Project Summary: Programmed inflammatory cell death, or pyroptosis, is a crucial innate defense mechanism that protects hosts against infection and orchestrates subsequent immune responses. Central to this process is Gasdermin D (GSDMD), a protein that forms plasma membrane pores upon activation, enabling the release of pro- inflammatory cytokines such as IL-1β and driving cell lysis. Although GSDMD-mediated pyroptosis has been conventionally understood to be controlled mainly at the post-translational level, through proteolytic cleavage by inflammatory caspases, we have discovered compelling evidence that alternative RNA processing may introduce additional, previously unappreciated complexity in GSDMD regulation. Our laboratories have developed and optimized a highly innovative long-read direct RNA sequencing pipeline, which bypasses conventional cDNA synthesis to avoid artifacts and enables unbiased discovery of native chimeric mRNA (chRNA) in mammalian cells. Using this approach, we have uncovered a remarkably diverse repertoire of chRNA species, including over a thousand unique fusions in murine macrophages and more than two thousand in human inflamed tissues. Among the chRNA found in mice, we identified a chRNA joining the effector domain of GSDMD with a novel C-terminal region encoded by Tmem106a, giving rise to the GSDMD:TMEM106A fusion protein. Functional studies demonstrate that GSDMD:TMEM106A is not only produced in response to inflammatory signals in macrophages but is critical for GSDMD-dependent cytokine release and optimal pyroptosis. Genetic loss of GSDMD:TMEM106A in mice results in reduced cytokine secretion and increased susceptibility to bacterial infection, while in vivo delivery of Gsdmd:Tmem106a mRNA is sufficient for protective immunity. Intriguingly, we have also identified a putative human counterpart, GSDMD:S100A6, which is highly inducible in colon biopsies from patients with inflammatory bowel disease. In this application, we propose a comprehensive exploration of this newly defined class of naturally occurring GSDMD fusion proteins. The specific aims are: (1) to elucidate the subcellular localization, protein-protein interactions, and pore-forming function of GSDMD:TMEM106A during canonical and non-canonical inflammasome activation; (2) to determine the transcriptomic, proteomic, and physiological consequences of GSDMD chRNA expression in vivo during infection, sepsis, and inflammatory disease, and to validate and functionally characterize GSDMD:S100A6 in relevant immune and barrier cell populations. Collectively, this work will establish chimeric splicing as a fundamental source of immunoregulatory protein diversity, redefining the landscape of cell death control in the immune system. By revealing new layers of gasdermin regulation and function, our studies have the potential to identify novel therapeutic strategies for infectious, auto-inflammatory, and immune-mediated diseases.

RNA degradation was thought to proceed through endonucleolytic fragmentation, followed by exo- ribonuclease trimming which generate short RNA fragments that are turned over into mononucleotides by oligoribonuclease (Orn). In the last funding period, we published data supporting that only specific enzymes (Orn, NrnA, NrnB, and NrnC) cleave diribonucleotides into monoribonucleotides, and that prokaryotic organisms need to encode at least one diribonuclease to fulfill this specific function. These results support a new perspective on RNA degradation in which the short oligoribonucleotides are processed through a sequence of discrete steps involving distinct enzymes. In addition, linear diribonucleotides appear to be biologically active molecules since we reported that mutants lacking these enzymes accumulate diribonucleotides and have altered cell growth, biofilm formation, motility, and sporulation. Here we present additional preliminary data supporting diribonucleotides as active signaling molecules in the cell including: 1. Specific enzymes act trinucleases to generate diribonucleotides, 2. RNase AM of Pseudomonas aeruginosa ∆orn is a cryptic diribonuclease, 3. Two enzymes in central metabolism are diribonucleotide- binding proteins, and 4. P. aeruginosa ∆orn has virulence defects in an animal model of catheter-associated urinary tract infection. Our past publications and preliminary data provide the scientific premise for our hypothesis that cells generate linear dinucleotides from RNA degradation and linearization of cyclic dinucleotides, which can bind target proteins to alter cell physiology and pathogenesis. To test these aims, we will perform the following specific aims: In Aim 1, we will characterize the generation and degradation of diribonucleotides by characterizing how diribonucleases and triribonucleases bind their respective substrates through molecular biology, biochemistry, and computational docking. In Aim 2, we will identify effects of dinucleotides on bacterial metabolism and physiology by characterizing the binding proteins that specifically interact with linear diribonucleotides. Building on our success of identifying cellular diribonucleotide receptors, we will screen for additional proteins from open reading libraries of P. aeruginosa and Bacillus anthracis. We will exploit the strains available to us that lack all diguanylate cyclases to reveal whether the effect of linear diribonucleotides is independent of c-di-GMP signaling. In Aim 3, we will characterize the effect of expression levels of dinucleases and the effect of dinucleotide accumulation on bacterial physiology and pathogenesis. We will develop mass spectrometry methods to detect di- and triribonucleotides. We will employ existing mutants lacking diribonucleases, including P. aeruginosa ∆orn to study the defects in chronic infection in a murine model of catheter-associated urinary tract infection. Results from these studies will advance our understanding of RNA degradation and open a new area of signaling by linear diribonucleotides with the potential to be applied to novel antibacterial strategies.

SUMMARY Clostridioides difficile infection (CDI) is a leading cause of healthcare-associated diarrhea, with rising incidence in community settings and a growing burden of asymptomatic colonization. Asymptomatic car- riers, particularly among the elderly and individuals consuming high-sugar diets, represent a critical but underexplored reservoir for transmission and disease progression. This proposal introduces novel, anti- biotic-independent mouse models demonstrating that both dietary sugar and aging independently pro- mote asymptomatic C. difficile colonization. We hypothesize that these factors disrupt colonization re- sistance (CR) through distinct but overlapping microbial, metabolic, and immune pathways. In Aim 1, we will define how traditional and emerging dietary sugars alter the gut environment to permit C. difficile colonization using in vitro bioreactors and in vivo models. Aim 2 will identify age-associated changes in microbiota and mucosal immunity that impair CR, using longitudinal studies and fecal micro- biota transfer. Aim 3 will functionally validate C. difficile genes upregulated during asymptomatic carriage using CRISPR-Cas9 mutants in both sugar- and age-induced models. This integrative, multi-omics approach will uncover the mechanisms enabling asymptomatic colonization and identify microbial and host targets for intervention. The findings will inform microbiome-based strat- egies to prevent CDI in vulnerable populations and shift current paradigms in CDI risk assessment and prevention.

It is important to characterize how HIV-1 proteins fulfill their functions in order to develop new approaches for curtailing the AIDS epidemic. One of the remaining frontiers of HIV-1 research concerns the mechanisms by which the HIV-1 matrix (MA) and envelope (Env) proteins collaborate with each other to ensure the assembly of infectious viruses. The HIV-1 MA protein directs the delivery of precursor Gag (PrGag) proteins to the plasma membranes (PMs) of infected cells, and drives the formation of lipid raft-like, liquid ordered (Lo) membrane domains. This membrane reorganization attracts a number of proteins that favor lipid raft-type microdomains. Such proteins appear to assemble into virus particles as innocent bystanders, and this appears to be how Env proteins that carry cytoplasmic tail deletions (CT) can be incorporated into virions. In contrast, wild type (WT) Env proteins additionally require an interaction with MA proteins to assemble into viruses. This is most easily understood in the context of the lattice that MA proteins construct at the PMs of infected cells. In particular, multiple lines of evidence imply that the CTs of WT Env proteins are trapped by MA lattices in immature, assembling virus particles, and then are released after assembled viruses are processed into their mature forms. Despite a seeming consensus on the MA-Env interaction steps, there are a number of very significant unknowns. Using our recent and preliminary results as a foundation, and taking advantage of the unique expertise of our collaborators, we propose the characterization of WT and mutant MA lattices, and of interactions of MA and Env with each other, and with membrane lipids. Our results will help clarify how MA and Env cooperate; they will illuminate aspects of host cell protein-membrane interactions; and they will foster the development of new approaches to intefere with HIV-1 replication.

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

ABSTRACT Despite remarkable advances in HIV cure science, emerging cure candidates will likely involve trade-offs (e.g., incomplete eradication, monitoring burdens) and must compete with increasingly convenient long-acting ART; without early implementation guidance, even efficacious products may see limited uptake, particularly among the ~30–40% of people with HIV (PWH) in the U.S. who are not durably suppressed. We propose REALISE, a multidisciplinary program to define plausible cure profiles, quantify end-user preferences, and project population-level impact to inform product design and policy before market entry. Aim 1 conducts qualitative interviews with ~30 researchers and developers to delineate credible 10–20-year cure and long-acting treatment scenarios (eradication vs functional control, safety, monitoring, durability), yielding bounded “target product profiles.” Aim 2 elicits patient-centered preferences through a two-stage study: formative interviews (n=60; ≥50% not virally suppressed) to identify salient attributes; best-worst scaling (n=360 across Missouri, Georgia, and San Francisco) to prioritize attributes; and a discrete choice experiment (n=360) to quantify trade-offs versus alternative therapies, with latent class analysis to identify preference segments and estimate potential reach. Aim 3 integrates preference-based uptake from Aim 2 with Aim 1 efficacy and cost inputs in a mathematical model to estimate health impact, QALYs, net QALYs, and incremental cost-effectiveness across heterogeneous populations and Ending the HIV Epidemic jurisdictions. Innovation lies in linking cure R&D horizons to end-user preferences and transmission-dynamic outcomes, an approach that anticipates real-world use rather than retrofitting after approval. Deliverables include ranked cure attributes for product optimization, uptake projections including among unsuppressed PWH, and jurisdiction-specific value assessments to guide public health investment. By aligning cure design with what patients will accept and systems can sustain, REALISE will accelerate effective deployment of future cure strategies and maximize their contribution to Ending the HIV Epidemic. In doing so, this study advances NIH's priorities by connecting implementation science with prevention, treatment, and cure research. Using a multidisciplinary strategy to refine and extend `target product profiles,' REALISE will ensure cure development reflects patient needs and accelerate translation into real-world benefit.

Project Summary/Abstract Sexually transmitted bacteria diseases caused by Chlamydia trachomatis (Ctr) and Neisseria gonorrhoeae (NG) are the two most common sexually transmitted bacterial diseases. The infections caused by these pathogens may result in infertility, ectopic pregnancy, blindness, and perinatal mortality. Over 1.70 M cases of chlamydia and 0.65 M cases of drug-resistant gonorrhea are reported yearly in the US. Women with gonorrhea are co- infected with chlamydia in 17.6%–57.9% of cases, while women with chlamydia are co-infected with gonorrhea in 2.1%–17.2% of cases. These infections are treated with broad spectrum antibiotics, which can favor the development of resistance on NG/CTr but also in other bacteria, or damage the microbiota, diminishing its protective function and allowing bacteria and viruses to infect the patient. The Caseinolytic protease (ClpP) proteolytic machinery regulates protein turnover and homeostasis and is key in bacterial growth and development The machinery consists of the proteolytic unit (the ClpP) and its chaperone (ClpX), which transports proteins to be degraded, and it is termed the ClpXP. Our theory is that molecules that inhibit the action of the ClpX chaperone can become efficient antibacterial agents against both pathogens. We have found that the dihydrothiazepines can erradicate both pathogens and prevent the action of the ClpXP complex. Our goal is to advance the dihydrothiazepines as selective agents against Ctr and NG infections. To develop these therapeutic agents, we have envisioned four specific aims. Specific Aim 1. Synthesis and Optimization of the Pharmacophore. Our goal is to use computational models to design dihydrothiazepines molecule that will be synthesized, purified, and characterized using chemical techniques. The molecules will be tested against Ctr and NG and their toxicity against human cells evaluated. Also, we will determine their effect in other bacterial, including those from the microbiota. Specific Aim 2. Assessment of Stability and In Vivo Activity. We will study the stability of the most active molecules under various conditions. Then, we will study the pharmacokinetics, biodistribution , and antibacterial activity against Ctr and NG in mice. Specific Aim 3. Target Validation and Effect. We will study the ability of the compounds to inhibit the activity of ClpX using a luciferase assay and to block protein degradation. We will try grow crystal of the protein and the molecule and will study if the molecules prevent the assembly of the ClpXP system. Finally, we will assess the ability of the bacteria to develop resistance to the molecules.

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.

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

Project Summary/Abstract Sepsis is a life-threatening condition characterized by a dysregulated host response to infection that can cause multi-organ damage and death. As the leading cause of in-hospital mortality, sepsis mortality rates reach up to 50%, and account for approximately 270,000 deaths and $38 billion annually in health care costs in the United States. Notably, patients with similar medical backgrounds can have vastly different sepsis outcomes— some survive with medical treatment while others die. The reasons for this dichotomy are unknown but is seen across all forms of bacterial bloodstream infections, is not specific to any strain-level differences in the infecting pathogen and cannot be explained by human genetic differences. Human microbiota studies suggest that gut microbial dysbiosis is associated with sepsis mortality and that these alterations influence gut barrier breakdown, leading to gram-negative bacteremia—one of the most common causes of sepsis and mortality. However, there are a lack of studies that investigate the causal role of the intestinal microbiota in sepsis mortality. This K08 proposal will elucidate the role of the intestinal microbiota in sepsis mortality. Utilizing the well- established murine model of sepsis by intraperitoneal injection of lipopolysaccharide (LPS), we combine microbiota taxonomic sequencing and metagenomics, advanced bioinformatic techniques and prediction modeling, with knowledge of mucosal immunity and germ-free mouse systems to characterize the microbiota features and members that correlate with, predict, and cause sepsis mortality. This proposal is organized into two specific aims: (1) identify baseline stool microbial features associated with and predictive of sepsis outcomes and (2) determine how colonization with immunostimulatory microbes heightens sepsis mortality. In this work, I will holistically characterize the host immunologic and microbiota features that are associated with and predictive of mortality and experimentally identify microbes and microbial pathways that cause death in our model. These findings will reveal new microbial and host biomarkers of sepsis mortality and identify novel targets for sepsis prevention and treatment to reduce the overall mortality rate of this deadly disease. My long-term goal is to become an independent physician-scientist who integrates cutting-edge computational methods with experimental biology to identify predictive biomarkers of disease onset and outcomes, investigate how they influence disease processes, and develop novel therapeutic and preventive strategies to improve patient care. This proposal details specific research aims and a structured career development and training plan that will allow me to acquire focused, in-depth and multidisciplinary training under the guidance of an internationally recognized team of experts in clinical infectious diseases, host-microbiota interactions, immunology, immunometabolism, and computational biology. The knowledge generated will address the fundamental role of the microbiota in sepsis outcomes and inform future preventative and therapeutic strategies that will lower the sepsis mortality rate worldwide.

Europe’s leading neuroscience conference, bringing together researchers, clinicians, and innovators across molecular, cellular, systems, cognitive, and clinical neuroscience.

Arterial spin labeling (ASL) MRI has become a vital tool in clinical neuroimaging, enabling noninvasive assessment of cerebral perfusion across a range of conditions including stroke, vascular malformations, and brain tumors. With broader clinical adoption, its practical strengths — as well as important limitations — have become increasingly clear.

Although stress can be considered as an ongoing process that helps an organism to cope with present and future challenges, when it is too intense or uncontrollable, it can lead to adverse consequences for physical and mental health. Social stress specifically, is a highly prevalent traumatic experience, present in multiple contexts, such as war, bullying and interpersonal violence, and it has been linked with increased risk for major depression and anxiety disorders. Nevertheless, not all individuals exposed to strong stressful events develop psychopathology, with the mechanisms of resilience and vulnerability being still under investigation. During this talk, I will identify key gaps in our knowledge about stress vulnerability and I will present our recent data from our contextual fear learning protocol based on social defeat stress in mice.

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

Traditionally, touch is associated with exteroception and is rarely considered a relevant sensory cue for controlling movements in space, unlike vision. We developed a technique to isolate and measure tactile involvement in controlling sliding finger movements over a surface. Young adults traced a 2D shape with their index finger under direct or mirror-reversed visual feedback to create a conflict between visual and somatosensory inputs. In this context, increased reliance on somatosensory input compromises movement accuracy. Based on the hypothesis that tactile cues contribute to guiding hand movements when in contact with a surface, we predicted poorer performance when the participants traced with their bare finger compared to when their tactile sensation was dampened by a smooth, rigid finger splint. The results supported this prediction. EEG source analyses revealed smaller current in the source-localized somatosensory cortex during sensory conflict when the finger directly touched the surface. This finding supports the hypothesis that, in response to mirror-reversed visual feedback, the central nervous system selectively gated task-irrelevant somatosensory inputs, thereby mitigating, though not entirely resolving, the visuo-somatosensory conflict. Together, our results emphasize touch’s involvement in movement control over a surface, challenging the notion that vision predominantly governs goal-directed hand or finger movements.

Over the last 20 years, neuroimaging and electrophysiology techniques have become central to understanding the mechanisms that accompany loss and recovery of consciousness. Much of this research is performed in the context of healthy individuals with neurotypical brain dynamics. Yet, a true understanding of how consciousness emerges from the joint action of neurons has to account for how severely pathological brains, often showing phenotypes typical of unconsciousness, can nonetheless generate a subjective viewpoint. In this presentation, I will start from the context of Disorders of Consciousness and will discuss recent work aimed at finding generalizable signatures of consciousness that are reliable across a spectrum of brain electrophysiological phenotypes focusing in particular on the notion of edge-of-chaos criticality.

Predictive processing offers a unifying view of neural computation, proposing that brains continuously anticipate sensory input and update internal models based on prediction errors. In this talk, I will present converging evidence for the computational mechanisms underlying this framework across human neuroscience and deep neural networks. I will begin with recent work showing that large-scale distributed prediction-error encoding in the human brain directly predicts how sensory representations reorganize through predictive learning. I will then turn to PredNet, a popular predictive coding inspired deep network that has been widely used to model real-world biological vision systems. Using dynamic stimuli generated with our Spatiotemporal Style Transfer algorithm, we demonstrate that PredNet relies primarily on low-level spatiotemporal structure and remains insensitive to high-level content, revealing limits in its generalization capacity. Finally, I will discuss new recurrent vision models that integrate top-down feedback connections with intrinsic neural variability, uncovering a dual mechanism for robust sensory coding in which neural variability decorrelates unit responses, while top-down feedback stabilizes network dynamics. Together, these results outline how prediction error signaling and top-down feedback pathways shape adaptive sensory processing in biological and artificial systems.

The Nature versus Nurture debate has generally been considered from the lens of genome versus experience dichotomy and has dominated our thinking about behavioral individuality and personality traits. In contrast, the role of nonheritable noise during brain development in behavioral variation is understudied. Using the Drosophila melanogaster visual system, I will discuss our efforts to dissect how individuality in circuit wiring emerges during development, and how that helps generate individual behavioral variation.

Accurate perception of the environment is a constructive process that requires integration of external bottom-up sensory signals with internally-generated top-down information reflecting past experiences and current aims. Decades of work have elucidated how sensory neocortex processes physical stimulus features. In contrast, examining how memory-related-top-down information is encoded and integrated with bottom-up signals has long been challenging. Here, I will discuss our recent work pinpointing the outermost layer 1 of neocortex as a central hotspot for processing of experience-dependent top-down information threat during perception, one of the most fundamentally important forms of sensation.

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

The COSYNE 2025 conference was held in Montreal with post-conference workshops in Mont-Tremblant, continuing to provide a premier forum for computational and systems neuroscience. Attendees exchanged cutting-edge research in a single-track main meeting and in-depth specialized workshops, reflecting Cosyne’s mission to understand how neural systems function.

Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. Bernstein Conference 2024, held in Frankfurt am Main, featured discussions, keynote lectures, and poster sessions, and has established itself as one of the most renowned conferences worldwide in this field.

Organised by FENS in partnership with the Austrian Neuroscience Association and the Hungarian Neuroscience Society, the FENS Forum 2024 will take place on 25–29 June 2024 in Vienna, Austria. The FENS Forum is Europe’s largest neuroscience congress, covering all areas of neuroscience from basic to translational research.

The COSYNE 2023 conference provided an inclusive forum for exchanging experimental and theoretical approaches to problems in systems neuroscience, continuing the tradition of bringing together the computational neuroscience community. The main meeting was held in Montreal followed by post-conference workshops in Mont-Tremblant, fostering intensive discussions and collaboration.

Neuromatch 5 (Neuromatch Conference 2022) was a fully virtual conference focused on computational neuroscience broadly construed, including machine learning work with explicit biological links. After four successful Neuromatch conferences, the fifth edition consolidated proven innovations from past events, featuring a series of talks hosted on Crowdcast and flash talk sessions (pre-recorded videos) with dedicated discussion times on Reddit.

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.

Neuroinflammation is an early and dynamic feature of preclinical Alzheimer's disease (AD) that may influence amyloid-β (Aβ) pathology. Diffusion-weighted MRI (DWI) offers a sensitive means of probing subtle tissue alterations <em>in vivo</em>, particularly when combined with multi-compartment biophysical modelling. However, clinical datasets are often not acquired with protocols suited for advanced DWI models. Here, we present preliminary evidence of microstructural alterations in cognitively unimpaired preclinical AD participants and evaluate simulation-based inference (SBI) as a flexible framework for diffusion model estimation. DWI data from a subset of participants in the ALFA+ study was analysed. Participants were classified as Aβ-positive or Aβ-negative using cerebrospinal fluid Aβ_42/40cut-offs. Diffusion tensor and free-water imaging metrics were quantified in predefined white matter tracts and AD-signature cortical grey matter regions. Fractional anisotropy (FA), mean diffusivity (MD), and free-water fraction (FW_F) were estimated using conventional weighted least-squares fitting and SBI. Agreement between approaches was assessed using Lin’s concordance correlation coefficient (CCC, voxel-wise agreement) and the structural similarity index (SSIM, spatial correspondence). Following quality control, 179 datasets were available for analysis, including 68 Aβ-positive participants. Aβ-positive participants exhibited lower MD in the uncinate fasciculus and inferior temporal cortex. A significant Aβ-by-C-reactive protein interaction was observed for uncinate FW_F. SBI-derived diffusion maps showed excellent correspondence with conventional fitting (FA: CCC = 0.94, SSIM = 0.94), supporting its validity. These findings identify the uncinate fasciculus as a potential locus of early microstructural change and highlight SBI as a promising framework for future estimation of diffusion indices derived from multi-compartment biophysical DWI models.

Recognizing biological motion from Point Light Displays (PLDs) may rely on the brain’s ability to minimize prediction errors under uncertainty. Although transcranial direct current stimulation (tDCS) can modulate social perception, its computational mechanisms remain unclear. Using an Active Inference framework, we examined whether tDCS affects perceptual learning rates or decision precision.In addition, we are extending this paradigm by using PLD stimuli specifically designed to display non-biological motion, with the aim of testing whether Point Light Displays can provide an acceptable and reliable representation of non-biological movement, analogous to what has been demonstrated for biological motion.<br>Eleven healthy participants performed a Signal Detection Task involving PLD stimuli (Biological/Non-Biological, Goal/Non-Goal oriented) with varying levels of noise. Participants underwent four randomized stimulation conditions: Baseline, Sham, Anodal, and Cathodal tDCS, with stimulation targeting the ventral premotor cortex. Behavioral responses were analyzed trial by trial using a two-level Bayesian model. The perceptual component, inspired by the Hierarchical Gaussian Filter, described belief updating as a function of precision-weighted sensory uncertainty, whereas the response component mapped beliefs onto behavior through two parameters: Decision Threshold (τ), indexing response bias, and Sensitivity (ζ), indexing decision precision.<br>The model indicated that stimulation did not substantially modify perceptual belief trajectories or response bias, with τ remaining close to 0.5 across conditions. Compared to Sham, Anodal stimulation increased<br>Decision Sensitivity (ζ), suggesting a higher signal-to-noise ratio in the transformation of beliefs into actions.

COVID-19 during pregnancy can trigger maternal immune activation, potentially disrupting placental homeostasis and fetal neurodevelopment, with effects depending on gestational stage. Given the challenges to source fetal tissue, the brain-placenta axis allows us to use placenta to study neurodevelopment and its molecular mechanisms. This study aimed at exploring genes in fetal neurodevelopment and the placenta of pregnant people with COVID-19 and understanding its differences across two mid-gestation periods. We meta-analyzed six placenta transcriptome datasets from COVID-infected pregnant people. The network medicine-based method NERI integrated the meta-analysis results into the protein-protein interaction (PPI) network BIOGRID and two healthy neurodevelopmental transcriptome datasets with data at the 12-13 post-conceptional weeks (pcw) and 16-21 pcw stages, from regions corresponding to the dorsolateral prefrontal cortex (DLPFC) and the hippocampus. Genes prioritized by NERI were tested for enrichment of genes from the neurodevelopmental disorders (NDD) interactome and Gene Ontology (GO) terms. The meta-analysis identified 43 genes consistently altered in the placenta of COVID-infected pregnant people. Their integration with PPI and fetal transcriptomes selected 193 hippocampal and 192 DLPFC genes (Figure 1A). NDD interactome genes were enriched in the selected genes from both DLPFC (139 genes, p-val = 4.19∙10²⁵) and hippocampus (122 genes, p-val = 4.98∙10²⁰). The GO analyses revealed enrichment of terms related to TORC1, MAPK and NFκβ, and others associated to neurodevelopment (Figure 1B-C). These results indicate that gestational COVID-19 may influence neurodeveloment in a time-dependent manner. Our study presents candidate pathways for future research on how viral infections affect the developmental origins of NDDs.<br><br><img src="https://file.documedias.systems/download/5639736b-7d6e-4503-b338-d4d0759f154a" class="fr-fil fr-dib fr-draggable" alt="Panel A: Workflow showing data integration. Text: six placenta transcriptomes datasets, n = 66 pregnant with COVID-19 versus n = 35 pregnant without COVID-19. Blue arrow, Text: 43 genes consistenly altered across datasets. Blue arrows joining the texts: NERI method, PPI network, fetal neurodevelopment transcriptome at 12 to 13 pcw versus 16 to 21 pcw. Pointing at: Prioritized genes 192 DLPFC and 193 hippocampal. Panels B and C: Greyscale scatter plot showing top 15 Gene Ontology Biological Process terms enriched in the genes pioritized in the dorsolateral prefrontal cortex and the hippocampus. The x-axis indicates fold-enrichment, y-axis indicates the Gene Ontology terms, the grayscale indicates the p-value at the Fisher’s exact test, and dot size indicates the number of genes enriched in that term. Number of genes ranges from 5 to 27. Terms from the DLPFC ordered by fold enrichment (higher to lower): Protein refolding, Cellular response to heat, Negative regulation of autophagy, TORC1 signaling, Cellular response to nutriente levels, MAPK Cascade, Endocytosis, Protein folding, Pos. reg. of canonical NFκβ signal transduction, Chromatin remodeling, Chromatin organization, Neg. reg. of DNA-templated transcription, Protein transport, Neg. reg. Of trancription by RNA PolII, Pos.reg. Of transcription by RNA PolI. Terms from the hipoccampus ordered by fold enrichment (higher to lower): Schwann cell Development, Neg. reg. Of protein-containing complex assembly, Canonical NFκβ signal transduction, Cellular response to UV, TORC1 signaling, Cellular response to nutrient levels, Neg. reg. Of TGF-β receptor signaling pathway, MAPK Cascade, Rhythmic process, Intracellular protein localization, Chromatin remodelling, Neg. reg. Of apoptotic process, Intracellular protein transport, Pos. reg. Of DNA-templated transcription, Pos.reg. Of transcription by RNA PolI.">

Serotonin (5-HT) has a multitude of functions in the central nervous system and, in addition to modulating neuronal function, has also been reported to act as a morphogen during development and affect neurite extension. However, the precise molecular mechanisms that underlie the effect of 5-HT on neurite extension are not well characterised and the interpretation of studies in the intact nervous system is challenging due to the complexity of cellular interactions, which makes it difficult to differentiate between direct and indirect effects. In order to address whether activation of 5HT1A receptors expressed on cortical neurons directly affects neurite extension, we have studied the effect of the highly selective 5HT1A receptor agonist NLX-101 on neurite extension and the morphology of ‘pyramidal-like’ neurons in primary cultures of mouse cortical neurons. Single cell tracings revealed a concentration-dependent subtle, but significant increase in neurite extension. Interestingly, application of SCH-772984 to block the extracellular signal-regulated kinase (ERK) signalling pathway did not appear to prevent the growth promoting effect of 5HT1A receptor activation. Instead, SCH-772984 mimicked the effect of 5HT1A receptor activation, and even on its own promoted neurite extension in primary cortical neurons. Thus, we suggest that 5HT1A receptor effects on neurite growth may not be mediated via the activation of ERK as suggested based on work in non-neuronal cells and immortalised hippocampal HN2-5 cells (Rojas PS and Fiedler JL, 2016, Front. Cell. Neurosci. 10:272. doi: 10.3389/fncel.2016.00272), but via some alternative signalling pathway, likely related to its effect on intracellular cAMP concentrations.

Linking word forms to their meanings is a fundamental aspect of language learning [1]. Transcranial direct current stimulation (tDCS) has shown promise in supporting this process, although its effects have been inconsistent [2]. This study aimed to identify reliable and functionally meaningful cortical targets for tDCS to enhance novel word learning, and to evaluate the test–retest-reliability (TRR) of behavioral and neural measures. Twenty healthy participants completed two functional magnetic resonance imaging (fMRI) sessions with parallel versions of a picture–pseudoword association task, alongside a lexical decision control task. Learning occurred across four blocks. Behavioral performance was analyzed using linear mixed models, and imaging data were examined using whole-brain and region-of-interest analyses. TRR was assessed using intraclass correlation coefficients [3]. Participants successfully acquired novel word forms, as reflected in increasing accuracy and faster response times, with behavioral measures demonstrating good-to-excellent TRR across sessions. The learning task elicited robust language-related brain activity, and changes across learning stages were associated with performance, whereas the control task did not show consistent activity changes. Despite some variability, approximately 81% of voxels within significant clusters demonstrated moderate-to-excellent reliability. Ongoing analyses examine task-based functional connectivity and its relationship to learning. Overall, these findings identify reliable cortical targets for tDCS and support the suitability of this paradigm for future combined tDCS–fMRI research, highlighting the importance of reliability-driven approaches in brain stimulation studies.<br > <br><strong>References</strong><br>[1] Shtyrov et al. (2012). <em>The Neuroscientist</em><br>[2] Meinzer et al. (2024). <em>Frontiers in Neuroscience</em><br>[3] Kocataş et al. (2025). bioRxiv

Cognitive impairment remains a major therapeutic challenge in neurodevelopmental and neuropsychiatric disorders. Targeting both epigenetic regulation and histaminergic signalling has emerged as a promising strategy for cognitive enhancement. A-366, a potent G9a inhibitor with histamine H3 receptor (H3R) antagonistic activity, represents a novel dual-acting compound with therapeutic potential. In this study, we investigated the effects of chronic A-366 administration on cognitive function and oxidative stress in the BTBR T+tf/J mouse model, an idiopathic model of autism.<br >Male BTBR T+tf/J mice were administered A-366 (0.5–2 mg/kg, i.p.) daily for 21 days. Cognitive behaviour was evaluated using the Fear Conditioning Test, Novel Object Recognition Test, and Open Field Test. Following behavioural assessments, hippocampal tissues were collected to measure oxidative stress markers, including superoxide dismutase (SOD) activity and malondialdehyde (MDA) levels.<br>Chronic administration of A-366 significantly improved cognitive performance in BTBR mice, evidenced by enhanced contextual and cued memory in the Fear Conditioning Test, increased discrimination indices in the Novel Object Recognition Test, and maintained exploratory behaviour in the Open Field Test. Biochemical analysis revealed elevated superoxide dismutase (SOD) activity and reduced malondialdehyde (MDA) levels in hippocampal tissue, indicating a reduction in oxidative stress.<br>Dual targeting of G9a and H3R demonstrates significant memory-enhancing effects in BTBR mice, mediated through combined modulation of epigenetic mechanisms and histaminergic signalling, with improved oxidative balance. These findings support the potential therapeutic value of dual-targeting G9a inhibitors/H3R antagonists as a promising class for the development of novel therapies for cognitive impairments associated with neurodevelopmental and neuropsychiatric disorders.

The ventral hippocampus is a key regulator of emotional behavior through its projections to hypothalamic defensive circuits. In particular, inputs to the anterior hypothalamic nucleus (AHN) contribute to anxiety, innate fear, and contextual fear responses. Here, we investigated whether hippocampal neurons projecting to the AHN distribute collateral outputs to further brain regions, supporting an extended integrative role. By injecting into the AHN an AAV retrograde vector carrying the enhanced yellow fluorescent protein (EYFP) reporter gene, we mapped the hippocampal neurons projecting to this region and found that they are primarily located along the rostrocaudal extent of the ventral subiculum. To determine their full projection pattern, we combined AHN-targeted retrograde delivery of Cre recombinase along with the Cre-dependent expression of membrane-bound green fluorescent protein (GFP) and synaptophysin-mRuby in the subiculum, enabling visualization of axonal projections and presynaptic terminals. This approach revealed that AHN-projecting ventral subicular neurons exhibit widespread branching projections to multiple brain regions implicated in memory, motivation, arousal, circadian regulation, neuroendocrine control, and goal-directed behavior. These findings demonstrate that hippocampal outputs to the AHN are embedded within a distributed network rather than a single pathway. Such organization positions ventral subicular neurons to coordinate complex behavioral and physiological responses, highlighting their role as integrative nodes in circuits underlying fear and anxiety behavior.

Prenatal alcohol exposure (PAE) is a major cause of fetal alcohol spectrum disorders (FASDs) and is associated with long-lasting neurodevelopmental impairments. Although alcohol can induce neuroinflammatory responses, whether neuroinflammation contributes to brain alterations induced by PAE remains largely unexplored. Using a well-established mouse model, this study investigates early neuroinflammatory-related changes in the developing brain of male and female embryos. The results suggest that early alcohol exposure is associated with impaired blood–brain barrier integrity, characterized by delayed barrier closure and dysregulation of tight junction protein expression (ZO-1, Occludin). In addition, microglial morphology and the expression of key microglial markers (Iba-1, P2RY12 and CX3CR1) are altered as early as embryonic day E17, suggesting disrupted microglial maturation and homeostasis. These findings support the central hypothesis that PAE has a major effect on the neuroimmune axis, which may contribute to the cognitive and behavioral impairments observed in fetal alcohol spectrum disorders.

Dynamical memory allows neural systems to retain useful internal states over short and intermediate timescales, supporting computations relevant to navigation, motor control, and working memory. Conventional models typically rely on recurrent networks with separate excitatory and inhibitory populations. However, recent observations of localized excitatory activity in the Drosophila head-direction system suggest that such dynamics may in fact be implemented by a handful of neurons. This raises a timely and fundamental question: what is the minimal neural substrate required to generate persistent activity?<br><br>Here, we show, contrary to common intuition, that a single leaky integrate-and-fire (LIF) neuron with recurrent slow self-excitation is sufficient to produce a persistent firing state that is stable and robust to distractors. Alongside numerical solutions, we provide an empirical demonstration using a minimal hardware implementation. We further show that this finding extends to the widely used Izhikevich and AdEx models, in which robust persistent activity can be obtained simply by reversing the sign of the slow adaptation variable. Together, these results identify a minimal substrate for memory-like dynamics and suggest a compact building block for future neuromorphic cognitive architectures.

Stress activates the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic nervous system (SNS), driving glucocorticoid and catecholamine release modulating splenic immune function. Although acute activation is adaptive, chronic or dysregulated signalling may promote inflammation and immune dysfunction. How different physiological stressors remodel splenic neuroimmune signalling, and whether these responses differ by sex, remains poorly defined. We investigated whether ageing, stroke, and caloric restriction (CR) induce patterns of splenic neuroimmune remodelling in murine models. Splenic neurotransmitter receptor expression was quantified by qPCR in spleen tissue and isolated lymphocyte populations, while glucocorticoid and catecholamine concentrations were measured in tissue by ELISA. Whole spleen β2-adrenergic receptor (β2-AR) and glucocorticoid receptor expression remained unchanged across conditions, suggesting that tissue-level analysis may mask changes within immune cell subsets. Consistent with this, β2-AR expression was reduced in CD4⁺ T cells acutely following stroke, indicating stressor-specific changes in adrenergic sensitivity in populations of cells. Glucocorticoid concentrations were significantly elevated after stroke and CR, but not ageing, demonstrating divergent endocrine adaptations. Adrenaline levels were unchanged across groups, whereas noradrenaline showed stressor- and sex-dependent regulation: increased following stroke and CR, but reduced with ageing in females only. These findings demonstrate that physiological stressors do not display a uniform splenic stress response, but instead drive selective neuroimmune remodelling. Stroke was associated with an enhanced sympathetic-endocrine profile, CR with a potentially adaptive regulated response, and ageing with impaired noradrenergic signalling, particularly in females. Ongoing immunohistochemical analyses will determine whether these molecular changes are accompanied by alterations in splenic neural and immune cell architecture.