Figure 1: Neural dynamics demonstrate early encoding of movement intent.

A) Task paradigm. B) Population activity from a representative session (participant NS) summarized as 1^st principal component of population response (42% variance explained, mean ± sem with single-trial examples of the population response in grey; 200 ms boxcar smoothing.) C) Single unit examples illustrating diverse temporal responses (500 ms boxcar smoothing). Colors identify four basic temporal profiles found within the population (Cluster analysis, Bayesian information criteria to determine the number of clusters.) Percent of total population falling into each cluster shown in parenthesis. D) Proportion of neurons whose temporal response is best explained relative to reported urge to move (W aligned), EMG onset (M aligned), or neither (No preference), broken up by cluster identity. Percentages in legend (bottom) refer to the total percentage of population collapsing across neural classes identified in panel C. E) Sample neural responses illustrating effector specific and effector general dynamics beginning with trial onset (mean ± sem). Each panel illustrates a separate unit. Panels from left to right are aligned to cue onset, clock onset, and time of reported urge (W). F) Percent of the population demonstrating significant modulation (p<0.05 uncorrected, linear regression) from baseline (black) and significant differences between effectors (grey) through trial progression. G) Population-level latent dimensions demonstrating effector independent and specific network dynamics (cross-validated mean ± 95% ci). The dashed line represents temporal discontinuity from concatenating cue-aligned and movement-aligned signals. We adopt the concatenated visualization for supervised learning techniques to emphasize dependencies between time points. See also Figures S1-3.