• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.6
• /
• pp.786-791
• /
• 2011

An optimal feature selection and extraction procedure is an important task that significantly affects the success of brain activity analysis in brain-computer interface (BCI) research area. In this paper, a novel method for extracting the optimal feature from electroencephalogram (EEG) signal is proposed. At first, a student's-t-statistic method is used to normalize and to minimize statistical error between EEG measurements. And, 2D time-frequency data set from the raw EEG signal was extracted using discrete wavelet transform (DWT) as a raw feature, standard deviations and mean of 2D time-frequency matrix were extracted as a optimal EEG feature vector along with other basis feature of sub-band signals. In the experiment, data set 1 of BCI competition IV are used and classification using SVM to prove strength of our new method.

• Biomedical Science Letters
• /
• v.13 no.2
• /
• pp.127-133
• /
• 2007

Heterotrimeric GTP binding proteins (G proteins) mediate signal generated by neurotransmitter and hormones. Among all G proteins, Go is the most abundant in brain but its role in brain is not clearly understood. To determine the function of the alpha subunit of Go (Go$\alpha$), we search for the interacting partner of Go$\alpha$ in brain using yeast two-hybrid system. A resistant to inhibitor of cholinesterase (Ric-8B) was identified as a Go$\alpha$ interacting protein. We confirmed interaction between Go$\alpha$ and Ric-8b employing in vitro affinity binding assay and showed that the Ric-8b increased the function of Go$\alpha$. Our findings indicate that Ric-8b is possible guanine nucleotide exchange factor for Go$\alpha$.

• Molecules and Cells
• /
• v.20 no.3
• /
• pp.348-353
• /
• 2005

Using in silico approaches and RACE we cloned a full length trinucleotide (CAG) repeat-containing cDNA (cag-3). The cDNA is 2478 bp long and the deduced polypeptide consists of 140 amino acids of which 73 are glutamines. The genomic sequence spans approximately 79 kb on mouse chromosome 7 and the gene is composed of four exons. Standard and real-time PCR analyses of several mouse tissues showed that the gene is exclusively expressed in the brain and is not detected in embryonic stages. Within the brain, it is expressed throughout the forebrain region with predominant expression in the hypothalamus and olfactory bulb and very low levels in the mid- and hindbrain.

• Proceedings of the Safety Management and Science Conference
• /
• 2011.11a
• /
• pp.583-591
• /
• 2011

A number of Brain-Computer Interface (BCI) studies have been performed to assess the cognitive status through EEG signal. However, there are a few studies trying to prevent user from unexpected safety-accident in BCI study. The EEGs were collected from 19 subjects who participated in two experiments (rest & event-related potential measurement). There was significant difference in EEG changes of both spontaneous and event-related potential. Beta power and P300 latency may be useful as a biomarker for prevention of response to safety-accident.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.1
• /
• pp.1-6
• /
• 2012

A number of Brain-Computer Interface (BCI) studies have been performed to assess the cognitive status through EEG signal. However, there are a few studies trying to prevent user from unexpected safety-accident in BCI study. The EEGs were collected from 19 subjects who participated in two experiments (rest & event-related potential measurement). There was significant difference in EEG changes of both spontaneous and event-related potential. Beta power and P300 latency may be useful as a biomarker for prevention of response to safety-accident.

• The Korean Journal of Nuclear Medicine
• /
• v.37 no.1
• /
• pp.63-72
• /
• 2003

Functional MRI (fMRI) provides an indirect mapping of cerebral activity, based on the detection of the local blood flow and oxygenation changes following neuronal activity (Blood Oxygenation Level Dependent). fMRI allows us to study noninvasively the normal and pathological aspects of functional cortical organization. Each fMRI study compares two different states of activity. Echo-Planar Imaging is the technique that makes it possible to study the whole brain at a rapid pace. Activation maps are calculated from a statistical analysis of the local signal changes. fMRI is now becoming an essential tool in the neurofunctional evaluation of normal volunteers and many neurological patients as well as the reference method to image normal or pathologic functional brain organization.

• Journal of Korean Neurosurgical Society
• /
• v.41 no.6
• /
• pp.421-424
• /
• 2007

Two patients, one with glioblastoma multiforme [GM] in the right thalamus and the other with meningioma at the right frontal convexity, had suffered bilateral cortical blindness after transtentorial herniation. On one of those patients, bilateral cortical blindness had occurred due to acute obstructive hydrocephalus caused by GM and on the other patient, cortical blindness had developed after acute hemorrhage from meningioma. Bilateral occipital lobes of those patients showed signal change on the brain magnetic resonance image [MRI]. There were no ophthalmologic abnormalities on fundoscopy and ophthalmologic examination. After recovery of consciousness, cortical blindness was detected in both patients, and during gradual recovery period, visual function was slowly recovered. The pattern of visual evoked potential [VEP] at 7 weeks and 12 weeks after herniation was normalized gradually. Cortical blindness due to herniation was reversible, even though the high signals of bilateral visual cortex still existed on MRI 16 month later in case 2.

• Proceedings of the Ginseng society Conference
• /
• 2004.12a
• /
• pp.53-53
• /
• 2004

• Journal of the Institute of Convergence Signal Processing
• /
• v.8 no.4
• /
• pp.227-236
• /
• 2007

Ubiquitous systems have grown explosively over the few years. Nowadays users' needs for high qualify service lead a various type of user terminals. One of various type of user interface, various types of effective human computer interface methods have been developed. In many researches, researchers have focused on using brain-wave interface, that is to say, BCI. Nowadays, researches which are related to BCI are under way to find out effective methods. But, most researches which are related to BCI are not centralized and not systematic. These problems brought about ineffective results of researches. In most researches related in HCI, that is to say - pattern recognition, the most important foundation of the research is to build correct and sufficient DB. But there is no effective and reliable standard research conditions when researchers are gathering brain-wave in BCI. Subjects as well as researchers do not know effective methods for gathering DB. Researchers do not know how to instruct subjects and subjects also do not know how to follow researchers' instruction. To solve these kinds of problems, we propose effective brain-wave DB building system using the five senses stimulation. Researcher instructs the subject to use the five senses. Subjects imagine the instructed senses. It is also possible for researchers to distinguish whether brain-wave is right or not. In real time, researches verify gathered brain-wane data using spectrogram. To verify effectiveness of our proposed system, we analyze the spectrogram of gathered brain-wave DB and pattern. On the basis of spectrogram and pattern analysis, we propose an effective brain-wave DB building method using the five senses stimulation.

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