A recurrent circuit implements normalization, simulating the dynamics of V1 activity.

ABSTRACT: The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model's defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. Despite the success of the normalization model, there are three unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another's normalization pool. It is unknown how weighted normaliza

SUBMITTER: Heeger DJ 

PROVIDER: S-EPMC7486719 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature