Primary motor cortex neurons classified in a postural task predict muscle activation patterns in a reaching task

Heming, Ethan A; Lillicrap, Timothy P.; Omrani, Mohsen; Herter, Troy M.; Pruszynski, J. Andrew; Scott, Stephen H.

doi:10.1152/jn.00971.2015

Cited by 16 publications

(11 citation statements)

References 68 publications

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“…This result echoes findings during reaching, where aspects of neural responses sometimes (but not always) depart from expectations under a muscle-encoding framework 1,2,11,17,35,46,65,66 . However, the dominance of non-muscle-like signals is more patent during cycling; non-muscle-like signals are apparent simply via inspection of projections onto the top principal components.…”

Section: Discussionsupporting

confidence: 85%

Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response

Russo

Bittner

Perkins

et al. 2018

Neuron

266

399

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Summary Primate motor cortex projects to spinal interneurons and motor neurons, suggesting that motor cortex activity may be dominated by muscle-like commands. Extensive observations during reaching lend support to this view, but evidence remains ambiguous and much-debated. To provide a different perspective, we employed a novel behavioral paradigm that affords extensive comparison between time-evolving neural and muscle activity. We found that single motor cortex neurons displayed many muscle-like properties, but the structure of population activity was not muscle-like. Unlike muscle activity, neural activity was structured to avoid ‘tangling’: moments where similar activity patterns led to dissimilar future patterns. Avoidance of tangling was present across tasks and species. Network models revealed a potential reason for this consistent feature: low tangling confers noise robustness. Finally, we were able to predict motor cortex activity from muscle activity alone, by leveraging the hypothesis that muscle-like commands are embedded in additional structure that yields low tangling.

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Section: Discussionsupporting

confidence: 85%

Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response

Russo

Bittner

Perkins

et al. 2018

Neuron

266

399

View full text Add to dashboard Cite

show abstract

“…Studies were approved by the Queen’s University Research Ethics Board and Animal Care Committee. Two non-human primates (NHP, macaca mulatta ) were trained to perform a postural perturbation task similar to those used in our previous studies (Herter et al, 2009; Omrani et al, 2014; Heming et al, 2016) using a KINARM exoskeleton robot (BKIN Technologies, Kingston, Canada; (Scott, 1999)). On each trial, the monkey maintained its right or left hand, represented by a white cursor (0.5cm diameter), at a stationary virtual target (0.8cm diameter, red for right, blue for left, luminance matched).…”

Section: Methodsmentioning

confidence: 99%

Keep your hands apart: independent representations of ipsilateral and contralateral forelimbs in primary motor cortex

Heming¹,

Cross²,

Takei³

et al. 2019

Preprint

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It is generally accepted that each cortical hemisphere primarily drives the opposite side of the body. Yet, primary motor cortical (M1) activity has been robustly correlated with both contralateral and ipsilateral arm movements. It has remained unanswered as to why ipsilaterallyrelated activity does not cause contralateral motor activity. Here we apply multi-joint elbow and shoulder loads to the left or right arms of monkeys during a postural perturbation task. We show that many M1 neurons respond to mechanical disturbances applied to either the contra-or ipsilateral arms. More neurons respond to loads applied to the contralateral arm with response magnitudes that were ~2x as large and had onset times that were ~10ms earlier. However, in some cases, neurons exhibited large and earlier responses to loads applied to the ipsilateral arm than loads applied to the contralateral arm. Similar effects were observed when the monkeys were maintaining postural control well after the load had been applied. Importantly, we show that the load preference to one arm has little predictive power on a neuron's preference in the opposite arm. Furthermore, we found contralateral and ipsilateral neural activity resided in orthogonal subspaces allowing for a weighted sum of neural responses to extract the contralateral activity without interference from the ipsilateral activity, and vice versa. These data show how activity in M1 unrelated to downstream motor targets can be segregated from downstream motor output.the torques were 0.20 Nm for single joint loads, and 0.14 Nm at each joint for multi-joint torques. All torque conditions were completed in random order, comprising one block. A minimum of 10 blocks were completed.Neural, EMG and kinematic recordings. After training, monkeys underwent surgery to implant 96-channel Utah Arrays (Blackrock Microsystems, Salt Lake City, UT) into the arm region of M1. Surgeries were performed under aseptic conditions and a head fixation post was also attached to the skull using dental cement. Spike waveforms were sampled at 30kHz and acquired using a 128-Channel Neural Signal Processor (Blackrock Microsystems, Salt Lake City, UT). Spikes were manually sorted offline (Offline Sorter, Plexon Inc., Dallas TX) using a space spanned by the top two principal components and the peak-trough voltage difference. Only well isolated single-units were used for analysis. For Monkey P we also implanted a chamber above the right arm area of M1 and neurons were recorded via single electrode over multiple recording sessions using standard techniques (Herter et al., 2009).We recorded intramuscular electromyographic (EMG) activity from Monkey P by inserting two thin wires into the muscle belly of brachioradialis, lateral and long head of triceps, long head of the biceps and pectoralis major. Signals were digitized at 1KHz. Joint angles, velocities, and accelerations for both arms, were recorded at 1 kHz by the Neural Signal Processor. All offline analysis was performed using custom MATLAB scripts (The MathWorks, Inc., ...

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“…For example, M1 activity during reaching and locomotion reflect distinct subspaces (Miri et al, 2017). Furthermore, load representations can change dramatically across postural control and reaching, although neurons still maintain similar tuning for external loads across these tasks (Kurtzer et al, 2005; Heming et al, 2016). Thus, neural representations in M1 remain relatively constant for a given behaviour but can show substantial changes across behaviours.…”

Section: Discussionmentioning

confidence: 99%

Maintained representations of the ipsilateral and contralateral limbs during bimanual control in primary motor cortex

Cross

Heming

Cook

et al. 2020

Preprint

Self Cite

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223/250 words) 3 3 Primary motor cortex (M1) almost exclusively controls the contralateral side of the body. 4However, M1 activity is also modulated during ipsilateral body movements. Previous work has 3 5shown that M1 activity related to the ipsilateral arm is independent of the M1 activity related to 3 6 the contralateral arm. How do these patterns of activity interact when both arms move 3 7 simultaneously? We explored this problem by training two monkeys (male, Macaca mulatta) in a 3 8 postural perturbation task while recording from M1. Loads were applied to one arm at a time 3 9

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Primary motor cortex neurons classified in a postural task predict muscle activation patterns in a reaching task

Cited by 16 publications

References 68 publications

Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response

Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response

Keep your hands apart: independent representations of ipsilateral and contralateral forelimbs in primary motor cortex

Maintained representations of the ipsilateral and contralateral limbs during bimanual control in primary motor cortex

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