• Korean Journal of Adult Nursing
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• v.19 no.1
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• pp.78-88
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• 2007

Purpose: The purpose of this study was to find out the degree of cognitive function among the elderly and to confirm its correlated factors. Methods: The subjects consisted of 392 elderly people over the age 65 who were living in Busan. Data were collected by the interview method, using a structured questionnaire and the K-MMSE scale. Results: The average points of the elderly's cognitive functions measured by K-MMSE were 23.76(${\pm}4.02$). With the cut-off point for cognitive impairment set as 24 points below using K-MMSE scale, 38.8% of the subjects have cognitive impairments. Among the variables related to cognitive functions, literacy showed the highest correlation with cognitive function(${\beta}=.330$, t=7.249, p<.001), followed in order by educational level, age, depression level, attendance of elderly's college, and religious activity. The total explanatory power of these variables is 36%. Conclusion: In order to prevent cognitive impairment among the elderly, elderly people have to maintain social relationships continuously, and expand the social network by participating in the related programs. Some efforts to prevent the occurrence of depression and to stimulate patients' brain activity need to be recommended.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.496-496
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• 2000

We propose a neuron computer for tracking motion of particles in multi-dimensional space. The neuron computer is constructed of neural networks and their connections, which is a simplified model of the brain. The neuron computer is assemblage of neural networks, it includes a control unit, and the actions of the unit are represented by instructions. We designed a neuron computer to recognize and predict motion of particles. The recognition unit is constructed of neuron-array, encoder, and control part. The neuron-array is a model of the retina, and particles crease an image on the array, where the image is binary. The encoder picks one particle from the array, and translates the particle's location to Cartesian coordinates, which is scaled in [0, 1] intervals. Next, the encoder picks another particle, and does same process. The ordering and reduction of complex processes are executed by instructions. The instructions are held in the control part. The prediction unit is constructed of a multi-layer neural network and a feedback loop, where real time learning is executed. The particles' future locations are forecasted by coordinate values. The neuron computer can chase maximum 100 particles that take evasions.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.414-416
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• 2012

고차 주성분 방법으로는 텐서 분석이 있었다. Electroencephalography(EEG) 데이터나 Social Network 데이터에 텐서 분석이 적용되어 주요한 성분들을 찾는 연구들이 있었다. 그러나 텐서 분석은 직관적으로 이해하기에 어려움이 있으며 중요한 노드를 찾는데에는 다소 어려움이 있다. 본 논문에서는 고차 하이퍼에지로 이차원 행렬을 만들고 주성분분석법을 이용하여 중요한 노드를 찾는 새로운 방법론을 제시한다. 데이터로는 Multimodal Memory Game(MMG) 수행시 촬영한 EEG 데이터를 사용하였다. MMG는 TV 드라마 기반의 기억인출게임이다. 베타파의 Power Spectrum Density(PSD)는 각 위치의 채널들의 활성도를 나타내는 지표이다. 우리는 Random Sampling을 바탕으로 PSD 상위 50%의 채널들간의 전이행렬을 구하였다. 그 후 고유치와 고유벡터를 구하였다. 가장 큰 고유치의 고유벡터는 주성분을 나타내며 고유벡터의 각 원소들은 중요도를 나타내는 centrality 이다. 세 명의 피험자에 대한 centrality 상위 30개의 중요한 채널들을 구하였고 세명에 공통적으로 포함되는 채널을 확인하였다.

• Annals of Clinical Neurophysiology
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• v.1 no.2
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• pp.147-153
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• 1999

Hippocampal slice models can be a powerful tool to study the mechanism of partial epilepsy. Despite the loss of connection with the rest of the brain, in vitro hippocampal slice preparations allow detailed physiological and pharmacological studies, which would be impossible, in vivo. There are several methods to induce electrographic seizures on hippocampal slice models. Those are electrical pulse train stimulation, 0 $Mg^{2+}$ artificial cerebrational fluid and high concentration of extracelluar $K^+$ on bath. Among them, the electrically triggered seizure may mimic the physiological communication between neuronal populations without any deterioration of normal physiologic and chemical status of the hippocampal slice models. Presumably, such communication from hyperexcitable areas to other neuronal populations is involved in the development of epilepsy. Electrographic seizures in hippocampal slice models occur in the network of neurons that are involved in epileptic seizures in the hippocampus in vivo. Because these models have many advantages and are very valuable to research of epileptogenesis on partial epilepsy, I would like to introduce the electrophysiological methods to induce electrographic seizure or epilepsy on hippocampal slice models briefly in this paper.

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.27-35
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• 2009

Recently, an interest in mobile games is increasing according to the extension of the high speed network infra and the development of mobile devices. In the paper, we propose a mobile Stouku game which trains a brain. The proposed game is user-oriented play style that the game users can raise their characters theirselves. It gives users a sense of achievement and can also help improve intelligence by becoming familiar with a numeral. The game raises an awareness and immersion by adding various events and lowering the degree of difficulty more than previews games. In the paper, we demonstrate the proposed Sudoku game in the mobile device and present the result.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.31 no.3
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• pp.105-120
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• 2020

Although autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social impairments, patients with ASD frequently manifest atypical sensory behaviors. Recently, atypical sensory perception in ASD has received much attention, yet little is known about its cause or neurobiology. Herein, we review the findings from neuroimaging studies related to visual perception in ASD. Specifically, we examined the neural underpinnings of visual detection, motion perception, and face processing in ASD. Results from neuroimaging studies indicate that atypical visual perception in ASD may be influenced by attention or higher order cognitive mechanisms, and atypical face perception may be affected by disrupted social brain network. However, there is considerable evidence for atypical early visual processing in ASD. It is likely that visual perceptual abnormalities are independent of deficits of social functions or cognition. Importantly, atypical visual perception in ASD may enhance difficulties in dealing with complex and subtle social stimuli, or improve outstanding abilities in certain fields in individuals with Savant syndrome. Thus, future research is required to elucidate the characteristics and neurobiology of autistic visual perception to effectively apply these findings in the interventions of ASD.

• Smart Structures and Systems
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• v.14 no.2
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• pp.159-189
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• 2014

One of the most important requirements in the evaluation of existing structural systems and ensuring a safe performance during their service life is damage assessment. Damage can be defined as a weakening of the structure that adversely affects its current or future performance which may cause undesirable displacements, stresses or vibrations to the structure. The mass and stiffness of a structure will change due to the damage, which in turn changes the measured dynamic response of the system. Damage detection can increase safety, reduce maintenance costs and increase serviceability of the structures. Artificial Neural Networks (ANNs) are simplified models of the human brain and evolved as one of the most useful mathematical concepts used in almost all branches of science and engineering. ANNs have been applied increasingly due to its powerful computational and excellent pattern recognition ability for detecting damage in structural engineering. This paper presents and reviews the technical literature for past two decades on structural damage detection using ANNs with modal parameters such as natural frequencies and mode shapes as inputs.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.353-358
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• 2021

Parkinson's disease is the second most common degenerative brain disease after Alzheimer's in old age. Symptoms of Parkinson's disease are factors that reduce the quality of life in daily life, such as shaking hands, slowing behavior and cognitive function. Parkinson's disease that can slow the progression of the disease through early diagnosis. To diagnoze Parkinson's disease early, an algorithm was implemented to extract features using wav2vec and to diagnose the presence or absence of Parkinson's disease with deep learning(ANN). As a results of the experiment, the accuracy was 97.47%. It was better than the results of diagnosing Parkinson's disease using the existing neural network. The audio voice file could simply reduce the experiment process and obtain improved results.

• Journal of Korean Neurosurgical Society
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• v.62 no.3
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• pp.361-365
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• 2019

Epilepsy has been known to humankind since antiquity. The surgical treatment of epilepsy began in the early days of neurosurgery and has developed greatly. Many surgical procedures have stood the test of time. However, clinicians treating epilepsy patients are now witnessing a huge tide of change. In 2017, the classification system for seizure and epilepsy types was revised nearly 36 years after the previous scheme was released. The actual difference between these systems may not be large, but there have been many conceptual changes, and clinicians must bid farewell to old terminology. Paradigms in drug discovery are changing, and novel anti-seizure drugs have been introduced for clinical use. In particular, drugs that target genetic changes harbor greater therapeutic potential than previous screening-based compounds. The concept of focal epilepsy has been challenged, and now epilepsy is regarded as a network disorder. With this novel concept, stereotactic electroencephalography (SEEG) is becoming increasingly popular for the evaluation of dysfunctioning neuronal networks. Minimally invasive ablative therapies using SEEG electrodes and neuromodulatory therapies such as deep brain stimulation and vagus nerve stimulation are widely applied to remedy dysfunctional epilepsy networks. The use of responsive neurostimulation is currently off-label in children with intractable epilepsy.

• Journal of Animal Reproduction and Biotechnology
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• v.37 no.3
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• pp.176-182
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• 2022

Norflurazon is widely used on agricultural lands and has a high potential to pollute water sources. However, its effects on fish have not been fully elucidated. The purpose of our study was to determine whether norflurazon adversely affects the developmental stage of zebrafish, which are frequently used as a model system to evaluate the environmental impact of pollutants. Norflurazon interfered with the hatching of zebrafish embryos and induced several sublethal deformities including body length reduction, increased yolk sac volume, and enlargement of the pericardial region. We further examined the cardiotoxicity of norflurazon in the flk1:eGFP transgenic zebrafish line. The vascular network, mainly in the brain region, was significantly disrupted in norflurazon-exposed zebrafish. In addition, due to the failure of cardiac looping, norflurazon-exposed zebrafish had an abnormal cardiac structure. These developmental abnormalities were related to the apoptotic process triggered by norflurazon. Overall, the present study demonstrated the non-target toxicity of norflurazon by analyzing the hazardous effects of norflurazon on developing zebrafish.