Publications by authors named "Chungki Lee"

We present non-invasive means that detect unilateral hand motor brain activity from one individual and subsequently stimulate the somatosensory area of another individual, thus, enabling the remote hemispheric link between each brain hemisphere in humans. Healthy participants were paired as a sender and a receiver. A sender performed a motor imagery task of either right or left hand, and associated changes in the electroencephalogram (EEG) mu rhythm (8-10 Hz) originating from either hemisphere were programmed to move a computer cursor to a target that appeared in either left or right of the computer screen.

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Background: Identifying a neural circuit mechanism that is differentially involved in tremor would aid in the diagnosis and cure of such cases. Here, we demonstrate that tremor-related cortical potential (TRCP) is differentially expressed in two different mouse models of tremor.

Results: Hybrid tremor analysis of harmaline-induced and genetic tremor in mice revealed that two authentic tremor frequencies for each type of tremor were conserved and showed an opposite dependence on CaV3.

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The mouse model is an important research tool in neurosciences to examine brain function and diseases with genetic perturbation in different brain regions. However, the limited techniques to map activated brain regions under specific experimental manipulations has been a drawback of the mouse model compared to human functional brain mapping. Here, we present a functional brain mapping method for fast and robust in vivo brain mapping of the mouse brain.

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Neuronal source estimation is a general tool for analyzing spatiotemporal dynamics in human EEG. Despite rapidly-evolving interest in human brain, there are few EEG based source estimation tools in rodent brain. Therefore, we implemented source estimation tool in a mouse model, using the FieldTrip open-source software.

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It is well established that motor action/imagery provokes an event-related desynchronization (ERD) response at specific brain areas with specific frequency ranges, typically the sensory motor rhythm and beta bands. However, there are individual differences in both brain areas and frequency ranges which can be used to identify ERD. This often results in low classification accuracy of ERD, which makes it difficult to implement of BCI application such as the control of external devices and motor rehabilitation.

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