BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:NeuroLunch: Ke Chen (Wang Lab) & Miranda Dawson (Fan Lab)
X-WR-TIMEZONE:Eastern Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260612T144710Z
UID:tag:localist.com\,2008:EventInstance_52109701729303
DTSTART:20260427T160000Z
DTEND:20260427T170000Z
DESCRIPTION:Title: Dopamine signatures of excessive and compulsive cocaine 
 and fentanyl use\n\nSpeaker: Ke Chen (Wang Lab)\n\nAbstract: Excessive and
  compulsive drug use despite adverse consequences is a hallmark of addicti
 on\, yet individuals differ markedly in their vulnerability. Drugs of abus
 e alter endogenous dopamine (DA) signaling\, but shared principles linking
  DA dynamics to compulsive use across individuals and drug classes are unc
 lear. Here\, we monitored DA release in nucleus accumbens (NAc) medial she
 ll during cocaine or fentanyl self-administration\, with or without punish
 ment\, in large mouse cohorts. Contingent cocaine and fentanyl self-admini
 stration evoked complex and individually distinct DA dynamics\, yet a robu
 st negative correlation emerged across both drugs: high takers showed lowe
 r drug-evoked DA signals. Under punished drug taking\, cocaine and fentany
 l produced distinct DA signatures of compulsivity. A computational model g
 rounded in the Actor-Critic temporal-difference (TD) learning framework wi
 th considerations ofinternal states\, action cost and drug-specific effect
 s captured the observed diversity in DA dynamics across conditions\, unify
 ing NAc DA as encoding TD reward prediction errors in addiction.\n\nTitle:
  Machine learning-guided rhodopsin engineering enables sensitive all-optic
 al voltage imaging and optogenetics\n\nSpeaker:Miranda Dawson (Fan Lab)\n\
 nAbstract:  Understanding how neural circuits change during learning and d
 isease requires tools that can measure fast synaptic voltage signals with 
 high spatial and temporal resolution. Genetically encoded voltage indicato
 rs (GEVIs) enable optical recording of membrane potential dynamics from ge
 netically defined neurons\, but current sensors lack the sensitivity and r
 obustness needed to reliably resolve subthreshold synaptic events on singl
 e trials in vivo during behavior. We develop and apply next-generation rho
 dopsin-based GEVIs optimized for brightness\, voltage sensitivity\, and ki
 netics. Using a machine learning-guided protein engineering framework\, ca
 ndidate indicators are computationally prioritized across multiple perform
 ance parameters and experimentally benchmarked using all-optical electroph
 ysiology in neuronal cultures. Top-performing variants are integrated with
  two-photon optogenetic approaches to establish an all-optical platform ca
 pable of resolving unitary synaptic excitation and inhibition in intact ne
 ural circuits during behavior. By enabling direct optical measurement of s
 ynaptic signaling during behavior\, this work overcomes a critical technic
 al barrier in systems neuroscience and provides new tools for investigatin
 g circuit plasticity mechanisms underlying learning\, memory\, and neurolo
 gical disorders.
GEO:42.362302;-71.091766
LOCATION:Building 46\, 3310
SUMMARY:NeuroLunch: Ke Chen (Wang Lab) & Miranda Dawson (Fan Lab)
URL;VALUE=URI:https://calendar.mit.edu/event/neurolunch-ke-chen-wang-lab-mi
 randa-dawson-fan-lab
CATEGORIES:Conferences/Seminars/Lectures
END:VEVENT
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