Watch, Imagine, Attempt: Motor Cortex Single-Unit Activity Reveals Context-Dependent Movement Encoding in Humans With Tetraplegia

Carlos E Vargas-Irwin, Jessica M Feldman, Brandon King, John D Simeral, Brittany L Sorice, Erin M Oakley, Sydney S Cash, Emad N Eskandar, Gerhard M Friehs, Leigh R Hochberg, John P Donoghue, Carlos E Vargas-Irwin, Jessica M Feldman, Brandon King, John D Simeral, Brittany L Sorice, Erin M Oakley, Sydney S Cash, Emad N Eskandar, Gerhard M Friehs, Leigh R Hochberg, John P Donoghue

Abstract

Planning and performing volitional movement engages widespread networks in the human brain, with motor cortex considered critical to the performance of skilled limb actions. Motor cortex is also engaged when actions are observed or imagined, but the manner in which ensembles of neurons represent these volitional states (VoSs) is unknown. Here we provide direct demonstration that observing, imagining or attempting action activates shared neural ensembles in human motor cortex. Two individuals with tetraplegia (due to brainstem stroke or amyotrophic lateral sclerosis, ALS) were verbally instructed to watch, imagine, or attempt reaching actions displayed on a computer screen. Neural activity in the precentral gyrus incorporated information about both cognitive state and movement kinematics; the three conditions presented overlapping but unique, statistically distinct activity patterns. These findings demonstrate that individual neurons in human motor cortex reflect information related to sensory inputs and VoS in addition to movement features, and are a key part of a broader network linking perception and cognition to action.

Keywords: human; microelectrode array; motor cortex; single unit; tetraplegia.

Figures

Figure 1
Figure 1
Single units in primary motor cortex (MI) are active during watch, imagine and attempt conditions. (A) WIA task sequence. The timeline of still frames indicates the time course of animated arm movements viewed by the participants, with 0 indicating movement onset. Event timing was identical for all movement directions. The same movies were utilized in different blocks paired with verbal instructions to watch, imagine, or attempt the displayed movements given before each block. (B–E) Single-unit activity for subject S3 (B,C) and T1 (D,E). The mean waveform for each unit is shown on the top left of each panel. Classification accuracy for each unit (% of correctly classified trials) according to volitional state (VoS) condition or action (within each VoS condition) are listed on the top left (see “Materials and Methods” section for details). Mean firing rates across W, I and A conditions (averaged over ~10 trials for each target in each condition) are highlighted in black, blue and orange, respectively. Subplots are arranged spatially according to target position (indicated by filled black circle in top right corner). Plots are aligned to center-out movement onset (time zero). Dashed lines mark peak velocities for the center-out and return to center movements. Firing rates were calculated in 1 ms bins smoothed with a 250 ms Gaussian kernel for each neuron.
Figure 2
Figure 2
Actions and VoS are encoded by overlapping populations of single units. (A,B) Percentage of neurons displaying information related to VoS (watch, imagine, or attempt) or action (different movement) conditions in each participant (SSIMS analysis, see “Materials and Methods” section). The proportion of VoS related neurons is lower in T1, despite similar percentages of action related neurons. (C) Classes of action-related neurons, depending on engagement across W, I, A conditions (for example, yellow bars represent AI neurons, which displayed different activity patterns for movements aimed at different targets in both A and I). (D) Same bars and color scheme as in (C), but with the bars stacked according to the types of neurons engaged in each VoS (separated by participant). The height of each bar represents the total percentage of action-related neurons recorded in each condition. Note that some of the stacked bars are shown more than once (for example, purple AW neurons are counted for both A and W conditions).
Figure 3
Figure 3
Single units display action-related information across volitional states. SSIMS NN classifiers were used to decode actions (reaching movements to four different targets) using single-unit data. (A–C) Distribution of single-unit classification results across neurons for each VoS, pooled across sessions for each participant. Gray bars correspond to participant S3, black outlines to participant T1. Black triangles on the x-axis mark the expected chance value. (D–F) Scatter plots comparing decoding performance across pairs of conditions. In each plot, units yielding classification below the 95% confidence limit of the chance distribution are shown in gray, units over the 95% confidence limit in only one category shown in orange, and units yielding significant decoding in two categories are shown in black. Filled circles correspond to units from participant S3, while + signs are used for units from participant T1. The units labeled (B–E) correspond to those shown in Figure 1.
Figure 4
Figure 4
Ensemble firing patterns reflect action as well as volitional states. (A,B) 2D SSIMS plots for one sample session in each participant. Each point represents the activity of the entire simultaneously recorded ensemble during one trial. The distance between points represents the similarity between the ensemble-level spiking patterns observed. Symbols denote W, I, A condition and colors denote reach target position, as shown in the key. Clustering of similar symbols denotes similarity between trials in the same VoS condition, while clustering of similar colors denotes similarity between trials with the action (movie). (C,D) Action and VoS decoding results for each session. Dashed lines represent the 95% confidence interval of the chance distribution (obtained empirically from 10,000 random shuffles of trial labels). (E,F) Similar plots to (C,D), except using 0.5 s of data recorded before the presentation of each movie (inter-trial interval, ITI). Only VoS decoding in participant S3 was above chance levels during the ITI.
Figure 5
Figure 5
Latency of neural response does not vary across volitional states. Histogram of single-unit response latencies (occurrence of first significant change in firing rate, see “Materials and Methods” section) for both participants (S3: A,C,E; T1: B,D,F) across the three VoS conditions (attempt: A,B; imagine: C,D; watch: E,F). Time zero corresponds to the beginning of the movies. Circles denote the time of target illumination, triangles movement onset, × maximum velocity and squares target acquisition. Black line shows the cumulative sum of the percentage of neurons displaying significant changes in firing rate at each time point.
Figure 6
Figure 6
Trends in ensemble firing rate across time. Ensemble firing rates (EFRs) for each trial (mean across all simultaneously recorded neurons) are plotted against total session time. (A–C) Sessions for participant S3. (D–F) Sessions for participant T1. Vertical dashed black lines separate VoS condition blocks, which are labeled above each plot (note reversed order of sessions in F). Dashed blue lines represent the Theil-Sen slope estimate for the full session. Solid orange lines represent the slope calculated for each W, I and A block separately. Only slopes significantly different form zero are shown (Kendall’s Tau). Asterisks are used to indicate p values (*p < 0.05; **p < 0.01; ***p < 0.0001).

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