GABA diffusion across neuronal columns for efficient sensory tuning.

Synaptic (phasic) lateral inhibition between neuronal columns mediated by GABAergic interneurons is, in general, essential for primary sensory cortices to respond selectively to elemental features. We propose here a neural network model with a nonsynaptic (tonic) lateral inhibitory mechanism. While firing, intrasynaptic GABA molecules spill over into extracellular space and accumulate in neuronal columns. Through accumulation in and diffusion across these columns, a level of ambient (extracellular) GABA changes in a neuronal activity-dependent manner. Ambient GABA molecules act on extrasynaptic receptors and provide neurons with tonic inhibitory currents. We examined whether and how the diffusion of GABA molecules across neuronal columns affects tuning performance of the network to a feature stimulus: selective responsiveness. The GABA diffusion led to reducing ambient GABA in the stimulus-relevant column while augmenting ambient GABA in stimulus-irrelevant columns, thereby improving the tuning performance. The GABA diffusion was effective especially when provided with a broader sensory input. Interestingly, this diffusion-based, nonsynaptic (tonic) lateral inhibitory scheme worked well together with the conventional, synaptic (phasic) lateral inhibitory scheme, enhancing the sensory tuning. We suggest that the nonsynaptic lateral inhibition, mediated through GABA diffusion across neuronal columns, may be beneficial for the cortex to tune to sensory features.