Information formatting in neuronal populations predicts differential functional contributions to behavior

Neurons throughout the brain encode essentially everything, so why have distinct areas? We proposed that areas format different information sources differently, implying their computational role. Here we compared the middle temporal (MT) area, involved in visual motion perception, and the dorsolateral prefrontal cortex (dlPFC), implicated in decision-making and reward. In a task that required monkeys to combine motion and reward information, both regions encoded both motion and reward, but formatted differently. Area MT represented them separably, whereas the dlPFC combined them in a decision-related format. A recurrent network model trained to reproduce that formatting predicted a distinct effect of stimulating those areas. Consistent with predictions, MT stimulation biased choices whereas dlPFC stimulation produced ‘winner-take-all’ outcomes. Our findings suggest that a modular structure flexibly reformats information to enable complex behaviors. Using experiments in monkeys and modeling, the authors demonstrate that the formatting of population information predicts the contribution of different brain areas to behavior.