To generate movements, the brain must combine information about movement goal and body posture. Motor cortex (M1) is a key node for the convergence of these information streams. How are posture and goal information organized within M1's activity to permit the flexible generation of movement commands? To answer this question, we recorded M1 activity while monkeys performed a variety of tasks with the forearm in a range of postures. We found that posture- and goal-related components of neural population activity were separable and resided in nearly orthogonal subspaces. The posture subspace was stable across tasks. Within each task, neural trajectories for each goal had similar shapes across postures. Our results reveal a simpler organization of posture information in M1 than previously recognized. The compartmentalization of posture and goal information might allow the two to be flexibly combined in the service of our broad repertoire of actions.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343157 | PMC |
http://dx.doi.org/10.1101/2024.08.12.607361 | DOI Listing |
J Exp Biol
November 2024
Department of Animal Physiology, Institute of Zoology, University of Cologne, 50674 Cologne, Germany.
Insects use walking behavior in a large number of contexts, such as exploration, foraging, escape and pursuit, or migration. A lot is known about how nervous systems produce this behavior in general and also how certain parameters vary with regard to walking direction or speed, for instance. An aspect that has not received much attention is whether and how walking behavior varies across individuals of a particular species.
View Article and Find Full Text PDFbioRxiv
August 2024
Dept. of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15260, USA.
To generate movements, the brain must combine information about movement goal and body posture. Motor cortex (M1) is a key node for the convergence of these information streams. How are posture and goal information organized within M1's activity to permit the flexible generation of movement commands? To answer this question, we recorded M1 activity while monkeys performed a variety of tasks with the forearm in a range of postures.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
April 2024
Striving to match the person identities between visible (VIS) and near-infrared (NIR) images, VIS-NIR reidentification (Re-ID) has attracted increasing attention due to its wide applications in low-light scenes. However, owing to the modality and pose discrepancies exhibited in heterogeneous images, the extracted representations inevitably comprise various modality and posture factors, impacting the matching of cross-modality person identity. To solve the problem, we propose a disentangling modality and posture factors (DMPFs) model to disentangle modality and posture factors by fusing the information of features memory and pedestrian skeleton.
View Article and Find Full Text PDFSci Rep
November 2023
Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, 600036, India.
The human hand, with many degrees of freedom, serves as an excellent tool for dexterous manipulation. Previous research has demonstrated that there exists a lower-dimensional subspace that synergistically controls the full hand kinematics. The elements of this subspace, also called synergies, have been viewed as the strategy developed by the CNS in the control of finger movements.
View Article and Find Full Text PDFHum Mov Sci
December 2023
Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Lecco, Italy. Electronic address:
In the last two decades, muscle synergies analysis has been commonly used to assess the neurophysiological mechanisms underlying human motor control. Several synergy models and algorithms have been employed for processing the electromyographic (EMG) signal, and it has been shown that the coordination of motor control is characterized by the presence of phasic (movement-related) and tonic (anti-gravity and related to co-contraction) EMG components. Neural substrates indicate that phasic and tonic components have non-homogeneous origin; however, it is still unclear if these components are generated by the same set of synergies or by distinct synergies.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!