Combinatorial Neural Inhibition for Stimulus Selection across Space

The ability to select the most salient among competing stimuli is essential for animal behavior and operates no matter which spatial locations stimuli happen to occupy. We provide evidence that the brain employs a combinatorially optimized inhibition strategy for selection across all pairs of stimulus locations. With experiments in a key inhibitory nucleus in the vertebrate midbrain selection network, called isthmi pars magnocellularis (Imc) in owls, we discovered that Imc neurons encode visual space with receptive fields that have multiple excitatory hot spots (“lobes”). Such multilobed encoding is necessitated by scarcity of Imc neurons. Although distributed seemingly randomly, the locations of these lobes are optimized across the high-firing Imc neurons, allowing them to combinatorially solve selection across space. This strategy minimizes metabolic and wiring costs, a principle that also accounts for observed asymmetries between azimuthal and elevational coding. Combinatorially optimized inhibition may be a general neural principle for efficient stimulus selection. Mahajan et al. show that a sparse set of midbrain inhibitory neurons encodes visual space with unusual multilobed receptive fields. This results in a combinatorially optimized solution for selection at all pairs of stimulus locations, which minimizes metabolic and neural wiring costs.