Independent generation of sequence elements by motor cortex

Abstract

Rapid execution of motor sequences is believed to depend on fusing movement elements into cohesive units that are executed holistically. We sought to determine the contribution of primary motor and dorsal premotor cortex to this ability. Monkeys performed highly practiced two-reach sequences, interleaved with matched reaches performed alone or separated by a delay. We partitioned neural population activity into components pertaining to preparation, initiation and execution. The hypothesis that movement elements fuse makes specific predictions regarding all three forms of activity. We observed none of these predicted effects. Rapid two-reach sequences involved the same set of neural events as individual reaches but with preparation for the second reach occurring as the first was in flight. Thus, at the level of dorsal premotor and primary motor cortex, skillfully executing a rapid sequence depends not on fusing elements, but on the ability to perform two key processes at the same time.

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Fig. 1: Task structure.
Fig. 2: Potential strategies for generating compound reaches.
Fig. 3: Single-neuron responses.
Fig. 4: Time-course of activity in preparatory dimensions.
Fig. 5: Patterns of preparatory activity.
Fig. 6: Evolution of the CIS.
Fig. 7: A recurrent network trained to generate reach sequences.
Fig. 8: Similarities between motor cortical activity and network activity.

Data availability

All relevant data are available from the authors upon reasonable request.

Code availability

The trained RNN used in Figs. 7 and 8 is available at Gigantum (https://doi.org/10.34747/n3rs-9w57).

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Acknowledgements

We thank Y. Pavlova for excellent animal care. This work was supported by the Grossman Center for the Statistics of Mind, the Simons Foundation (M.M.C.), the McKnight Foundation (M.M.C.), NIH Director’s New Innovator Award DP2 NS083037 (M.M.C.), NIH CRCNS R01NS100066 (M.M.C.), NIH 1U19NS104649 (M.M.C.), P30 EY019007 (M.M.C.), the National Science Foundation (A.J.Z.) and the Kavli Foundation (M.M.C.).

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A.J.Z. and M.M.C. conceived the experiments, designed the data analyses and wrote and edited the manuscript. A.J.Z. collected the data and performed the analyses.

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Correspondence to Mark M. Churchland.

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Peer review information Nature Neuroscience thanks Paul Cisek and Katja Kornysheva for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Single and compound-reach conditions.

a, Reach paths for single-reach conditions (same as in Fig. 1a) for Monkey B. Paths are averaged across all trials and sessions. b, Reach paths for all compound-reach conditions performed by monkey B (a superset of those in Fig. 1a). Most first-target locations were used for only one compound-reach condition, to maintain a reasonable trial-counts. This was necessary because monkey B performed delayed double-reach conditions using three instructed pauses, which added to the total number of conditions performed. For similar reasons, delayed double-reach conditions employed a subset of the two-target combinations (those in red and blue) that were employed during compound reaches. c, Same as a, but for monkey H. For monkey H, the bottom-right and top-right targets were shifted slightly to the right and left (respectively) compared to the locations used for monkey B. This shift was necessary to prevent the animal’s arm from blocking sight of the second target during certain conditions (the two monkeys were of different sizes and employed slightly different postures when reaching). d, Same as b, but for monkey H. Monkey H performed a greater number of compound reach conditions than monkey B.

Extended Data Fig. 2 Activity of neuron 066 (Monkey B) across all conditions.

a, Response during single-reach conditions, as in Fig. 3a, but for all single reaches. Circles indicate the time of target onset (t), reach onset (r), and reach end (e). b, Response during delayed double reaches with a 600 ms instructed pause, as in Fig. 3b. c, Response during delayed double-reaches with a 300 ms instructed pause. d, Response during delayed double-reaches with a 100 ms instructed pause. e, Response during all compound reach conditions, as in Fig. 3c, but for all conditions.

Extended Data Fig. 3 Responses of four exemplar motor cortex units.

a, Response of neuron 322, recorded from Monkey H. Same as in Fig. 3d–f, but for all single reaches and all two-reach combinations. Circles indicate the time of target onset (t), reach onset (r), and reach end (e). bd, Responses of three additional example units. As is typical, these units are active during both the delay and execution-epochs of single reaches. It is thus difficult to determine via inspection whether there is a second bout of preparation during compound reaches.

Extended Data Fig. 4 Time-course of activity in preparatory dimensions during all conditions, monkey B.

Same as in Fig. 4a–f, but with the addition of data for delayed double reaches with 300 and 100 ms pauses. a, Same data shown in Fig. 4a: projections of population activity during single reach conditions onto the first preparatory dimension. Circles indicate the time of target onset (t), reach onset (r), and reach end (e). bd, Activity in the first preparatory dimension during delayed double-reach conditions with an instructed pause of 600 ms (b), 300 ms (c) and 100 ms (d). e, Activity in the first preparatory dimension during compound reach conditions, as in Fig. 4c. f, Occupancy of all 20 preparatory dimensions during single reach conditions. This panel plots the same data shown in Fig. 4d. Shaded regions indicate the standard deviation of the sampling error estimated by resampling individual units (n = 1,000 resampled populations). gi, Occupancy of preparatory dimensions during delayed double-reach conditions with an instructed pause of 600 ms (g), 300 ms (h) and 100 ms (i). j, Occupancy of preparatory dimensions during compound reach conditions, as in Fig. 4f.

Extended Data Fig. 5 Defining the preparatory dimensions using all preparatory epochs.

Same analysis as in Fig. 4d,e,f,k,l,m, but identification of dimensions employed an epoch of dwell-period activity from compound reach conditions (activity within a 40 ms window beginning 140 ms before the onset of the second reach) in addition to the epochs contributed by single and delayed-double reaches. a, Occupancy (of 20 preparatory dimensions) during single reaches for monkey B. Circles indicate the time of target onset (t), reach onset (r), and reach end (e). Shaded regions indicate the standard deviation of the sampling error estimated by resampling individual units (n = 1000 resampled populations). b, Occupancy of the same preparatory dimensions during delayed double reaches. c, Occupancy of the same preparatory dimensions during compound reaches. This panel plots the same data shown in Fig. 4g. df, Same as ac, but for monkey H.

Extended Data Fig. 6 Patterns of execution-related activity.

Analysis is similar to that in Fig. 5, but was applied to activity during movement. a, Comparison between single and compound reaches. Each marker plots the activity (in 1 of 10 execution dimensions, at a single point in time) for a pair of conditions that share a first reach. Because execution activity (unlike preparatory activity) is strongly time-varying, we include activity from 4 time points (50 ms intervals, starting 25 ms before reach onset). Data are from monkey B. b, same but for monkey H.

Extended Data Fig. 7 The ability to predict preparatory activity from first-reach muscle activity does not differ for compound reaches, relative to single and delayed double-reaches.

The holistic hypothesis predicts that preparatory activity, during the instructed delay, should reflect the full compound reach. If so, it should not be readily predicted from the characteristics of the first reach alone. We thus asked whether the ability to predict preparatory activity from first-reach muscle activity was reduced for compound reaches. We used dimensionality reduction to summarize muscle activity via a small number of variables, and used these as regressors to predict the low-dimensional preparatory state (see Methods for full details). Prediction performance was quantified using cross-validation. a, Results for monkey B. Gray circles plot leave-one-out cross-validation performance for each individual condition. Red circles and error bars show the median and the median absolute deviation. Performance for compound reach conditions was not significantly lower than that for single and delayed-double reach conditions. Indeed it was slightly higher. Median R2 = 0.92 and 0.95 for single/delayed-double and compound reach conditions, respectively (p = 0.92, Mann-Whitney one-tailed test; n = 12 and 10). b, Same as a, but for monkey H. Performance for compound reach conditions was not significantly lower than that for single and delayed-double reach conditions. Median R2 = 0.97 and 0.95 for single/delayed-double and compound-reach conditions, respectively (p = 0.07, Mann-Whitney one-tailed test; n = 22 and 16).

Extended Data Fig. 8 Individual-unit delay-period activity is similar before compound reaches and corresponding single reaches.

a, The trial-averaged firing rate of each unit, for each condition, was calculated during a 100 ms window, beginning 170 ms prior to reach onset. For each recorded unit, we then correlated the firing rates before compound reaches with those before corresponding single reaches. A unity correlation indicates that firing rates depended only on the identity of the first reach. A correlation less than unit could indicate either the influence of the second reach (as proposed by the holistic hypothesis) or the influence of measurement noise. The latter is relevant because many units had weak-to-modest ‘preparatory tuning’ (the range of firing rates across conditions), making strong correlations unlikely given measurement noise. We thus plotted the correlation versus the strength of preparatory tuning. Each light gray marker represents an individual unit. To improve visibility, marker size increases with tuning strength. Error bars represent the 95% confidence interval of the correlation for each unit, calculated by resampling individual trials with replacement (n = 1000 resampled populations). The correlation between the delay-period activity of single and compound reaches increases sharply with tuning strength (red trace) and plateaued near unity, consistent with the independent hypothesis. Data were fit with a hyperbolic tangent with a single free parameter that determined the slope of the function. Data are for monkey B. b, Distribution of correlations for all individual units from monkey B (median ρ = 0.77). c, Same but for units with stronger preparatory tuning (top tertile; median ρ = 0.94). d–f, Same as a–c, but for monkey H. Median ρ was 0.74 and 0.90 for the two distributions.

Extended Data Fig. 9 Activity within condition-invariant dimensions during all conditions, monkey B.

Same as in Fig. 6a–c, but with the addition of data for delayed double reaches with 300 and 100 ms pauses. The added analyses are in panels c and h (300 ms pause) and d and i (100 ms pause). The other panels are reproduced from Fig. 6. Traces are colored to highlight peri-reach activity. Circles indicate the time of target onset (t), reach onset (r), and reach end (e). The pattern displayed by the condition-invariant signal, during compound reaches (e and j) lay on a continuum with the pattern during delayed double-reaches (bi).

Extended Data Fig. 10 Both PMd and M1 populations obey the predictions of the independent hypothesis.

a,b, Same analysis as Fig. 4d–f, performed for units recorded from rostral (a) and caudal (b) burr holes of monkey B (n = 138 and 89, respectively). Shaded regions indicate the standard deviation of the sampling error estimated by resampling individual units (n = 1000 resampled populations). Circles indicate the time of target onset (t), reach onset (r), and reach end (e). c,d, Same analysis as Fig. 5c (ρ = 0.97 and 0.89, respectively). e,f, Same analysis as Fig. 6a–c. A notable quantitative difference is that delay-period activity was stronger (relative to movement-epoch activity) for the rostral subpopulation. This indicates that the two subpopulations likely made differently sized contributions to the preparatory and execution-related dimensions in the original analysis of the full population. This was indeed the case. Preparatory weights for caudal units were modestly smaller (69% on average) than those of rostral units. Conversely, execution weights for the rostral units were modestly smaller (79%) than those of caudal units.

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Zimnik, A.J., Churchland, M.M. Independent generation of sequence elements by motor cortex. Nat Neurosci (2021). https://doi.org/10.1038/s41593-021-00798-5

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