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Cortical Correlates of Fitts’ Law
Fitts’ law describes the fundamental trade-off between movement accuracy and speed: it states that the duration of reaching movements is a function of target size (TS) and distance. While Fitts’ law has been extensively studied in ergonomics and has guided the design of human–computer interfaces, th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Research Foundation
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3250970/ https://www.ncbi.nlm.nih.gov/pubmed/22275888 http://dx.doi.org/10.3389/fnint.2011.00085 |
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author | Ifft, Peter J. Lebedev, Mikhail A. Nicolelis, Miguel A. L. |
author_facet | Ifft, Peter J. Lebedev, Mikhail A. Nicolelis, Miguel A. L. |
author_sort | Ifft, Peter J. |
collection | PubMed |
description | Fitts’ law describes the fundamental trade-off between movement accuracy and speed: it states that the duration of reaching movements is a function of target size (TS) and distance. While Fitts’ law has been extensively studied in ergonomics and has guided the design of human–computer interfaces, there have been few studies on its neuronal correlates. To elucidate sensorimotor cortical activity underlying Fitts’ law, we implanted two monkeys with multielectrode arrays in the primary motor (M1) and primary somatosensory (S1) cortices. The monkeys performed reaches with a joystick-controlled cursor toward targets of different size. The reaction time (RT), movement time, and movement velocity changed with TS, and M1 and S1 activity reflected these changes. Moreover, modifications of cortical activity could not be explained by changes of movement parameters alone, but required TS as an additional parameter. Neuronal representation of TS was especially prominent during the early RT period where it influenced the slope of the firing rate rise preceding movement initiation. During the movement period, cortical activity was correlated with movement velocity. Neural decoders were applied to simultaneously decode TS and motor parameters from cortical modulations. We suggest that sensorimotor cortex activity reflects the characteristics of both the movement and the target. Classifiers that extract these parameters from cortical ensembles could improve neuroprosthetic control. |
format | Online Article Text |
id | pubmed-3250970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Frontiers Research Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-32509702012-01-24 Cortical Correlates of Fitts’ Law Ifft, Peter J. Lebedev, Mikhail A. Nicolelis, Miguel A. L. Front Integr Neurosci Neuroscience Fitts’ law describes the fundamental trade-off between movement accuracy and speed: it states that the duration of reaching movements is a function of target size (TS) and distance. While Fitts’ law has been extensively studied in ergonomics and has guided the design of human–computer interfaces, there have been few studies on its neuronal correlates. To elucidate sensorimotor cortical activity underlying Fitts’ law, we implanted two monkeys with multielectrode arrays in the primary motor (M1) and primary somatosensory (S1) cortices. The monkeys performed reaches with a joystick-controlled cursor toward targets of different size. The reaction time (RT), movement time, and movement velocity changed with TS, and M1 and S1 activity reflected these changes. Moreover, modifications of cortical activity could not be explained by changes of movement parameters alone, but required TS as an additional parameter. Neuronal representation of TS was especially prominent during the early RT period where it influenced the slope of the firing rate rise preceding movement initiation. During the movement period, cortical activity was correlated with movement velocity. Neural decoders were applied to simultaneously decode TS and motor parameters from cortical modulations. We suggest that sensorimotor cortex activity reflects the characteristics of both the movement and the target. Classifiers that extract these parameters from cortical ensembles could improve neuroprosthetic control. Frontiers Research Foundation 2011-12-22 /pmc/articles/PMC3250970/ /pubmed/22275888 http://dx.doi.org/10.3389/fnint.2011.00085 Text en Copyright © 2011 Ifft, Lebedev and Nicolelis. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited. |
spellingShingle | Neuroscience Ifft, Peter J. Lebedev, Mikhail A. Nicolelis, Miguel A. L. Cortical Correlates of Fitts’ Law |
title | Cortical Correlates of Fitts’ Law |
title_full | Cortical Correlates of Fitts’ Law |
title_fullStr | Cortical Correlates of Fitts’ Law |
title_full_unstemmed | Cortical Correlates of Fitts’ Law |
title_short | Cortical Correlates of Fitts’ Law |
title_sort | cortical correlates of fitts’ law |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3250970/ https://www.ncbi.nlm.nih.gov/pubmed/22275888 http://dx.doi.org/10.3389/fnint.2011.00085 |
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