BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//BHI - ECPv6.15.10//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:BHI
X-ORIGINAL-URL:https://brainhealthinstitute.rutgers.edu
X-WR-CALDESC:Events for BHI
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:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20270314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20271107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260923T100000
DTEND;TZID=America/New_York:20260923T110000
DTSTAMP:20261031T112332
CREATED:20260915T105735Z
LAST-MODIFIED:20260917T150739Z
UID:10569-1790157600-1790161200@brainhealthinstitute.rutgers.edu
SUMMARY:CCNP Seminar: Michael Hallquist\, PhD (Emory University)
DESCRIPTION:“Reinforcement learning states and the dynamics of mood”\nDate and Time: Wednesday\, September 23\, 10-11 AM EDT (Eastern)\nZoom link: https://princeton.zoom.us/j/6397147065 \nSpeaker: Michael Hallquist\nAssociate Professor\, Department of Psychology\, Emory University\n\n\nWhy do our moods change over days\, sometimes without an obvious change in our circumstances? Computational accounts propose that mood reflects both rewarding and punishing experiences and how much we learn from them. I will present evidence that fluctuating reinforcement learning states help explain the emergence of positive and negative moods in everyday life.\n\nIn a 28-day study\, 318 participants completed smartphone-based learning tasks twice daily and reported their mood and daily experiences four times daily\, alongside wearable EEG and ECG recordings. A Bayesian reinforcement learning model used choices between stimuli learned on different days to identify dissociable changes in reward and punishment learning. States of amplified reward learning predicted subsequent increases in positive mood\, whereas amplified punishment learning predicted increases in negative mood\, across lags extending to seven days and accounting for prior mood. These learning states were also reflected in cortical and cardiac responses to reinforcement and moderated the relationship between everyday experiences and subsequent mood. Stronger coupling between punishment learning and later negative mood was associated with greater trait negative emotionality.\n\nThese findings support a computational account in which changing learning states influence how experiences accumulate into sustained affective states. I will discuss how connecting learning\, physiology\, and mood across naturalistic timescales can clarify mechanisms of psychiatric vulnerability and motivate new approaches to studying mood disturbances.
URL:https://brainhealthinstitute.rutgers.edu/event/ccnp-seminar-michael-hallquist-phd-emory-university/
END:VEVENT
END:VCALENDAR