Skip to contentSkip to filters

We use cookies for analytics.

Topic: stimulus-driven decorrelation

ePoster
1 ePoster

In Computational Neuroscience and Mathematical Biology

ePoster · Computational Neuroscience

Gain-mediated statistical adaptation in recurrent neural networks

Lyndon Duong,Colin Bredenberg,David Heeger,Eero Simoncelli · COSYNE 2022

Thu, Mar 17, 2022

Sensory neurons in different species, brain areas, and modalities adjust their sensitivity (gain) in response to recent stimulus history. This gain control offers a mechanism for single neurons to rapidly and reversibly adapt to different stimulus contexts while preserving synaptic weights that serve to represent features that remain consistent across contexts. From a normative perspective, this allows an individual neuron to adjust the dynamic range of its responses to accommodate changes in input statistics -- a core tenet of Barlow's efficient coding theory. However, experimental measureme