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SUMMARY:Computational Neuroscience Journal Club - David Liu and Jeroen Oli
 eslagers
DTSTART:20210223T150000Z
DTEND:20210223T163000Z
UID:TALK157633@talks.cam.ac.uk
CONTACT:Jake Stroud
DESCRIPTION:Please join us for our fortnightly journal club online via zoo
 m where two presenters will jointly present a topic together. The next top
 ic is ‘optimal spike coding’ presented by David Liu and Jeroen Oliesla
 gers.\n\nZoom information:\nhttps://us02web.zoom.us/j/84958321096?pwd=dFps
 YnpJYWVNeHlJbEFKbW1OTzFiQT09\nMeeting ID: 849 5832 1096\nPasscode: 506576\
 n\nIn this journal club\, we will explore the topic of optimal spike codin
 g. This line of research provides an alternative view on neural coding. In
  particular\, individual spikes carry significant information\, and stocha
 sticity arising in networks is not merely noise as viewed from a conventio
 nal Poisson rate model perspective. Different versions of such spiking dyn
 amics have been explored in the literature\, but the main idea underpinnin
 g this framework is simple: each neuron only fires whenever the error in d
 ecoding the encoded signal exceeds some threshold. This assigns functional
  meaning to spiking thresholds\, membrane potentials and synaptic connecti
 ons. When applied to recurrently connected networks\, activity exhibits Po
 isson-like statistics and mirrors the asynchronous firing states reported 
 for spontaneous activity in the cortex. We will go through the following p
 apers that introduce this framework\, as well as extensions to probabilist
 ic representations of uncertainty:\n\nDavid:\n1. Bourdoukan\, Ralph\, et a
 l. "Learning optimal spike-based representations." Advances in neural info
 rmation processing systems 25 (2012): 2285-2293.\n\n2. Boerlin\, Martin\, 
 and Sophie Denève. "Spike-based population coding and working memory." PL
 oS Comput Biol 7.2 (2011): e1001080.\n\nJeroen:\n3. Savin\, Cristina\, and
  Sophie Deneve. "Spatio-temporal Representations of Uncertainty in Spiking
  Neural Networks." NIPS. Vol. 27. 2014.\n\n4. Brendel W\, Bourdoukan R\, V
 ertechi P\, Machens CK\, Denéve S. "Learning to represent signals spike b
 y spike." PLoS computational biology. 2020 Mar 16\;16(3):e1007692.\n
LOCATION:Online on Zoom
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