• Anxiety and mood
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• v.10 no.1
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• pp.44-51
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• 2014

Objective : The amygdala has been considered to be a critical region in the pathophysiology of social anxiety disorder, but subregional connectivity pattern has not been examined yet despite lots of previous functional neuroimaging studies. Methods : Resting-state functional magnetic resonance imaging data was obtained in 19 patients with social anxiety disorder and 20 normal controls, and default mode functional connectivity with each of basolateral, centromedial and superficial areas of the amygdala was measured and compared between the two groups. Results : Differential amygdala-based networks between the two groups were distributed to all over the brain. In particular, however, a bias on the amygdala-cingulate pathway was observed in the superficial amygdala only. Connectivity strengths between the superficial amygdala and perigenual anterior cingulate cortex were correlated with scores of social interaction and avoidance. Conclusion : Our findings provide new insights into understanding of the intrinsic cognitive bias model of social anxiety disorder. An abnormality in superficial amygdala-anterior cingulate connectivity may influence on cognitive processing of socially-relevant information in social anxiety disorder.

• Korean Institute of Interior Design Journal
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• v.20 no.2
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• pp.120-130
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• 2011

The purpose of this study is to propose cognitive ecological effects of fractal patterns in space design. This study investigated the perception and cognition problems regarding landscape patterns showing fractal properties from the cognitive perspective instead of the traditional speculative approach. In particular, the researcher has verified that fractal geometry theory and fractal pattern concept provide insight in space aesthetic values and cognitive effects. Research results are as follows. First, most environmentally-friendly fractal urban forms provide cognitive connectivity. In particular, this space provides a positive emotional response and preference to humans and displays self-organized complexity. This study found that such complexity of space form has characteristics corresponding to parallel cognitive structures of the human brain. Simultaneously, the researcher suggests that the fractal landscape pattern is an alternative for stiff and homogenized modern space. Second, fractal patterns provide hierarchical connectivity within the brain through continuous difference and repetition. In particular, self-similarities of fractal patterns administer significant visual grouping and coherence in human perception. It can be determined whether scaling coherence facilitates easier organization in cognitive organization. Third, fractal patterns in space design provide the basic method for achieving the connection between concept, construction, and urban factors. As a result, the researcher has suggested that scale distribution of geometrical factors, such as fractal patterns, an be a design method to connect various space typologies.

• Molecules and Cells
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• v.40 no.6
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• pp.379-385
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• 2017

Drug addiction is a severe psychiatric disorder characterized by the compulsive pursuit of drugs of abuse despite potential adverse consequences. Although several decades of studies have revealed that psychostimulant use can result in extensive alterations of neural circuits and physiology, no effective therapeutic strategies or medicines for drug addiction currently exist. Changes in neuronal connectivity and regulation occurring after repeated drug exposure contribute to addiction-like behaviors in animal models. Among the involved brain areas, including those of the reward system, the striatum is the major area of convergence for glutamate, GABA, and dopamine transmission, and this brain region potentially determines stereotyped behaviors. Although the physiological consequences of striatal neurons after drug exposure have been relatively well documented, it remains to be clarified how changes in striatal connectivity underlie and modulate the expression of addiction-like behaviors. Understanding how striatal circuits contribute to addiction-like behaviors may lead to the development of strategies that successfully attenuate drug-induced behavioral changes. In this review, we summarize the results of recent studies that have examined striatal circuitry and pathway-specific alterations leading to addiction-like behaviors to provide an updated framework for future investigations.

• Korean Journal of Biological Psychiatry
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• v.25 no.1
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• pp.1-8
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• 2018

Insomnia is a common sleep-related symptom which occurs in many populations, however, the neural mechanism underlying insomnia is not yet known. The hyperarousal model explains the neural mechanism of insomnia to some extent, and the frontal cortex dysfunction has been known to be related to primary insomnia. In this review, we discuss studies that applied resting state and/or task-related functional magnetic resonance imaging to demonstrate the deficits/dysfunctions of functional activation and network in primary insomnia. Empirical evidence of the hyperarousal model and proposed relation between the frontal cortex and other brain regions in primary insomnia are examined. Reviewing these studies could provide critical insights regarding the pathophysiology, brain network and cerebral activation in insomnia and the development of novel methodologies for the diagnosis and treatment of insomnia.

• Anxiety and mood
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• v.14 no.2
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• pp.63-70
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• 2018

It has been suggested that aberrant self-referential processing (SRP) is one of the important components of the explanatory models of social anxiety disorder (SAD). The default mode network (DMN), which reflects intrinsic brain functions, is known to play a critical role in SRP. Recently, resting state functional magnetic resonance imaging (fMRI) research on the functional connectivity in the brain network has gained greater attention as a tool to elucidate the neurobiological basis of various psychiatric disorders. We reviewed resting state fMRI studies that investigated the resting state functional connectivity (RSFC) of the DMN in SAD. Despite of the heterogeneity of the analytic methods and occasional negative findings, most studies consistently reported abnormalities of RSFC within the DMN, suggesting that the DMN may be significant neural correlates of aberrant SRP in SAD. Also, changes in RSFC of the DMN are associated with clinical improvements of therapeutic interventions. Moreover, emerging findings provide the basis for potential use of RSFC as a complementary method in diagnosis of SAD. Ongoing and future research to investigate RSFC of the DMN could broaden our understanding regarding the neurobiological basis of SAD, and contribute to the development of novel treatments for SAD.

• Applied Microscopy
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• v.46 no.2
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• pp.100-104
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• 2016

Electron microscopy is currently the only available technique with a spatial resolution sufficient to identify fine neuronal processes and synaptic structures in densely packed neuropil. For large-scale volume reconstruction of neuronal connectivity, serial block-face scanning electron microscopy allows us to acquire thousands of serial images in an automated fashion and reconstruct neural circuits faster by reducing the alignment task. Here we introduce the whole reconstruction procedure of synaptic network in the rat hippocampal CA1 area and discuss technical issues to be resolved for improving image quality and segmentation. Compared to the serial section transmission electron microscopy, serial block-face scanning electron microscopy produced much reliable three-dimensional data sets and accelerated reconstruction by reducing the need of alignment and distortion adjustment. This approach will generate invaluable information on organizational features of our connectomes as well as diverse neurological disorders caused by synaptic impairments.

• 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.

• Korean Journal of Biological Psychiatry
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• v.22 no.3
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• pp.101-108
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• 2015

Recent breakthroughs in functional neuroimaging techniques have launched the quest of mapping the connections of the human brain, otherwise known as the human connectome. Imaging connectomics is an umbrella term that refers to the neuroimaging techniques used to generate these maps, which recently has enabled comprehensive brain mapping of network connectivity combined with graph theoretic methods. In this review, we present an overview of the key concepts in functional connectomics. Furthermore, we discuss articles that applied task-based and/or resting-state functional magnetic resonance imaging to examine network deficits in post-traumatic stress disorder (PTSD). These studies have provided important insights regarding the etiology of PTSD, as well as the overall organization of the brain network. Advances in functional connectomics are expected to provide insight into the pathophysiology and the development of biomarkers for diagnosis and treatment of PTSD.

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.32-32
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• 2003

The purpose of paper is to implement a PC-based software for 3D visualization of brain fiber tractography and high-resolution anatomical data 서론： DTI (Diffusion tensor imaging) is a very useful noninvasive MRI technique for providing the direction and connectivity information of brain fiber tracts. Especially in patients with glioma, fiber tracts on the lesion side in the brain had varying degrees of displacement or disruption as a result of the tumor. Tract disruption resulted from direct tumor involvement, compression on the tract, and vasogenic edema surrounding the tumor. To combine information on fiber tracts surrounding turner with a high-resolution anatomical 3D image may be clinically useful for surgical planning. Therefore we implemented a software for visualizing both brain fiber tractography and anatomical data.

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.83-83
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• 2003

Purpose： The purpose of paper is to implement a PC-based software for 3D visualization of brain fiber tractography and high-resolution anatomical data introduction： DTI (Diffusion tensor imaging) is a very useful noninvasive MRI technique for providing the direction and connectivity information of brain fiber tracts. Especially in patients with glioma, fiber tracts on the lesion side in the brain had varying degrees of displacement or disruption as a result of the tumor. Tract disruption resulted from direct tumor involvement, compression on the tract, and vasogenic edema surrounding the tumor. To combine information on fiber tracts surrounding tumor with a high-resolution anatomical 3D image may be clinically useful for surgical planning. Therefore we implemented a software for visualizing both brain fiber tractography and anatomical data.