• 한국초전도학회:학술대회논문집
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• 2008.08a
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• pp.11-11
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• 2008

• Science of Emotion and Sensibility
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• v.13 no.3
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• pp.551-558
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• 2010

Pain is very complex and multi-level experience that should be objective or subjective. Acupuncture is a traditional method to heal the pain and have been based on meridian theory. There have been many clinical evidences showing the pain-relieving effect of acupuncture but science-based understanding of it was poor. Furthermore in daily life, we feel huge gap between the source of pain and pain control by acupuncture stimulation. However, the underlying connection between pain control and acupuncture stimulation has been reported in many recent reports. In this paper, we briefly introduce the brain imaging techniques (functional magnetic resonance images, positron emission tomography, electroencephalograph, and magnetoencephalography) and review researches in pain and acupuncture. Through this, the brain areas that activated by pain and acupuncture will be verified, and compared each other regarding their specificity and similarity. In addition, detailed understanding of brain function which is related to pain and acupuncture analgesia through brain imaging techniques will be discussed.

• Journal of Biomedical Engineering Research
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• v.31 no.6
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• pp.456-463
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• 2010

In the present study, we proposed a new subspace scanning algorithm to enhance the spatial resolution of electroencephalography (EEG) and magnetoencephalography(MEG) source localization. Subspace scanning algorithms, represented by the multiple signal classification (MUSIC) algorithm and the first principal vector (FINE) algorithm, have been widely used to localize asynchronous multiple dipolar sources in human cerebral cortex. The conventional MUSIC algorithm used principal component analysis (PCA) to extract the noise vector subspace, thereby having difficulty in discriminating two or more closely-spaced cortical sources. The FINE algorithm addressed the problem by using only a part of the noise vector subspace, but there was no golden rule to determine the number of noise vectors. In the present work, we estimated a non-orthogonal signal vector set using independent component analysis (ICA) instead of using PCA and performed the source scanning process in the signal vector subspace, not in the noise vector subspace. Realistic 2D and 3D computer simulations, which compared the spatial resolutions of various algorithms under different noise levels, showed that the proposed ICA-MUSIC algorithm has the highest spatial resolution, suggesting that it can be a useful tool for practical EEG/MEG source localization.

• Progress in Superconductivity
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• v.4 no.1
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• pp.42-47
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• 2002

Measuring magnetic fields with a SQUID sensor always requires preliminary adjustments such as optimum bas current determination and flux-locking point search. A conventional magnetoencephalography (MEG) system consists of several dozens of sensors and we should condition each sensor one by one for an experiment. This timeconsuming job is not only cumbersome but also impractical for the common use in hospital. We had developed a serial port communication protocol between SQUID sensor controllers and a personal computer in order to control the sensors. However, theserial-bus-based control is too slow for adjusting all the sensors with a sufficient accuracy in a reasonable time. In this work, we introduce programmatic control sequence that saves the number of the control pulse arrays. The sequence separates into two stages. The first stage is a function for searching flux-locking points of the sensors and the other stage is for determining the optimum bias current that operates a sensor in a minimum noise level Generally, the optimum bias current for a SQUID sensor depends on the manufactured structure, so that it will not easily change about. Therefore, we can reduce the time for the optimum bias current determination by using the saved values that have been measured once by the second stage sequence. Applying the first stage sequence to a practical use, it has taken about 2-3 minutes to perform the flux-locking for our 37-channel SQUID magnetometer system.

• Annals of Clinical Neurophysiology
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• v.8 no.2
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• pp.163-170
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• 2006

Backgrounds: MEG can measure the task-specific neurophysiologic activity with good spatial and time resolution. Language lateralization using noninvasive method has been a subject of interest in resective brain surgery. We purposed to develop a paradigm for language lateralization using MEG and validate its feasibility. Methods: Magnetic fields were obtained in 12 neurosurgical candidates and one volunteer for language tasks, with a 306 channel whole head MEG. Language tasks were word listening, reading and picture naming. We tested two word listening paradigms: semantic decision of meaning of abstract nouns, and recognition of repeated words. The subjects were instructed to silently name or read, and respond with pushing button or not. We decided language dominance according to the number of acceptable equivalent current dipoles (ECD) modeled by sequential single dipole, and the mean magnetic field strength by root mean square value, in each hemisphere. We collected clinical data including Wada test. Results: Magnetic fields evoked by word listening were generally distributed in bilateral temporoparietal areas with variable hemispheric dominance. Language tasks using visual stimuli frequently evoked magnetic field in posterior midline area, which made laterality decision difficult. Response during task resulted in more artifacts and different results depending on responding hand. Laterality decision with mean magnetic field strength was more concordant with Wada than the method with ECD number of each hemisphere. Conclusions: Word listening task without hand response is the most feasible paradigm for language lateralization using MEG. Mean magnetic field strength in each hemisphere is a proper index for hemispheric dominance.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2006.06a
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• pp.61-65
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• 2006

본 연구는 한국어 어휘중의성 해결과정에 관련된 대뇌활동을 살펴보기 위하여 MEG(magnetoencephalography)를 이용한 실험을 실시하였다. 일차적으로 기존의 중의성 관련 fMRI 실험 결과들이 MEG를 이용한 신호원 국소화 결과와 유사한 패턴을 보이는지 확인하였고, 본 실험의 주요 목적인 중의성 관련 처리과정에 기저하는 하위 처리과정이 어떠한 기능적 처리 요소들로 분해될 수 있는 지에 대해서도 시간 해상도가 높은 MEG의 특성을 이용하여 관찰하였다. 분석 결과, 한국어 중의어 해소과정의 하위처리 과정은 어휘의미 접속이라는 기본적인 과정 비에, 이들의 의미분지를 유발하는 단서의 유무가 그 활성화 영역의 시간적인 패턴과 중의성 해결을 위한 지속시간에 영향을 미치는 것으로 확인되었다.

• 한국초전도학회:학술대회논문집
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• v.13
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• pp.59-59
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• 2003

• 한국초전도학회:학술대회논문집
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• 2009.07a
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• pp.66-66
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• 2009

• 한국초전도학회:학술대회논문집
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• v.12
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• pp.43-43
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• 2002

• International Journal of Knowledge Content Development & Technology
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• v.3 no.1
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• pp.19-29
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• 2013

Insights from the recent wealth of popular books on neuroscience are offered to suggest a strengthening of theory in information science. Information theory has traditionally neglected the human dimension in favour of 'scientific' theory often derived from the Shannon-Weaver model. Neuroscientists argue in excitingly fresh ways from the evidence of case studies, non-intrusive experimentation and the measurements that can be obtained from technologies that include electroencephalography, positron emission tomography (PET), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). The way in which the findings of neuroscience intersect with ideas such as those of Kahneman on fast and slow thinking and Csikszentmihalyi on flow, is tentatively explored as lines of connection with information science. It is argued that the beginnings of a theoretical underpinning for current web-based information searching in relation to established information retrieval methods can be drawn from this.