Connectome-based biophysical modeling of a figure-ground discrimination circuit
Figure-ground discrimination (FGD) via relative motion represents a highly conserved visual computation essential for breaking camouflage. Over forty years ago, the Reichardt-Poggio-Hausen (RPH) model proposed a circuit architecture to explain this phenomenon, relying on an inhibitory wide-field pool cell to aggregate global motion and subsequently inhibit elementary motion detectors. However, a biological implementation of the RPH model has remained elusive. Using Drosophila connectomics data and biophysically accurate modeling, we reveal a biological circuit implementing this canonical architecture. Strikingly, we find that while the dendrites of the elemental motion detectors, T4a, are tuned to motion, their axon terminals compute relative motion. This secondary computation is achieved via presynaptic shunting inhibition from the ventral Centrifugal Horizontal (vCH) cell, which acts as a global motion integrator that normalizes the signal carried by the T4 axon terminals during whole-field optic flow. We extend our model to include the motion-opponency and the binocular communication pathways and show that FGD depends on the T4a-vCH interactions. We further show that specific circuit adjustments are sufficient for our model to make predictions consistent with several physiological and behavioral experiments across different fly species. Ultimately, by uniting connectomic connectivity with morphologically accurate biophysics, our approach demonstrates how detailed, synapse-resolution models of the brain can yield fine-grained biological predictions.