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Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model

How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest...

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Autores principales: Hammer, Jiří, Pistohl, Tobias, Fischer, Jörg, Kršek, Pavel, Tomášek, Martin, Marusič, Petr, Schulze-Bonhage, Andreas, Aertsen, Ad, Ball, Tonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869816/
https://www.ncbi.nlm.nih.gov/pubmed/26984895
http://dx.doi.org/10.1093/cercor/bhw033
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author Hammer, Jiří
Pistohl, Tobias
Fischer, Jörg
Kršek, Pavel
Tomášek, Martin
Marusič, Petr
Schulze-Bonhage, Andreas
Aertsen, Ad
Ball, Tonio
author_facet Hammer, Jiří
Pistohl, Tobias
Fischer, Jörg
Kršek, Pavel
Tomášek, Martin
Marusič, Petr
Schulze-Bonhage, Andreas
Aertsen, Ad
Ball, Tonio
author_sort Hammer, Jiří
collection PubMed
description How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest in the representation of movement parameters in neuronal population activity, such as reflected in the intracranial EEG (iEEG). We show that in iEEG, contrasting to what has been previously found on the single neuron level, speed predominates over velocity. The predominant speed representation was present in nearly all iEEG signal features, up to the 600–1000 Hz range. Using a model of motor-cortical signals arising from neuronal populations with realistic single neuron tuning properties, we show how this reversal can be understood as a consequence of increasing population size. Our findings demonstrate that the information profile in large population signals may systematically differ from the single neuron level, a principle that may be helpful in the interpretation of neuronal population signals in general, including, for example, EEG and functional magnetic resonance imaging. Taking advantage of the robust speed population signal may help in developing brain–machine interfaces exploiting population signals.
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spelling pubmed-48698162016-05-26 Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model Hammer, Jiří Pistohl, Tobias Fischer, Jörg Kršek, Pavel Tomášek, Martin Marusič, Petr Schulze-Bonhage, Andreas Aertsen, Ad Ball, Tonio Cereb Cortex Articles How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest in the representation of movement parameters in neuronal population activity, such as reflected in the intracranial EEG (iEEG). We show that in iEEG, contrasting to what has been previously found on the single neuron level, speed predominates over velocity. The predominant speed representation was present in nearly all iEEG signal features, up to the 600–1000 Hz range. Using a model of motor-cortical signals arising from neuronal populations with realistic single neuron tuning properties, we show how this reversal can be understood as a consequence of increasing population size. Our findings demonstrate that the information profile in large population signals may systematically differ from the single neuron level, a principle that may be helpful in the interpretation of neuronal population signals in general, including, for example, EEG and functional magnetic resonance imaging. Taking advantage of the robust speed population signal may help in developing brain–machine interfaces exploiting population signals. Oxford University Press 2016-06 2016-03-16 /pmc/articles/PMC4869816/ /pubmed/26984895 http://dx.doi.org/10.1093/cercor/bhw033 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Articles
Hammer, Jiří
Pistohl, Tobias
Fischer, Jörg
Kršek, Pavel
Tomášek, Martin
Marusič, Petr
Schulze-Bonhage, Andreas
Aertsen, Ad
Ball, Tonio
Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model
title Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model
title_full Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model
title_fullStr Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model
title_full_unstemmed Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model
title_short Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model
title_sort predominance of movement speed over direction in neuronal population signals of motor cortex: intracranial eeg data and a simple explanatory model
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4869816/
https://www.ncbi.nlm.nih.gov/pubmed/26984895
http://dx.doi.org/10.1093/cercor/bhw033
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