Global cortical activity predicts shape of hand during grasping
Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via el...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2015-04-01
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| Series: | Frontiers in Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00121/full |
| _version_ | 1811209648568532992 |
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| author | Harshavardhan Ashok Agashe Andrew Young Paek Yuhang eZhang Yuhang eZhang Jose Luis Contreras-Vidal |
| author_facet | Harshavardhan Ashok Agashe Andrew Young Paek Yuhang eZhang Yuhang eZhang Jose Luis Contreras-Vidal |
| author_sort | Harshavardhan Ashok Agashe |
| collection | DOAJ |
| description | Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across fifteen hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06 and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural ‘symphony’ as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs. |
| first_indexed | 2024-04-12T04:42:45Z |
| format | Article |
| id | doaj.art-f24fba82ba324bc58edabd70b48b9637 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-04-12T04:42:45Z |
| publishDate | 2015-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-f24fba82ba324bc58edabd70b48b96372022-12-22T03:47:34ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2015-04-01910.3389/fnins.2015.00121130471Global cortical activity predicts shape of hand during graspingHarshavardhan Ashok Agashe0Andrew Young Paek1Yuhang eZhang2Yuhang eZhang3Jose Luis Contreras-Vidal4University of HoustonUniversity of HoustonUniversity of HoustonUniversity of HoustonUniversity of HoustonRecent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across fifteen hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06 and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural ‘symphony’ as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs.http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00121/fullDecodingElectroencephalography (EEG)graspingDelta bandsynergies of grasping |
| spellingShingle | Harshavardhan Ashok Agashe Andrew Young Paek Yuhang eZhang Yuhang eZhang Jose Luis Contreras-Vidal Global cortical activity predicts shape of hand during grasping Frontiers in Neuroscience Decoding Electroencephalography (EEG) grasping Delta band synergies of grasping |
| title | Global cortical activity predicts shape of hand during grasping |
| title_full | Global cortical activity predicts shape of hand during grasping |
| title_fullStr | Global cortical activity predicts shape of hand during grasping |
| title_full_unstemmed | Global cortical activity predicts shape of hand during grasping |
| title_short | Global cortical activity predicts shape of hand during grasping |
| title_sort | global cortical activity predicts shape of hand during grasping |
| topic | Decoding Electroencephalography (EEG) grasping Delta band synergies of grasping |
| url | http://journal.frontiersin.org/Journal/10.3389/fnins.2015.00121/full |
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