Conference on Cognitive Computational Neuroscience

Complex behavior is supported by the effective coordination of multiple brain regions. Here, we propose a general modeling framework to cross-system interactions encompassing perception and cognition. Coordination is achieved by a controller-peripheral architecture in which peripherals (e.g., sensory streams) aim to supply needed inputs to controllers (e.g., hippocampus and prefrontal cortex) while expending minimal resources. We developed a model within this framework to address how multiple brain regions coordinate to support rapid learning from images. The model captured category learning behavior and how higher-level activity in the controller shaped lower-level visual representations, affecting their precision and sparsity in a manner that paralleled brain measures. Alternative models optimized by gradient descent irrespective of architectural constraints could not account for human behavior or brain responses.