Seminars

Gašper Tkačik explores whether the language of information in biology can become a predictive scientific theory. The lecture connects information transfer from DNA to proteins, positional signals that guide cell fate during development, neural information processing, and the storage and inheritance of information in evolving genomes. It brings physics, information theory and quantitative biology together to examine these processes across biological scales. Tkačik is Professor at the Institute of Science and Technology Austria. Shinya Kuroda provides commentary; Arisa Ema moderates. Online via Zoom Webinar. Wednesday 14 October 2026, 14:00–15:00 JST (Asia/Tokyo; UTC+9). Public advance registration is required through the organizer’s event page. The lecture is in English with Japanese interpretation. Organized by Tokyo College, The University of Tokyo Institutes for Advanced Study.

Liver toxicity can emerge late in drug development when early assays fail to capture human biology, exposure or injury mechanisms. This webinar introduces Axiom’s hepatic profiling approach, combining multicellular liver systems, high-content imaging, transcriptomics, proteomics and ADME measurements. Its reasoning agent integrates those results with partner assays, chemical-series context, exposure estimates and clinical evidence to assess mechanistic liver-safety risks. Rather than using a single cell-toxicity score, the approach develops interpretable, series-specific structure–toxicity hypotheses, compares analogues, ranks compounds and suggests follow-up experiments or structural changes. Performance on established liver-injury reference compounds and newer molecules is examined through case studies, showing how multimodal evidence can inform medicinal-chemistry decisions and predicted therapeutic index.

Shantanu Jadhav presents work on coordinated hippocampal-prefrontal activity and the neural mechanisms that support memory-guided cognition and decisions. The seminar draws on systems electrophysiology and circuit analysis to connect distributed network dynamics with behavior.

Ilaria Ferlenghi discusses a career spanning structural biology, cryo-electron microscopy, vaccine research and development, and the growing role of artificial intelligence and machine learning in scientific innovation and entrepreneurship.

Real-time measurement of local biomolecule concentrations in living tissue requires sensors that are stable, selective and minimally invasive. This seminar examines single-walled carbon nanotubes, whose durable near-infrared fluorescence and sensitivity to their surroundings support optical biosensing. Biopolymer functionalization gives the nanotubes biological compatibility and selectivity for particular molecular targets. Spectroscopy, microscopy and machine-learning-assisted analysis are used to characterize sensor interactions and extract biological information, with applications spanning live-cell imaging, wearable sensing and continuous monitoring.

Takaki Komiyama will discuss how cortical circuits maintain information about the value of behavioral options across trials and transform past experience into future choices. The talk draws on longitudinal imaging and circuit manipulation in mice to examine distinct neuronal populations and local and long-range interactions in history-dependent decision-making.

Deep networks are often thought of as black boxes. Their ability to encompass vast swathes of knowledge indeed makes them hard to explain. Yet many of their behaviours — generalization under overparametrization, grokking, OOD failures, neural scaling laws — recur across architectures and scales, and each, however surprising, can be reproduced and explained in controlled settings. I will review these efforts to identify and explain the universal phenomena of deep learning, and suggest that an LLM may amount to a sum of such tractable sub-phenomena, interpolative in nature. Finally, leaving scientific rigor aside, I'll argue that what separates this prosaic picture from the apparent magic of LLMs may well be the industrial scale of compute and human labour behind it, and that AGI in its deeper extrapolative sense may be much further away than claimed.

This public discussion examines the factors that help preserve brain health during aging. Researchers working on neuroscience, brain stimulation, the microbiome and brain health consider how stress, everyday behavior and social and environmental conditions can affect resilience over a lifetime. The panel discusses emerging evidence about early vulnerability, possible interventions through lifestyle changes and stress management, and more targeted approaches. It also addresses the limits of current knowledge and the uncertainties that remain when translating these findings into ways to protect cognitive health.

Jan Kosinski explains how AlphaFold-style methods predict protein complexes and why their reliance on evolutionary information makes interactions between host and pathogen proteins especially difficult. The talk reviews large-scale studies, interpreting both successful predictions and failures rather than treating reported success rates as universal performance. It then examines ways to improve predictions through broader sampling, altered sequence alignments and experimental restraints, including crosslinking mass spectrometry, with influenza A virus as a worked research example. The session is suitable for students and researchers interested in host-pathogen interactions and structural bioinformatics; basic knowledge of protein structures and sequence alignments is useful, but prior AlphaFold experience is unnecessary.

Navigation and memory require coordination between map-like allocentric representations and body-centered egocentric actions. Aaron Wilber examines how the parietal–retrosplenial–anterior thalamic–hippocampal network performs these transformations, and how disrupted coordination contributes to spatial deficits in aging and Alzheimer’s disease. Rat sequence-task experiments reveal bidirectional hippocampal–parietal interactions across route-centered, place and egocentric representations. Because that task does not isolate reference-frame use, the laboratory developed a freely available task separating egocentric, allocentric and transformation conditions. Validation indicates that parietal cortex and anterior thalamus are required for transformation; ongoing work examines population states associated with each condition. The talk then connects impaired hippocampal–cortical communication during sleep to navigation deficits in 3xTg-AD mice, reporting recovery of circuit function and cognition after early, circuit-targeted 40 Hz entrainment. Related investigations examine this network during waking navigation. In TgF344-AD rats, egocentric impairments appear before transformation deficits, addressing the shortage of rodent studies of reference-frame coordination in Alzheimer’s disease.

How do humans stabilize an inverted pendulum, and why does a balanced pole eventually fall? Drawing on 25 years of fingertip pole-balancing research, this talk examines neural correction delays: longer poles move more slowly relative to the nervous system’s response time. Delay-differential models can stabilize the upright position, yet skilled people still experience falls. The proposed explanation is microchaos arising from interactions among delay, sensory dead zones and frequency-dependent force encoding. A region of transient falling solutions lies next to stable microchaotic dynamics. Such microchaos is absent in virtual frontal-plane balancing tasks, while models of standing postural sway lack the corresponding transient regime. The comparison suggests that human falls, unlike pole falls, are more plausibly associated with medical events or slips and trips.

Robot missions require both collision-free trajectories and logical task ordering, such as collecting a resource before entering a restricted region. Augmented graphs of convex sets combine continuous trajectory optimization and discrete task sequencing in one problem. A layered graph constructed from an exact convex partition of free space selects an optimal task order and trajectory through a shortest-path calculation, exact up to finite Bézier parameterization. Its structure corresponds to Bellman–Held–Karp dynamic programming for the travelling-salesperson problem, retaining singly exponential worst-case complexity and improving exponentially on general temporal-logic tools. A library of specifications covers ordered collection, alternative keys, combined prerequisites, timing and conditional logic with correctness guarantees. Numerical benchmarks demonstrate exponential speedups and near-global optimality. Possible extensions include moving environments, safety-aware planning with conformal prediction sets and a large galactic-survey benchmark.

To orchestrate complex behaviors in mammals, the cerebral cortex must continuously transmit its processing results to subcortical regions. While internal cortical processing relies on highly selective sparse codes, these descending cortical output streams employ an enigmatic dense code, characterized by high firing rates and low feature selectivity. This dense population code presents a profound paradox: how can downstream regions extract precise, cognitively relevant signals when most cortical output neurons can be active at any moment? We address this paradox by testing the hypothesis that cortex does not lose information when switching to a dense code. Instead, it utilizes a mechanism for sparse-to-dense coding transformations discovered by my laboratory: thalamocortical synapses target specifically the dendritic initiation zone for calcium action potentials (APs), which enables cortical output neurons to transmit multiple information streams simultaneously via a multiplexed 1-2-3 AP syntax. I will provide first evidence that this remarkable synaptic specificity and coding syntax generalize across long-range pathways. Information coupling via an anatomically and biophysically distinct dendritic nexus may hence be a ubiquitous mechanism for sparse-to-dense coding transformations in cortex. Dissecting these mechanistic origins of cortical output streams is only now possible due to a unique in vivo – in silico approach, perfected over two decades, that my laboratory developed for bridging the gaps between dendritic and population-level computations

Yixuan He (Arizona State University) considers graph neural networks for social, financial and biological networks in which edge signs and directions contain information needed for clustering and prediction. After an introduction to graph neural networks, the talk explains how signed and directed methods preserve relationships lost when every connection is treated as unsigned and undirected. The seminar then asks when a representation learned before the final task can transfer to a different graph or to a setting with few labels. Two theoretical perspectives address transfer across graph domains and the use of link prediction for linear community detection. TopoDIG and TopoSIGN combine encoders that preserve edge structure with persistent topological features, enabling pre-training and prompt-based adaptation on directed and signed networks.

Picower Institute Colloquium on the Brain and Cognition featuring Christopher Harvey, PhD, of Harvard University, held in Singleton Auditorium (46-3002) at MIT Building 46, 43 Vassar Street.

Ivo D. Dinov examines augmented intelligence as a partnership between people and computational systems. The talk traces the technical and philosophical development of neural networks, then introduces complex-time, or kime, representations and the inference methods they support. Applications include medical imaging, healthcare and economic forecasting. It also considers the academic mission, societal consequences of AI and tensions between rapid technical development and human values, framing mathematical AI methods as extensions of human reasoning. Free hybrid seminar hosted by Wayne State University's Institute for AI and Data Science, AIDaS: CAD Seminar Series. Wednesday 30 September 2026, 14:30–15:30 EDT (America/Detroit; UTC−4). Attend in Room 1146, Faculty/Administration Building, 656 W. Kirby, Detroit, MI 48202, USA, or use the Zoom link on the official event page. Researchers, practitioners, students and faculty are welcome; the organizer encourages in-person attendance.

Mansi Chhajed examines how the move from home sleep patterns to disrupted hospital sleep relates to cognitive outcomes after surgery. The session combines longitudinal sleep measurements with clinical assessments of postoperative delirium to identify baseline markers of vulnerability and consider practical ways to improve recovery. It connects sleep architecture, biological and environmental influences, and preoperative risk with proactive, sleep-informed patient care. Chhajed is a Clinical Research Coordinator at Massachusetts General Hospital. Online via Zoom Webinar. Tuesday 29 September 2026 at 14:00 ET / 13:00 CT (America/New_York; EDT, UTC−4). Organized by the Sleep Research Society — Virtual Seminar Series. Follow Register Today on the organizer's page to the event-specific Zoom form, which requests name and email. The form is publicly accessible; advance registration supplies webinar access.

Vanessa Siffredi explores why the corpus callosum is central to typical brain development, yet some children born without it or with callosal abnormalities develop comparably to their peers. The talk connects callosal structure and communication between hemispheres with cognition, attention, executive function, memory, language and socio-emotional development. Structural and functional neuroimaging studies of typical development and callosal dysgenesis examine how developing brains compensate for alterations in this major white-matter pathway. Siffredi is affiliated with CHUV and UNIL; Carole Guedj chairs the seminar. Hybrid: Auditoire de pédiatrie Fred Bamatter, HUG, Hôpital des Enfants, Geneva; online via Zoom. Tuesday 29 September 2026, 09:30–10:30 CEST (Europe/Zurich; UTC+2), followed by CIBM news and networking until 11:00. Organized by CIBM Center for Biomedical Imaging — Breakfast and Science. In-person attendance is free without registration. Remote attendees must register through the Zoom link on the event page and select the 29 September occurrence.

Irene Rombel discusses how artificial intelligence and machine learning can address bottlenecks, quality issues, and production costs in cell, gene, and RNA therapy manufacturing. The seminar focuses on real-world process-development applications that improve reproducibility, speed, and cost effectiveness.

Merav Ahissar examines how expertise emerges through learning the statistics of task-relevant stimuli. Slow learning builds familiarity with stable regularities, such as syllable patterns in language, while fast adaptation supports flexible responses to changing situations, including surprising social interactions. The talk considers atypical learning dynamics in dyslexia and autism and how these may explain difficulties in linguistic and social skill acquisition, respectively. The discussion draws on Gertsovski and Ahissar, Trends in Cognitive Sciences, 2026. Speaker: Merav Ahissar, Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem. Organized by Cornell Cognitive Science. Friday 25 September 2026, 15:00–16:30 America/New_York (EDT). Attend online through the public Join via Zoom link on the official event page; the link opens Zoom’s app and browser join options. Cornell advertises the source event as hybrid, but this listing covers the verified online attendance route.