Decoding natural grasp types from human ECoG
| Autor: | Andreas Schulze-Bonhage, Tonio Ball, Ad Aertsen, Carsten Mehring, Tobias Pistohl |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Adolescent
Movement Cognitive Neuroscience Speech recognition Signal medicine Humans Natural (music) Brain–computer interface Brain Mapping Hand Strength Movement (music) GRASP Motor Cortex Electroencephalography Signal Processing Computer-Assisted Hand Electrodes Implanted body regions medicine.anatomical_structure Neurology Frontal lobe Arm Female Psychology Algorithms Decoding methods Motor cortex |
| Zdroj: | NeuroImage. 59:248-260 |
| ISSN: | 1053-8119 |
| DOI: | 10.1016/j.neuroimage.2011.06.084 |
| Popis: | Electrocorticographic (ECoG) signals have been successfully used to provide information about arm movement direction, individual finger movements and even continuous arm movement trajectories. Thus, ECoG has been proposed as a potential control signal for implantable brain–machine interfaces (BMIs) in paralyzed patients. For the neuronal control of a prosthesis with versatile hand/arm functions, it is also necessary to successfully decode different types of grasping movements, such as precision grip and whole-hand grip. Although grasping is one of the most frequent and important hand movements performed in everyday life, until now, the decoding of ECoG activity related to different grasp types has not been systematically investigated. Here, we show that two different grasp types (precision vs. whole-hand grip) can be reliably distinguished in natural reach-to-grasp movements in single-trial ECoG recordings from the human motor cortex. Self-paced movement execution in a paradigm accounting for variability in grasped object position and weight was chosen to create a situation similar to everyday settings. We identified three informative signal components (low-pass-filtered component, low-frequency and high-frequency amplitude modulations), which allowed for accurate decoding of precision and whole-hand grips. Importantly, grasp type decoding generalized over different object positions and weights. Within the frontal lobe, informative signals predominated in the precentral motor cortex and could also be found in the right hemisphere's homologue of Broca's area. We conclude that ECoG signals are promising candidates for BMIs that include the restoration of grasping movements. Highlights ► Two modes of natural grasping can be reliably discriminated from human ECoG. ► The decoding of grasp types generalizes over different object positions and weights. ► A low-frequency component and high-frequency amplitudes yield best decoding. ► ECoG may be used in BMIs for the restoration of grasping movements. |
| Databáze: | OpenAIRE |
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