Stochastic and synchronous neural circuit dynamics underlying feature-similarity gain modulation
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Transcript of Stochastic and synchronous neural circuit dynamics underlying feature-similarity gain modulation
Stochastic and synchronous neural circuit dynamicsunderlying feature-similarity gain modulation
Xiao-Jing Wang With Salvador Ardid and Albert Compte
Calibrate MT network:normalization by strong recurrent
inhibitionInput coming from V1 MT model output
Snowden, Treue, Erickson, Andersen 1991; Heeger 1992
MT activity when A=S are covaried
Martinez-Trujillo and Treue, 2004
Attno Att
Network pattern in a single trial
Neural label
R(,S,A)=G(A-) R0(-S)
R(,S,A)=R(-S,-A,A-S)
R(-S,-A)=G(A-) R0(-S)
G(A-)= 1+g0 cos(A-)
Feature-similarity
Multiplicative scaling of single cell’s tuning curve But selective enhancement of population activity profile in single trials
Feature-similarity gain principleholds for transparent motion
Att
no Attprediction
Neural label
R(-S,-A)=G(A-) R0(-S)