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 Motor cortex activity across movement speeds is predicted by network-level strategies for generating muscle activity

2021 ◽  
Author(s):  
Shreya Saxena ◽  
Abigail A. Russo ◽  
John P. Cunningham ◽  
Mark M. Churchland
Keyword(s):  
Motor Cortex ◽  
Muscle Activity ◽  
Single Neuron ◽  
Activity Patterns ◽  
Network Activity ◽  
Movement Speed ◽  
Neural Population ◽  
Recurrent Networks ◽  
Neural Signals ◽  
Population Activity

AbstractLearned movements can be skillfully performed at different paces. What neural strategies produce this flexibility? Can they be predicted and understood by network modeling? We trained monkeys to perform a cycling task at different speeds, and trained artificial recurrent networks to generate the empirical muscle-activity patterns. Network solutions reflected the principle that smooth well-behaved dynamics require low trajectory tangling, and yielded quantitative and qualitative predictions. To evaluate predictions, we recorded motor cortex population activity during the same task. Responses supported the hypothesis that the dominant neural signals reflect not muscle activity, but network-level strategies for generating muscle activity. Single-neuron responses were better accounted for by network activity than by muscle activity. Similarly, neural population trajectories shared their organization not with muscle trajectories, but with network solutions. Thus, cortical activity could be understood based on the need to generate muscle activity via dynamics that allow smooth, robust control over movement speed.

scholarly journals Motor cortex signals for each arm are mixed across hemispheres and neurons yet partitioned within the population response

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Katherine Cora Ames ◽  
Mark M Churchland
Keyword(s):  
Motor Cortex ◽  
Muscle Activity ◽  
Population Level ◽  
The Other ◽  
Contralateral Hemisphere ◽  
Population Response

Motor cortex (M1) has lateralized outputs, yet neurons can be active during movements of either arm. What is the nature and role of activity across the two hemispheres? We recorded muscles and neurons bilaterally while monkeys cycled with each arm. Most neurons were active during movement of either arm. Responses were strongly arm-dependent, raising two possibilities. First, population-level signals might differ depending on the arm used. Second, the same population-level signals might be present, but distributed differently across neurons. The data supported this second hypothesis. Muscle activity was accurately predicted by activity in either the ipsilateral or contralateral hemisphere. More generally, we failed to find signals unique to the contralateral hemisphere. Yet if signals are shared across hemispheres, how do they avoid impacting the wrong arm? We found that activity related to each arm occupies a distinct subspace, enabling muscle-activity decoders to naturally ignore signals related to the other arm.

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 Role of cutaneous and proprioceptive inputs in sensorimotor integration and plasticity occurring in the facial primary motor cortex

2020 ◽  
Vol 598 (4) ◽  
pp. 839-851 ◽  
Author(s):  
Giovanna Pilurzi ◽  
Francesca Ginatempo ◽  
Beniamina Mercante ◽  
Luigi Cattaneo ◽  
Giovanni Pavesi ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Sensorimotor Integration ◽  
Primary Motor Cortex ◽  
Proprioceptive Inputs

Role of Voluntary Drive in Encoding an Elementary Motor Memory

2005 ◽  
Vol 93 (2) ◽  
pp. 1099-1103 ◽  
Author(s):  
Alain Kaelin-Lang ◽  
Lumy Sawaki ◽  
Leonardo G. Cohen
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Motor Memory ◽  
Motor Drive ◽  
Motor Training ◽  
Corticomotor Excitability ◽  
Proprioceptive Input ◽  
Active Training ◽  
Passive Movements

Motor training consisting of repetitive thumb movements results in encoding of motor memories in the primary motor cortex. It is not known if proprioceptive input originating in the training movements is sufficient to produce this effect. In this study, we compared the ability of training consisting of voluntary (active) and passively-elicited (passive) movements to induce this form of plasticity. Active training led to successful encoding accompanied by characteristic changes in corticomotor excitability, while passive training did not. These results support a pivotal role for voluntary motor drive in coding motor memories in the primary motor cortex.

Environment

2013 ◽  
pp. 290-295
Author(s):  
Christopher R. Holroyd ◽  
Nicholas C. Harvey ◽  
Mark H. Edwards ◽  
Cyrus Cooper
Keyword(s):  
Rheumatoid Arthritis ◽  
Life Course ◽  
Disease Risk ◽  
Association Studies ◽  
Population Level ◽  
Environment Interaction ◽  
Disease Pattern ◽  
The Individual ◽  
The Life Course

Musculoskeletal disease covers a broad spectrum of conditions whose aetiology comprises variable genetic and environmental contributions. More recently it has become clear that, particularly early in life, the interaction of gene and environment is critical to the development of later disease. Additionally, only a small proportion of the variation in adult traits such as bone mineral density has been explained by specific genes in genome-wide association studies, suggesting that gene-environment interaction may explain a much larger part of the inheritance of disease risk than previously thought. It is therefore critically important to evaluate the environmental factors which may predispose to diseases such as osteorthritis, osteoporosis, and rheumatoid arthritis both at the individual and at the population level. In this chapter we describe the environmental contributors, across the whole life course, to osteoarthritis, osteoporosis and rheumatoid arthritis, as exemplar conditions. We consider factors such as age, gender, nutrition (including the role of vitamin D), geography, occupation, and the clues that secular changes of disease pattern may yield. We describe the accumulating evidence that conditions such as osteoporosis may be partly determined by the early interplay of environment and genotype, through aetiological mechanisms such as DNA methylation and other epigenetic phenomena. Such studies, and those examining the role of environmental influences across other stages of the life course, suggest that these issues should be addressed at all ages, starting from before conception, in order to optimally reduce the burden of musculoskeletal disorders in future generations.

Comparison of Neural Activity in the Supplementary Motor Area and in the Primary Motor Cortex in Monkeys

1991 ◽  
Vol 8 (1) ◽  
pp. 27-44 ◽  
Author(s):  
Chen Dao-fen ◽  
B. Hyland ◽  
V. Maier ◽  
A. Palmeri ◽  
M. Wiesendanger
Keyword(s):  
Motor Cortex ◽  
Neural Activity ◽  
Primary Motor Cortex ◽  
Supplementary Motor Area ◽  
Motor Area
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