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SUMMARY:Computational Neuroscience Journal Club - Dr. David Barrett (Unive
 rsity of Cambridge)
DTSTART:20150609T150000Z
DTEND:20150609T160000Z
UID:TALK59799@talks.cam.ac.uk
CONTACT:Guillaume Hennequin
DESCRIPTION:David Barrett will cover:\n\n* Diverse coupling of neurons to 
 populations in sensory cortex\n* M Okun\, N A Steinmetz\, L Cossell\, M F 
 Iacaruso\, H Ko\,P Barthó\,	T Moore\, S B Hofer\, T D Mrsic-Flogel\, M Ca
 randini	& K D Harris\n* Nature (2015)\n* http://www.nature.com/nature/jour
 nal/v521/n7553/full/nature14273.html\n\nA large population of neurons can\
 , in principle\, produce an astronomical number of distinct firing pattern
 s. In cortex\, however\, these patterns lie in a space of lower dimension 
 as if individual neurons were “obedient members of a huge orchestra”. 
 Here we use recordings from the visual cortex of mouse (Mus musculus) and 
 monkey (Macaca mulatta) to investigate the relationship between individual
  neurons and the population\, and to establish the underlying circuit mech
 anisms. We show that neighbouring neurons can differ in their coupling to 
 the overall firing of the population\, ranging from strongly coupled ‘ch
 oristers’ to weakly coupled ‘soloists’. Population coupling is large
 ly independent of sensory preferences\, and it is a fixed cellular attribu
 te\, invariant to stimulus conditions. Neurons with high population coupli
 ng are more strongly affected by non-sensory behavioural variables such as
  motor intention. Population coupling reflects a causal relationship\, pre
 dicting the response of a neuron to optogenetically driven increases in lo
 cal activity. Moreover\, population coupling indicates synaptic connectivi
 ty\; the population coupling of a neuron\, measured in vivo\, predicted su
 bsequent in vitro estimates of the number of synapses received from its ne
 ighbours. Finally\, population coupling provides a compact summary of popu
 lation activity\; knowledge of the population couplings of n neurons predi
 cts a substantial portion of their n2 pairwise correlations. Population co
 upling therefore represents a novel\, simple measure that characterizes th
 e relationship of each neuron to a larger population\, explaining seemingl
 y complex network firing patterns in terms of basic circuit variables.\n
LOCATION:Cambridge University Engineering Department\, CBL\, BE-438 (http:
 //learning.eng.cam.ac.uk/Public/Directions)
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