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Related Experiment Video

Updated: Feb 10, 2026

Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans

Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans

Published on: January 15, 2018

Mouse sensorimotor cortex reflects complex kinematic details during reaching and grasping.

Harrison A Grier¹, Sohrab Salimian¹, Matthew T Kaufman^2,3,4

¹Graduate Program in Computational Neuroscience, The University of Chicago, Chicago, United States.

|February 9, 2026

Summary

This summary is machine-generated.

Researchers investigated how the mouse brain controls forelimb movements like reaching and grasping. Both the primary motor cortex (M1-fl) and somatosensory cortex (S1-fl) encode joint angles, but differ in timing for target-specific information.

Keywords:

encoding joint angles mouse neuroscience primary motor cortex primary somatosensory cortex sensorimotor systems two-photon calcium imaging

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The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors

Published on: May 2, 2021

Area of Science:

Neuroscience
Motor Control
Sensorimotor Cortex

Background:

Coordinated forelimb movements involve complex motor commands from abstract goals to precise muscle actions.
The sensorimotor cortex is crucial for motor control, but the distribution of detailed command signals across its subregions, particularly in mice, is not fully understood.
It remains unclear if the primary motor cortex (M1) and somatosensory cortex (S1) in mice encode low-level joint angle details alongside high-level movement direction signals.

Purpose of the Study:

To investigate the representation of movement-related activity in the mouse forelimb primary motor cortex (M1-fl) and forelimb somatosensory cortex (S1-fl) during a reach-to-grasp task.
To determine if M1-fl and S1-fl encode low-level joint angle information and high-level target-specific signals.
To elucidate the distinct and shared contributions of M1-fl and S1-fl to forelimb motor control.

Main Methods:

Utilized high-quality markerless tracking and two-photon imaging in mice performing a reach-to-grasp task.
Quantified movement-related neural activity in M1-fl and S1-fl.
Applied linear decoding models to analyze the representation of joint angles and target-specific information.

Main Results:

Both M1-fl and S1-fl demonstrated strong and comparable encoding of proximal and distal joint angles.
M1-fl showed early onset and sustained encoding of target-specific signals.
S1-fl exhibited transient modulation of target-specific information around movement onset, differing from M1-fl.

Conclusions:

Mouse M1-fl and S1-fl share the encoding of low-level joint angle details for forelimb control.
Distinct temporal dynamics in encoding high-level target information suggest unique roles for M1-fl and S1-fl.
These findings suggest a more distributed cortical circuit for mouse forelimb control than previously assumed.