BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Penn Engineering Events - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Penn Engineering Events
X-ORIGINAL-URL:https://seasevents.nmsdev7.com
X-WR-CALDESC:Events for Penn Engineering Events
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20230312T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20231105T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20240310T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20241103T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20240404T153000
DTEND;TZID=America/New_York:20240404T163000
DTSTAMP:20260403T192756
CREATED:20240311T173357Z
LAST-MODIFIED:20240311T173357Z
UID:10949-1712244600-1712248200@seasevents.nmsdev7.com
SUMMARY:BE Seminar: "A Task-Optimized Approach to Systems Neuroscience" (Aran Nayebi\, MIT)
DESCRIPTION:Note that this seminar will be held in Wu & Chen Auditorium (Levine 101).\n\nHumans and animals exhibit a range of interesting behaviors in complex environments\, and it is unclear how the brain reformats dense sensory information to enable these behaviors. To gain traction on this problem\, new recording paradigms now facilitate the ability to record and manipulate hundreds to thousands of neurons in awake\, behaving animals. Consequently\, a pressing need arises to distill these data into interpretable insights about how neural circuits give rise to intelligent behaviors.\n\nTo engage with these issues\, I take a computational approach\, known as “task-optimized modeling”\, that leverages recent advancements in artificial intelligence (AI) to express hypotheses for the evolutionary constraints of neural circuits. These constraints guide the iterative optimization of artificial neural networks to achieve a specific behavior (“task”). By carefully analyzing the factors that contribute to model fidelity in predicting large-scale neural response patterns\, we can gain insight into why certain brain areas respond as they do\, and what selective pressures over evolutionary and developmental timescales give rise to the diversity of observed neural responses.\n\nIn this talk\, I apply this approach to examine the functional constraints of brain areas involved in the perception-action loop across multiple timescales: 1. the role of recurrent processing in rapid object recognition (within 250 ms)\, and 2. visually-grounded mental simulation of future environmental states (within several seconds). Finally\, I conclude with future directions towards closing the perception-action loop by extending task-optimized modeling to build integrative\, embodied agents to gain a systems-level understanding of an organism’s brain. These agents would serve as normative accounts of how brain areas collaborate to enable meaningful actions in the physical world. Their design will elucidate the algorithmic principles of natural intelligence conserved across species\, and yield safer\, more grounded embodied AI algorithms.
URL:https://seasevents.nmsdev7.com/event/be-seminar-a-task-optimized-approach-to-systems-neuroscience-aran-nayebi-mit/
LOCATION:Wu and Chen Auditorium (Room 101)\, Levine Hall\, 3330 Walnut Street\, Philadelphia\, PA\, 19104\, United States
CATEGORIES:Seminar
ORGANIZER;CN="Bioengineering":MAILTO:be@seas.upenn.edu
END:VEVENT
END:VCALENDAR