Calendar of Events
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Title: Neural circuit mechanisms of value-based decision-making Abstract: The value of the environment determines animals’ motivational states and sets expectations for error-based learning. But how are values computed? We developed a novel temporal wagering task with latent structure, and used high-throughput behavioral training to obtain well-powered behavioral datasets from hundreds of rats that learned the… |
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Title: Fast and Flexible Group Decision-Making Abstract: A wide range of animals live and move in groups. Many animals do better in groups than alone when, for example, foraging for food, migrating, and avoiding predators. A key to group success is social interaction. Less well understood is how a group, with no centralized control, is… |
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Monday (9/15) the Continual Learning Group will have a presentation from group member Yunfan Zhang. Yunfan will be sharing his ongoing work on developing a continual learning benchmark based on deriving up-to-date facts from news over time. Date: Monday, September 15 Time: 3-4pm Room: CSB 480 Zoom: upon request @ [email protected] |
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Title and Abstract: TBD Zoom: Meeting ID: 993 3345 6502 Passcode: Upon request @ [email protected] |
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Title: Neural computations underlying the regulation of motivated behavior Abstract: As we interact with the world around us, we experience a constant stream of sensory inputs, and must generate a constant stream of behavioral actions. What makes brains more than simple input-output machines is their capacity to integrate sensory inputs with an animal’s own internal motivational state… |
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Next Monday, September 29, we will continue our fall semester program with a group workshop on the topic of neural memory models. First, we will have a presentation from group member Max Bennett about our ongoing work on generalized neural memory systems that perform flexible updates based on learning instructions specified in natural language. After the presentation,… |
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Biological Learning first fall 2025 working group session of the year! Pingsheng Li, PhD student with Blake Richards at MILA, will be presenting Log-Normal Multiplicative Dynamics for Stable Low-Precision Training of Large Networks. Brief discussion of how the group can all collaborate together on a project, define a benchmark for ourselves with some metrics… |
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