• Journal of Digital Convergence
• /
• v.13 no.6
• /
• pp.177-184
• /
• 2015

Brain-computer interface is (BCI) is a communication device that the brain activity is directly input to the computer without input devices, such as a mouse or keyboard. As the brain wave interface hardware technology evolves, expensive and large EEG equipment has been downsized cheaply. So it will be applied to various multimedia applications. Among BCI studies, we suggest the domestic and foreign research trend about how the BCI is applied about the game almost people use. Next, look at the problems of the game with the BCI, we would like to propose the future direction of domestic BMI research and development.

• Korean Journal of Veterinary Research
• /
• v.17 no.2
• /
• pp.51-61
• /
• 1977

The smears and tissue sections of organs (liver, lung, kidney, heart, lymph-node, brain) were carried out to compare the detection of parasites in the splenectomized calves artificially infected with B. bigemina and B. argentina, respectively. The results obtained from this experiment were abstracted as follows: 1. In the calves infected with B. argentina the parasites were easily detected by the blood smears and tissue smears but, particularly, the detection of parasites in the kidneys and brain by tissue smears and tissue sections was greater useful. In this experiment, the packing of the parasite-infected red blood cells was found in the capillary vessels of the organs. 2. When the fresh infected-brain was kept at $5^{\circ}C$ refrigerator, Babesia argentina could be detected during 9 days from the brain smears. According to this results, we could do differentiate the parasites from the brain of the dead animal by the doubtful babesiosis in the field. 3. If we use the brain smears and brain sections in order to survey or detect Babesia infections of cattle in Korea, these methods could be worthwhile for the differential diagnosis of B. argentina and B. bigemina.

• BMB Reports
• /
• v.36 no.2
• /
• pp.154-158
• /
• 2003

Collagen is a family of proteins which consists of several genetically distinct molecular species and is intimately involved in tissue organization, function, differentiation and development. The purpose of this study was to investigate the concentration of different hydroxyproline (Hyp) fractions viz., total, free, peptide-bound, protein-bound, soluble- and insoluble-collagen hydroxyproline (Hyp) in various bovine tissues. Results showed that liver had the highest concentration of free Hyp followed by kidney, brain, spleen, lungs, muscle and heart. Liver also had the highest concentration of peptide-bound collagen Hyp followed by kidney, heart, spleen, lungs, brain and muscle. The concentration of protein-bound collagen Hyp was highest in the liver, followed by kidney, spleen, lungs, muscle, brain and heart. Total Hyp was highest in the liver, followed by kidney, spleen, brain, heart, muscle and lungs. Liver also had significantly high concentration of collagen as compared to other tissues examined (P<0.001). Spleen had the significantly higher concentration of soluble-collagen Hyp when compared to other tissues (P<0.001). This was followed by heart, muscle, lungs, brain, kidney and liver. Heart had the highest concentration of insoluble-collagen Hyp followed by lungs, kidney, liver, muscle, spleen and brain. The variation among the insoluble-collagen Hyp concentration of heart and muscle, spleen and brain was significant (P<0.001). We speculate that these differences could be due to the variation in turn over of rate of collagen metabolism in this species.

• Molecules and Cells
• /
• v.41 no.10
• /
• pp.881-888
• /
• 2018

During the cortical development, cells in the brain acquire somatic mutations that can be implicated in various neurodevelopmental disorders. There is increasing evidence that brain somatic mutations lead to sporadic form of epileptic disorders with previously unknown etiology. In particular, malformation of cortical developments (MCD), ganglioglioma (GG) associated with intractable epilepsy and non-lesional focal epilepsy (NLFE) are known to be attributable to brain somatic mutations in mTOR pathway genes and others. In order to identify such somatic mutations presenting as low-level in epileptic brain tissues, the mutated cells should be enriched and sequenced with high-depth coverage. Nevertheless, there are a lot of technical limitations to accurately detect low-level of somatic mutations. Also, it is important to validate whether identified somatic mutations are truly causative for epileptic seizures or not. Furthermore, it will be necessary to understand the molecular mechanism of how brain somatic mutations disturb neuronal circuitry since epilepsy is a typical example of neural network disorder. In this review, we overview current genetic techniques and experimental tools in neuroscience that can address the existence and significance of brain somatic mutations in epileptic disorders as well as their effect on neuronal circuitry.

• Interdisciplinary Bio Central
• /
• v.4 no.3
• /
• pp.7.1-7.8
• /
• 2012

With the development of many methods of studying the brain, the field of neuroscience has generated large amounts of information obtained from various techniques: imaging techniques, electrophysiological techniques, techniques for analyzing brain connectivity, techniques for getting molecular information of the brain, etc. A plenty of neuroinformatics databases have been made for storing and sharing this useful information and those databases can be publicly accessed by researchers as needed. However, since there are too many neuroinformatics databases, it is difficult to find the appropriate database depending on the needs of researcher. Moreover, many researchers in neuroscience fields are unfamiliar with using neuroinformatics databases for their studies because data is too diverse for neuroscientists to handle this and there is little precedent for using neuroinformatics databases for their research. Therefore, in this article, we review databases in the field of neuroscience according to both their methods for obtaining data and their objectives to help researchers to use databases properly. We also introduce major neuroinformatics databases for each type of information. In addition, to show examples of novel uses of neuroinformatics databases, we represent several studies that combine neuroinformatics databases of different information types and discover new findings. Finally, we conclude our paper with the discussion of potential applications of neuroinformatics databases.

• Progress in Superconductivity
• /
• v.13 no.1
• /
• pp.18-23
• /
• 2011

We developed a four-channel first order gradiometer system to measure magnetoencephalogram for mice. We used double relaxation oscillation SQUID (DROS). The diameter of the pickup coil is 4 mm and the distance between the coils is 5 mm. Coil distance was designed to have good spatial resolution for a small mouse brain. We evaluated the current dipole localization confidence region for a mouse brain, using the spherical conductor model. The white noise of the measurement system was about 30 fT/$Hz^{1/2}$/cm when measured in a magnetically shielded room. We measured magnetic signal from a phantom having the same size of a mouse brain, which was filled with 0.9% saline solution. The results suggest that the developed system has a feasibility to study the functions of brain of small animals.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.3
• /
• pp.541-550
• /
• 2009

This research attempted to find out any implications for strategies to design and develop the connections between the activities of the brain function and the fields of English learning (dictation, word level, speaking, word memory, listening). Thus, in developing the brain based learning model for the English education, attempts need to be made to help learners to keep the whole brain toward learning. On this point, this study indicated the significant results for the exclusive brain location and the brainwaves on the each English learning field by the quantitative EEG analysis. The results of this study presented the guidelines for the balanced development of the left brain and the right brain to train the specific site of the brain connected to the English learning fields. In addition, whole brain training model is developed by the quantitative EEG data not by the theoretical learning methods focused on the right brain training.

• Dementia and Neurocognitive Disorders
• /
• v.21 no.4
• /
• pp.138-146
• /
• 2022

Background and Purpose: Magnetic resonance imaging (MRI) helps with brain development analysis and disease diagnosis. Brain volumes measured from different ages using MRI provides useful information in clinical evaluation and research. Therefore, we trained machine learning models that predict the brain age gap of healthy subjects in the East Asian population using T1 brain MRI volume images. Methods: In total, 154 T1-weighted MRIs of healthy subjects (55-83 years of age) were collected from an East Asian community. The information of age, gender, and education level was collected for each participant. The MRIs of the participants were preprocessed using FreeSurfer(https://surfer.nmr.mgh.harvard.edu/) to collect the brain volume data. We trained the models using different supervised machine learning regression algorithms from the scikit-learn (https://scikit-learn.org/) library. Results: The trained models comprised 19 features that had been reduced from 55 brain volume labels. The algorithm BayesianRidge (BR) achieved a mean absolute error (MAE) and r squared (R²) of 3 and 0.3 years, respectively, in predicting the age of the new subjects compared to other regression methods. The results of feature importance analysis showed that the right pallidum, white matter hypointensities on T1-MRI scans, and left hippocampus comprise some of the essential features in predicting brain age. Conclusions: The MAE and R² accuracies of the BR model predicting brain age gap in the East Asian population showed that the model could reduce the dimensionality of neuroimaging data to provide a meaningful biomarker for individual brain aging.

• Proceedings of the Korean Society of Toxicology Conference
• /
• 2001.05a
• /
• pp.123-123
• /
• 2001

The distribution of necrotic and apoptotic neural cells, and expression of astrocytic glial fibrillary acidic protein (GFAP) in the brain of rats poisoned intraperitoneally with diisopropylfluorophosphate were investigated. Pyridostigmine bromide (0.1 mg/kg) and atropine methylnitrate (20 mg/kg), which are centrally inactive, were treated intramuscularly 30 min and 10 min, respectively, before diisopropylfluorophosphate (4 - 10 mg/kg) poisoning to reduce the mortality.(omitted)

• Journal of Korean Neurosurgical Society
• /
• v.61 no.3
• /
• pp.343-351
• /
• 2018

Diffuse intrinsic pontine glioma (DIPG) is a deadly paediatric brain cancer. Transient response to radiation, ineffective chemotherapeutic agents and aggressive biology result in rapid progression of symptoms and a dismal prognosis. Increased availability of tumour tissue has enabled the identification of histone gene aberrations, genetic driver mutations and methylation changes, which have resulted in molecular and phenotypic subgrouping. However, many of the underlying mechanisms of DIPG oncogenesis remain unexplained. It is hoped that more representative in vitro and preclinical models-using both xenografted material and genetically engineered mice-will enable the development of novel chemotherapeutic agents and strategies for targeted drug delivery. This review provides a clinical overview of DIPG, the barriers to progress in developing effective treatment, updates on drug development and preclinical models, and an introduction to new technologies aimed at enhancing drug delivery.