• Journal of Yeungnam Medical Science
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• v.35 no.2
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• pp.192-198
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• 2018

Background: Chronic inflammation can lower the seizure threshold and have influence on epileptogenesis. The components of red ginseng (RG) have anti-inflammatory effects. The abundance of peripherally derived immune cells in resected epileptic tissue suggests that the immune system is a potential target for anti-epileptogenic therapies. The present study used continuous electroencephalography (EEG) to evaluate the therapeutic efficacy of RG in intrahippocampal kainic acid (IHKA) animal model of temporal lobe epilepsy. Methods: Prolonged status epilepticus (SE) was induced in 7-week-old C57BL/6J mice via stereotaxic injection of kainic acid (KA, 150 nL; 1 mg/mL) into the right CA3/dorsal hippocampus. The animals were implanted electrodes and monitored for spontaneous seizures. Following the IHKA injections, one group received treatments of RG (250 mg/kg/day) for 4 weeks (RG group, n=7) while another group received valproic acid (VPA, 30 mg/kg/day) (VPA group, n=7). Laboratory findings and pathological results were assessed at D29 and continuous (24 h/week) EEG monitoring was used to evaluate high-voltage sharp waves on D7, D14, D21, and D28. Results: At D29, there were no differences between the groups in liver function test but RG group had higher blood urea nitrogen levels. Immunohistochemistry analyses revealed that RG reduced the infiltration of immune cells into the brain and EEG analyses showed that it had anticonvulsant effects. Conclusion: Repeated treatments with RG after IHKA-induced SE decreased immune cell infiltration into the brain and resulted in a marked decrease in electrographic seizures. RG had anticonvulsant effects that were similar to those of VPA without serious side effects.

• Journal of Haehwa Medicine
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• v.22 no.2
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• pp.81-92
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• 2014

Objective : The purpose of this study was to assess the effects of Cyperus rotundus L. essential oil on relaxation in highly stressed volunteers with heart rate variability(HRV) and electroencephalography(EEG). Methods : 11 highly stressed volunteers participated in this study. The volunteers were examined with HRV and EEG before and after inhalation of Cyperus rotundus L. essential oil. Results : After smelling Cyperus rotundus L. essential oil, mean RR(mean of RR intervals) was incresed significantly(p<0.01), mean HRV(mean of heart rate), HF(high frequency) were decreased significantly(p<0.01). norm LF(low frequency), LF/HF ratio were decreased significantly(p<0.05), norm HF(normalized high frequency) was increased significantly(p<0.05) on HRV. After smelling Cyperus rotundus L. essential oil, relative ${\theta}$ power was decreased significantly(p<0.05) at P3(left parietal) and relative ${\alpha}$ power was increased significantly(p<0.05) at Fp1(left prefrontal), Fp2(right prefrontal) and relative ${\beta}$ power was decreased significantly(p<0.05) at Fp1(left prefrontal) and relative ${\gamma}$ power was decreased significantly(p<0.05) at Fp1(left prefrontal) on EEG. Conclusions : This results show that inhalation of Cyperus rotundus L. essential oil effects on relaxation and decreasing stress.

• Korean Journal of Veterinary Research
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• v.45 no.1
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• pp.131-137
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• 2005

To assess anesthetic depth using quantitative electroencephalography (q-EEG), we recorded processed EEG (raw EEG) till 100 minutes in beagle dogs anesthetized for 60 minutes with tiletamine/zolazepam (n=5, TZ group), xylazine/ketamine (n=5, XK group) and propofol (n=5, PI group) by intermittent bolus injection. Raw EEG was converted into 95% spectral edge frequency (SEF) and median frequency (MF) through fast fourier transformation (FFT) method. 95% SEF value of TZ group was significantly higher (p<0.05) than the XK group from 10 minutes to 100 minutes. 95% SEF value of PI group was significantly higher (p<0.05) than the XK group from 10 minutes to 40 minutes, and significantly low (p<0.05) than XK group at 90 and 100 minutes. MF was significantly higher (p<0.05) in TZ group from 60 minutes to 100 minutes. Based on these results, using dissociative agent with ${\alpha}_2$-adrenergic agent is more potent in CNS depressed than using dissociative agent alone, and low doses of propofol has a disinhibitory effect on CNS.

• Korean Journal of Biological Psychiatry
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• v.23 no.3
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• pp.102-107
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• 2016

This review will summarize EEG studies of learning and memory based on frequency bands including theta waves (4-7 Hz), gamma waves (> 30 Hz) and alpha waves (7-12 Hz). Authors searched and reviewed EEG papers especially focusing on learning and memory from PubMed. Theta waves are associated with acquisition of new information from stimuli. Gamma waves are connected with comparing and binding old information in preexisting memory and new information from stimuli. Alpha waves are linked with attention. Eventually it mediates the learning and memory process. Although EEG studies of learning and memory still have controversial issues, the future EEG studies will facilitate clinical benefits by virtue of more developed and encouraging prospects.

• Annals of Clinical Neurophysiology
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• v.4 no.1
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• pp.21-27
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• 2002

Background : Spatial analysis of EEG is a phenomenal assessment and not so informative for phase space and dynamic aspect of EEG data. In contrast, nonlinear EEG analysis attempts to characterize the dynamics of neural networks in the brain. We have analyzed the features of EEG nonlinearly in subjects with white matter change on brain MRI and compared the results with cognitive function in each. Methods : Digital EEG data were taken for 30 seconds in 9 subjects with white matter degeneration and in 5 healthy normal controls without white matter change on MRI. Then we analyzed them nonlinearly to calculate the correlation dimension(D2) using the MATLAB software. The cognitive function was assessed by 3MS(modified mini-mental state examination). The severity of white matter change was assessed by Scheltens scale. Results : The mean D2 value of normal control was greater than that of white matter degeneration group. The D2s of some channels were correlative with 3MS and degree of white matter degeneration significantly. Conclusions : nonlinear analysis of EEG can be used as one of adjuvant functional studies for prediction of cognitive impairment in subjects with white matter degeneration and subcortical white matter change can be influential on cognitive function and correlation dimension of EEG.

• Journal of Chest Surgery
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• v.34 no.6
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• pp.465-471
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• 2001

Background: Hypothermia protects the brain by suppressing the cerebral metabolism and it is performed well enough before the total circulatory arrest(TCA) in the operation of aortic disease. Generally, TCA has been performed depending on the rectal or nasopharyngeal temperatures; however, there is no definite range of optimal temperature for TCA or an objective indicator determining the temperature for safe TCA. In this study, we tried to determine the optimal range of temperature for safe hypothermic circulatory arrest by using the intraoperative electroencephalogram(EEG), and studied the role of EEG as an indicator of optimal hypothermia. Material and Method: Between March, 1999 and August 31, 2000, 27 patients underwent graft replacement of the part of thoracic aorta using hypothermia and TCA with intraoperative EEG. The rectal and nasopharyngeal temperatures were monitored continuously from the time of anesthetic induction and the EEG was recorded with a ten-channel portable electroencephalography from the time of anesthetic induction to electrocerebral silence(ECS). Result: On ECS, the rectal and nasopharyngeal temperatures were not consistent but variable(rectal 11$^{\circ}C$ -$25^{\circ}C$, nasopharynx 7.7$^{\circ}C$ -23$^{\circ}C$). The correlation between two temperatures was not significant(p=0.171). The cooling time from the start of cardiopulmonary bypass to ECS was also variable(25-127min), but correlated with the body surface area(p=0.027). Conclusion: We have found that ECS appeared at various body temperatures, and thus, the use of rectal or nasopharyngeal temperature were not useful in identifying ECS. Conclusively, we can not fully assure cerebral protection during hypothermic circulatory arrest in regards to the body temperatures, and therefore, the intraoperative EEG is one of the necessary methods for determining the range of optimal hypothermia for safe circulatory arrest. :

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.197-206
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• 2014

Motor imagery based Brain-computer Interface(BCI), which has recently attracted attention, is the technique for decoding the user's voluntary motor intention using Electroencephalography(EEG). For classifying the motor imagery, event-related desynchronization(ERD), which is the phenomenon of EEG voltage drop at sensorimotor area in ${\mu}$-band(8-13Hz), has been generally used but this method are not free from the performance degradation of the BCI system because EEG has low spatial resolution and shows different ERD-appearing band according to users. Common spatial pattern(CSP) was proposed to solve the low spatial resolution problem but it has a disadvantage of being very sensitive to frequency-band selection. Discriminative filter bank common spatial pattern(DFBCSP) tried to solve the frequency-band selection problem by using the Fisher ratio of the averaged EEG signal power and establishing discriminative filter bank(DFB) which only includes the feature frequency-band. However, we found that DFB might not include the proper filters showing the spatial pattern of ERD. To solve this problem, we apply a band-selection process using CSP feature vectors and linear discriminant analysis to DFBCSP instead of the averaged EEG signal power. The filter selection results and the classification accuracies of the existing and the proposed methods show that the CSP feature is more effective than signal power feature.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.3
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• pp.191-199
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• 2008

This paper proposes a new method for the inverse problem of the three-dimensional reconstruction of the electrical activity of the brain from electroencephalography (EEG). Compared to conventional direct methods using additional parameters, the proposed approach solves the EEG inverse problem iteratively without any parameter. We describe the Lagrangian corresponding to the minimization problem and suggest the numerical inverse algorithm. The restriction of influence space and the lead field matrix reduce the computational cost in this approach. The reconstructed divergence of primary current converges to a reasonable distribution for three dimensional sphere head model.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.59-66
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• 2024

Measurable electrophysiological changes in the scalp are frequently linked to brain activities. These progressions are called related evoked potentials (ERP), which are transient electrical responses recorded by electroencephalography (EEG) in light of tactile, mental, or motor enhancements. This painless strategy is gradually being used as a conclusion and clinical help. In this article, we will talk about the main ways to monitor brain activities in people with neurological diseases like Alzheimer's disease by analyzing EEG signals using ERP. We will also talk about how this method helps to detect the disease at an early stage.

• Korean Journal of Applied Biomechanics
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• v.34 no.2
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• pp.71-80
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• 2024

Objective: This study aimed to explore the brain connectivity between brain and biomechanical variables by exploring motion recognition through FFT (fast fourier transform) analysis and AI (artificial intelligence) focusing on quiet standing movement patterns. Method: Participants included 12 young adult males, comprising university students (n=6) and elite gymnasts (n=6). The first experiment involved FFT of biomechanical signals (f_CoP, f_AJtorque and f_EEG), and the second experiment explored the optimization of AI-based GRU (gated recurrent unit) using f_EEG data. Results: Significant differences (p<.05) were observed in frequency bands and maximum power based on group and posture types in the first experiment. The second study improved motion prediction accuracy through GRU performance metrics derived from brain signals. Conclusion: This study delved into the movement pattern of upright standing posture through the analysis of bio-signals linking the cerebral cortex to motor performance, culminating in the attainment of motion recognition prediction performance.