Abstract
AbstractThere is considerable trial-to-trial variability in single cortical neurons when performing the same action repeatedly. One possibility is that neural populations are more stable in representing actions; alternatively, they too may be distinctly engaged from trial-to-trial. To address the nature of variability in large neural populations, we captured the EEG signals time-locked to repeated voluntary thumb flexion movements (∼500 repetitions, 23 subjects). By using non-negative matrix factorization on the low-frequency sensorimotor cortical signals, we quantified the trial-to-trial motor-related potentials (MRPs) in terms of prototypical signals (meta-MRPs) and their corresponding prominence at each trial (meta-trials). Clustering the meta-MRPs across the sampled population revealed 5 distinct signal patterns. There were brain-wide correlates of these meta-MRP clusters. Cortical hemispheres were distinctly recruited from trial-to-trial as certain clusters were accompanied by bilateral motor negativity while others were characterized by ipsilateral motor negativity. The sensory feedback too was distinctly processed from trial-to-trial as the central post-movement positivity was present only for certain clusters. A poorly understood pre-motor positivity accompanied all clusters albeit varying in their timing from trial-to-trial. These patterns – including the time-varying positivity preceding the movement – were rendered invisible by the traditional averaging of the signals. We suggest that the variability in EEG signals is not just noise but a consequence of distinct activation patterns deployed by the cortex. We support the idea that the cortex flexibly switches between distinct forms of neural processing to achieve the same behavioral goals.
Publisher
Cold Spring Harbor Laboratory