eLife Assessment
This study investigates the temporal dynamics of neural activity preceding self-initiated movements and makes a valuable contribution to this field. To overcome methodological and analytical limitations in previous work the authors introduce a matched control condition in which no response is required to assess when neural activity is predictive of self-initiated movement (using electro- and magnetoencephalography). Applying solid methods and machine-learning analyses, the authors show that a late-stage neural event is most predictive of upcoming movements (~100 ms before the response), whereas earlier neural activity is less informative. This finding contradicts previous work that suggested that earlier build-up of neural activity (e.g., starting 500 ms before the response) reflects the planning and preparation of movement.