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CATEGORIES:Computational Neuroscience
SUMMARY:Computational Neuroscience Journal Club - Johannes
  Friedrich ( CBL\,  Cambridge University\, Enginee
 ring Dept.)
DTSTART;TZID=Europe/London:20140211T160000
DTEND;TZID=Europe/London:20140211T170000
UID:TALK50843AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/50843
DESCRIPTION:Johannes Friedrich will cover:\nThe importance of 
 mixed selectivity in complex cognitive tasks\nRigo
 tti et al.\, Nature (2013)\nhttp://www.nature.com/
 nature/journal/v497/n7451/full/nature12160.html\n\
 nABSTRACT: Single-neuron activity in the prefronta
 l cortex (PFC) is tuned to mixtures of multiple ta
 sk-related aspects. Such mixed selectivity is high
 ly heterogeneous\, seemingly disordered and theref
 ore difficult to interpret. We analysed the neural
  activity recorded in monkeys during an object seq
 uence memory task to identify a role of mixed sele
 ctivity in subserving the cognitive functions ascr
 ibed to the PFC. We show that mixed selectivity ne
 urons encode distributed information about all tas
 k-relevant aspects. Each aspect can be decoded fro
 m the population of neurons even when single-cell 
 selectivity to that aspect is eliminated. Moreover
 \, mixed selectivity offers a significant computat
 ional advantage over specialized responses in term
 s of the repertoire of input–output functions impl
 ementable by readout neurons. This advantage origi
 nates from the highly diverse nonlinear selectivit
 y to mixtures of task-relevant variables\, a signa
 ture of high-dimensional neural representations. C
 rucially\, this dimensionality is predictive of an
 imal behaviour as it collapses in error trials. Ou
 r findings recommend a shift of focus for future s
 tudies from neurons that have easily interpretable
  response tuning to the widely observed\, but rare
 ly analysed\, mixed selectivity neurons.
LOCATION:Cambridge University Engineering Department\, CBL 
 Rm #438 (http://learning.eng.cam.ac.uk/Public/Dire
 ctions)
CONTACT:Guillaume Hennequin
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