Information dynamics in neuronal networks of macaque cerebral cortex reflect cognitive state and behavior.

Abstract One of the essential functions biological neural networks is the processing of information. This comprises processing sensory information to perceive the environment, up to processing motor information to interact with the environment. Due to methodological concerns, it has been historically unclear how information processing changes during different cognitive or behavioral states, and to what extent information is processed within or between the network of neurons in different brain areas. In this study, we leverage recent advances in the calculation of information dynamics to explore neural-level processing within and between the fronto-parietal areas AIP, F5 and M1 during a delayed grasping task performed by three macaque monkeys. While information processing was high within all areas during all cognitive and behavioral states of the task, inter-areal processing varied widely: during visuo-motor transformation, AIP and F5 formed a reciprocally connected processing unit, while no processing was present between areas during the memory period. Movement execution was processed globally across all areas with a predominance of processing in the feedback direction. Additionally, the fine-scale network structure re-configured at the neuron-level in response to different grasping conditions, despite of no differences in the overall amount of information present. These results suggest that areas dynamically form higher-order processing units according to the cognitive or behavioral demand, and that the information processing network is hierarchically organized at the neuron-level, with the coarse network structure determining the behavioral state and finer changes reflecting different conditions. Significance Statement What does it mean to say that the brain “processes information?” Scientists often discuss the brain in terms of information processing – animals take in information from their environment through their senses, and use it to make decisions about how to act in the world. In this work, we use a mathematical framework called information theory to explore how signals from the environment influence brain activity, and how brain activity in turn informs on behaviors. We found that different brain regions processed information in dynamic and flexible ways, with signals flowing up and down the hierarchy of sensory-motor depending on the demands of the moment. This shows how “computation” in the brain can reflect complex behaviors and cognitive states.