Context-dependent relationship in high-resolution micro-ECoG studies during finger movements
Department of Neurosurgery, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan;
School of Medicine, National Yang-Ming University, Taipei, Taiwan;
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Center for Sensorimotor Neural Engineering, University of Washington, Seattle, Washington;
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Center for Sensorimotor Neural Engineering, University of Washington, Seattle, Washington;
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Center for Sensorimotor Neural Engineering, University of Washington, Seattle, Washington;
Department of Radiology, University of Washington, Seattle, Washington
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Graduate Program in Neuroscience, and
Center for Sensorimotor Neural Engineering, University of Washington, Seattle, Washington;
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OBJECTIVE
The activation of the sensorimotor cortex as measured by electrocorticographic (ECoG) signals has been correlated with contralateral hand movements in humans, as precisely as the level of individual digits. However, the relationship between individual and multiple synergistic finger movements and the neural signal as detected by ECoG has not been fully explored. The authors used intraoperative high-resolution micro-ECoG (µECoG) on the sensorimotor cortex to link neural signals to finger movements across several context-specific motor tasks.
METHODS
Three neurosurgical patients with cortical lesions over eloquent regions participated. During awake craniotomy, a sensorimotor cortex area of hand movement was localized by high-frequency responses measured by an 8 × 8 µECoG grid of 3-mm interelectrode spacing. Patients performed a flexion movement of the thumb or index finger, or a pinch movement of both, based on a visual cue. High-gamma (HG; 70–230 Hz) filtered µECoG was used to identify dominant electrodes associated with thumb and index movement. Hand movements were recorded by a dataglove simultaneously with µECoG recording.
RESULTS
In all 3 patients, the electrodes controlling thumb and index finger movements were identifiable approximately 3–6-mm apart by the HG-filtered µECoG signal. For HG power of cortical activation measured with µECoG, the thumb and index signals in the pinch movement were similar to those observed during thumb-only and index-only movement, respectively (all p > 0.05). Index finger movements, measured by the dataglove joint angles, were similar in both the index-only and pinch movements (p > 0.05). However, despite similar activation across the conditions, markedly decreased thumb movement was observed in pinch relative to independent thumb-only movement (all p < 0.05).
CONCLUSIONS
HG-filtered µECoG signals effectively identify dominant regions associated with thumb and index finger movement. For pinch, the µECoG signal comprises a combination of the signals from individual thumb and index movements. However, while the relationship between the index finger joint angle and HG-filtered signal remains consistent between conditions, there is not a fixed relationship for thumb movement. Although the HG-filtered µECoG signal is similar in both thumb-only and pinch conditions, the actual thumb movement is markedly smaller in the pinch condition than in the thumb-only condition. This implies a nonlinear relationship between the cortical signal and the motor output for some, but importantly not all, movement types. This analysis provides insight into the tuning of the motor cortex toward specific types of motor behaviors.
ABBREVIATIONS
BCI = brain-computer interface; BOLD = blood oxygen level dependent; ECoG = electrocorticography; fMRI = functional MRI; HG = high gamma; KNN = K nearest neighbor; µECoG = micro-ECoG.Illustration from Ivan et al. (pp 1517–1528). Copyright Kenneth Probst. Published with permission.
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