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Neuronal heterogeneity of normalization strength in a circuit model
Abstract Neurons in higher-order visual areas integrate information through a canonical computation called normalization. The strength of normalization is highly heterogeneous across neurons, and this heterogeneity correlates with attention-mediated modulations in neural responses. However, the circuit mechanism underlying the heterogeneous normalization strength is unclear. In this work, we study normalization in a spiking neuron network model of visual cortex.
Neuronal heterogeneity of normalization strength in a circuit model
Abstract The size of a neuron's receptive field increases along the visual hierarchy. Neurons in higher-order visual areas integrate information through a canonical computation called normalization, where neurons respond sublinearly to multiple stimuli in the receptive field. Neurons in the visual cortex exhibit highly heterogeneous degrees of normalization.
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