• Journal of Biomedical Engineering Research
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• v.26 no.2
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• pp.95-99
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• 2005

We have performed EEG current source imaging on the cortical surface using visual evoked potentials (VEPs) recorded inside a 3.0 T MRI magnet. In order to remove ballistocardiogram (BCG) artifacts in the VEPs, an improved BCG template subtraction technique is devised. Using the cortically constrained current source imaging technique and pattern-reversal visual stimulations, we have obtained current source maps from 10 subjects. To validate the EEG current source imaging inside the magnet, we have compared the current source maps to the ones obtained outside the magnet. The experimental results demonstrate that there is a strong correspondence between the current source maps, proving that current source imaging is feasible with the evoked potentials recorded inside a 3.0 T MRI magnet.

• Journal of Biomedical Engineering Research
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• v.27 no.2
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• pp.64-72
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• 2006

The present study introduces a new cortical patch-based source model for EEG/MEG cortical source imaging to consider anatomical constraints more precisely. Conventional source models for EEG/MEG cortical source imaging have used coarse cortical surface mesh or sampled small number of vertices from fine surface mesh, and thus they failed to utilize full anatomical information which nowadays we can get with sub-millimeter modeling accuracy. Conventional ones placed a single dipolar source on each cortical patch and estimated its intensity by means of various inverse algorithms; whereas the suggested cortical patch-based model integrates whole cortical area to construct lead field matrix and estimates current density that is assumed to be constant in each cortical patch. We applied the proposed and conventional models to realistic EEG data and compared the results quantitatively. The quantitative comparisons showed that the proposed model can provide more precise spatial descriptions of neuronal source distribution.

• Investigative Magnetic Resonance Imaging
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• v.7 no.2
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• pp.108-115
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• 2003

Purpose : To evaluate the effect of the gradient switching noise on the ECD source localization with the EEG data recorded during the MRI scan. Materials and Methods : We have fabricated a spherical EEG phantom that emulates a human head on which multiple electrodes are attached. Inside the phantom, electric current dipole(ECD) sources are located to evaluate the source localization error. The EEG phantom was placed in the center of the whole-body 3.0 Tesla MRI magnet, and a sinusoidal current was fed to the ECD sources. With an MRI-compatible EEG measurement system, we recorded the multi channel electric potential signals during gradient echo single-shot EPI scans. To evaluate the effect of the gradient switching noise on the ECD source localization, we controlled the gradient noise level by changing the FOV of the EPI scan. With the measured potential signals, we have performed the ECD source localization. Results : The source localization error depends on the gradient switching noise level and the ECD source position. The gradient switching noise has much bigger negative effects on the source localization than the Gaussian noise. We have found that the ECD source localization works reasonably when the gradient switching noise power is smaller than $10\%$ of the EEG signal power. Conclusion : We think that the results of the present study can be used as a guideline to determine the degree of gradient switching noise suppression in EEG when the EEG data are to be used to enhance the performance of fMRI.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2005.05a
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• pp.151-153
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• 2005

We investigated the brain substrate of repetition priming on the implicit memory taskusing low-resolution electromagnetic tomography (LORETA) with high-density 128 channel EEG and individual MRI as a realistic head model. Thirteen right-handed, healthy subjects performed a word/nonword discrimination task, in which the words and nonwords were presented visually,and some of the words appeared twice with a lag of one or five items. All of the subjects exhibited repetition priming with respect to the behavioral data, in which a faster reaction time was observed to the repeated word (old word) than to the first presentation of the word (new word). The old words elicited more positive-going potentials than the new words, beginning at 200 ms and lasting until 500 ms post-stimulus. We conducted source reconstruction using LORETA at a latency of 400 ms with the peak mean global field potentials and used statistical parametric mapping for the statistical analysis. We found that the source elicited by the old words exhibited a statistically significant current density reduction in the left inferior frontal gyrus. This is the first study to investigate the generators of repetition priming using voxel-by-voxel statistical mapping of the current density with individual MRI and high-density EEG.

• Sleep Medicine and Psychophysiology
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• v.17 no.2
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• pp.91-99
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• 2010

Objectives: Deficit schizophrenia (DS) constitutes a disease separate from non-deficit schizophrenia (NDS). The aim of the current study was to compare the quantitative EEG and low resolution electromagnetic tomography (LORETA) imaging between DS and NDS. Methods: This study was performed by 32 channels EEG for 42 schizophrenia patients who we categorized into DS and NDS using proxy instrument deficit syndrome (PDS). We performed the absolute power spectral analyses for delta, theta, alpha, low beta and high beta activities. We compared power spectrum between two groups using Independent t-test. Partial correlation test was performed with clinical parameters. Standardized LORETA (sLORETA) was used for comparison of cortical activity, and statistical nonparametric mapping (SnPM) was applied for the statistical analysis. Results: DS showed significantly increased delta and theta absolute power in fontal and parietal region compared with NDS (p<0.05). Power spectrum showed significant correlation with 'anergia' and 'hostility/suspiciousness' subscale of brief psychiatric rating scale (BPRS)(p<0.05). sLORETA found out the source region (anterior cingulate cortex/limbic part) that delta activity was significantly increased in DS (p=0.042). Conclusions: DS showed different cortical activity compared with NDS. Our results may suggest QEEG and LORETA could be the marker in differentiating between DS and NDS.

• Korean Journal of Biological Psychiatry
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• v.10 no.2
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• pp.168-176
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• 2003

Objectives:We investigated the characteristics of P300 generators in obsessive-compulsive disorder(OCD) patients by using voxel-based statistical parametric mapping of current density images. Methods:P300 generators, produced by a rare target tone of 1500Hz under a frequent non-target tone of 1,000Hz, were measured in 15 right-handed OCD patients and 15 controls. Low Resolution Electromagnetic Tomography(LORETA), using a realistic head model of the boundary element method based on individual MRI, was applied to the 128-channel EEG. Statistical parametric mapping(SPM) was applied for the statistical analysis. Results:We found that both groups had the mean current density of P300 in the parietal, temporal and prefrontal lobe. There was a trend for decreased current density in the prefrontal area in OCD patients. The statistical comparison showed current density increase in the supraparietal area, a statistically significant longer P300 latency and a trend for reduced P300 amplitude in OCD patients. Conclusion:It suggests that P300 source of both groups exists in multiple brain regions at the same time. And both groups had no statistically significant differences in the current density of P300 except for increased current density in the supraparietal area in OCD patients. But, considering the statistically significant longer P300 latency, a trend for reduced P300 amplitude and relative mean current density reduction in the prefrontal area in OCD patients, this study suggests that the frontal lobe may have a reduced normal inhibitory process in OCD patients.

• Advances in robotics research
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• v.1 no.2
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• pp.155-169
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• 2014

Study results in the last decades show that amount and quality of physical exercises, then the active participation, and now the cognitive involvement of patient in rehabilitation training are known of crux to enhance recovery outcome of motor dysfunction patients after stroke. Rehabilitation robots mainly have been developing along this direction to satisfy requirements of recovery therapy, or focusing on one or more of the above three points. Therefore, neuro-machine interaction based active rehabilitation robot has been proposed for assisting paralyzed limb performing designed tasks, which utilizes motor related EEG, UCSDI (Ultrasound Current Source Density Imaging), EMG for rehabilitation robot control and feeds back the multi-sensory interaction information such as visual, auditory, force, haptic sensation to the patient simultaneously. This neuro-controlled and perceptual rehabilitation robot will bring great benefits to post-stroke patients. In order to develop such kind of robot, some key technologies such as noninvasive precise detection of neural signal and realistic sensation feedback need to be solved. There are still some grand challenges in solving the fundamental questions to develop and optimize such kind of neuro-machine interaction based active rehabilitation robot.