Distributed neural dynamics underlie the shift from movement preparation to execution

Abstract

Dissociating the neural mechanisms of movement preparation from those of execution across the brain is fundamental to understanding motor control. Invasive recordings in primary motor cortex (M1) indicate that shared neural populations support both phases by unfolding within orthogonal subspaces or "manifolds", yet whether and how these dynamics evolve across the broader set of brain regions involved in memory-guided skilled action remains poorly understood. Here, we used magnetoencephalography (MEG) data obtained during a memoryguided delayed finger-sequence task to track fast population dynamics across M1, premotor cortices, and the hippocampus. Linear discriminant analysis decoding of sequence-specific preparatory and execution patterns revealed a transition from preparation to execution patterns across all regions prior to movement onset. Importantly, the onset of execution exhibited region-specific timing, with M1 shifting last,[~] 100 ms before the first button press, consistent with the established cortical motor hierarchy. Low-dimensional trajectories showed that preparatory and execution states occupied distinct manifolds, yet were not fully orthogonal, suggesting partial overlap in tuning. MEG dynamics were dominated by peri-movement phase activity in the primary motor and premotor regions. Nevertheless, above-chance sequence decoding was recoverable from all motor and premotor regions during execution and in M1 during preparation. The state shift and the decoding accuracy were driven by distributed modulations across multiple frequency bands, indicating that full-band population dynamics carry richer information than band-limited features alone. These results demonstrate that non-invasive MEG can resolve continuous, hierarchical neural state transitions in the human brain in the context of memory-guided movement control. They offer mechanistic insight into distributed motor-related brain dynamics and support developing brain-computer-interfaces that incorporate signals from multiple brain regions beyond the primary motor cortex.