BEGIN:VCALENDAR VERSION:2.0 PRODID:-//wp-events-plugin.com//7.2.3.1//EN TZID:America/Los_Angeles X-WR-TIMEZONE:America/Los_Angeles BEGIN:VEVENT UID:258@escience.washington.edu DTSTART;TZID=America/Los_Angeles:20250313T163000 DTEND;TZID=America/Los_Angeles:20250313T172000 DTSTAMP:20250303T184021Z URL:https://escience.washington.edu/events/uw-data-science-seminar-kris-bo uchard/ SUMMARY:UW Data Science Seminar: Kris Bouchard DESCRIPTION:Please join us for a UW Data Science Seminar featuring Kris Bou chard\, an Assistant Adjunct Professor at UC Berkeley\, on Thursday\, Marc h 13th from 4:30 to 5:20 p.m. PT.\n\n\nThe seminar will be held in Hitchco ck Hall 132 – Campus Map.\n"Feedback control is a normative theory of n eural population dynamics"\n\nAbstract: Brain computations emerge from col lective dynamics of distinct neural populations. Behaviors including reach ing and speech are explained by principles of feedback control. However\, if feedback control explains neural population dynamics is unknown. We cre ated dimensionality reduction methods that identify subspaces of neural po pulation data that are most feed-forward controllable (FFC) vs. feedback c ontrollable (FBC). We show that FBC and FFC subspaces diverge for dynamics generated by neuro-anatomical connectivity. In neural recordings from acr oss the brain\, we show that FBC subspaces were better decoders of externa l variables (e.g. reach velocity\, visual stimuli\, animal location). Comp ared to FFC subspaces\, FBC subspaces emerged from collective interactions of a population of neurons with distinct activity profiles. Finally\, in M1/S1\, we revealed that FBC subspaces emphasize rotational dynamics due t o enhanced system stability\, while FFC subspaces emphasize scaling dynami cs. These results demonstrate feedback controllability is a novel\, normat ive theory of neural population dynamics\, and connect distinct neuronal p opulations to differing regimes of emergent dynamics carrying out distinct computations.\n\n Biography: Kris Bouchard is Assistant Adjunct Profess or in the Helen Wills Neuroscience Institute & Redwood Center for Theoreti cal Neuroscience at UC Berkeley. He is PI of the Neural Systems and Machin e Learning Lab (NSML) at UCB and Lead of the Computational Biosciences Gro up in the Scientific Data Division\, LBNL. The NSML lab is interdisciplina ry team that focuses on understanding how distributed neural circuits give rise to coordinated behaviors and perceptions. We take a multi-pronged ap proach to this problem by developing novel theoretical frameworks for neur al circuit function\, conducting in vivo neuroscience experiments\, and de veloping state of the art machine learning tools to address diverse system s biology questions. On the neuroscience side\, we investigate functional organization and dynamic coordination in the brain by combining in vivo mu lti-scale electrophysiology and optogenetics in rodents. This multi-modal\ , multi-scale approach provides the simultaneous breadth of coverage and s patio-temporal resolution required to determine neural computations at the speed of thought. On the computational side\, we aim to reveal the proces ses that generate complex (neuro-) biological data by combining ideas from control theory\, information theory\, high-dimensional statistical learni ng\, statistical mechanics\, and modern deep learning to develop novel met hods and apply them to general biological and neuroscience problems.\nThe 2024-2025 seminars will be held in person\, and are free and open to the p ublic. ATTACH;FMTTYPE=image/jpeg:https://escience.washington.edu/wp-content/uploa ds/2025/03/Kristofer-Bouchard-300x300-1.png END:VEVENT BEGIN:VTIMEZONE TZID:America/Los_Angeles X-LIC-LOCATION:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20250309T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT END:DAYLIGHT END:VTIMEZONE END:VCALENDAR