Neural population dynamics in motor cortex are different for reach and grasp
Abstract
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.
Data availability
The data that support the findings of this study have been deposited in Dryad, accessible at https://doi.org/10.5061/dryad.xsj3tx9cm
-
Neural population dynamics in motor cortex are different for reach and graspDryad Digital Repository, doi:10.5061/dryad.xsj3tx9cm.
Article and author information
Author details
Funding
National Institute of Neurological Disorders and Stroke (NS082865)
- Nicholas G Hatsopoulos
- Sliman J Bensmaia
National Institute of Neurological Disorders and Stroke (NS096952)
- Aneesha K Suresh
National Institute of Neurological Disorders and Stroke (NS045853)
- Nicholas G Hatsopoulos
National Institute of Neurological Disorders and Stroke (NS111982)
- Nicholas G Hatsopoulos
National Institute of Neurological Disorders and Stroke (NS101325)
- Sliman J Bensmaia
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All surgical, behavioral, and experimental procedures conformed to the guidelines of the National Institutes of Health and were approved by the University of Chicago Institutional Animal Care and Use Committee (#72042).
Copyright
© 2020, Suresh et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,152
- views
-
- 761
- downloads
-
- 48
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
We used diffusion MRI and x-ray synchrotron imaging on monkey and mice brains to examine the organisation of fibre pathways in white matter across anatomical scales. We compared the structure in the corpus callosum and crossing fibre regions and investigated the differences in cuprizone-induced demyelination in mouse brains versus healthy controls. Our findings revealed common principles of fibre organisation that apply despite the varying patterns observed across species; small axonal fasciculi and major bundles formed laminar structures with varying angles, according to the characteristics of major pathways. Fasciculi exhibited non-straight paths around obstacles like blood vessels, comparable across the samples of varying fibre complexity and demyelination. Quantifications of fibre orientation distributions were consistent across anatomical length scales and modalities, whereas tissue anisotropy had a more complex relationship, both dependent on the field-of-view. Our study emphasises the need to balance field-of-view and voxel size when characterising white matter features across length scales.
-
- Biochemistry and Chemical Biology
- Neuroscience
The buildup of knot-like RNA structures in brain cells may be the key to understanding how uncontrolled protein aggregation drives Alzheimer’s disease.