Behavioral Neuroscience

Scott J. Russo examines how chronic psychosocial stress alters communication between the immune system and the brain in depression and anxiety. Human observations and mouse experiments connect persistent increases in circulating monocytes and inflammatory signals with stress-related illness. The talk describes stress-responsive neurons that project to bone marrow and regulate monocyte production, release and trafficking. It also considers how stress disrupts the blood–brain barrier, allowing peripheral inflammatory proteins to affect reward regions such as the nucleus accumbens. Together, these findings examine how peripheral immune cells act at the neurovascular interface to change brain circuits and behaviour, providing potential mechanisms relevant to treatment-resistant mood disorders. Online via Rutgers Brain Health Institute Zoom. Thursday 1 October 2026, 12:00–13:00 EDT (America/New_York; UTC−4). Open the organizer’s event page and follow its Zoom link; the meeting ID and passcode are supplied there. Hosted by Yong Kim as part of the BHI Plenary Seminar Series. This listing advertises the verified remote option.

Takaki Komiyama presents longitudinal imaging and circuit-manipulation studies of history-dependent decision-making. The work identifies retrosplenial-cortex populations and local and long-range interactions that maintain option values across trials, update them after outcomes and translate past experience into future choices.

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.

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.

Why do individuals, both humans and animals, exhibit personal biases in two-alternative decision-making tasks, even when no clear reason exists to favor one alternative over another? In this talk, I will explore two competing hypotheses to explain these idiosyncratic biases. The first suggests that such tendencies arise from unique personal experiences, where past associations between actions and feedback influence future choices. The second hypothesis proposes that the bias reflects irreducible microscopic heterogeneities in the dynamics of decision-making networks. I will present experimental data and theoretical findings that support the latter hypothesis, shedding new light on the neural mechanisms behind seemingly irrational preferences. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2025-03-05. Recording duration: 00:50:36.

The dynamics of learning in natural and artificial environments is a problem of great interest to both neuroscientists and artificial intelligence experts. However, standard analyses of animal training data either treat behavior as fixed, or track only coarse performance statistics (e.g., accuracy and bias), providing limited insight into the dynamic evolution of behavioral strategies over the course of learning. To overcome these limitations, we propose a dynamic psychophysical model that efficiently tracks trial-to-trial changes in behavior over the course of training. In this talk, I will describe recent work based on a dynamic logistic regression model that captures the time-varying dependencies of behavior on stimuli and other task covariates, which we applied to mouse training data from the International Brain Lab (IBL). Secondly, I will discuss efforts to infer animal learning rules from time-varying behavior in order to characterize how they adjust their policy in response to reward. Finally, I will describe recent work on adaptive optimal training, which combines ideas from reinforcement learning and adaptive experimental design to formulate methods for inferring animal learning rules from behavior, and using these rules to speed up animal training. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2025-01-15. Recording duration: 00:49:39.

Persistent, stimulus-dependent neuronal activity has been observed in numerous brain areas during tasks that require the temporary maintenance of information. Several competing hypotheses for the neuronal mechanisms underlying persistent activity have been proposed. We have employed data-driven models in conjunction with optogenetic disruptions of neural circuits within memory-guided motor tasks. Our findings revealed a mechanism governed by dynamic attractors, pivotal in sustaining neuronal activity. This mechanism, shaped by time-varying inputs reflecting temporal predictions, is instrumental in regulating the impact of sensory information on the premotor cortex, thereby preserving memory traces from distracting stimuli. We then asked how persistent activity driven by attractor dynamics emerges during motor learning. It has been proposed that activity-dependent synaptic plasticity underpins motor learning, as it can reconfigure network architectures to produce the appropriate neural dynamics for specific behaviors. To verify this hypothesis, we investigated how the mouse premotor cortex acquires specific neural dynamics that govern the planning of movement at different stages of motor learning. We developed network models that replicated the effects of acute manipulations of synaptic plasticity. The models, which display attractor dynamics, also explain flexible behavior after learning has ended. By leveraging the model's predictions, we can formulate testable hypotheses regarding the distinct mechanisms governing movement planning at various stages of the learning process. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2024-05-01. Recording duration: 00:39:52.

In theoretical neuroscience, the brain is usually described as an information processing system that encodes and manipulates representations of knowledge to produce plans of action. This view leads to a decomposition of brain functions into putative processes such as object recognition, working memory, decision-making, action planning, etc., inspiring the search for the neural correlates of these processes. However, neurophysiological data do not support many of the predictions of these classic subdivisions. Instead, there is divergence and broad distribution of functions that should be unified, mixed representations combining functions that should be distinct, and a general incompatibility with the conceptual subdivisions posited by theories of information processing. In this talk, I will explore the possibility of resynthesizing a different set of functional subdivisions, guided by the growing body of data on the evolutionary process that produced the human brain. I will summarize, in chronological order, a proposed sequence of innovations that appeared in nervous systems along the lineage that leads from the earliest multicellular animals to humans. Along the way, functional subdivisions and elaborations will be introduced in parallel with the neural specializations that made them possible, gradually building up an alternative conceptual taxonomy of brain functions. These functions emphasize mechanisms for real-time interaction with the world, rather than for building explicit knowledge of the world, and the relevant representations emphasize pragmatic outcomes rather than decoding accuracy, mixing variables in the way seen in real neural data. I suggest that this alternative taxonomy may better delineate the real functional pieces into which the brain is organized, and can offer a more natural mapping between behavior and neural mechanisms. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2024-03-13. Recording duration: 00:52:50.

The Stagkourakis Lab at Karolinska Institutet is recruiting a postdoctoral scholar to study neural circuits governing survival and homeostatic behaviors. The project combines systems neuroscience, Neuropixels recordings, imaging, circuit manipulation and transcriptomics in the SciLifeLab and Department of Neuroscience research environment.

Design and conduct behavioural and neuroimaging studies of learning-related brain plasticity at the Center for Lifespan Psychology. The project tests the EESR theory through motor-skill learning and analyses of brain change. Responsibilities include study design, advanced statistical analysis, manuscripts and scientific presentations. The Berlin appointment is initially for three years at 39 hours per week. This vacancy belongs to the September 2026 Max Planck Postdoc Program call, which accepts applications until 13 October 2026 at 12:00 CEST through the official application platform.

Scott J. Russo examines how chronic psychosocial stress alters communication between the immune system and the brain in depression and anxiety. Human observations and mouse experiments connect persistent increases in circulating monocytes and inflammatory signals with stress-related illness. The talk describes stress-responsive neurons that project to bone marrow and regulate monocyte production, release and trafficking. It also considers how stress disrupts the blood–brain barrier, allowing peripheral inflammatory proteins to affect reward regions such as the nucleus accumbens. Together, these findings examine how peripheral immune cells act at the neurovascular interface to change brain circuits and behaviour, providing potential mechanisms relevant to treatment-resistant mood disorders. Online via Rutgers Brain Health Institute Zoom. Thursday 1 October 2026, 12:00–13:00 EDT (America/New_York; UTC−4). Open the organizer’s event page and follow its Zoom link; the meeting ID and passcode are supplied there. Hosted by Yong Kim as part of the BHI Plenary Seminar Series. This listing advertises the verified remote option.

The Sarvestani Lab at Cornell University is recruiting a postdoctoral scientist in systems neuroscience to study how visual and motor systems across the brain and body support perception and embodied cognition. Projects use cross-species behavioral experiments, multiphoton microscopy, electrophysiology, motion capture, and wireless sensors in tree shrews and rats.

Design and conduct behavioural and neuroimaging studies of learning-related brain plasticity at the Center for Lifespan Psychology. The project tests the EESR theory through motor-skill learning and analyses of brain change. Responsibilities include study design, advanced statistical analysis, manuscripts and scientific presentations. The Berlin appointment is initially for three years at 39 hours per week. This vacancy belongs to the September 2026 Max Planck Postdoc Program call, which accepts applications until 13 October 2026 at 12:00 CEST through the official application platform.