• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.832-837
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• 2007

Many researchers are studying brain activity to using functional Magnetic Resonance Imaging (fMRI), Time Resolved Spectroscopy(TRS), Electroencephalography(EEG), and etc. They are used detection of seizures or epilepsy and deception detection in the main. In this paper, we focus on emotion recognition by recording brain waves. We specially use fMRI, TRS, and EEG for measuring brain activity Researchers are experimenting brain waves to get only a measuring apparatus or to use both fMRI and EEG. This paper is measured that we take images of fMRI and TRS about brain activity as human emotions and then we take data of EEG signals. Especially, we focus on EEG signals analysis. We analyze not only original features in brain waves but also transferred features to classify into five sections as frequency. And we eliminate low frequency from 0.2 to 4Hz for EEG artifacts elimination.

• Sleep Medicine and Psychophysiology
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• v.25 no.2
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• pp.82-91
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• 2018

Objectives: Synchronous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) has been used to explore sleep stage dependent functional brain networks. Despite a growing number of sleep studies using EEG-fMRI, few studies have conducted network analysis on whole night sleep due to difficulty in data acquisition, artifacts, and sleep management within the MRI scanner. Methods: In order to perform network analysis for whole night sleep, we proposed experimental procedures and data processing techniques for EEG-fMRI. We acquired 6-7 hours of EEG-fMRI data per participant and conducted signal processing to reduce artifacts in both EEG and fMRI. We then generated a functional brain atlas with 68 brain regions using independent component analysis of sleep fMRI data. Using this functional atlas, we constructed sleep level dependent functional brain networks. Results: When we evaluated functional connectivity distribution, sleep showed significantly reduced functional connectivity for the whole brain compared to that during wakefulness. REM sleep showed statistically different connectivity patterns compared to non-REM sleep in sleep-related subcortical brain circuits. Conclusion: This study suggests the feasibility of exploring functional brain networks using sleep EEG-fMRI for whole night sleep via appropriate experimental procedures and signal processing techniques for fMRI and EEG.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.7-10
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• 2007

많은 과학자들은 인간의 사고를 functional Magnetic Resonance Imaging (fMRI), Time Resolved Spectroscopy(TRS), Electroencephalography(EEG)등을 이용해서 두뇌 활동 영역을 연구하고 있다. 주로 의학 분야와 심리학의 영역에서 두뇌의 활동을 연구하여 간질이나 발작을 알아내고 거짓말 탐지 분야에서도 사용된다. 본 논문에서는 사람의 두뇌활동을 측정하여 인간의 감정을 인식하는 연구에 중점을 두었다. 특히 fMRI와 TRS 그리고 EEG를 이용해서 사람의 두뇌활동을 측정하는 연구를 하였다. 많은 연구자들이 한 가지 측정 장치만을 사용하여서 측정하거나 fMRI와 EEG를 동시에 측정하는 연구를 진행하고 있다. 현재에는 단순히 두뇌의 활동을 측정하거나 측정시 발생하는 잡음들을 제거하는 연구들에 중점을 두고 진행되고 있다. 본 연구에서는 fMRI와 TRS를 동시에 측정하여 얻은 두뇌 활동 데이터를 가지고 감정에 따른 활동영역의 EEG신호를 측정하였다. EEG 신호분석에 있어서 기존의 뇌파만을 가지고 특정을 찾아내는 것을 넘어서 각각의 채널에서 기록되는 뇌파의 파형을 주파수에 따라서 분류하고 정확한 측정을 위해 낮은 주파수를 제거하고 연구자가 필요한 부분의 뇌파를 분석하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.13-14
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• 2023

뇌의 전기적 신경활동을 측정하는 뇌전도(EEG)는 저렴하게 취득할 수 있고 높은 시간 해상도를 갖는 반면 공간적 정보를 제공하지는 않는다. 기능적 자기공명영상(fMRI)은 혈류변화를 감지하여 뇌활동을 측정하는 방식으로서 높은 공간 분해능을 갖지만 고가의 비용과 설비를 요구한다. 최근 저렴하게 취득할 수 있는 EEG 데이터로부터 딥러닝을 사용하여 fMRI 합성영상을 생성하는 기술이 제안되었지만, 저주파수 대역에서 EEG와 fMRI 간의 뇌과학적 상관관계를 반영하지는 않는다. 본 연구에서는 휴식상태에서 취득된 EEG 데이터를 스펙트로그램으로 변환한 후 저주파수 특성을 사용하여 fMRI 합성영상을 생성하는 U-net 기반의 크로스 모달리티 변환 모델의 실현가능성을 평가하였다.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.223-230
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• 2005

This paper presents a new approach to investigate spatial correlation between independent components of brain alpha activity in functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). To avoid potential problems of simultaneous fMRI and EEG acquisitions in imaging pure alpha activity, data from each modality were acquired separately under a 'three conditions' setup where one of the conditions involved closing eyes and relaxing, thus making it conducive to generation of alpha activity. The other two conditions -- eyes open in a lighted room or engaged in a mental arithmetic task, were designed to attenuate alpha activity. Using a Mixture Density Independent Component Analysis (MD-ICA) that incorporates flexible non-linearity functions into the conventional ICA framework, we could identify the spatiotemporal components of fMRI activations and EEG activities associated with the alpha rhythm. Then, the sources of the individual EEG alpha activity component were localized by a Maximum Entropy (ME) method that is specially designed to find the most probable dipole distribution minimizing the localization error in sense of LMSE. The resulting active dipoles were spatially transformed to 3D MRls of the subject and compared to fMRI alpha activity maps. A good spatial correlation was found in the spatial distribution of alpha sources derived independently from fMRI and EEG, suggesting the proposed method can localize the cortical areas responsible for generating alpha activity successfully in either fMRI or EEG. Finally a functional connectivity analysis was applied to show that alpha activity sources of both modalities were also functionally connected to each other, implying that they are involved in performing a common function: 'the generation of alpha rhythms'.

• Investigative Magnetic Resonance Imaging
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• v.8 no.1
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• pp.1-8
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• 2004

Purpose : Information about electrical activity inside the brain during fMRl scans is very useful in monitoring physiological function of the patient or locating the spatial position of the activated region in the brain. However, many additional noises appear in the EEG signal acquired during the MRI scan. Gradient induced noise is the biggest one among the noises. In this work, we propose a gradient noise reduction method using the independent component analysis (ICA) method. Materials and Methods : We used a 29-channel MR-compatible EEG measurement system and a 3.0 Tesla MRI system. We measured EEG signals on a subject lying inside the magnet during EPI scans. We selectively removed the gradient noise from the measured EEG signal using the ICA method. We compared the results with the ones obtained with conventional averaging method and PCA method. Results : All the noise reduction methods including the averaging and PCA methods were effective in removing the noise in some extent. However, the proposed ICA method was found to be superior to the other methods. Conclusion : Gradient noise in EEG signals acquired during fMRI scans can be effectively reduced by the ICA method. The noise-reduced EEG signal can be used in fMRI studies of epileptic patients or combinatory studies of fMRI and EEG.

• Smart Media Journal
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• v.10 no.2
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• pp.55-60
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• 2021

In this research, we design and perform experiment to investigate whether neuronal activity patterns elicited while solving game tasks are spontaneously reactivated in during sleep. In order to recognize human activity EEG-fMRI signals are used at the same time. Experimental results shows that reward for the success of tasks performed before sleeping have an effect on sleep brain activity. The study uncovers a neural mechanism whereby rewarded life experiences are preferentially replayed and consolidated while we sleep.

• Korean Journal of Acupuncture
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• v.21 no.2
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• pp.1-28
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• 2004

Objectives : Human physiological changes in the state of qigong has been measured using EEG(Electroencephalography), functional MRI(functional Magnetic Resonance Image), EAV(Electro-Acupuncture according to Voll) and SQUID(Superconducting Quantum Interference Device) measurements. Methods & Results : EEGs were measured to study the differences between Qigong masters and Qi receiver on the changes of EEG. During Qigong, an alpha waves were increased. The power spectra indicate that the peak frequency of alpha waves increased during Qigong. Qi receiver's EEG signals seemed to affected by the state of himself. Brain activation did not observed when qigong master concentrates the Qi at Laogong(P8). But a localization of fMRI signal in the sensory cortex was observed by electric acupuncture stimulation at Laogong(P8). Five phase deviation of EAV were clearly changed in the both cases of Qigong master and Qi receiver. When a Qigong master concentrates the Qi at Yintang, Laogong(P8), Qihai(CV6) meridian points during Qigong state, the change of magnetic field around acupoints Yintang, Laogong points has been measured using 40-Channel DROS-SQUID apparatus. After smoothing process of the continuously measured magnetic signal around acupoints for a few minutes, we could observe that a series of peaks, magnitude of -1.0~2.5pT appeared. But there was no significant difference in changes of magnetic signal around acupoints. Physical signals of magnetocardiogram has been measured by using 2-Channel DROS SQUID(Magnetocardiogram). Physical signals of magnetocardiogram were clealy changed at the ST segments after S-wave when qigong master concentrates the Qi.

• Korean Journal of Biological Psychiatry
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• v.3 no.1
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• pp.57-65
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• 1996

The Evaluation of patients complaining of psychiatric symptoms following head injury is much affected by the results of various tests. The objecive of this paper is to investigate the effectiveness of each lest by comparing the structual and fuctional brain studies. The subjects were 93 organic menial disorder in and out patients at the Dept. of Neuropsychiatry of the Kyung Hee University Hospital. After carrying out MRI, CT, SPECT, EEG, the results of each were analysed for the sesitivity and ability to detect focal lesion. The degree of inter-test correlations of lest results were also investigated. Furthermore, the characteristic features of psychological tests were studied and the relationship between each of above mentioned tests and psychological test was examined. As for the test sensitivity to diagnosis, the SPECT was the most superior followed by MRI, CT, EEG in thai order. In the case of abnormality, SPECT ranked 1st in detection of focal lesion, followed by MRI, CT in that order. In the inter-test result correlation, the correlation of SPECT-MRI was statistically significant. When mare than moderate abnormality EEG finding was reported, it correlated significantly with that of MRI findings. In the MMPI, the average scores on F, Hs, D, Hy, Pa, Pt, Sc subscales were above 60. Abnormal SPECT group scored significantly high on the F, Pd, Pa, Sc, Ma scales and therefore in comparison ot the SPECT normal group, displayed more psychotic features. In K-WAIS, the mean full scale IQ was down to 77. 23(Verbal IQ : 78.76, Performance IQ : 77.44) but there was no characterogic significant relationship between the lowered to and abnormal SPECT, MRI, CT and EEG results. In conclusion, 1) The SPECT was mast superior in sensitivity and detection of focal lesions. In comparision with other tests, the results of SPECT correlated well with MRI had thus is thought to be very usefull testing method in the evaluation of organic mental disorder patients. 2) The MRI had relatively high sensitivity, ability to detect focal lesion and superior correlation with other test. 3) Although EEG fared less an sensitivity in comparison to other tests, the results of above moderate abnormal grade group and that of MRI correlated significantly. 4) In the MMPI highly scored in F, Hs, D, Hy, Pa, Pt, Sc subscales and abnormal SPECT patients were shown to display more sever psychotic features. There was no significant character relationship between the lowered IQ(in K-WAIS) and abnormal findings on MRI, CT, SPECT, EEG.

• Journal of Biomedical Engineering Research
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• v.45 no.1
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• pp.26-36
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• 2024

Functional brain imaging techniques have been used to diagnose psychiatric disorders such as dementia, depression, and autism. Recently, these techniques have also been actively used to study hearing loss. The present study reviewed the application of the functional brain imaging techniques in auditory research, especially those focusing on hearing loss, over the past decade. EEG, fMRI, fNIRS, MEG, and PET have been utilized in auditory research, and the number of research studies using these techniques has been increasing. In particular, fMRI and EEG were the most frequently used technique in auditory research. EEG studies mostly used event-related designs to analyze the direct relationship between stimulus and the related response, and in fMRI studies, resting-state functional connectivity and block designs were utilized to analyze alterations in brain functionality in hearing-related areas. In terms of age, while studies involving children mainly focused on congenital and pre- and post-lingual hearing loss to analyze developmental characteristics with and without hearing loss, those involving adults focused on age-related hearing loss to investigate changes in the characteristics of the brain based on the presence of hearing loss and the use of a hearing device. Overall, ranging from EEG to PET, various functional brain imaging techniques have been used in auditory research, but it is difficult to perform a comprehensive analysis due to the lack of consistency in experimental designs, analysis methods, and participant characteristics. Thus, it is necessary to develop standardized research protocols to obtain high-quality clinical and research evidence.