ArticleCerebral cortex (New York, N.Y. : 1991)2016
Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model.
Article in Cerebral cortex (New York, N.Y. : 1991), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed, 52 citations in OpenAlex.
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- Directional hand movement can be classified from insular cortex SEEG signals using recurrent neural networks and high-gamma band features.Scientific reports · 2025Article
- Human cortical high-gamma power scales with movement rate in healthy participants and stroke survivors.The Journal of physiology · 2025Article
- Non-Invasive Brain-Computer Interfaces: State of the Art and Trends.IEEE reviews in biomedical engineering · 2025Review
- Antagonistic behavior of brain networks mediated by low-frequency oscillations: electrophysiological dynamics during internal-external attention switching.Communications biology · 2024Article
- Timing of Allocentric and Egocentric Spatial Processing in Human Intracranial EEG.Brain topography · 2023Article
- On closed-loop brain stimulation systems for improving the quality of life of patients with neurological disorders.Frontiers in human neuroscience · 2023Review
- Feel Your Reach: An EEG-Based Framework to Continuously Detect Goal-Directed Movements and Error Processing to Gate Kinesthetic Feedback Informed Artificial Arm Control.Frontiers in human neuroscience · 2022Review
- Applying Dimensionality Reduction Techniques in Source-Space ElectroencephalographyFrontiers in human neuroscience · 2022Article
- Motor Imagery Classification for Brain Computer Interface Using Deep Convolutional Neural Networks and Mixup Augmentation.IEEE open journal of engineering in medicine and biology · 2022Article
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Stability of motor cortex network states during learning-associated neural reorganizations.Journal of neurophysiology · 2020Article
- Distinct cortical networks for hand movement initiation and directional processing: An EEG study.NeuroImage · 2020Article
- Mapping the Scene and Object Processing Networks by Intracranial EEG.Frontiers in human neuroscience · 2020Article
- Encoding of kinetic and kinematic movement parameters in the sensorimotor cortex: A Brain-Computer Interface perspective.The European journal of neuroscience · 2019Review
- Attempted Arm and Hand Movements can be Decoded from Low-Frequency EEG from Persons with Spinal Cord Injury.Scientific reports · 2019Article
- G-Causality Brain Connectivity Differences of Finger Movements between Motor Execution and Motor Imagery.Journal of healthcare engineering · 2019Article
- Cortical and subcortical areas involved in the regulation of reach movement speed in the human brain: An fMRI study.Human brain mapping · 2019Article
- Human Sensorimotor Cortex Control of Directly Measured Vocal Tract Movements during Vowel Production.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2018Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.