know how to behave appropriately in dynamic environments with ever-changing conditions? The Tye Lab is interested in understanding how neural circuits important for driving positive and negative motivational valence (seeking pleasure or avoiding punishment) are anatomically, genetically and functionally arranged. We study the neural mechanisms that underlie a wide range of behaviors ranging from learned to innate, including social, feeding, reward-seeking and anxiety-related behaviors. We have also become interested in “social homeostasis” -- how our brains establish a preferred set-point for social contact, and how this maintains stability within a social group. How are these circuits interconnected with one another, and how are competing mechanisms orchestrated on a neural population level? We employ optogenetic, electrophysiological, electrochemical, pharmacological and imaging approaches to probe these circuits during behavior.

Time as a continuous dimension in natural and artificial networks

Neural representations of time are central to our understanding of the world around us. I review cognitive, neurophysiological and theoretical work that converges on three simple ideas. First, the time of past events is remembered via populations of neurons with a continuum of functional time constants. Second, these time constants evenly tile the log time axis. This results in a neural Weber-Fechner scale for time which can support behavioral Weber-Fechner laws and characteristic behavioral effects in memory experiments. Third, these populations appear as dual pairs---one type of population contains cells that change firing rate monotonically over time and a second type of population that has circumscribed temporal receptive fields. These ideas can be used to build artificial neural networks that have novel properties. Of particular interest, a convolutional neural network built using these principles can generalize to arbitrary rescaling of its inputs. That is, after learning to perform a classification task on a time series presented at one speed, it successfully classifies stimuli presented slowed down or sped up. This result illustrates the point that this confluence of ideas originating in cognitive psychology and measured in the mammalian brain could have wide-reaching impacts on AI research.

From a by-stander to an influencer: How microglia adapt to altered environments and influence neuronal activity

Microglia, traditionally classified as immune-responsive, adjust synaptic connections during development and disease. However, their role in the adult nervous system has been mostly diminished to an observer. In my research group, we are interested in how microglia are involved in establishing and maintaining accurate neuronal circuit function in the retina and in the visual cortex. In my talk, I will introduce our strategies how to decipher the microglia’s functional identity and how this information guided us to microglia enabled extracellular matrix remodeling and reinstatment of juvenile-like plasticity in the adult brain.

Elucidating the mechanism underlying Stress and Caffeine-induced motor dysfunction using a mouse model of Episodic Ataxia Type 2

Episodic Ataxia type 2 (EA2), caused by mutations in the CACNA1A gene, results in a loss-of-function of the P/Q type calcium channel, which leads to baseline ataxia, and attacks of dyskinesia, that can last a few hours to a few days. Attacks are brought on by consumption of caffeine, alcohol, and physical or emotional stress. Interestingly, caffeine and stress are common triggers among other episodic channelopathies, as well as causing tremor or shaking in otherwise healthy adults. The mechanism underlying stress and caffeine induced motor impairment remains poorly understood. Utilizing behavior, and in vivo and in vitro electrophysiology in the tottering mouse, a well characterized mouse model of EA2, or WT mice, we first sought to elucidate the mechanism underlying stress-induced motor impairment. We found stress induces attacks in EA2 though the activation of cerebellar alpha 1 adrenergic receptors by norepinephrine (NE) through casein kinase 2 (CK2) dependent phosphorylation. This decreases SK2 channel activity, causing increased Purkinje cell irregularity and motor impairment. Knocking down or blocking CK2 with an FDA approved drug CX-4945 prevented PC irregularity and stress-induced attacks. We next hypothesized caffeine, which has been shown to increase NE levels, could induce attacks through the same alpha 1 adrenergic mechanism in EA2. We found caffeine increases PC irregularity and induces attacks through the same CK2 pathway. Block of alpha 1 adrenergic receptors, however, failed to prevent caffeine-induced attacks. Caffeine instead induces attacks through the block of cerebellar A1 adenosine receptors. This increases the release of glutamate, which interacts with mGluR1 receptors on PC, resulting in erratic firing and motor attacks. Finally, we show a novel direct interaction between mGluR1 and CK2, and inhibition of mGluR1 prior to initiation of attack, prevents the caffeine-induced increase in phosphorylation. These data elucidate the mechanism underlying stress and caffeine-induced motor impairment. Furthermore, given the success of CX-4945 to prevent stress and caffeine induced attacks, it establishes ground-work for the development of therapeutics for the treatment of caffeine and stress induced attacks in EA2 patients and possibly other episodic channelopathies.

MBI Webinar on preclinical research into brain tumours and neurodegenerative disorders

WEBINAR 1 Breaking the barrier: Using focused ultrasound for the development of targeted therapies for brain tumours presented by Dr Ekaterina (Caty) Salimova, Monash Biomedical Imaging Glioblastoma multiforme (GBM) - brain cancer - is aggressive and difficult to treat as systemic therapies are hindered by the blood-brain barrier (BBB). Focused ultrasound (FUS) - a non-invasive technique that can induce targeted temporary disruption of the BBB – is a promising tool to improve GBM treatments. In this webinar, Dr Ekaterina Salimova will discuss the MRI-guided FUS modality at MBI and her research to develop novel targeted therapies for brain tumours. Dr Ekaterina (Caty) Salimova is a Research Fellow in the Preclinical Team at Monash Biomedical Imaging. Her research interests include imaging cardiovascular disease and MRI-guided focused ultrasound for investigating new therapeutic targets in neuro-oncology. - WEBINAR 2 Disposition of the Kv1.3 inhibitory peptide HsTX1[R14A], a novel attenuator of neuroinflammation presented by Sanjeevini Babu Reddiar, Monash Institute of Pharmaceutical Sciences The voltage-gated potassium channel (Kv1.3) in microglia regulates membrane potential and pro-inflammatory functions, and non-selective blockade of Kv1.3 has shown anti-inflammatory and disease improvement in animal models of Alzheimer’s and Parkinson’s diseases. Therefore, specific inhibitors of pro-inflammatory microglial processes with CNS bioavailability are urgently needed, as disease-modifying treatments for neurodegenerative disorders are lacking. In this webinar, PhD candidate Ms Sanju Reddiar will discuss the synthesis and biodistribution of a Kv1.3-inhibitory peptide using a [64Cu]Cu-DOTA labelled conjugate. Sanjeevini Babu Reddiar is a PhD student at the Monash Institute of Pharmaceutical Sciences. She is working on a project identifying the factors governing the brain disposition and blood-brain barrier permeability of a Kv1.3-blocking peptide.

COSYNE 2022

The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The main meeting is single-track, with invited talks selected by the Executive Committee and additional talks and posters selected by the Program Committee based on submitted abstracts. The workshops feature in-depth discussion of current topics of interest in a small group setting.

Expression of interest: Japan-UK joint call for collaborations in Advanced Connectivity Technologies

Innovation Loans Expression of Interest

NOAEL dose interest assessment as an optimized dose of oxime in the treatment of organophosphorus compounds exposure

Pharmacokinetic and safety of a novel pleiotropic compound in C57BL/6J mice with potential therapeutic interest in Alzheimer’s disease

FENS Forum 2024