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SUMMARY:Interplay of random and nonnormally structured connectivity in the
  dynamics of neural networks I
DTSTART;VALUE=DATE-TIME:20130422T093000Z
DTEND;VALUE=DATE-TIME:20130422T103000Z
DTSTAMP;VALUE=DATE-TIME:20260702T170348Z
UID:indico-event-1907@indico.ific.uv.es
DESCRIPTION:Neuronal networks exhibit significant randomness in their syna
 ptic connectivity. But importantly\, alongside randomness\, the synaptic c
 onnectivity of most neural networks also features ordered structure on var
 ious levels\, depending on the network's function. Investigating the inter
 play of these two features of connectivity and their respective role in th
 e dynamics of neural networks and the computations they perform constitute
 s a general theoretical problem in neuroscience. Of particular interest ar
 e connectivity structures that can be described by a nonnormal matrix. In 
 this case the network can be described as having a hidden feedforward conn
 ectivity structure between orthogonal activity patterns\, each of which ca
 n also excite or inhibit itself. Such networks arise naturally from the se
 paration of excitatory and inhibitory neurons and yield large transient am
 plification of patterns without any dynamical slowing. This latter effect 
 has been used to explain the similarity of the fluctuating patterns of spo
 ntaneous activity in primary visual cortex (V1) to patterns of activity ev
 oked by visual stimuli.\nIn my first talk\, I will give a general overview
  of the early visual system\, review some of the relevant literature beari
 ng on the above problems and topics\, including the experimental observati
 ons of the spontaneous activity in V1\, and two different theoretical appr
 oaches to modeling them.\n\nhttps://indico.ific.uv.es/event/1907/
LOCATION:Edf. Institutos de Investigación Sala Seminarios IFIC
URL:https://indico.ific.uv.es/event/1907/
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