• Investigative Magnetic Resonance Imaging
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• 제15권2호
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• pp.110-122
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• 2011

목적 : 본 연구의 목적은 확산텐서영상에 기반하여 한국 아동 집단의 해부학적 뇌연결성 지도를 확립하고 뇌신경망의 효율성을 평가하는 기법을 개발하는 것이다. 대상 및 방법 : 건강한 아동 12명에서 얻은 확산텐서영상과 뇌구획영상을 바탕으로 구조 연결 행렬을 구하여 집단의 구조 연결성을 평가하였다. 일표본 t-검정을 시행하여 평균적인 구조 연결성을 파악하였고 이 때 얻은 각 피험자의 백질 다발을 표준공간으로 정규화하여 집단의 해부학적 뇌연결망 지도를 확립했다. 뇌신경망의 군집정도(clustering coefficient), 평균이동거리(characteristic path length), 전체/부분 연결망 효율성(global/local efficiency) 등 연결망 속성을 계산한 후 시각화 하였다. 결과 : 연결망 측면에서 한국 아동 집단의 뇌연결성이 작은세상속성을 가짐을 밝혔다. 또한 해부학적 뇌연결망 지도를 얻었는데 대뇌 반구 내의 연결성이 높게 나타남과 뇌간과 운동/감각 영역간에 많은 신경 연결이 집중되어 있음을 확인하였다. 결론 : 한국 아동 집단의 해부학적 뇌연결망 지도를 작성하는 방법론을 제시하여 뇌를 연결성 측면에서 이해하고 발달 장애와 성인 뇌신경망의 효율성을 평가할 수 있는 기본 도구를 확립하게되었다.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.561-575
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• 2023

Brain network analysis has attracted the interest of neuroscience researchers in studying brain diseases. Magnetoencephalography (MEG) is especially proper for analyzing functional connectivity due to high temporal and spatial resolution. The application of graph theory for functional connectivity analysis has been studied widely, but research on network modeling for MEG still needs more. Temporal exponential random graph model (TERGM) considers temporal dependencies of networks. We performed the brain network analysis, including static/temporal network statistics, on two groups of epilepsy patients who removed the left (LT) or right (RT) part of the brain and healthy controls. We investigate network differences using Multiset canonical correlation analysis (MCCA) and TERGM between epilepsy patients and healthy controls (HC). The brain network of healthy controls had fewer temporal changes than patient groups. As a result of TERGM, on the simulation networks, LT and RT had less stable state than HC in the network connectivity structure. HC had a stable state of the brain network.

• 생물정신의학
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• 제20권4호
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• pp.136-143
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• 2013

Objectives We reviewed cellular and synaptic dysconnectivity, disturbances in micro- and macro- circuitries, and neurodevelopmentally-derived disruptions of neural connectivity in the pathogenesis of schizophrenia. Method We reviewed the selected articles about disturbances in neural circuits which had been proposed as a pathogenetic mechanism of schizophrenia. Results The literature review reveals that schizophrenia may be a disease related to disturbance in neurodevelopmental mechanism, shown as 'a misconnection syndrome of neural circuit or neural network'. In descriptive psychopathological view, definition of a disorder of brain connectivity has limitation to explain other aspects of schizophrenia including deterministic strictness in thought process. Conclusion Schizophrenia is considered as a disorder of brain connectivity as well as a neurodevelopmental disorder related with genetic and environmental factors. We could make a suggestion that "JoHyeonByung (attunement disorder)" denotes the disturbances of psychic fine-tuning which correspond to the neural correlates of brain dysconnectivity metaphorically.

• Annals of Clinical Neurophysiology
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• 제22권2호
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• pp.82-91
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• 2020

Electroencephalography (EEG) produces time-series data of neural oscillations in the brain, and is one of the most commonly used methods for investigating both normal brain functions and brain disorders. Quantitative EEG analysis enables identification of frequencies and brain activity that are activated or impaired. With studies on the structural and functional networks of the brain, the concept of the brain as a complex network has been fundamental to understand normal brain functions and the pathophysiology of various neurological disorders. Functional connectivity is a measure of neural synchrony in the brain network that refers to the statistical interdependency between neural oscillations over time. In this review, we first discuss the basic methods of EEG analysis, including preprocessing, spectral analysis, and functional-connectivity and graph-theory measures. We then review previous EEG studies of brain network characterization in several neurological disorders, including epilepsy, Alzheimer's disease, dementia with Lewy bodies, and idiopathic rapid eye movement sleep behavior disorder. Identifying the EEG-based network characteristics might improve the understanding of disease processes and aid the development of novel therapeutic approaches for various neurological disorders.

• Communications for Statistical Applications and Methods
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• 제12권1호
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• pp.241-252
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• 2005

In this study we suggest that the spatial correlation structure of the brain fMRI data be used to characterize the functional connectivity of the brain. For some concussion and recovery data, we examine how the correlation structure changes from one step to another in the data analyses, which will allow us to see the effect of each analysis to the spatial correlation or the functional connectivity of the brain. This will lead us to spot the processes which cause significant changes in the spatial correlation structure of the brain. We discuss whether or not we can decompose correlation matrices in terms of its causes of variations in the data.

• Annals of Clinical Neurophysiology
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• 제23권2호
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• pp.69-81
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• 2021

Cortico-cortical evoked potential (CCEP) mapping is a rapidly developing method for visualizing the brain network and estimating cortical excitability. The CCEP comprises the early N1 component the occurs at 10-30 ms poststimulation, indicating anatomic connectivity, and the late N2 component that appears at < 200 ms poststimulation, suggesting long-lasting effective connectivity. A later component at 200-1,000 ms poststimulation can also appear as a delayed response in some studied areas. Such delayed responses occur in areas with changed excitability, such as an epileptogenic zone. CCEP mapping has been used to examine the brain connections causally in functional systems such as the language, auditory, and visual systems as well as in anatomic regions including the frontoparietal neocortices and hippocampal limbic areas. Task-based CCEPs can be used to measure behavior. In addition to evaluations of the brain connectome, single-pulse electrical stimulation (SPES) can reflect cortical excitability, and so it could be used to predict a seizure onset zone. CCEP brain mapping and SPES investigations could be applied both extraoperatively and intraoperatively. These underused electrophysiologic tools in basic and clinical neuroscience might be powerful methods for providing insight into measures of brain connectivity and dynamics. Analyses of CCEPs might enable us to identify causal relationships between brain areas during cortical processing, and to develop a new paradigm of effective therapeutic neuromodulation in the future.

• 한국멀티미디어학회논문지
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• 제24권5호
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• pp.684-694
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• 2021

Resting-state Functional Magnetic Resonance Imaging(fMRI) data detects the temporal correlations in Blood Oxygen Level Dependent(BOLD) signal and these temporal correlations are regarded to reflect intrinsic cortical connectivity, which is deactivated during attention demanding, non-self referential tasks, called Default Mode Network(DMN). The relationship between fMRI and anatomical connectivity has not been studied in detail, however, the preceded studies have tried to clarify this relationship using Diffusion Tensor Imaging(DTI) and fMRI. These studies use method that fMRI data assists DTI data or vice versa and it is used as guider to perform DTI tractography on the brain image. In this study, we hypothesized that functional connectivity in resting state would reflect anatomical connectivity of DMN and the combined images include information of fMRI and DTI showed visible connection between brain regions related in DMN. In the previous study, functional connectivity was determined by subjective region of interest method. However, in this study, functional connectivity was determined by objective and advanced method through Independent Component Analysis. There was a stronger connection between Posterior Congulate Cortex(PCC) and PHG(Parahippocampa Gyrus) than Anterior Cingulate Cortex(ACC) and PCC. This technique might be used in several clinical field and will be the basis for future studies related to aging and the brain diseases, which are needed to be translated not only functional connectivity, but structural connectivity.

• 한국과학교육학회지
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• 제29권3호
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• pp.348-358
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• 2009

The purpose of this study was to investigate brain activation pattern and functional connectivity network during experimental design on the biological phenomena. Twenty six right-handed healthy science teachers volunteered to be in the present study. To investigate participants' brain activities during the tasks, 3.0T fMRI system with the block experimental-design was used to measure BOLD signals of their brain and SPM2 software package was applied to analyze the acquired initial image data from the fMRI system. According to the analyzed data, superior, middle and inferior frontal gyrus, superior and inferior parietal lobule, fusiform gyrus, lingual gyrus, and bilateral cerebellum were significantly activated during participants' carrying-out experimental design. The network model was consisting of six nodes (ROIs) and its six connections. These results suggested the notion that the activation and connections of these regions mean that experimental design process couldn't succeed just a memory retrieval process. These results enable the scientific experimental design process to be examined from the cognitive neuroscience perspective, and may be used as a basis for developing a teaching-learning program for scientific experimental design such as brain-based science education curriculum.

• 한국과학교육학회지
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• 제29권7호
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• pp.751-758
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• 2009

The purpose of this study was to investigate brain activation pattern and functional connectivity network during classification on the biological phenomena. Twenty six right-handed healthy science teachers volunteered to be in the present study. To investigate participants' brain activities during the tasks, 3.0T fMRI system with the block experimental-design was used to measure BOLD signals of their brain. According to the analyzed data, superior, middle and inferior frontal gyrus, superior and inferior parietal lobule, fusiform gyrus, lingual gyrus, and bilateral cerebellum were significantly activated during participants' carrying-out classification. The network model was consisting of six nodes (ROIs) and its fourteen connections. These results suggested the notion that the activation and connections of these regions mean that classification is consist of two sub-network systems (top-down and bottom-up related) and it functioning reciprocally. These results enable the examination of the scientific classification process from the cognitive neuroscience perspective, and may be used as basic materials for developing a teaching-learning program for scientific classification such as brain-based science education curriculum in the science classrooms.

• 응용통계연구
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• 제29권6호
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• pp.1129-1145
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• 2016

뇌기능 연결성 문제는 뇌의 신경역학적 현상과 밀접한 관련이 있다는 의미에서 뇌과학에서 주요 연구주제이다. 본 논문에서는 기능적 자기공명영상(fMRI)자료를 뇌활동에 대한 반응 자료의 주요 형태로써 선택하였는데, 이 fMRI자료는 높은 해상도 때문에 뇌과학 연구에서 선호되는 자료 형태이다. 뇌활동에 대한 생리학적 반응을 측정해서 자료로 사용한다는 전제하에서 뇌의 기능적 연결성을 분석하는 방법들을 고찰하였다. 여기서의 전제란 상태공간 및 측정 모형을 다룬다는것을 의미하는데, 여기서 상태공간 모형은 뇌신경역학을 표현한다고 가정한다. 뇌기능 영상자료의 분석은 무엇을 측정하였느냐에 따라서 분석방법과 그 해석이 조금씩 달라진다. 실제 fMRI자료를 고차원 자기회귀모형을 적용해서 분석한 결과를 논문에 포함하였는데, 이 결과를 통해서 서로 다른 도형문제를 푸는데 서로 다른 뇌신경 역학관계가 요구된다는 것을 엿볼 수 있었다.