Overlapping Cortical Substrate of Biomechanical Control and Subjective Agency.

The sense of agency (SoA) during movement may be linked to the same neural representations that solve the biomechanical control problem. Using fMRI and a deep neural network performing the same hand-control task in simulation, the authors found detailed cortical encodings of sensorimotor states in visual areas that were best explained by inverse dynamics computations. When they manipulated SoA by electrically stimulating participants' muscles, the same voxels predicted SoA. Model-brain correspondences and robust SoA decoding were achieved within single subjects, enabling individual-level study of motor representations and awareness.

Study at a glance

Abstract

Every movement requires the nervous system to solve a complex biomechanical control problem, but this process is mostly veiled from one's conscious awareness. Simultaneously, we also have conscious experience of controlling our movements-our sense of agency (SoA). Whether SoA corresponds to those neural representations that implement actual neuromuscular control is an open question with ethical, medical, and legal implications. If SoA is the conscious experience of control, this predicts that SoA can be decoded from the same brain structures that implement the so-called "inverse dynamics" computations for planning movement. We correlated human (male and female) fMRI measurements during hand movements with the internal representations of a deep neural network performing the same hand control task in a biomechanical simulation-revealing detailed cortical encodings of sensorimotor states, idiosyncratic to each subject. We then manipulated SoA by usurping control of participants' muscles via electrical stimulation and found that the same voxels which were best explained by modeled inverse dynamics representations-which, strikingly, were located in canonically visual areas-also predicted SoA. Importantly, model-brain correspondences and robust SoA decoding could both be achieved within single subjects, enabling relationships between motor representations and awareness to be studied at the level of the individual.