[Koglist] [CEU Cogsci Talks] CCC Colloquium talks: Constantin Rothkopf (June 19) and Xaq Pitkow (June 20) CEU Budapest

Dear All, The CEU Department of Cognitive Science and the Center for Cognitive Computation invites you to the following two talks on June 19 and 20: **************************************** Time and date: Thursday, June 19, 2025, 5:00 PM Venue: CEU Budapest site (1051 Budapest, Nádor u. 15.) N15. room 106. Speaker: Constantin A. Rothkopf<https://www.pip.tu-darmstadt.de/members_pip/publications.en.jsp> Centre for Cognitive Science & Institute of Psychology, Technical University of Darmstadt; Hessian Center for Artificial Intelligence, Darmstadt, Germany Title: Human navigation as path-planning in belief-space Abstract: Goal-directed navigation requires continuously integrating uncertain self-motion and landmark cues into an internal sense of location and direction, concurrently planning future paths, and sequentially executing motor actions. We provide a unified account of these processes with a computational model of probabilistic path planning in the framework of optimal feedback control under uncertainty. This model gives rise to diverse human navigational strategies previously believed to be distinct behaviors and predicts quantitatively both the errors and the variability of navigation across numerous experiments. This furthermore explains how sequential egocentric landmark observations form an uncertain allocentric cognitive map, how this internal map is used both in route planning and during execution of movements, and reconciles seemingly contradictory results about cue-integration behavior in navigation. Finally, we show, how moment to moment interactions of sensory, cognitive, and action uncertainty give rise to gaze behavior shifting from active learning to active sensing. Taken together, the present work provides a parsimonious explanation of how patterns of human goal-directed sensorimotor navigation behavior arise from the continuous and dynamic interactions of spatial uncertainties in perception, cognition, and action. Chair: Máté Lengyel (CEU, Cambridge) Zoom Meeting ID: 992 4543 3354<https://ceu-edu.zoom.us/j/99245433354?pwd=iH9CZSVwTjJ8r8invTjrHDQQLxAByd.1> Passcode: 326339 **************************************** Time and date: Friday, June 20, 2025, 5:00 PM Venue: CEU Budapest site (1051 Budapest, Nádor u. 15.) N15. room 103. Speaker: Xaq Pitkow (Associate Professor, Neuroscience Institute, CMU)<https://www.cmu.edu/ni/people/faculty/xpitkow.html> Title: Interpreting neural dynamics by modeling beliefs Abstract: Complex behaviors are often driven by an internal model, which integrates sensory information over time and facilitates long-term planning to reach subjective goals. We interpret behavioral data by assuming an agent behaves rationally --- that is, they take actions that optimize their subjective reward according to their understanding of the task and its relevant causal variables. We apply a new method, Inverse Rational Control (IRC), to learn an agent's internal model and reward function by maximizing the likelihood of its measured sensory observations and actions. Technically, we define an animal's strategy as solving a Partially Observable Markov Decision Process (POMDP), and we invert this model to find the task and subjective costs that have maximum likelihood. This is a generalization of both Inverse Reinforcement Learning and Inverse Optimal Control. Our mathematical formulation thereby extracts rational and interpretable thoughts of the agent from its behavior. We apply this method to behavioral data from primates catching fireflies in virtual reality, and use it to understand properties of the mental model monkeys use to navigate by optic flow. The thoughts imputed to the animal can then serve as latent targets for neural analyses. Using these targets, we provide a framework for interpreting the linked processes of encoding, recoding, and decoding of neural data in light of the rational model for behavior. We first demonstrate the merits of this approach on synthetic neural data during a foraging task. We then analyze real neural activity in primate prefrontal cortex (PFC) and posterior parietal cortex (PPC) to discover computations relevant to foraging tasks. In PFC, we find that reward dynamics are represented in a subspace of the high-dimensional population activity, and predict animal’s subsequent choice better than either the true experimental variables or the raw neural responses. In PPC, we find representations of latent navigation-relevant variables, and find that task manipulations alter the coupling between neurons, suggesting that these interactions reflect the mental model used to perform task-relevant computations. Overall, our approach may identify explainable structure in complex neural activity patterns. This framework lays a foundation for discovering how the brain chooses to act using dynamic beliefs about the uncertain world. Chair: Máté Lengyel (CEU, Cambridge) Zoom Meeting ID: 995 7581 0673<https://ceu-edu.zoom.us/j/99575810673?pwd=iCAk9h82KCXurpjbbmal4TAo4HzbSp.1> Passcode: 635375 **************************************** Please, be informed that video/photo recording might take place at the event and the edited version of the video material might be published to communicate or promote CEU PU's activities. Please, find our Privacy Notice here<https://www.ceu.edu/privacy>cy>. 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