Abstract
Visual stimuli are represented by a highly efficient code in the primary visual cortex, but the development of this code is still unclear. Two distinct factors control coding efficiency: Representational efficiency, which is determined by neuronal tuning diversity, and metabolic efficiency, which is influenced by neuronal gain. How these determinants of coding efficiency are shaped during development, supported by excitatory and inhibitory plasticity, is only partially understood. We investigate a fully plastic spiking network of the primary visual cortex, building on phenomenological plasticity rules. Our results suggest that inhibitory plasticity is key to the emergence of tuning diversity and accurate input encoding. We show that inhibitory feedback (random and specific) increases the metabolic efficiency by implementing a gain control mechanism. Interestingly, this led to the spontaneous emergence of contrast-invariant tuning curves. Our findings highlight that (1) interneuron plasticity is key to the development of tuning diversity and (2) that efficient sensory representations are an emergent property of the resulting network.
Highlights
The primary visual cortex (V1) represents visual stimuli in a highly efficient manner [1, 2]
Our model suggests that a single underlying mechanism—the interaction of excitatory and inhibitory plasticity—can explain the stable emergence of reliable and efficient input encoding
To the best of our knowledge, our simulations are the first demonstration of the parallel emergence of fundamental properties of the primary visual cortex such as sparse coding, contrast invariant tuning curves and high accuracy input representation, in a spiking network with spike timing-dependent plasticity rules
Summary
The primary visual cortex (V1) represents visual stimuli in a highly efficient manner [1, 2]. Metabolic efficiency in terms of the number of spikes required to represent a specific input stimulus. This aspect is strongly influenced by gain control mechanisms caused by inhibitory feedback processing [4, 5]. As the synaptic plasticity of inhibitory interneurons in V1 likely exerts strong effects on the outcome of excitatory plasticity [10], complex circuit-level interactions occur between both types of plasticity. This notion has received further support based on recent theoretical studies [11]. These findings raise the question of how excitatory and inhibitory plasticity can cooperate to enable the development of an efficient stimulus code
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