B eeg
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Physicians who specialize in the performance and interpretation of neuroimaging in the clinical setting are known as neuroradiologists. It is a relatively new discipline within medicine, neuroscience, and psychology. Neuroimaging, or brain scanning, includes the use of various techniques to directly or indirectly image the structure, function, or pharmacology of the brain. magnetic field: A condition in the space around a magnet or electric current in which there is a detectable magnetic force and two magnetic poles are present.conductivity: The ability of a material to conduct electricity, heat, fluid, or sound.
B EEG SERIES
Functional magnetic resonance imaging (fMRI) scans are a series of MRIs measuring brain function via a computer’s combination of multiple images taken less than a second apart.Magnetic resonance imaging (MRI) scans use echo waves to discriminate among grey matter, white matter, and cerebrospinal fluid.Positron emission tomography (PET) scans show brain processes by using the sugar glucose in the brain to illustrate where neurons are firing.Electroencephalography (EEG) is used to show brain activity under certain psychological states, such as alertness or drowsiness.Neuroimaging falls into two broad categories: structural imaging and functional imaging.Neuroimaging, or brain scanning, includes the use of various techniques to either directly or indirectly image the structure, function, or pharmacology of the brain.(A) Spatial patterns (B) Averaged PSDs in motor imagery practice. Spatial patterns and averaged PSDs of the three motor ICs for Subject 5. In (A), (B), and (C), each solid line connects left hand and right hand data for a subject. (F) Weighted single-trial EEG power of motor ICs during motor imagery. (E) Single-trial EEG baseline power of motor ICs during resting.
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(D) Single-trial EEG power of motor ICs during motor imagery on one subject. (A) EEG power of motor ICs during motor imagery (B) EEG power of motor ICs during resting (C) Weighted EEG power of motor ICs during motor imagery (original power divided by the mean power of the resting data). (A) power difference between left- and right-hand motor imagery conditions (B) difference of spatial patterns between left and right independent motor components obtained from the motor imagery data.ĮEG power of motor ICs during resting and motor imagery states. Spatial distributions of EEG power difference and IC spatial pattern difference. (A) monopolar scalp data at C3 and C4 electrodes (B) motor-related independent components extracted by ICA using the motor imagery data (C) motor-related independent components extracted by ICA using the resting data.Ĭlassification accuracy (%) for all subjects using different feature extraction methods.Ĭlassification accuracy (%) of the session-to-session transfer method on three subjects. In each subfigure, the left and right motor ICs for all subjects were grouped on the left and the right panel respectively.Ĭorrelation coefficients of spatial patterns and spatial filters between the resting state and the motor imagery state.Īveraged power spectrum density of EEG signals in motor imagery practice across all subjects. Black dots in each scalp map indicate positions of C3 and C4 electrodes. (A) spatial patterns of the resting state (B) spatial patterns of the motor imagery state (C) spatial filters of the resting state (D) spatial filters of the motor imagery state. Spatial patterns and spatial filters of the motor components for all nine subjects. Spatial filters obtained from the resting data could be used as estimates of those from the motor imagery data.
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Similar spatial filters and spatial patterns were obtained by ICA on data corresponding to the two conditions separately. (A) Group-averaged time-frequency distributions of ERSP for the left motor IC and the right motor IC corresponding to left and right hand movement imaginations (B) Group-averaged PSD of left and right motor ICs under different conditions (RE: resting state, MI: motor imagery state, MI-L: left-hand motor imagery, MI-R: right-hand motor imagery).ĭiagram of translating spatial filters from the resting state to the motor imagery state. Group-averaged ERSP and PSD for two motor components. Parameters for automatic identification of motor ICs on a sample subject. details of the identification process in Table 1). IC5 and IC7, which both show a unilateral spatial distribution over the sensorimotor cortex and a mu/beta-band dominant spectral profile, are highlighted by a black rectangle as the selected motor components (cf. Scalp topographies and PSDs of all ICs from one subject. Experiment paradigm for the motor imagery-based brain-computer interface.