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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Published in:Cerebral cortex (New York, N.Y. 1991) N.Y. 1991), 2016-06, Vol.26 (6), p.2863-2881
Main Authors: Hammer, Jiří, Pistohl, Tobias, Fischer, Jörg, Kršek, Pavel, Tomášek, Martin, Marusič, Petr, Schulze-Bonhage, Andreas, Aertsen, Ad, Ball, Tonio
Format: Article
Language:English
Subjects:
Adolescent
Adult
Arm - physiology
Biomechanical Phenomena
Electrocorticography
Female
Humans
Male
Middle Aged
Models, Neurological
Motor Activity - physiology
Motor Cortex - physiology
Neurons - physiology
Neuropsychological Tests
Young Adult
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Summary: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.
ISSN:1047-3211
1460-2199
DOI:10.1093/cercor/bhw033