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SUMMARY:Restless engrams: the origin of continually reconfiguring neural r
 epresentations - Tim O'Leary\, Department of Engineering\, University of C
 ambridge
DTSTART:20210125T160000Z
DTEND:20210125T171500Z
UID:TALK155674@talks.cam.ac.uk
CONTACT:Marisa Parsonage
DESCRIPTION:During learning\, populations of neurons alter their connectiv
 ity and activity patterns\, enabling the brain to construct a model of the
  external world. Conventional wisdom holds that the durability of a such a
  model is reflected in the stability of neural responses and the stability
  of synaptic connections that form memory engrams. However\, recent experi
 mental findings have challenged this idea\, revealing that neural populati
 on activity in circuits involved in sensory perception\, motor planning an
 d spatial memory continually change over time during familiar behavioural 
 tasks. This continual change suggests significant redundancy in neural rep
 resentations\, with many circuit configurations providing equivalent funct
 ion. I will describe recent work that explores the consequences of such re
 dundancy for learning and for task representation. Despite large changes i
 n neural activity\, we find cortical responses in sensorimotor tasks admit
  a relatively stable readout at the population level. Furthermore\, we fin
 d that redundancy in circuit connectivity can make a task easier to learn 
 and compensate for deficiencies in biological learning rules. Finally\, if
  neuronal connections are subject to an unavoidable level of turnover\, th
 e level of plasticity required to optimally maintain a memory is generally
  lower than the total change due to turnover itself\, predicting continual
  reconfiguration of an engram.
LOCATION:Online via zoom
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