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Decoding spatial locations from primate lateral prefrontal cortex neural activity during virtual navigation
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DOI：10.1088/1741-2552/acb5c2.png)
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Objective. Decoding the intended trajectories from brain signals using a brain-computer interface system could be used to improve the mobility of patients with disabilities. Approach. Neuronal activity associated with spatial locations was examined while macaques performed a navigation task within a virtual environment. Main results. Here, we provide proof of principle that multi-unit spiking activity recorded from the lateral prefrontal cortex (LPFC) of non-human primates can be used to predict the location of a subject in a virtual maze during a navigation task. The spatial positions within the maze that require a choice or are associated with relevant task events can be better predicted than the locations where no relevant events occur. Importantly, within a task epoch of a single trial, multiple locations along the maze can be independently identified using a support vector machine model. Significance. Considering that the LPFC of macaques and humans share similar properties, our results suggest that this area could be a valuable implant location for an intracortical brain-computer interface system used for spatial navigation in patients with disabilities.
Keyword:
invasive brain-computer interface
spatial navigation
lateral prefrontal cortex
non-human primates
support vector machine
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