Convergence-divergence circuits for multimodal integration of innate and learned opponent valences.

Valence detection in complex environment is critical for natural behaviors like foraging. Previous studies have explored valence processing in brain regions like lateral horn (LH) and mushroom body (MB) using simple synthetic stimuli in Drosophila. However, the neural basis for valence detection of natural objects in complex contexts remains unclear. Here, by brain-wide connectome analysis, we identified the evolutionarily conserved superior protocerebrum (SP) that integrates brain-wide multimodal inputs mainly via LH and MB, and sends widespread outputs particularly to the central complex (CX). This forms a convergence-divergence circuit resembling an autoencoder architecture, with SP as the bottleneck integrating multimodal information into low-dimensional valence signals. Specifically, SP input LH neurons integrate ethologically related innate valences for robust valence detection in natural environments, and the integration can be unimodal, such as that of diverse odors signaling food, or multimodal, such as that of wind and temperature signaling lousy weather. Opponent valences of attraction and aversion are further integrated into SP for complex valence detection. MB learned valences are also integrated into SP to update LH innate valences with recent experience for flexible valence detection. Attractive and aversive valences, either innate or learned, are integrated via excitatory and inhibitory synapses, respectively to form complex valence signals in a single SP neuron. Organized synaptic compartments support dendritic computation, with SP neurons exhibiting opposite synaptic organizations for opponent valences, indicating dendritic integration for complex valence detection. Our study highlights the importance of SP in multimodal opponent valence integration and suggests generalizable network and dendritic structures for complex valence processing.