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SUMMARY:Computational Neuroscience Journal Club - Cristina Savin (Computat
 ional and Biological Learning Lab\, Department of Engineering\, University
  of Cambridge)
DTSTART:20101005T150000Z
DTEND:20101005T160000Z
UID:TALK27011@talks.cam.ac.uk
CONTACT:Prof Máté Lengyel
DESCRIPTION:Cristina Savin presents\n\nWiechert MT\, Judkewitz B\, Riecke 
 H\, Friedrich RW\n\n*Mechanisms of pattern decorrelation by recurrent neur
 onal circuits*\n\n_Nature Neuroscience_ 13:1003-10\, 2010. \n\nThe paper i
 s available at http://www.nature.com/neuro/journal/v13/n8/full/nn.2591.htm
 l\n\nAbstract:\n\nDecorrelation is a fundamental computation that optimize
 s the format of neuronal activity patterns. Channel decorrelation by adapt
 ive mechanisms results in efficient coding\, whereas pattern decorrelation
 \nfacilitates the readout and storage of information. Mechanisms achieving
  pattern decorrelation\, however\, remain unclear. We developed a theoreti
 cal framework that relates high-dimensional pattern decorrelation to neuro
 nal and circuit properties in a mathematically\nstringent fashion. For a g
 eneric class of random neuronal networks\, we proved that pattern decorrel
 ation emerges from neuronal nonlinearities and is amplified by recurrent c
 onnectivity. This mechanism does not\nrequire adaptation of the network\, 
 is enhanced by sparse connectivity\, depends on the baseline membrane pote
 ntial and is robust. Connectivity measurements and computational modeling 
 suggest that this mechanism is\ninvolved in pattern decorrelation in the z
 ebrafish olfactory bulb. These results reveal a generic relationship betwe
 en the structure and function of neuronal circuits that is probably releva
 nt for pattern\nprocessing in various brain areas.\n
LOCATION:Cambridge University Engineering Department\, Rm BE4-38 (http://l
 earning.eng.cam.ac.uk/Public/Directions)
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