Behavioral and Neural Variability of Naturalistic Arm Movements

Motor behaviors are central to many functions and dysfunctions of the brain, and understanding their neural basis has consequently been a major focus in neuroscience. However, most studies of motor behaviors have been restricted to artificial, repetitive paradigms, far removed from natural movements performed "in the wild." Here, we leveraged recent advances in machine learning and computer vision to analyze intracranial recordings from 12 human subjects during thousands of spontaneous, unstructured arm reach movements, observed over several days for each subject. These naturalistic movements elicited cortical spectral power patterns consistent with findings from controlled paradigms, but with considerable neural variability across subjects and events. We modeled inter-event variability using ten behavioral and environmental features; the most important features explaining this variability were reach angle and day of recording. Our work is among the first studies connecting behavioral and neural variability across cortex in humans during unstructured movements and contributes to our understanding of long-term naturalistic behavior. SIGNIFICANCE STATEMENT Understanding the neural basis of human movement has long been a key focus in neuroscience. However, researchers often study constrained, monotonous tasks that differ greatly from the rich and diverse natural movements we actually make. Here, we use data-intensive computational approaches to reveal patterns in neural activity underlying naturalistic human arm movements. While such movements match previous experimental findings on average, there is substantial neural variability from one movement to the next. We partially explain this variability by aspects of the movement observed, though much variability remains unaccounted for. Our study sheds light on how the brain generates natural arm movements and emphasizes the critical need to study brain activity in more unstructured settings that mimic daily life.