Antagonistic inhibitory subnetworks control cooperation and competition across cortical space

The cortical microcircuit can dynamically adjust to dramatic changes in the strength, scale, and complexity of its input. In the primary visual cortex (V1), pyramidal cells (PCs) integrate widely across space when signals are weak, but integrate narrowly when signals are strong, a phenomenon known as contrast-dependent surround suppression. Theoretical work has proposed that local interneurons could mediate a shift from cooperation to competition of PCs across cortical space, underlying this computation. We combine calcium imaging and electrophysiology to constrain a stabilized superlinear network model that explains how the four principal cell types in layer 2/3 (L2/3) of mouse V1– somatostatin (SST), parvalbumin (PV), and vasoactive intestinal peptide (VIP) interneurons, and PCs transform inputs from layer 4 (L4) PCs to encode drifting gratings of varying size and contrast. Using bidirectional optogenetic perturbations, we confirm key predictions of the model. Our data and modeling show that network nonlinearities set up by recurrent amplification mediate a shift from a positive PC-VIP feedback loop at small size and low contrast to a negative PC-SST feedback loop at large size and high contrast to support this flexible computation. This may represent a widespread mechanism for gating competition across cortical space to optimally meet task demands. ### Competing Interest Statement The authors have declared no competing interest.