Events

Seminar Time: 11:30am Date: 11/21/25 Seminar Location: JLG, L5-084 Host: Ji Xia Title: Illuminating synaptic learning Abstract: How do synapses in the middle of the brain know how to adjust their weight to advance a behavioral goal? This is referred to as the synaptic ‘credit assignment problem’. A large variety of synaptic learning rules have been proposed, mainly in the context…

Alan Stocker Professor of Psychology at UPenn Title: Economics of temporal evidence integration Abstract: The temporal integration of sensory information is an important aspect of many human decision tasks. I will present results of ongoing research in my laboratory aimed at understanding the dynamic processes underlying evidence integration. In particular, I will discuss a novel…

Next Meeting Info Date: Thursday, Dec 11 Time: 3pm-4pm Room: CEPSR 620 Zoom: Upon request @ [email protected]

Title: Adaptive problem solving in the primate frontal cortex Abstract: Humans excel at solving problems adaptively. When missing the bus to an appointment, for instance, we might wait for the next one, call a taxi, cancel, or reschedule, depending on the situation. This ability to assess context and choose a suitable strategy is central to…

Seminar Time: 11:30am Date: 12/19/25 Seminar Location: JLG, L5-084 Host: Tahereh Toosi   Title: Flexible decision-making: policies and rules   Abstract: Flexible behavior requires flexible decision-making. We adapt seamlessly to changing environments—adjusting biases, altering decision rules, and inferring hidden task contexts—often without explicit cues. In this talk, I will outline a framework that formalizes different levels of this flexibility and…

Title: A normative perspective on diversity of dopamine neurons Abstract: TBD

Title: Frugal Inference for Control Abstract: A key challenge in advancing artificial intelligence is achieving the right balance between utility maximization and resource use by both external movement and internal computation. While this trade-off has been studied in fully observable settings, our understanding of resource efficiency in partially observable environments remains limited. Motivated by this challenge, we…

To kick off the Continual Learning Working Group activities for this year, the Continual Learning working group will meet on Thursday, Jan 22 at 3pm on Zoom and in CEPSR 620. The meeting will be brief, and we'll discuss our agenda and scheduling for the coming semester, including our goals for the benchmark project. Join via Zoom: Upon request…

Title: When and How to Parallelize Seemingly Sequential Models   Abstract: Transformers have become the de facto model for sequential data in large part because they are well adapted to modern hardware: At training time, the loss can be evaluated in parallel over the sequence length on GPUs and TPUs. By contrast, evaluating nonlinear recurrent neural networks…

Initial Meeting! About: The ARNI Language & Vision Working Group aims to bring together researchers across neuroscience, cognitive science, computer science, and AI to collaboratively advance our understanding of how humans and machines construct multimodal experiences. Its goal is to create a space for discussing ongoing language- and vision-focused projects, identifying natural points of overlap,…

Title:A multimodal sleep foundation model for disease prediction Abstract: Sleep is a fundamental biological process with broad implications for physical and mental health, yet its complex relationship with disease remains poorly understood. Polysomnography (PSG)—the gold standard for sleep analysis—captures rich physiological signals but is underutilized due to challenges in standardization, generalizability and multimodal integration. To…

Herbert Zheng Wu Title: Neural Basis of Leader–Follower Dynamics in Cooperative Behavior Abstract: Cooperation allows social species to achieve outcomes that individuals cannot accomplish alone. Even in simple groups, cooperative behavior often depends on complementary social roles such as leaders and followers, yet the neural computations supporting these dynamic relationships are not well understood. Our lab investigates…