scholarly journals Primary motor cortex activity traces distinct trajectories of population dynamics during spontaneous facial motor sequences in mice

2021 ◽  
Author(s):  
Juan Carlos Boffi ◽  
Tristan Wiessalla ◽  
Robert Prevedel
Keyword(s):  
Population Dynamics ◽  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Neuronal Population ◽  
Future Research ◽  
Sequencing Analysis ◽  
Population Activity ◽  
Neuronal Populations ◽  
Custom Made ◽  
Facial Area

AbstractWe explore the link between on-going neuronal activity at primary motor cortex (M1) and face movement in awake mice. By combining custom-made behavioral sequencing analysis and fast volumetric Ca2+-imaging, we simultaneously tracked M1 population activity during many different facial motor sequences. We show that a facial area of M1 displays distinct trajectories of neuronal population dynamics across different spontaneous facial motor sequences, suggesting an underlying population dynamics code.Significance statementHow our brain controls a seemingly limitless diversity of body movements remains largely unknown. Recent research brings new light into this subject by showing that neuronal populations at the primary motor cortex display different dynamics during forelimb reaching movements versus grasping, which suggests that different motor sequences could be associated with distinct motor cortex population dynamics. To explore this possibility, we designed an experimental paradigm for simultaneously tracking the activity of neuronal populations in motor cortex across many different motor sequences. Our results support the concept that distinct population dynamics encode different motor sequences, bringing new insight into the role of motor cortex in sculpting behavior while opening new avenues for future research.

scholarly journals Neural population dynamics in motor cortex are different for reach and grasp

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Aneesha K Suresh ◽  
James M Goodman ◽  
Elizaveta V Okorokova ◽  
Matthew Kaufman ◽  
Nicholas G Hatsopoulos ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Population Level ◽  
Basic Structure ◽  
Neuronal Population ◽  
Neural Population ◽  
Population Activity ◽  
Muscle Activations ◽  
Low Dimensional ◽  
Analytical Approaches

Low-dimensional linear dynamics are observed in neuronal population activity in primary motor cortex (M1) when monkeys make reaching movements. This population-level behavior is consistent with a role for M1 as an autonomous pattern generator that drives muscles to give rise to movement. In the present study, we examine whether similar dynamics are also observed during grasping movements, which involve fundamentally different patterns of kinematics and muscle activations. Using a variety of analytical approaches, we show that M1 does not exhibit such dynamics during grasping movements. Rather, the grasp-related neuronal dynamics in M1 are similar to their counterparts in somatosensory cortex, whose activity is driven primarily by afferent inputs rather than by intrinsic dynamics. The basic structure of the neuronal activity underlying hand control is thus fundamentally different from that underlying arm control.

scholarly journals NEURAL POPULATION DYNAMICS IN MOTOR CORTEX ARE DIFFERENT FOR REACH AND GRASP

2019 ◽  
Author(s):  
Aneesha K. Suresh ◽  
James M. Goodman ◽  
Elizaveta V. Okorokova ◽  
Matthew T. Kaufman ◽  
Nicholas G. Hatsopoulos ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Population Level ◽  
Pattern Generator ◽  
Neuronal Population ◽  
Rotational Dynamics ◽  
Neural Population ◽  
Population Activity ◽  
Reach And Grasp ◽  
Smooth Dynamics

AbstractRotational dynamics are observed in neuronal population activity in primary motor cortex (M1) when monkeys make reaching movements. This population-level behavior is consistent with a role for M1 as an autonomous pattern generator that drives muscles to produce movement. Here, we show that M1 does not exhibit smooth dynamics during grasping movements, suggesting a more input-driven circuit.

scholarly journals Population subspaces reflect movement intention for arm and brain-machine interface control

2019 ◽  
Author(s):  
H. Lalazar ◽  
J.M. Murray ◽  
L.F. Abbott ◽  
E. Vaadia
Keyword(s):  
Motor Cortex ◽  
Neural Activity ◽  
Primary Motor Cortex ◽  
Action Observation ◽  
Neuronal Population ◽  
Brain Machine Interface ◽  
Population Activity ◽  
Interface Control ◽  
Machine Interface ◽  
Movement Intention

Motor cortex is active during covert motor acts, such as action observation and mental rehearsal, when muscles are quiescent. Such neuronal activity, which is thought to be similar to the activity underlying overt movement, is exploited by neural prosthetics to afford subjects control of an external effector. We compared neural activity in primary motor cortex of monkeys who controlled a cursor using either their arm or a brain-machine interface (BMI) to identify what features of neural activity are similar or dissimilar in these two control contexts. Neuronal population activity parcellates into orthogonal subspaces, with some representations that are unique to arm movements and others that are shared between arm and BMI control. The shared subspace is invariant to the effector used and to biomechanical details of the movement, revealing a representation that reflects movement intention. This intention representation is likely the signal extracted by BMI algorithms for cursor control, and subspace orthogonality accounts for how neurons involved in arm control can drive a BMI while the arm remains at rest. These results provide a resolution to the long-standing debate of whether motor cortex represents muscle activity or abstract movement variables, and it clarifies various puzzling aspects of neural prosthetic research.

scholarly journals Paradoxical facilitation alongside interhemispheric inhibition

2021 ◽  
Author(s):  
Michel Belyk ◽  
Russell Banks ◽  
Anna Tendera ◽  
Robert Chen ◽  
Deryk S. Beal
Keyword(s):  
Motor Cortex ◽  
Corpus Callosum ◽  
Primary Motor Cortex ◽  
Conditioning Stimulus ◽  
Future Research ◽  
Homologous Region ◽  
Inhibitory Influence ◽  
Interhemispheric Inhibition ◽  
Opposite Hemisphere ◽  
Surprising Effect

AbstractNeurophysiological experiments using transcranial magnetic stimulation (TMS) have sought to probe the function of the motor division of the corpus callosum. Primary motor cortex sends projections via the corpus callosum with a net inhibitory influence on the homologous region of the opposite hemisphere. Interhemispheric inhibition (IHI) experiments probe this inhibitory pathway. A test stimulus (TS) delivered to the motor cortex in one hemisphere elicits motor evoked potentials (MEPs) in a target muscle, while a conditioning stimulus (CS) applied to the homologous region of the opposite hemisphere modulates the effect of the TS. We predicted that large CS MEPs would be associated with increased IHI since they should be a reliable index of how effectively contralateral motor cortex was stimulated and therefore of the magnitude of interhemispheric inhibition. However, we observed a strong tendency for larger CS MEPs to be associated with reduced interhemispheric inhibition which in the extreme lead to a net effect of facilitation. This surprising effect was large, systematic, and observed in nearly all participants. We outline several hypotheses for mechanisms which may underlie this phenomenon to guide future research.

Abstract MP58: Motor Cortex and Spinal Cord Transcriptome After Post-Stroke Optogenetic Neuronal Stimulation

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Michelle Y Cheng ◽  
Haruto Uchino ◽  
Terrance Chiang ◽  
Anika Kim ◽  
Zhijuan Cao ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Motor Cortex ◽  
Rna Sequencing ◽  
Primary Motor Cortex ◽  
Cholesterol Metabolism ◽  
Sequencing Analysis ◽  
Beam Test ◽  
Rotating Beam ◽  
Molecular Changes ◽  
Post Stroke

Background: Post-stroke brain stimulation is a promising neurorestorative technique to promote recovery. However, the underlying molecular mechanisms driving recovery are still unclear. Here we investigate the molecular changes in both the primary motor cortex and the cervical spinal cord after large cortical stroke in mice receiving repeated optogenetic stimulations in the ipsilateral primary motor cortex (iM1). Methods: C57Bl6 male mice (8 weeks) underwent stereotaxic surgery to express Channelrhodopsin2 in excitatory neurons in iM1, with optical fiber implanted in the same location. After five weeks the mice underwent a transient middle cerebral artery occlusion to induce stroke. Optogenetic stimulations were given daily from post-stroke days (PD) 5-14. Non-stimulated mice were used as controls. Rotating beam test was used to evaluate functional recovery after stroke. At PD 7 and 15, ipsi- and contralesional primary motor cortex (iM1 and cM1) and cervical spinal cords (iSp and cSp) were dissected and processed for RNA sequencing. Results: Repeated iM1 stimulations resulted in a robust recovery on the rotating beam test at PD14, with significant improvement in distance traveled (p<0.05). RNA sequencing analysis (stimulated vs non-stimulated mice) revealed differential transcriptome in both motor cortex and spinal cord. Higher number of differentially expressed genes (DEGs) were observed in the ipsilesional regions (iM1 and iSp). At PD 7, stimulated mice exhibited upregulation of activity-dependent and neuroplasticity-related genes in iM1. Interestingly, at PD15, cholesterol metabolism and neuroinflammatory related genes in iM1 were downregulated. The expressions of the genes were negatively correlated with behavioral recovery. Higher number of DEGs were altered in the spinal cord than motor cortex, suggesting more dynamic molecular changes occur in this area during the post-stroke reinnervation processes. Expressions of synaptogenesis related genes were altered in both iSp and cSp at both timepoints. Conclusions: These transcriptome data reveal important insights into the molecular signaling involved in post-stroke stimulation-induced recovery and provide potential drug targets for enhancing recovery in stroke patients.

Perturbation-evoked responses in primary motor cortex are modulated by behavioral context

2014 ◽  
Vol 112 (11) ◽  
pp. 2985-3000 ◽  
Author(s):  
Mohsen Omrani ◽  
J. Andrew Pruszynski ◽  
Chantelle D. Murnaghan ◽  
Stephen H. Scott
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Initial Perturbation ◽  
Motor Task ◽  
Initial Response ◽  
Mechanical Perturbation ◽  
Population Activity ◽  
Motor Action ◽  
Central Target ◽  
Postural Task

Corrective responses to external perturbations are sensitive to the behavioral task being performed. It is believed that primary motor cortex (M1) forms part of a transcortical pathway that contributes to this sensitivity. Previous work has identified two distinct phases in the perturbation response of M1 neurons, an initial response starting ∼20 ms after perturbation onset that does not depend on the intended motor action and a task-dependent response that begins ∼40 ms after perturbation onset. However, this invariant initial response may reflect ongoing postural control or a task-independent response to the perturbation. The present study tested these two possibilities by examining if being engaged in an ongoing postural task before perturbation onset modulated the initial perturbation response in M1. Specifically, mechanical perturbations were applied to the shoulder and/or elbow while the monkey maintained its hand at a central target or when it was watching a movie and not required to respond to the perturbation. As expected, corrective movements, muscle stretch responses, and M1 population activity in the late perturbation epoch were all significantly diminished in the movie task. Strikingly, initial perturbation responses (<40 ms postperturbation) remained the same across tasks, suggesting that the initial phase of M1 activity constitutes a task-independent response that is sensitive to the properties of the mechanical perturbation but not the goal of the ongoing motor task.

scholarly journals Neuronal populations in primary motor cortex encode bimanual arm movements

2002 ◽  
Vol 15 (8) ◽  
pp. 1371-1380 ◽  
Author(s):  
O. Steinberg ◽  
O. Donchin ◽  
A. Gribova ◽  
S. Cardoso De Oliveira ◽  
H. Bergman ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Arm Movements ◽  
Neuronal Populations

scholarly journals Motor cortex signals corresponding to the two arms are shared across hemispheres, mixed among neurons, yet partitioned within the population response

2019 ◽  
Author(s):  
K. Cora Ames ◽  
Mark M. Churchland
Keyword(s):  
Motor Cortex ◽  
Neural Activity ◽  
Muscle Activity ◽  
Primary Motor Cortex ◽  
Population Level ◽  
Response Patterns ◽  
Neural Signals ◽  
Population Activity ◽  
The Individual

AbstractPrimary motor cortex (M1) has lateralized outputs, yet M1 neurons can be active during movements of either arm. What is the nature and role of activity in the two hemispheres? When one arm moves, are the contralateral and ipsilateral cortices performing similar or different computations? When both hemispheres are active, how does the brain avoid moving the “wrong” arm? We recorded muscle and neural activity bilaterally while two male monkeys (Macaca mulatta) performed a cycling task with one or the other arm. Neurons in both hemispheres were active during movements of either arm. Yet response patterns were arm-dependent, raising two possibilities. First, the nature of neural signals may differ (e.g., be high versus low-level) depending on whether the ipsilateral or contralateral arm is used. Second, the same population-level signals may be present regardless of the arm being used, but be reflected differently at the individual-neuron level. The data supported this second hypothesis. Muscle activity could be predicted by neural activity in either hemisphere. More broadly, we failed to find signals unique to the hemisphere contralateral to the moving arm. Yet if the same signals are shared across hemispheres, how do they avoid impacting the wrong arm? We found that activity related to the two arms occupied distinct, orthogonal subspaces of population activity. As a consequence, a linear decode of contralateral muscle activity naturally ignored signals related to the ipsilateral arm. Thus, information regarding the two arms is shared across hemispheres and neurons, but partitioned at the population level.

scholarly journals Human electrocorticography reveals a common neurocognitive pathway for mentalizing about the self and others

2021 ◽  
Author(s):  
Kevin Tan ◽  
Amy Daitch ◽  
Pedro Pinheiro-Chagas ◽  
Kieran Fox ◽  
Josef Parvizi ◽  
...  
Keyword(s):  
Social Cognitive ◽  
Response Times ◽  
Human Subjects ◽  
Neuronal Population ◽  
Spatiotemporal Resolution ◽  
Population Activity ◽  
Psychological Traits ◽  
Self And Other ◽  
Neuronal Populations ◽  
The Social

Abstract Hundreds of neuroimaging studies show that mentalizing (i.e., theory of mind) recruits default mode network (DMN) regions with remarkable consistency. Nevertheless, the social-cognitive functions of individual DMN regions remain unclear, perhaps due to the limited spatiotemporal resolution of neuroimaging. We used electrocorticography (ECoG) to record neuronal population activity while 16 human subjects judged the psychological traits of themselves and others. Self- and other-mentalizing recruited near-identical neuronal populations in a common spatiotemporal sequence: activations were earliest in visual cortex, followed by temporoparietal DMN regions, and finally medial prefrontal cortex. Critically, regions with later activations showed greater functional specificity for mentalizing, greater self/other differentiation, and stronger associations with behavioral response times. Moreover, other-mentalizing evoked slower and lengthier activations than self-mentalizing across successive DMN regions, suggesting temporally extended demands on higher-level processes. Our results reveal a common neurocognitive pathway for self- and other-mentalizing that follows a hierarchy of functional specialization across DMN regions.

scholarly journals Learning and attention reveal a general relationship between neuronal variability and perception

2017 ◽  
Author(s):  
Amy M. Ni ◽  
Douglas A. Ruff ◽  
Joshua J. Alberts ◽  
Jen Symmonds ◽  
Marlene R. Cohen
Keyword(s):  
Visual Cortex ◽  
Neuronal Population ◽  
Population Coding ◽  
Task Demands ◽  
Spike Count ◽  
Current Debate ◽  
Visually Guided ◽  
Population Activity ◽  
Neuronal Populations ◽  
And Performance

The trial-to-trial response variability that is shared between pairs of neurons (termed spike count correlations1 or rSC) has been the subject of many recent studies largely because it might limit the amount of information that can be encoded by neuronal populations. Spike count correlations are flexible and change depending on task demands2-7. However, the relationship between correlated variability and information coding is a matter of current debate2-14. This debate has been difficult to resolve because testing the theoretical predictions would require simultaneous recordings from an experimentally unfeasible number of neurons. We hypothesized that if correlated variability limits population coding, then spike count correlations in visual cortex should a) covary with subjects’ performance on visually guided tasks and b) lie along the dimensions in neuronal population space that contain information that is used to guide behavior. We focused on two processes that are known to improve visual performance: visual attention, which allows observers to focus on important parts of a visual scene15-17, and perceptual learning, which slowly improves observers’ ability to discriminate specific, well-practiced stimuli18-20. Both attention and learning improve performance on visually guided tasks, but the two processes operate on very different timescales and are typically studied using different perceptual tasks. Here, by manipulating attention and learning in the same task, subjects, trials, and neuronal populations, we show that there is a single, robust relationship between correlated variability in populations of visual neurons and performance on a change-detection task. We also propose an explanation for the mystery of how correlated variability might affect performance: it is oriented along the dimensions of population space used by the animal to make perceptual decisions. Our results suggest that attention and learning affect the same aspects of the neuronal population activity in visual cortex, which may be responsible for learning- and attention-related improvements in behavioral performance. More generally, our study provides a framework for leveraging the activity of simultaneously recorded populations of neurons, cognitive factors, and perceptual decisions to understand the neuronal underpinnings of behavior.

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