• Journal of IKEEE
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• v.25 no.4
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• pp.679-688
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• 2021

Gait is an evaluation index used in various clinical area including brain nervous system diseases. Signal source localizing and time-frequency analysis are mainly used after extracting independent components for Electroencephalogram data as a method of measuring and analyzing brain activation related to gait. Existing treadmill-based walking EEG analysis performs signal preprocessing, independent component analysis(ICA), and source localizing by merging data after the multiple EEG measurements, and extracts representative component clusters through inter-subject clustering. In this study we propose an analysis method, without merging to single dataset, that performs signal preprocessing, ICA, and source localization on each measurements, and inter-subject clustering is conducted for ICs extracted from all subjects. The effect of data merging on the IC clustering and time-frequency analysis was investigated for the proposed method and two conventional methods. As a result, it was confirmed that a more subdivided gait-related brain signal component was derived from the proposed "non-merging" method (4 clusters) despite the small number of subjects, than conventional method (2 clusters).

• Genomics & Informatics
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• v.4 no.1
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• pp.23-32
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• 2006

In order to investigate the molecular basis of the aging process in brain, we have employed high-density oligonucleotide microarrays providing data on 10,108 gene clusters to define transcriptional patterns in three brain regions, cerebral cortex, cerebellum, and hippocampus. Comparison of the expression patterns between young (6-week-old) and aged (17-month-old) C57BL/6 male micerevealed that about ten percent (1098) of the genes showed a significant change in the expression level in at least one of the three tissues. Among them, 23 genes were upregulated and 62 genes were downregulated in all three tissues of the old mice. The number of genes upregulated exclusively in hippocampus (337) was much larger compared to other tissues. Gene ontology-based analysis showed the genes related with signal transduction or molecular transports are more likely to be upregulated than downregulated in the aging process of hippocampus. These data may provide some useful means for elucidating the molecular aspect of aging in hippocampus and other regions in brain.

• Biomedical Science Letters
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• v.12 no.4
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• pp.405-411
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• 2006

Heterotrimeric GTP binding proteins (G proteins) mediate signal transduction generated by neurotransmitter and hormones. Among G-proteins, Go is classified as a member of the Go/Gi family and the most abundant heterotrimeric G protein in brain. Most of the mechanistic analyses on the activation of Go indicated its action to be mediated by the $G{\beta}{\gamma}$ dimer because downstream effectors for its ${\alpha}$ subunit have not been clearly defined. To determine the downstream effectors of alpha subunits of Go ($Go{\alpha}$), we used yeast two-hybrid system to screen $Go{\alpha}$ interacting partners in cDNA library from the human brain. A brain specific high mobility group box containing protein (BHX), A possible transcription factor, was identified as a $Go{\alpha}$ interacting protein. We confirmed interaction between $Go{\alpha}$ and BHX employing in vitro affinity binding assay. Moreover, active form of $Go{\alpha}$ preferentially interacts with BHX than inactive farm. Our findings indicate that $Go{\alpha}$ could modulate gene expression via interaction with BHX during neuronal or brain development.

• Journal of KIISE
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• v.41 no.12
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• pp.1050-1057
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• 2014

Electroencephalogram (EEG)-based brain-computer interfaces (BCI) can be used for a number of purposes in a variety of industries, such as to replace body parts like hands and feet or to improve user convenience. In this paper, we propose a method to decompose and extract motor imagery EEG signal using Empirical Mode Decomposition (EMD) and Fast Fourier Transforms (FFT). The EEG signal classification consists of the following three steps. First, during signal decomposition, the EMD is used to generate Intrinsic Mode Functions (IMFs) from the EEG signal. Then during feature extraction, the power spectral density (PSD) is used to identify the frequency band of the IMFs generated. The FFT is used to extract the features for motor imagery from an IMF that includes mu rhythm. Finally, during classification, the Support Vector Machine (SVM) is used to classify the features of the motor imagery EEG signal. 10-fold cross-validation was then used to estimate the generalization capability of the given classifier., and the results show that the proposed method has an accuracy of 84.50% which is higher than that of other methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.176-181
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• 2016

In this paper, the autonomous mobile robot control system for detecting fire was proposed using the wearable device based on EMG(Electromyogram) signal. Myo armband is used for detecting the user's EMG signal. The gesture was classified after sending the data of EMG signal to a computer using Bluetooth communication. Then the robot named 'uBrain' was implemented to move by received data from Bluetooth communication in our experiment. 'Move front', 'Turn right', 'Turn left', and 'Stop' are controllable commands for the robot. And if the robot cannot receive the Bluetooth signal from a user or if a user wants to change manual mode to autonomous mode, the robot was implemented to be in the autonomous mode. The robot flashes the LED when IR sensor detects the fire during moving.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.442-450
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• 2002

In measuring EEG, which is widely used for studying brain function, EEG is frequently mixed with noise and artifact. In this study, the signals relevant to the artifact were distracted by applying ICA to EEG signal. First, each independent component which was assumed to be the source was separated by applying ICA to EEG which involved artifact relevant to the eye movement of a normal person. Next, the signal which was assumed to be artifact was removed from the separated 18 independent components, and the nonlinear analysis method such as correlation dimension and the Iyapunov exponent was applied to each reconstructed EEG signal and the original signal including artifact in order to find meaningful difference between the two signals and infer the anatomical localization of its source and distribution. This study shows it is possible not only to analyze the brain function visually and spatially for visually complex EEG signal, but also to observe its meaningful change through the quantitative analysis of EEG by means of the nonlinear analysis.

• Journal of Korean Neurosurgical Society
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• v.50 no.3
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• pp.173-178
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• 2011

Objective : The rat middle cerebral artery thread-occlusion model has been widely used to investigate the pathophysiological mechanisms of stroke and to develop therapeutic treatment. This study was conducted to analyze energy metabolism, apoptotic signal pathways, and genetic changes in the hippocampus of the ischemic rat brain. Methods : Focal transient cerebral ischemia was induced by obstructing the middle cerebral artery for two hours. After 24 hours, the induction of ischemia was confirmed by the measurement of infarct size using 2,3,5-triphenyltetrazolium chloride staining. A cDNA microarray assay was performed after isolating the hippocampus, and was used to examine changes in genetic expression patterns. Results : According to the cDNA microarray analysis, a total of 1,882 and 2,237 genes showed more than a 2-fold increase and more than a 2-fold decrease, respectively. When the genes were classified according to signal pathways, genes related with oxidative phosphorylation were found most frequently. There are several apoptotic genes that are known to be expressed during ischemic brain damage, including Akt2 and Tnfrsf1a. In this study, the expression of these genes was observed to increase by more than 2-fold. As energy metabolism related genes grew, ischemic brain damage was affected, and the expression of important genes related to apoptosis was increased/decreased.Conclusion : Our analysis revealed a significant change in the expression of energy metabolism related genes (Atp6v0d1, Atp5g2, etc.) in the hippocampus of the ischemic rat brain. Based on this data, we feel these genes have the potential to be target genes used for the development of therapeutic agents for ischemic stroke.

• Progress in Medical Physics
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• v.30 no.4
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• pp.139-149
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• 2019

Purpose: With neurodegeneration, the signal intensity of the cerebrospinal fluid (CSF) in the brain increases. The objective of this study was to evaluate chemical exchange saturation transfer (CEST) signals with and without the contribution of CSF signals in elderly human brains using two different 3T magnetic resonance imaging (MRI) sequences Methods: Full CEST signals were acquired in ten subjects (Group I) with a three-dimensional (3D)-segmented gradient-echo echo-planar imaging (EPI) sequence and in ten other subjects (Group II) with a 3D gradient and spin-echo (GRASE) sequence using two different 3T MRI systems. The segmented tissue compartments of gray and white matter were used to mask the CSF signals in the full CEST images. Two sets of magnetization transfer ratio asymmetry (MTR_asym) maps were obtained for each offset frequency in each subject with and without masking the CSF signals (masked and unmasked conditions, respectively) and later compared using paired t-tests. Results: The region-of-interest (ROI)-based analyses showed that the MTR_asym values for both the 3D-segmented gradient-echo EPI and 3D GRASE sequences were altered under the masked condition compared with the unmasked condition at several ROIs and offset frequencies. Conclusions: Depending on the imaging sequence, the MTR_asym values can be overestimated for some areas of the elderly human brain when CSF signals are unmasked. Therefore, it is necessary to develop a method to minimize this overestimation in the case of elderly patients.

• Investigative Magnetic Resonance Imaging
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• v.19 no.3
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• pp.146-152
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• 2015

Purpose: The purpose of this study was to evaluate the associated brain parenchymal abnormalities of developmental venous anomalies (DVA) with susceptibility-weighted image (SWI). Materials and Methods: Between January 2012 and June 2013, 2356 patients underwent brain MR examinations with contrast enhancement. We retrospectively reviewed their MR examinations and data were collected as per the following criteria: incidence, locations, and associated parenchymal signal abnormalities of DVAs on T2-weighted image, fluid-attenuated inversion recovery (FLAIR), and SWI. Contrast enhanced T1-weighted image was used to diagnose DVA. Results: Of the 2356 patients examined, 57 DVAs were detected in 57 patients (2.4%); 47 (82.4%) were in either lobe of the supratentorial brain, 9 (15.7%) were in the cerebellum, and 1 (1.7%) was in the pons. Of the 57 DVAs identified, 20 (35.1%) had associated parenchymal abnormalities in the drainage area. Among the 20 DVAs which had associated parenchymal abnormalities, 13 showed hemorrhagic foci on SWI, and 7 demonstrated only increased parenchymal signal abnormalities on T2-weighted and FLAIR images. In 5 of the 13 patients (38.5%) who had hemorrhagic foci, the hemorrhagic lesions were demonstrated only on SWI. Conclusion: The overall incidence of DVAs was 2.4%. Parenchymal abnormalities were associated with DVAs in 35.1% of the cases. On SWI, hemorrhage was detected in 22.8% of DVAs. Thus, we conclude that SWI might give a potential for understanding of the pathophysiology of parenchymal abnormalities in DVAs.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.112-124
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• 2010

Studies that can find resolutions to problems of subjective psychiatric analysis must be performed and indeed they are in the process. However there still lies many problems in researches of mentality examination, which should be the foundation of finding potential resolutions. One of the biggest problems in the conventional system is that there are many different opinions by psychiatrists depending on their educations and experiences. There is no objective standard on the subjects and there is no effective psychiatric analysis method. Also, the characteristic of such examinations is that it cannot be applied to disabilities, foreigners and infants alyce the examination is ch examinconversation. The objective of this atudy is to standardize TAT(Thematic Apperception Test)analysiBallken index method so that subjective data from the examination can be excluded and the examination thus maklysithe examination objectified. Furthermore, objective result and patients' brain wave pattern is read with BCI(Brain Computer Interface) ch exaTherenvironment to Alsare it to brain wave characteristics vectors to reate brain-wave characteristics vector DB. Therefore, such DB can be utilize durlysithe examination and diagnosis to reate objective examination method and standardized diagnosis system. Thus, mentality examination can be performed only with brain-wave scans with BCI based TAT system.