Seminars

Matthew J. Girgenti discusses how research on individual brain cells and the three-dimensional organization of DNA is changing the biological understanding of post-traumatic stress disorder. The seminar examines how these approaches reveal trauma-associated brain changes and identify possible targets for more effective, personalized treatments. Girgenti is a neuroscientist in Yale School of Medicine’s Department of Psychiatry. Jeffrey Borenstein moderates this Meet the Scientist session. Online via the BBRF Zoom webinar. Tuesday 13 October 2026, 14:00 EDT (America/New_York; UTC−4). Follow Register Today on the organizer’s event page to the event-specific Zoom form. Advance registration is available to researchers, students, healthcare providers, mental-health organizations, patients and family members.

Yun Xia presents macrophage–kidney assembloids that address missing immune and vascular components in stem-cell organoids. Directed differentiation, self-organization, genetic perturbation, xenotransplantation and single-cell analysis reveal immune–epithelial interactions. Macrophages from the same parental cells acquire resident phenotypes; diabetic and polycystic kidney models show context-dependent effects on inflammation, epithelial injury and disease progression. Minoru Takasato addresses kidney organoids’ missing urinary outflow by generating bladder tissue from human pluripotent cells. Stepwise differentiation passes through endoderm, hindgut and cloaca; FGF4 posteriorization and growth-factor screening promote urothelial identity. The resulting sacs contain stratified urothelial cell types, stretch and form a barrier, supporting developmental, disease and future therapeutic studies. Online via Zoom. Tuesday 13 October, 11:00–12:30 SGT (Asia/Singapore). Both talks share this session; individual start times are unspecified. Register through the organizer page. Professional, trainee or student status in stem cells, regenerative medicine or an adjacent field is required; organizer approval and recording restrictions apply.

Tom Nowakowski explains lineage barcoding and single-cell sequencing approaches for reconstructing neural stem-cell family trees and early wiring programs in developing mouse and human brains.

Marty Weissman presents a University of California, Santa Cruz course that develops mathematics for the life sciences through models of biological dynamics. Adapted from UCLA’s LS30 course, it integrates calculus, dynamical systems and linear algebra. The seminar describes the curriculum and its active learning discussion sections, where deliberate choices range from custom dynamical-system simulators to paper exercises and blackboard work. Drawing on two years of teaching, Weissman reflects on which approaches appear to support student learning and the development of the teaching team.

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.

Anthony Letai discusses how understanding programmed cell death can guide the selection of cancer treatments. The seminar explains how apoptotic signalling can be measured and how these measurements can identify drugs capable of killing cancer cells. Hybrid: New Research Building Auditorium, Georgetown University Medical Center, Washington, DC, and Zoom. Monday 5 October 2026, 16:30–17:30 EDT (America/New_York; UTC−4). Use the attendance registration form or the event’s Zoom link on the organizer page. Organized by Georgetown’s Distinguished Scientist Seminar Series. Letai is Director of the National Cancer Institute. An in-person reception follows the seminar.

Navid Azizan presents methods that make neural models obey physical, safety and operational constraints at deployment. Hard-constrained neural networks, or HardNets, enforce input-dependent constraints by construction while preserving universal approximation within the feasible function class. Applications include models of chaotic dynamics with bounded trajectories, energy-constrained operator learning, safe reinforcement learning and control with formal guarantees. The talk then turns to enforcing constraints during sampling from pretrained diffusion and flow-matching models. Formulating generation as trajectory optimization allows receding-horizon control to guide outputs toward feasibility without retraining or imposing excessive restrictions on the sampling process. Examples from fluid dynamics, robot planning and control, PDE control and language-guided image editing illustrate how constraints can define admissible behavior while retaining expressive learning and generation.

Uddipan Banik derives a dynamical account of dark-matter halo density profiles using the Boltzmann–Poisson equations for an expanding Universe populated by subhalos of many masses. A self-similar solution links density slope to halo mass growth; including gravitational scattering and subhalo capture gives gamma = 6/(s + 2). Initial collapse with s = 2 produces a prompt cusp of slope 3/2. Hierarchical growth connects the slope to the primordial power spectrum and recovers the Syer–White relation during matter domination. Stable clustering selects an inner Navarro–Frenk–White cusp of slope one, while stalled accretion approaches the outer slope of three. The framework connects these profiles to successive stages of halo assembly.

Leonid Berlyand discusses mathematical models for the onset of cell motion driven by myosin contraction. A two-dimensional free-boundary PDE model links cell-shape evolution to diffusion and Keller–Segel-type transport. The talk examines linear stability, a stability-determining eigenvalue and the way nonlinear diffusion changes the bifurcation from supercritical to subcritical. It also considers the curvature of the bifurcation curve, connections to bistability, and the role of non-self-adjoint operators. An example illustrates why a spectral gap alone need not guarantee stability. This is an in-person Analysis of Fluids and Related Topics seminar at Princeton.

Taillte May investigates how unstable black-hole quasinormal-mode spectra affect observed gravitational-wave signals. Small changes in a gravitational potential can substantially shift the frequencies normally used to test astrophysical black holes. A simple time-domain model reveals a delay before those shifts appear, tied to the echo travel time between the perturbation and the main potential. In the perturbative regime, the frequency change after one echo agrees with the conventional frequency-domain prediction. Beyond that regime, the intermediate waveform cannot be represented by a single constant frequency shift.

MIT Biology Colloquium Series talk by David Bilder (University of California, Berkeley), hosted by Yukiko Yamashita, on invertebrate oncology and the ancient evolutionary origins of tumor-host interactions.

Michael Hutchings introduces Reeb vector fields and explains why their periodic orbits are substantially better understood in three dimensions through Seiberg-Witten theory. The colloquium develops Irie's closing lemma, which creates a periodic orbit through a selected region after a small perturbation, and discusses a quantitative refinement connecting the perturbation size to an upper bound on the orbit period.

Shiv Grewal discusses how chromatin and epigenetic mechanisms establish, maintain, and transmit genome states beyond the DNA sequence itself. This NIH Wednesday Afternoon Lecture Series event is offered in person and through NIH VideoCast.

This English-language webinar examines advances in organoid research, production, and drug discovery. Hideya Sakaguchi covers the developmental-biology origins of neural organoid research and its potential for drug discovery, followed by a keynote from Thomas Mitchell of The Organoid Company and a live question session.

Suhrid Ghosh will present work on how cell mechanics and cytoskeletal dynamics shape the evolution of reproductive structures in Drosophila ovaries. Cross-species morphology, ex-vivo live imaging, perturbations of cortical tension, and newly isolated terminal-filament cells reveal how somatic-cell deformability can alter ovariole architecture and reproductive fitness.

Thesis presentation by Tiffany Zhang, graduate fellow in the Vinogradova Lab at The Rockefeller University, on chemical proteomics approaches revealing post-translational remodeling of endosomal pathways during macrophage activation. Open to the tri-institutional community.

Klemens Rottner (Helmholtz Centre for Infection Research, Braunschweig) presents evidence that profilin acts as a master regulator of actin filament dynamics essential for cell migration and growth, controlling both formin- and Arp2/3 complex-dependent actin assembly pathways.

Large recurrent networks are important models in several fields, including neuroscience, machine learning, physics, and applied mathematics. Yet their dynamics are difficult to study directly, because high-dimensional nonlinear systems can exhibit rich behavior that is hard to summarize in terms of individual trajectories. In this talk, I will discuss an approach that seeks to understand such dynamics through the structure of the network’s equilibria. I will focus on a random balanced network of threshold-linear units that undergoes a transition from a single stable equilibrium to extensive chaos as the disorder strength crosses a critical value. Using a combination of Kac–Rice theory, replica calculations, numerical root-finding, and dynamical mean-field theory, we show that the chaotic regime contains an exponentially large number of equilibria. These equilibria are all saddles, but with only a fractionally small number of unstable directions. Surprisingly, despite the completely random connectivity, the equilibria are not scattered randomly through phase space. Instead, they are strongly correlated and confined to a comparatively small region. The chaotic attractor lies within this same region, suggesting a direct geometric link between the organization of unstable equilibria and the collective structure of the dynamics. This picture helps explain why networks with extensive chaos can nevertheless display dynamics dominated by a relatively small number of collective modes. More broadly, the results suggest that the geometry of equilibria provides a useful complementary perspective to dynamical mean-field theory for understanding high-dimensional neural dynamics. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2026-05-27. Recording duration: 00:46:40.

Networks of interconnected neurons display diverse patterns of activity. Relating these patterns to the structure of the network is a central goal of theoretical neuroscience. Classic neural field and rate models have been powerful tools for this purpose due to their analytical tractability. Here, we show that the recently-developed combinatorial threshold-linear network (CTLN) model is a mean-field theory for excitatory-inhibitory Hawkes networks, with clustered connectivity, in an inhibition-stabilized regime. This mapping allows us to leverage powerful analytical results for CTLN networks to predict diverse macroscopic dynamics of clustered Hawkes networks, including metastability between various macroscopic fixed points, limit cycles, and chaotic attractors. We will then examine an extension of this approach to models with nonlinear dendritic dynamics, focusing on dendritic calcium spikes.We uncover a marked point process mean-field theory for these n etworks and use this to examine how somatic vs dendritic-targeting connectivity shapes the mean-field equilibrium phase diagram. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2026-05-13. Recording duration: 00:54:14.

How does a cat gracefully walk and suddenly freeze when spotting a mouse? In this talk, we look at how networks in the spinal cord generate movement. In particular, we address the fundamental yet poorly understood question of motor control: How can rhythmic movements, such as walking, be generated and stopped at any point in the cycle while posture is preserved? Since conventional models of spinal motor function rely on alternation between flexor and extensor modules, which are limited to just two phases, this question exposes the essential shortcoming of the conventional understanding: How can a system with only two phases generate and stop walking in any phase? To address this question and better understand the generation and stopping of motor activity, we use Neuropixels probes in the rat spinal cord during voluntary, freely moving locomotion. We utilize optogenetic activation of a brainstem nucleus to induce stopping. During locomotion, neuronal manifold activity exhibits robust rotational patterns that are topologically invariant with respect to speed (Linden 2022). Furthermore, this trajectory converges on a stable point-attractor precisely at the moment of arrest, and it persists until the movement is resumed. Through computational modeling, we propose that the walk-to-stop represents a bifurcation from a limit cycle to a fixed point attractor. We also propose a structural network mechanism for its physical implementation (Komi 2026). The structural mechanism entails a longitudinal projectome with a skewed Mexican hat topology, i.e., primarily local recurrent excitation and longer-range inhibition. Such a network can generate motor patterns via traveling waves, with frequency and amplitude controlled independently, and rhythm induced without requiring cellular pacemaker mechanisms. Together, our experimental observations support a new theory for the mechanism behind the generation of movement by networks in the spinal cord. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2026-03-25. Recording duration: 00:37:44.