Distinct neural modes carry information about attempted grasp timing and force in the sensorimotor cortex

Humans perform a variety of complex hand movements to manipulate objects, requiring precise control of changing forces. Understanding the role of sensorimotor cortex and the cortical dynamics underlying these actions is crucial for developing interventions that restore dexterous hand function after injury or disease. In this study, two male individuals with tetraplegia resulting from cervical spinal cord injury attempted a series of isometric grasps. Neural activity was recorded from the motor and somatosensory cortices using intracortical microelectrode arrays while participants attempted to exert a static or ramping force up and down. Despite their inability to execute movement and limited afferent input, the spiking activity in motor and somatosensory cortex was modulated with the task. Within the neural response we identified independent neural modes - distinct patterns of population-level neural activity that were informative about both the timing and magnitude of the attempted force. Moreover, distinct neural modes were observed during static and dynamic grasping conditions, suggesting independent control schemes for maintaining and changing forces. These modes were related to phases of the task, including the onset, offset, holding periods, as well as increasing and decreasing attempted forces. These results will inform the design of intracortical brain-computer interface (iBCI) systems that can leverage the patterns of grasp and force control evident in sensorimotor cortex during attempted movement to restore dexterous hand function. Significance Statement Restoring dexterous hand function after injury remains a major challenge, partly due to an incomplete understanding of the cortical dynamics underlying grasping and force control. In this study, we investigated neural activity within the motor and somatosensory cortices of individuals with tetraplegia attempting to perform grasps to different target forces with varying temporal profiles. We identified distinct neural modes modulated during specific phases of grasp that encode attempted force information throughout the task. These findings suggest that brain-computer interfaces could leverage these neural modes to restore grasping and force modulation.