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 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 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 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 Population dynamics of choice representation in dorsal premotor and primary motor cortex

2018 ◽  
Author(s):  
Diogo Peixoto ◽  
Roozbeh Kiani ◽  
Chandramouli Chandrasekaran ◽  
Stephen I. Ryu ◽  
Krishna V. Shenoy ◽  
...  
Keyword(s):  
Decision Making ◽  
Stimulus Duration ◽  
Primary Motor Cortex ◽  
Population Level ◽  
Motor Preparation ◽  
Neural Population ◽  
Decision Making Process ◽  
Decision Variable ◽  
Single Trial ◽  
Population Activity

SummaryStudies in multiple species have revealed the existence of neural signals that lawfully co-vary with different aspects of the decision-making process, including choice, sensory evidence that supports the choice, and reaction time. These signals, often interpreted as the representation of a decision variable (DV), have been identified in several motor preparation circuits and provide insight about mechanisms underlying the decision-making process. However, single-trial dynamics of this process or its representation at the neural population level remain poorly understood. Here, we examine the representation of the DV in simultaneously recorded neural populations of dorsal premotor (PMd) and primary motor (M1) cortices of monkeys performing a random dots direction discrimination task with arm movements as the behavioral report. We show that single-trial DVs covary with stimulus difficulty in both areas but are stronger and appear earlier in PMd compared to M1 when the stimulus duration is fixed and predictable. When temporal uncertainty is introduced by making the stimulus duration variable, single-trial DV dynamics are accelerated across the board and the two areas become largely indistinguishable throughout the entire trial. These effects are not trivially explained by the faster emergence of motor kinematic signals in PMd and M1. All key aspects of the data were replicated by a computational model that relies on progressive recruitment of units with stable choice-related modulation of neural population activity. In contrast with several recent results in rodents, decision signals in PMd and M1 are not carried by short sequences of activity in non-overlapping groups of neurons but are instead distributed across many neurons, which once recruited, represent the decision stably during individual behavioral epochs of the trial.

scholarly journals Movement Decomposition in the Primary Motor Cortex

2018 ◽  
Vol 29 (4) ◽  
pp. 1619-1633 ◽  
Author(s):  
Naama Kadmon Harpaz ◽  
David Ungarish ◽  
Nicholas G Hatsopoulos ◽  
Tamar Flash
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Temporal Dynamics ◽  
Single Cells ◽  
Brain Regions ◽  
Specific Pattern ◽  
Neural Representation ◽  
Neural Population ◽  
Population Activity ◽  
Acceleration And Deceleration

Abstract A complex action can be described as the composition of a set of elementary movements. While both kinematic and dynamic elements have been proposed to compose complex actions, the structure of movement decomposition and its neural representation remain unknown. Here, we examined movement decomposition by modeling the temporal dynamics of neural populations in the primary motor cortex of macaque monkeys performing forelimb reaching movements. Using a hidden Markov model, we found that global transitions in the neural population activity are associated with a consistent segmentation of the behavioral output into acceleration and deceleration epochs with directional selectivity. Single cells exhibited modulation of firing rates between the kinematic epochs, with abrupt changes in spiking activity timed with the identified transitions. These results reveal distinct encoding of acceleration and deceleration phases at the level of M1, and point to a specific pattern of movement decomposition that arises from the underlying neural activity. A similar approach can be used to probe the structure of movement decomposition in different brain regions, possibly controlling different temporal scales, to reveal the hierarchical structure of movement composition.

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 Latent factors and dynamics in motor cortex and their application to brain-machine interfaces

2018 ◽  
Author(s):  
Chethan Pandarinath ◽  
K. Cora Ames ◽  
Abigail A Russo ◽  
Ali Farshchian ◽  
Lee E Miller ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Movement Planning ◽  
Neural Population ◽  
Great Effort ◽  
Single Neurons ◽  
Latent Factors ◽  
Brain Machine Interfaces ◽  
Population Activity ◽  
Systems Perspective ◽  
Behaving Monkeys

In the fifty years since Evarts first recorded single neurons in motor cortex of behaving monkeys, great effort has been devoted to understanding their relation to movement. Yet these single neurons exist within a vast network, the nature of which has been largely inaccessible. With advances in recording technologies, algorithms, and computational power, the ability to study network-level phenomena is increasing exponentially. Recent experimental results suggest that the dynamical properties of these networks are critical to movement planning and execution. Here we discuss this dynamical systems perspective, and how it is reshaping our understanding of the motor cortices. Following an overview of key studies in motor cortex, we discuss techniques to uncover the “latent factors” underlying observed neural population activity. Finally, we discuss efforts to leverage these factors to improve the performance of brain-machine interfaces, promising to make these findings broadly relevant to neuroengineering as well as systems neuroscience.

scholarly journals Motor Cortex Neural Correlates of Output Kinematics and Kinetics During Isometric-Force and Arm-Reaching Tasks

2005 ◽  
Vol 94 (4) ◽  
pp. 2353-2378 ◽  
Author(s):  
Lauren E. Sergio ◽  
Catherine Hamel-Pâquet ◽  
John F. Kalaska
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Isometric Force ◽  
Arm Movements ◽  
Population Level ◽  
Emg Activity ◽  
Hand Motion ◽  
Arm Reaching ◽  
Direction Of Movement ◽  
Isometric Forces

We recorded the activity of 132 proximal-arm-related neurons in caudal primary motor cortex (M1) of two monkeys while they generated either isometric forces against a rigid handle or arm movements with a heavy movable handle, in the same eight directions in a horizontal plane. The isometric forces increased in monotonic fashion in the direction of the force target. The forces exerted against the handle in the movement task were more complex, including an initial accelerating force in the direction of movement followed by a transient decelerating force opposite to the direction of movement as the hand approached the target. EMG activity of proximal-arm muscles reflected the difference in task dynamics, showing directional ramplike activity changes in the isometric task and reciprocally tuned “triphasic” patterns in the movement task. The apparent instantaneous directionality of muscle activity, when expressed in hand-centered spatial coordinates, remained relatively stable during the isometric ramps but often showed a large transient shift during deceleration of the arm movements. Single-neuron and population-level activity in M1 showed similar task-dependent changes in temporal pattern and instantaneous directionality. The momentary dissociation of the directionality of neuronal discharge and movement kinematics during deceleration indicated that the activity of many arm-related M1 neurons is not coupled only to the direction and speed of hand motion. These results also demonstrate that population-level signals reflecting the dynamics of motor tasks and of interactions with objects in the environment are available in caudal M1. This task-dynamics signal could greatly enhance the performance capabilities of neuroprosthetic controllers.

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

2016 ◽  
Vol 115 (4) ◽  
pp. 2021-2032 ◽  
Author(s):  
Ethan A. Heming ◽  
Timothy P. Lillicrap ◽  
Mohsen Omrani ◽  
Troy M. Herter ◽  
J. Andrew Pruszynski ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Muscle Activation ◽  
Primary Motor Cortex ◽  
Network Connectivity ◽  
Spatiotemporal Patterns ◽  
Neural Population ◽  
Activation Patterns ◽  
Reaching Task ◽  
Muscle Activation Patterns ◽  
Muscle Groups

Primary motor cortex (M1) activity correlates with many motor variables, making it difficult to demonstrate how it participates in motor control. We developed a two-stage process to separate the process of classifying the motor field of M1 neurons from the process of predicting the spatiotemporal patterns of its motor field during reaching. We tested our approach with a neural network model that controlled a two-joint arm to show the statistical relationship between network connectivity and neural activity across different motor tasks. In rhesus monkeys, M1 neurons classified by this method showed preferred reaching directions similar to their associated muscle groups. Importantly, the neural population signals predicted the spatiotemporal dynamics of their associated muscle groups, although a subgroup of atypical neurons reversed their directional preference, suggesting a selective role in antagonist control. These results highlight that M1 provides important details on the spatiotemporal patterns of muscle activity during motor skills such as reaching.

scholarly journals Decoding Complete Reach and Grasp Actions from Local Primary Motor Cortex Populations

2010 ◽  
Vol 30 (29) ◽  
pp. 9659-9669 ◽  
Author(s):  
C. E. Vargas-Irwin ◽  
G. Shakhnarovich ◽  
P. Yadollahpour ◽  
J. M. K. Mislow ◽  
M. J. Black ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Reach And Grasp
Sign in / Sign up

Export Citation Format

Share Document