The Experts below are selected from a list of 4716 Experts worldwide ranked by ideXlab platform

Philip A Starr - One of the best experts on this subject based on the ideXlab platform.

S.k. Han - One of the best experts on this subject based on the ideXlab platform.

  • International Conference on Computational Science - Single Trial Discrimination between Right and Left Hand Movement-Related EEG Activity
    Computational Science - ICCS 2004, 2004
    Co-Authors: Sunyoung Cho, J.a. Kim, Dong-uk Hwang, S.k. Han
    Abstract:

    We propose an EEG-based discrimination method for the right/left hand movement in a single trial. The EEG was recorded during the voluntary movement and imagination of the hand movement. We made a feature vector for every second that represents the characteristics to reflect the process of the right/left movement. It was composed of the ERD, ERS patterns of the mu and Beta Rhythm and the coefficients of the autoregressive model best fitting for the data of the given period. Linear discrimination of their distributions in the vector space classified the right/left hand movement-related EEG activity efficiently.

  • Single trial discrimination between right and left hand movement with EEG signal
    Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439), 2003
    Co-Authors: J.a. Kim, Dong-uk Hwang, S.y. Cho, S.k. Han
    Abstract:

    We propose an EEG-based discrimination method for the right/left hand movement in a single trial. The EEG was recorded during the voluntary movement and imagination of the hand movement. We made a feature vector for every second that represents the characteristics to reflect the process of the right/left movement, including the ERD, ERS pattern of the mu and Beta Rhythm and the coefficients of the autoregressive model best fitting for the data of the given period. Linear discrimination of their distribution in the vector space divided the right/left hand movement efficiently.

Wingho Yung - One of the best experts on this subject based on the ideXlab platform.

  • therapeutic deep brain stimulation in parkinsonian rats directly influences motor cortex
    Neuron, 2012
    Co-Authors: Qian Li, Ya Ke, Danny C W Chan, Zhongming Qian, Ken K L Yung, Ho Ko, G W Arbuthnott, Wingho Yung
    Abstract:

    Much recent discussion about the origin of Parkinsonian symptoms has centered around the idea that they arise with the increase of Beta frequency waves in the EEG. This activity may be closely related to an oscillation between subthalamic nucleus (STN) and globus pallidus. Since STN is the target of deep brain stimulation, it had been assumed that its action is on the nucleus itself. By means of simultaneous recordings of the firing activities from populations of neurons and the local field potentials in the motor cortex of freely moving Parkinsonian rats, this study casts doubt on this assumption. Instead, we found evidence that the corrective action is upon the cortex, where stochastic antidromic spikes originating from the STN directly modify the firing probability of the corticofugal projection neurons, destroy the dominance of Beta Rhythm, and thus restore motor control to the subjects, be they patients or rodents.

Arno Villringer - One of the best experts on this subject based on the ideXlab platform.

  • Neurophysiological investigations into the human somatosensory system
    2014 International Winter Workshop on Brain-Computer Interface (BCI), 2014
    Co-Authors: Arno Villringer
    Abstract:

    Using noninvasive neuroimaging methods in human subjects, we attempt to understand functional neuroanatomy and neurophysiological processes (somatotopy, inhibition, excitation, spike bursts, background activity) underlying somatosensory function. In order to define functional neuroanatomy, we use mainly task-based fMRI to identify somatotopy e.g., in SI and SII. Recently, we showed that gross somatotopy can also be extracted from task-less resting-state fMRI. Regarding neurophysiological processes, we show that the strength of background Rhythms (Rolandic alpha, Beta Rhythm) determines receptiveness of the somatosensory system to activation and is inversely related to cortical BOLD-fMRI signal. We establish a model of predominant inhibitory processing using subliminal stimulation and we show that this decreases BOLD-fMRI signal, decreases connectivity of SI, and transiently increases alpha Rhythm. Using simultaneous EEG-fMRI, we identify correlates of spike bursts in human subjects non-invasively and relate them to BOLD fMRI signal along the path of somatosensory processing.

  • rolandic alpha and Beta eeg Rhythms strengths are inversely related to fmri bold signal in primary somatosensory and motor cortex
    Human Brain Mapping, 2009
    Co-Authors: Petra Ritter, Matthias Moosmann, Arno Villringer
    Abstract:

    Similar to the posterior alpha Rhythm, pericentral (Rolandic) EEG Rhythms in the alpha and Beta frequency range are referred to as “idle Rhythms” indicating a “resting state” of the respective system. The precise function of these Rhythms is not clear. We used simultaneous EEG-fMRI during a bimanual motor task to localize brain areas involved in Rolandic alpha and Beta EEG Rhythms. The identification of these Rhythms in the MR environment was achieved by a blind source separation algorithm. Rhythm “strength”, i.e. spectral power determined by wavelet analysis, inversely correlated most strongly with the fMRI-BOLD signal in the postcentral cortex for the Rolandic alpha (mu) Rhythm and in the precentral cortex for the Rolandic Beta Rhythm. FMRI correlates of Rolandic alpha and Beta Rhythms were distinct from those associated with the posterior “classical” alpha Rhythm, which correlated inversely with the BOLD signal in the occipital cortex. An inverse correlation with the BOLD signal in the respective sensory area seems to be a general feature of “idle Rhythms”. Hum Brain Mapp 2009. © 2008 Wiley-Liss, Inc.

  • rolandic alpha and Beta eeg Rhythms strengths are inversely related to fmri bold signal in primary somatosensory and motor cortex
    Human Brain Mapping, 2009
    Co-Authors: Petra Ritter, Matthias Moosmann, Arno Villringer
    Abstract:

    Similar to the posterior alpha Rhythm, pericentral (Rolandic) EEG Rhythms in the alpha and Beta frequency range are referred to as "idle Rhythms" indicating a "resting state" of the respective system. The precise function of these Rhythms is not clear. We used simultaneous EEG-fMRI during a bimanual motor task to localize brain areas involved in Rolandic alpha and Beta EEG Rhythms. The identification of these Rhythms in the MR environment was achieved by a blind source separation algorithm. Rhythm "strength", i.e. spectral power determined by wavelet analysis, inversely correlated most strongly with the fMRI-BOLD signal in the postcentral cortex for the Rolandic alpha (mu) Rhythm and in the precentral cortex for the Rolandic Beta Rhythm. FMRI correlates of Rolandic alpha and Beta Rhythms were distinct from those associated with the posterior "classical" alpha Rhythm, which correlated inversely with the BOLD signal in the occipital cortex. An inverse correlation with the BOLD signal in the respective sensory area seems to be a general feature of "idle Rhythms".

Coralie De Hemptinne - One of the best experts on this subject based on the ideXlab platform.