technology

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

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

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

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

Weak Cell Adhesion is a Prognostic Signature of Invasive Cancer

Project Summary Despite early detection, low-grade and localized breast cancers such as ductal carcinoma in situ (DCIS) can relapse in up to 20% of cases despite standard of care. For DCIS, relapse affects over 12,000 U.S. women annually and has increased 60% in the last 40 years. Current diagnostic assessments including histopathological markers often miss early disseminating cells, lack specificity, or cannot distinguish cancer from non-cancer cells in the stroma. Hence there is an unmet need for cancer diagnostic technologies that employ radically different characterization methods. For example, significant physical differences exist between metastasizing and benign breast cancer cells, owing to metastasizing cells detaching from the primary tumor, migrating through the surrounding stroma, intravasating and extravasating, and ultimately engrafting in distant tissues. We recently demonstrated that cancer cells with weaker adhesion migrate faster and metastasize more frequently in murine breast cancer models than strongly adherent cells. In a small pilot study of human breast tumors, we also observed that the abundance of weakly adherent (WA) cells scales with disease severity; subpopulations from invasive carcinomas were the least adherent. However, a subset of DCIS cases displayed much less adhesion, suggesting that these patients may have a tumor subpopulation that progresses to metastatic disease despite standard-of-care treatment. Weak adhesion is a defining physical characteristic of tumors, but to establish their role in initiation, metastasis, and patient outcomes, we will leverage model systems and our newly patented adhesion technology to answer these fundamental questions of cancer biology and clinical translation. To understand the impact of adhesion on cancer progression, we will evaluate the tumor-initiating potential of WA versus strongly adherent (SA) tumor cells in a murine breast cancer model before confirming how weak adhesion advantages cells to cause secondary disease using bioengineered in vitro models. In dissecting the stages of metastasis where WA cells exhibit advantages, e.g., recapitulating stromal niche, transendothelial migration, and tissue-specific colonization, we will identify mechanisms that enable WA cells to thrive and evaluate therapeutic targets that disrupt these pathways. Finally, we will analyze the adhesion profiles of resected tumors and stroma from 80 breast cancer patients with DCIS or invasive disease. Adhesion data will be correlated with conventional assessment methods and ultimately with patient outcomes, e.g., disease-free and progression-free intervals. We anticipate that the DCIS subpopulation that aligns with the adhesion signature of invasive carcinomas will have shorter intervals and survival time. This integrated study design bridges mouse models, mechanistic bioengineering assays, and human samples to clarify the metastatic potential and prognostic value of WA breast cancer cells. Our use of mouse models in this grant is required to study the interactions among tumor cells, immune cells, vasculature, and stromal tissues that drive tumor formation in vivo. Bioengineered in vitro systems lack the complexity to ask such questions and using injected tumor cells is not possible in humans.

Urothelial Resurfacing with Irreversible Electroporation for Adjuvant Therapy of Bladder Cancer

PROJECT SUMMARY Over 70% of bladder cancer (BCa) patients are diagnosed with early-stage and localized non-muscle invasive disease (NMIBC), yet achieving durable cancer-free survival remains a significant challenge. Most of these patients will experience local tumor recurrence within five years following standard of care (SoC) transurethral resection of bladder tumor (TURBT) and intravesical adjuvant chemo- or immunotherapy. Recurrence is driven by microscopic tumors and premalignant lesions dispersed within the urothelial layer that survive and escape these treatments. As TURBT effectively treats tumors visible on imaging, current research has predominantly focused on drugs and biologics for improving intravesical adjuvant therapy. In this proposal we pose the provocative question whether a TURBT-like ablative technique can be extended to debulk malignancy in the entire bladder and investigate the synergy with intravesical adjuvant therapy in improving outcomes. Our objective is to address this technology and knowledge gap by developing and validating whole bladder urothelial resurfacing (WBUR) using irreversible electroporation (IRE). During IRE, microsecond-long pulsed electric fields (PEF) are used to induce rapid cell death by catastrophic permeabilization of the cell membrane, without affecting the extracellular matrix (ECM) within the treated tissue. In prior work, we designed devices that utilized this unique mechanism of IRE for performing penetrative ablation in the ureter, bile duct and bronchus of swine while preserving lumen function. Our findings provided strong rationale for IRE being an ideal candidate for WBUR as alternate techniques such as thermal ablation or ionizing radiation must be performed with extreme care in the bladder to avoid perforation or fistula formation. In subsequent preliminary work we developed technology to demonstrate the feasibility and safety of WBUR with IRE in a rat model of BCa and scalability in human-sized swine bladder. In Aim 1, we will investigate the cancer treatment efficacy of combination WBUR and intravesical adjuvant therapy. In Aim 2, validate WBUR derived liquid biopsy for monitoring cancer status. In Aim 3, engineer PEF delivery strategy to enhance the safety and specificity of WBUR. The innovation of our proposed work is defined by developing whole bladder ablation as a debulking strategy and examining its synergy with SOC adjuvant therapy (Aim 1), enabled by new electrode paradigm and PEF delivery strategy (Aim 3), monitoring by an unconventional liquid biopsy approach (Aim 2). Our work can immediately aid the management of NMIBC patients who cannot undergo radical cystectomy, with future application as a cancer prevention strategy in high-risk patients. Success of individual aims will result in major contributions to the topics of IRE, BCa treatment and diagnosis.

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.

Transcriptional control of activation induced deaminase (AID) function

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

Linking Single-Cell Transcriptomic, Morphological, and Temporal Signatures of Vulnerability in Neurodegeneration

Neurodegeneration involves complex cellular phenotypes and molecular changes that vary widely among the cells of the nervous system. Current methodologies permit either detailed molecular profiling (e.g., single-cell transcriptomics) or functional phenotyping (e.g., live imaging of neuronal activity), but not both in the same cells. Thus, it is difficult to directly link a neuron's functional state or fate with its gene expression profile. To address this limitation, we developed an innovative technology, VISTA-FISH (Video Imaging with Spatial- Temporal Analysis by FISH), that couples prospective live-cell imaging with high-resolution spatial transcriptomic profiling of the same cells. This approach enables in situ comparisons of gene expression in neurons that exhibit divergent behaviors or outcomes. Using VISTA-FISH, we will profile iPS-derived human neurons to link single-cell gene expression, morphology, and temporal phenotypes to study molecular pathways driving resilience as well as susceptibility. After exposing neurons carrying TDP43 and C9orf72 mutations to a stimulus inducing TDP43 aggregation, we will jointly record TDP43 localization and neuron activity using live-cell microscopy, then measure single-cell gene expression of the same cells (Aim 1). We will also combine live-cell measurements of TDP43 half-life with CRISPR screening and single-cell gene expression (Aim 2). These rich datasets will enable us to determine transcriptomic changes associated with differences in protein aggregation, protein synthesis, and protein degradation in individual cells, providing an unprecedented molecular perspective on factors responsible for vulnerability and resilience to neurodegeneration.

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.

Developing a novel technology for studying T cell differentiation in vivo

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

A NOVEL GEMM TO ELUCIDATE THE ROLE OF CHAF1A IN NEUROBLASTOMA DEVELOPMENT

PROJECT SUMMARY: This proposal focuses on the fundamental understanding on how the CHAF1A oncogene drives molecular mechanisms, cellular signaling, and metabolic processes in the oncogenesis of neuroblastoma (NB). NB is an aggressive pediatric cancer, which accounts for 15% of pediatric cancer mortalities. High-risk NB is thought to arise from a small number of recurrent genetic alterations that block the ability of neural crest cells (NCCs) to differentiate. To assess the molecular mechanisms governing NC differentiation, our laboratory has established a definitive role of the epigenetic regulator CHAF1A in blocking NC differentiation and driving NB oncogenesis. In this proposal, we will determine the impact of CHAF1A on NB initiation and progression. To accomplish this goal, we propose to develop a novel CHAF1A-driven genetically-engineered mouse model (GEMM) of NB and test the impact of CHAF1A on NB incidence, histology and metastasis, and the tumor immune microenvironment (TIME). We hypothesize that CHAF1A will increase de novo incidence of NB, reduce mouse survival, and promote a suppressive TIME. By developing a novel GEMM of NB and employing innovative technology (including ATAC-seq, lipidomics, and scRNA-seq), we will: 1- elucidate the role of CHAF1A in NB tumor initiation and progression; and 2- determine the impact of CHAF1A on MYCN-induced oncogenesis. These findings will provide a novel view on the molecular mechanisms driving NB initiation, and will have high clinical implications, informing future differentiation-based interventions for high-risk NBs.

A PROTAC Strategy to Combat Botulinum Neurotoxicity

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

Facilitating the Advancement of Research and Education for Undergraduate Students by Incorporating Laser Scanning Confocal Microscopy (FAREUS-LSCM)

PROJECT SUMMARY/ABSTRACT The University of Puerto Rico at Aguadilla (UPR-Aguadilla) requests funding to acquire a Nikon AX Galvo Confocal Laser Scanning Microscope (LSCM) with a TI2-E inverted platform and a four- laser configuration (405/488/561/640 nm) to establish transformative imaging capabilities at our resource-limited institution serving 96% Pell Grant recipients. This state-of-the-art instrument addresses a critical infrastructure gap, enabling high-resolution fluorescence imaging, live-cell microscopy, and quantitative analysis essential for competitive biomedical research and undergraduate education. The LSCM will directly support four active research projects spanning parasitology (monogenean host-specificity studies), plant pathology (coffee biocontrol development), environmental chemistry (metalloprotein biomarkers), and neuroscience (astrocyte dysfunction in diabetic epilepsy) while integrating into core laboratory courses including Immunology (BIOL 4009) and Undergraduate research courses (BIOL 3108 and QUIM 4999). Our multidisciplinary faculty, in partnership with the Neuroimaging and Electrophysiology Facility (NIEF) Excellence Imaging Center, offers expertise in confocal microscopy, encompassing advanced imaging and specialized sample preparation techniques. This collaboration ensures effective implementation of the technology, sustained technical support, and high-quality training programs that will enhance research productivity and broaden educational impact. The broad, long-term objective is to transform UPR-Aguadilla from a primarily teaching institution into a research-active campus capable of producing graduate-school-ready students equipped with cutting-edge technical skills. Access to advanced confocal microscopy will stimulate new research collaborations, enhance faculty productivity, and provide 30-40 students annually with hands-on experience in modern imaging technologies currently absent from our curriculum. The instrument will strengthen our partnership with the emerging Natural History Museum of Puerto Rico for specimen digitization and support comprehensive outreach programs targeting 25-50 high school students annually through "Seeing Science Up Close" workshops. Expected outcomes include 1- 2 peer-reviewed publications within three years, establishment of 1-2 new institutional collaborations, and measurable enhancement of biomedical research capacity. This investment will significantly advance STEM education and research opportunities at UPR-Aguadilla while expanding access to cutting-edge scientific instrumentation for students pursuing biomedical careers and contributing to the development of skilled researchers in the biomedical sciences.

Functional Imaging of the Human Brain: A Window into the Organization of the Human Mind

Neural control of internal affective states”

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

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

Harnessing Big Data in Neuroscience: From Mapping Brain Connectivity to Predicting Traumatic Brain Injury

Neuroscience is experiencing unprecedented growth in dataset size both within individual brains and across populations. Large-scale, multimodal datasets are transforming our understanding of brain structure and function, creating opportunities to address previously unexplored questions. However, managing this increasing data volume requires new training and technology approaches. Modern data technologies are reshaping neuroscience by enabling researchers to tackle complex questions within a Ph.D. or postdoctoral timeframe. I will discuss cloud-based platforms such as brainlife.io, that provide scalable, reproducible, and accessible computational infrastructure. Modern data technology can democratize neuroscience, accelerate discovery and foster scientific transparency and collaboration. Concrete examples will illustrate how these technologies can be applied to mapping brain connectivity, studying human learning and development, and developing predictive models for traumatic brain injury (TBI). By integrating cloud computing and scalable data-sharing frameworks, neuroscience can become more impactful, inclusive, and data-driven..

Multisensory perception in the metaverse

Pharmacological exploitation of neurotrophins and their receptors to develop novel therapeutic approaches against neurodegenerative diseases and brain trauma

Neurotrophins (NGF, BDNF, NT-3) are endogenous growth factors that exert neuroprotective effects by preventing neuronal death and promoting neurogenesis. They act by binding to their respective high-affinity, pro-survival receptors TrkA, TrkB or TrkC, as well as to p75NTR death receptor. While these molecules have been shown to significantly slow or prevent neurodegeneration, their reduced bioavailability and inability to penetrate the blood-brain-barrier limit their use as potential therapeutics. To bypass these limitations, our research team has developed and patented small-sized, lipophilic compounds which selectively resemble neurotrophins’ effects, presenting preferable pharmacological properties and promoting neuroprotection and repair against neurodegeneration. In addition, the combination of these molecules with 3D cultured human neuronal cells, and their targeted delivery in the brain ventricles through soft robotic systems, could offer novel therapeutic approaches against neurodegenerative diseases and brain trauma.

Brain Emulation Challenge Workshop

Brain Emulation Challenge workshop will tackle cutting-edge topics such as ground-truthing for validation, leveraging artificial datasets generated from virtual brain tissue, and the transformative potential of virtual brain platforms, such as applied to the forthcoming Brain Emulation Challenge.

Digital Minds: Brain Development in the Age of Technology

Digital Minds: Brain Development in the Age of Technology examines how our increasingly connected world shapes mental and cognitive health. From screen time and social media to virtual interactions, this seminar delves into the latest research on how technology influences brain development, relationships, and emotional well-being. Join us to explore strategies for harnessing technology's benefits while mitigating its potential challenges, empowering you to thrive in a digital age.

Analyzing Network-Level Brain Processing and Plasticity Using Molecular Neuroimaging

Behavior and cognition depend on the integrated action of neural structures and populations distributed throughout the brain. We recently developed a set of molecular imaging tools that enable multiregional processing and plasticity in neural networks to be studied at a brain-wide scale in rodents and nonhuman primates. Here we will describe how a novel genetically encoded activity reporter enables information flow in virally labeled neural circuitry to be monitored by fMRI. Using the reporter to perform functional imaging of synaptically defined neural populations in the rat somatosensory system, we show how activity is transformed within brain regions to yield characteristics specific to distinct output projections. We also show how this approach enables regional activity to be modeled in terms of inputs, in a paradigm that we are extending to address circuit-level origins of functional specialization in marmoset brains. In the second part of the talk, we will discuss how another genetic tool for MRI enables systematic studies of the relationship between anatomical and functional connectivity in the mouse brain. We show that variations in physical and functional connectivity can be dissociated both across individual subjects and over experience. We also use the tool to examine brain-wide relationships between plasticity and activity during an opioid treatment. This work demonstrates the possibility of studying diverse brain-wide processing phenomena using molecular neuroimaging.

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.

Rett syndrome, MECP2 and therapeutic strategies

The development of the iPS cell technology has revolutionized our ability to study development and diseases in defined in vitro cell culture systems. The talk will focus on Rett Syndrome and discuss two topics: (i) the use of gene editing as an approach to therapy and (ii) the role of MECP2 in gene expression (i) The mutation of the X-linked MECP2 gene is causative for the disease. In a female patient, every cell has a wt copy that is, however, in 50% of the cells located on the inactive X chromosome. We have used epigenetic gene editing tools to activate the wt MECP2 allele on the inactive X chromosome. (ii) MECP2 is thought to act as repressor of gene expression. I will present data which show that MECP2 binds to Pol II and acts as an activator for thousands of genes. The target genes are significantly enriched for Autism related genes. Our data challenge the established model of MECP2’s role in gene expression and suggest novel therapeutic approaches.

Decision and Behavior

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

Charting the fetal development of neural complexity

A novel tool to combat stress (-hormone receptor) signatures

Immature brain insults and possible effects on cholinergic system neuroplasticity

Metabolic Remodelling in the Developing Forebrain in Health and Disease

Little is known about the critical metabolic changes that neural cells have to undergo during development and how temporary shifts in this program can influence brain circuitries and behavior. Motivated by the identification of autism-associated mutations in SLC7A5, a transporter for metabolically essential large neutral amino acids (LNAAs), we utilized metabolomic profiling to investigate the metabolic states of the cerebral cortex across various developmental stages. Our findings reveal significant metabolic restructuring occurring in the forebrain throughout development, with specific groups of metabolites exhibiting stage-specific changes. Through the manipulation of Slc7a5 expression in neural cells, we discovered an interconnected relationship between the metabolism of LNAAs and lipids within the cortex. Neuronal deletion of Slc7a5 influences the postnatal metabolic state, resulting in a shift in lipid metabolism and a cell-type-specific modification in neuronal activity patterns. This ultimately gives rise to enduring circuit dysfunction.

Spatial and Single Cell Genomics for Next Generation Neuroscience

The advent of next generation sequencing ushered in a ten-year period of exuberant technology development, enabling the quantification of gene expression and epigenetic features within individual cells, and within intact tissue sections.  In this seminar, I will outline our technological contributions, beginning with the development of Drop-seq, a method for high-throughput single cell analysis, followed by the development of Slide-seq, a technique for measuring genome-wide expression at 10 micron spatial resolution.  Using a combination of these techniques, we recently constructed a comprehensive cell type atlas of the adult mouse brain, positioning cell types within individual brain structures.  I will discuss the major findings from this dataset, including emerging principles of neurotransmission, and the localization of disease gene signatures to specific cell types.  Finally, I will introduce a new spatial technology, Slide-tags, that unifies single cell and spatial genomics into a single, highly scalable assay.

Synaptic mechanisms of pattern completion in the hippocampal CA3 region

Freeze or flee ? New insights from rodent models of autism

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

How a fungus overcomes the defence of C. elegans

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.

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

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

Minute-scale periodic sequences in medial entorhinal cortex

The medial entorhinal cortex (MEC) hosts many of the brain’s circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience. While location is known to be encoded by a plethora of spatially tuned cell types in this brain region, little is known about how the activity of entorhinal cells is tied together over time. Among the brain’s most powerful mechanisms for neural coordination are network oscillations, which dynamically synchronize neural activity across circuit elements. In MEC, theta and gamma oscillations provide temporal structure to the neural population activity at subsecond time scales. It remains an open question, however, whether similarly coordination occurs in MEC at behavioural time scales, in the second-to-minute regime. In this talk I will show that MEC activity can be organized into a minute-scale oscillation that entrains nearly the entire cell population, with periods ranging from 10 to 100 seconds. Throughout this ultraslow oscillation, neural activity progresses in periodic and stereotyped sequences. The oscillation sometimes advances uninterruptedly for tens of minutes, transcending epochs of locomotion and immobility. Similar oscillatory sequences were not observed in neighboring parasubiculum or in visual cortex. The ultraslow periodic sequences in MEC may have the potential to couple its neurons and circuits across extended time scales and to serve as a scaffold for processes that unfold at behavioural time scales.

Meta-learning functional plasticity rules in neural networks

Synaptic plasticity is known to be a key player in the brain’s life-long learning abilities. However, due to experimental limitations, the nature of the local changes at individual synapses and their link with emerging network-level computations remain unclear. I will present a numerical, meta-learning approach to deduce plasticity rules from either neuronal activity data and/or prior knowledge about the network's computation. I will first show how to recover known rules, given a human-designed loss function in rate networks, or directly from data, using an adversarial approach. Then I will present how to scale-up this approach to recurrent spiking networks using simulation-based inference.

The medial prefrontal cortex replays generalized sequences

Whilst spatial navigation is a function ascribed to the hippocampus, flexibly adapting to a change in rule depends on the medial prefrontal cortex (mPFC). Single-units were recorded from the hippocampus and mPFC of rats shifting between a spatially- and cue-guided rule on a plus-maze. The mPFC population coded for the relative position between start and goal arm. During awake immobility periods, the mPFC replayed organized sequences of generalized positions which positively correlated with rule-switching performance. Conversely, hippocampal replay negatively correlated with performance and occurred independently of mPFC replay. Sequential replay in the hippocampus and mPFC may thus serve different functions.

Probabilistic simplicity in the study of sensory systems

Taking the pulse of ageing: the role of cerebrovascular risk factors in ageing and dementia

Cerebrovascular support is critical for healthy cognitive ageing. Reduced cerebral blood flow in ageing is caused, among other things, by hypertension, arteriosclerosis (i.e. stiffening of the arteries) and plaque formation. Arterial stiffness is predictive of cognitive decline, is a critical risk factor for cerebrovascular accidents, and has been linked to heightened risks for Alzheimer’s Disease and other forms of dementia. The elasticity of cerebral arteries is influenced by lifestyle factors, including cardiorespiratory fitness. Monica will discuss data obtained in their laboratory with new noninvasive measures of cerebrovascular health (pulse-DOT, a diffuse optical tomographic method for studying cerebral arteriosclerosis), in conjunction with structural and functional brain measures and cognitive assessments. These findings support a model in which localised changes in arteriosclerosis lead to specific profiles of structural, functional, and cognitive declines, paving a way to individualised interventions.

Why dendrites matter for biological and artificial circuits

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.

Lifelong Learning AI via neuro inspired solutions

AI embedded in real systems, such as in satellites, robots and other autonomous devices, must make fast, safe decisions even when the environment changes, or under limitations on the available power; to do so, such systems must be adaptive in real time. To date, edge computing has no real adaptivity – rather the AI must be trained in advance, typically on a large dataset with much computational power needed; once fielded, the AI is frozen: It is unable to use its experience to operate if environment proves outside its training or to improve its expertise; and worse, since datasets cannot cover all possible real-world situations, systems with such frozen intelligent control are likely to fail. Lifelong Learning is the cutting edge of artificial intelligence - encompassing computational methods that allow systems to learn in runtime and incorporate learning for application in new, unanticipated situations. Until recently, this sort of computation has been found exclusively in nature; thus, Lifelong Learning looks to nature, and in particular neuroscience, for its underlying principles and mechanisms and then translates them to this new technology. Our presentation will introduce a number of state-of-the-art approaches to achieve AI adaptive learning, including from the DARPA’s L2M program and subsequent developments. Many environments are affected by temporal changes, such as the time of day, week, season, etc. A way to create adaptive systems which are both small and robust is by making them aware of time and able to comprehend temporal patterns in the environment. We will describe our current research in temporal AI, while also considering power constraints.

INC Day 2022: Neuroethics

Organized by the INC in partnership with the BioMedical Engineering Paris international Master’s program and the NeuroParis Master’s programs and is supported by the Faculty of Sciences of Paris Cité University and the Graduate school Psychological science.

AI-assisted language learning: Assessing learners who memorize and reason by analogy

Vocabulary learning applications like Duolingo have millions of users around the world, but yet are based on very simple heuristics to choose teaching material to provide to their users. In this presentation, we will discuss the possibility to develop more advanced artificial teachers, which would be based on modeling of the learner’s inner characteristics. In the case of teaching vocabulary, understanding how the learner memorizes is enough. When it comes to picking grammar exercises, it becomes essential to assess how the learner reasons, in particular by analogy. This second application will illustrate how analogical and case-based reasoning can be employed in an alternative way in education: not as the teaching algorithm, but as a part of the learner’s model.

September webinar

Time as its own representation? Exploring a link between timing of cognition and time perception

The way we represent and perceive time has crucial implications for studying temporality in conscious experience. Contrasting positions posit that temporal information is separately abstracted out like any other perceptual property, or that time is represented through representations having temporal properties themselves. To add to this debate, we investigated alterations in felt time in conditions where only conscious visual experience is altered while a bistable figure remains physically unchanged. In this talk, I will discuss two studies that we have done in relation to answering this question. In study 1, we investigated whether perceptual switches in fixed intervals altered felt time. In three experiments we showed that a break in visual experience (via a perceptual switch) also leads to a break in felt time. In study 2, we are currently looking at figure-ground perception in ambigous displays. Here, in experiment 1 we show that differences in flicker frequencies on ambigous regions can induce figure-ground segregation. To see if a reverse complementarity exists for felt time, we ask participants to view ambigous regions as figure/ground and show that they have different temporal resolutions for the same region based on whether it is seen as figure or background. Overall, the two studies provide evidence for temporal mirroring and isomorphism in visual experience, arguing for a link between the timing of experience and time perception.

Learning static and dynamic mappings with local self-supervised plasticity

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

Learning with less labels for medical image segmentation

Accurate segmentation of medical images is a key step in developing Computer-Aided Diagnosis (CAD) and automating various clinical tasks such as image-guided interventions. The success of state-of-the-art methods for medical image segmentation is heavily reliant upon the availability of a sizable amount of labelled data. If the required quantity of labelled data for learning cannot be reached, the technology turns out to be fragile. The principle of consensus tells us that as humans, when we are uncertain how to act in a situation, we tend to look to others to determine how to respond. In this webinar, Dr Mehrtash Harandi will show how to model the principle of consensus to learn to segment medical data with limited labelled data. In doing so, we design multiple segmentation models that collaborate with each other to learn from labelled and unlabelled data collectively.

The role of astroglia-neuron interactions in generation and spread of seizures

Astroglia-neuron interactions are involved in multiple processes, regulating development, excitability and connectivity of neural circuits. Accumulating number of evidences highlight a direct connection between aberrant astroglial genetics and physiology in various forms of epilepsies. Using zebrafish seizure models, we showed that neurons and astroglia follow different spatiotemporal dynamics during transitions from pre-ictal to ictal activity. We observed that during pre-ictal period neurons exhibit local synchrony and low level of activity, whereas astroglia exhibit global synchrony and high-level of calcium signals that are anti correlated with neural activity. Instead, generalized seizures are marked by a massive release of astroglial glutamate release as well as a drastic increase of astroglia and neuronal activity and synchrony across the entire brain. Knocking out astroglial glutamate transporters leads to recurrent spontaneous generalized seizures accompanied with massive astroglial glutamate release. We are currently using a combination of genetic and pharmacological approaches to perturb astroglial glutamate signalling and astroglial gap junctions to further investigate their role in generation and spreading of epileptic seizures across the brain.

Imperial Neurotechnology 2022 - Annual Research Symposium

A diverse mix of neurotechnology talks and posters from researchers at Imperial and beyond. Visit our event page to find out more. The event is in-person but talk sessions will be broadcast via Teams.

The 15th David Smith Lecture in Anatomical Neuropharmacology: Professor Tim Bliss, "Memories of long term potentiation

The David Smith Lectures in Anatomical Neuropharmacology, Part of the 'Pharmacology, Anatomical Neuropharmacology and Drug Discovery Seminars Series', Department of Pharmacology, University of Oxford. The 15th David Smith Award Lecture in Anatomical Neuropharmacology will be delivered by Professor Tim Bliss, Visiting Professor at UCL and the Frontier Institutes of Science and Technology, Xi’an Jiaotong University, China, and is hosted by Professor Nigel Emptage. This award lecture was set up to celebrate the vision of Professor A David Smith, namely, that explanations of the action of drugs on the brain requires the definition of neuronal circuits, the location and interactions of molecules. Tim Bliss gained his PhD at McGill University in Canada. He joined the MRC National Institute for Medical Research in Mill Hill, London in 1967, where he remained throughout his career. His work with Terje Lømo in the late 1960’s established the phenomenon of long-term potentiation (LTP) as the dominant synaptic model of how the mammalian brain stores memories. He was elected as a Fellow of the Royal Society in 1994 and is a founding fellow of the Academy of Medical Sciences. He shared the Bristol Myers Squibb award for Neuroscience with Eric Kandel in 1991, the Ipsen Prize for Neural Plasticity with Richard Morris and Yadin Dudai in 2013. In May 2012 he gave the annual Croonian Lecture at the Royal Society on ‘The Mechanics of Memory’. In 2016 Tim, with Graham Collingridge and Richard Morris shared the Brain Prize, one of the world's most coveted science prizes. Abstract: In 1966 there appeared in Acta Physiologica Scandinavica an abstract of a talk given by Terje Lømo, a PhD student in Per Andersen’s laboratory at the University of Oslo. In it Lømo described the long-lasting potentiation of synaptic responses in the dentate gyrus of the anaesthetised rabbit that followed repeated episodes of 10-20Hz stimulation of the perforant path. Thus, heralded and almost entirely unnoticed, one of the most consequential discoveries of 20th century neuroscience was ushered into the world. Two years later I arrived in Oslo as a visiting post-doc from the National Institute for Medical Research in Mill Hill, London. In this talk I recall the events that led us to embark on a systematic reinvestigation of the phenomenon now known as long-term potentiation (LTP) and will then go on to describe the discoveries and controversies that enlivened the early decades of research into synaptic plasticity in the mammalian brain. I will end with an observer’s view of the current state of research in the field, and what we might expect from it in the future.

Social immunity in ants: disease defense of the colony

Social insects fight disease as a collective. Their colonies are protected against disease by the combination of the individual immune defenses of all colony members and their jointly performed nest- and colony-hygiene. This social immunity is achieved by cooperative behaviors to reduce pathogen load of the colony and to prevent transmission along the social interaction networks of colony members. Individual and social immunity interact: performance of sanitary care can affect future disease susceptibility, yet also vice versa, individuals differing in susceptibility adjust their sanitary care performance to their individual risk of infection. I present the integrated approach we use to understand how colony protection arises from the individual and collective actions of colony members and how it affects pathogen communities and hence disease ecology.

Light-induced moderations in vitality and sleep in the field

Retinal light exposure is modulated by our behavior, and light exposure patterns show strong variations within and between persons. Yet, most laboratory studies investigated influences of constant lighting settings on human daytime functioning and sleep. In this presentation, I will discuss a series of studies investigating light-induced moderations in sleepiness, vitality and sleep, with a strong focus on the temporal dynamics in these effects, and the bi-directional relation between persons' light profiles and their behavior.

Let's talk about failure!

Try again. Fail again. Fail better. (Samuel Beckett)

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.

Remembering Immunity, Central regulation of peripheral immune processes

Thoughts and emotions can impact physiology. This connection is evident by the emergence of disease following stress, psychosomatic disorders, or recovery in response to placebo treatment. Nevertheless, this fundamental aspect of physiology remains largely unexplored. In this talk, I will focus on the brain’s involvement in regulating the peripheral immune response and explore the question of how the brain evaluates and represents the state of the immune system it regulates.

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

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

Network resonance: a framework for dissecting feedback and frequency filtering mechanisms in neuronal systems

Resonance is defined as a maximal amplification of the response of a system to periodic inputs in a limited, intermediate input frequency band. Resonance may serve to optimize inter-neuronal communication, and has been observed at multiple levels of neuronal organization including membrane potential fluctuations, single neuron spiking, postsynaptic potentials, and neuronal networks. However, it is unknown how resonance observed at one level of neuronal organization (e.g., network) depends on the properties of the constituting building blocks, and whether, and if yes how, it affects the resonant and oscillatory properties upstream. One difficulty is the absence of a conceptual framework that facilitates the interrogation of resonant neuronal circuits and organizes the mechanistic investigation of network resonance in terms of the circuit components, across levels of organization. We address these issues by discussing a number of representative case studies. The dynamic mechanisms responsible for the generation of resonance involve disparate processes, including negative feedback effects, history-dependence, spiking discretization combined with subthreshold passive dynamics, combinations of these, and resonance inheritance from lower levels of organization. The band-pass filters associated with the observed resonances are generated by primarily nonlinear interactions of low- and high-pass filters. We identify these filters (and interactions) and we argue that these are the constitutive building blocks of a resonance framework. Finally, we discuss alternative frameworks and we show that different types of models (e.g., spiking neural networks and rate models) can show the same type of resonance by qualitative different mechanisms.

Remembering immunity: Neuronal representation of immune responses

Accumulating data indicate that the brain can affect immunity, as evidenced, for example, by the effects of stress, stroke, and reward system activity on the peripheral immune system. However, our understanding of this neuroimmune interaction is still limited. Importantly, we do not know how the brain evaluates and represents the state of the immune system. In this talk, I will present our latest study from our lab, designed to test the existence of immune-related information in the brain and determine its relevance to immune regulation. We hypothesized that the InsCtx, specifically the posterior InsCtx (as a primary cortical site of interoception in the brain), is especially suited to contain such a representation of the immune system. Using activity-dependent cell labeling in mice (FosTRAP), we captured neuronal ensembles in the InsCtx that were active under two different inflammatory conditions (dextran sulfate sodium [DSS]-induced colitis and zymosan-induced peritonitis). Chemogenetic reactivation of these neuronal ensembles was sufficient to broadly retrieve the inflammatory state under which these neurons were captured. Moreover, using retrograde neuronal tracing, we found an anatomical efferent pathway linking these InsCtx neurons to the inflamed peripheral sites. Taken together, we show that the brain can store and retrieve specific immune responses, extending the classical concept of immunological memory to neuronal representations of inflammatory information.

‘Studying cortical development through the lens of human disorders’

The neuroscience of lifestyle interventions for mental health: the BrainPark approach

Our everyday behaviours, such as physical activity, sleep, diet, meditation, and social connections, have a potent impact on our mental health and the health of our brain. BrainPark is working to harness this power by developing lifestyle-based interventions for mental health and investigating how they do and don’t change the brain, and for whom they are most effective. In this webinar, Dr Rebecca Segrave and Dr Chao Suo will discuss BrainPark’s approach to developing lifestyle-based interventions to help people get better control of compulsive behaviours, and the multi-modality neuroimaging approaches they take to investigating outcomes. The webinar will explore two current BrainPark trials: 1. Conquering Compulsions - investigating the capacity of physical exercise and meditation to alter reward processing and help people get better control of a wide range of unhelpful habits, from drinking to eating to cleaning. 2. The Brain Exercise Addiction Trial (BEAT) - an NHMRC funded investigation into the capacity of physical exercise to reverse the brain harms caused by long-term heavy cannabis use. Dr Rebecca Segrave is Deputy Director and Head of Interventions Research at BrainPark, the David Winston Turner Senior Research Fellow within the Turner Institute for Brain and Mental Health, and an AHRPA registered Clinical Neuropsychologist. Dr Chao Suo is Head of Technology and Neuroimaging at BrainPark and a Research Fellow within the Turner Institute for Brain and Mental Health.

Learning with dendrites in brains and machine

Assessing the role of α7 nicotinic acetylcholine receptors in executive function using touchscreen technology in rat models

Magnesium fluoride thin films as cover layer for multi-electrode array technology aiming to combine neuronal network recording and super-resolution microscopy

Designing a transmodal technology to feel sound through touch: The multichannel vibrotactile gloves

FENS Forum 2024

Exploring social hierarchies: An experimental study using RFID technology in mice

FENS Forum 2024

Investigating design parameters for improved tissue integration in brain-computer-interface technology

FENS Forum 2024

Organoid technology: A new way to model ischemic stroke

FENS Forum 2024

Three-dimensional structural analysis of GABAergic neurons in the mouse claustrum using tissue-clearing technology

FENS Forum 2024

Unravelling the role of prefrontal α7 nicotinic acetylcholine receptors in inhibitory control in physiological and pathological contexts: A behavioral investigation using touchscreen technology

FENS Forum 2024