• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.63-76
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• 2022

Emotional labor, characterized by a dysfunctional type of emotional regulation called surface acting, has detrimental psychological consequences on employees, including depression and social anxiety. Because such disorders exhibit psychological characteristics manifested through brain activation, previous studies have succeeded in distinguishing individuals with depression and social anxiety from healthy controls using their functional connectivity characteristics. However, it has not been established whether the functional connectivity characteristics associated with emotional labor are distinguishable. Thus, we obtained resting-state fMRI data from participants in the emotion labor (EL) group and control (CTRL) group, and we subjected their whole-brain functional connectivity matrices to a linear support vector machine classifier. Our analysis revealed that the EL and CTRL groups could be successfully distinguished on the basis of individuals' connectivity patterns, and confidence in the classification was correlated with the scores on the depression and social anxiety scales. These results are expected to provide insight on the neurobiological characteristics of emotional labor and enable the sorting of employees undergoing adverse emotional labor utilizing neurobiological observations.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.87-104
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• 2024

Most functional magnetic resonance imaging (fMRI) studies in resting state have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant. However, increased interest has recently been in quantifying possible dynamic changes in FC during fMRI experiments. FC study may provide insight into the fundamental workings of brain networks to brain activity. In this work, we focus on the specific problem of estimating the dynamic behavior of pairwise correlations between time courses extracted from two different brain regions. We compare the sliding-window techniques such as moving average (MA) and exponentially weighted moving average (EWMA), dynamic causality with vector autoregressive (VAR) model, dynamic conditional correlation (DCC) based on volatility, and the proposed alternative methods to use differencing and recursive residuals. We investigate the properties of those techniques in a series of simulation studies. We also provide an application with major depressive disorder (MDD) patient fMRI data to demonstrate studying dynamic correlations.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.23 no.2
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• pp.57-62
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• 2012

Objectives : Characteristic symptoms, including hyperactivity and easy distractibility, in children with attention-deficit hyperactivity disorder (ADHD) suggest that their brain status, even at rest, might differ from that of healthy children. This study was conducted in order to determine whether resting state brain activity is compromised in medication-naive children with ADHD. Methods : Twenty medication-naive children with ADHD (mean age $10.3{\pm}2.5$) and 28 age- and gender-matched healthy volunteers (mean age $10.3{\pm}2.0$) underwent measurements for resting state brain activity using functional magnetic resonance imaging (fMRI). Among resting state related-independent components (RSICs) extracted from fMRI data using independent component analysis, a significant difference in RSICs was observed between groups, using a mixed Gaussian/gamma model. Results : Except for IQ, which was higher in the healthy control group, no demographic difference was observed between the two groups (p<.001). Significantly less activation of one RSIC, which includes the bilateral precuneus/posterior cingulate cortex, occipito-temporal junction, and anterior cingulate cortex, was observed in the ADHD group, compared with the control group (p<.05). Conclusion : An abnormal RSIC, posterior default mode network (DMN), was observed in the medication-naive ADHD group. Results of our study suggest that abnormality of posterior DMN is one of the main pathophysiologies of ADHD.

• Journal of the Korean Society of Radiology
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• v.81 no.3
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• pp.676-687
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• 2020

Purpose To analyze the altered brain regions and intrinsic brain activity patterns in trauma-exposed firefighters without posttraumatic stress disorder (PTSD). Materials and Methods Resting-state functional MRI (rsfMRI) was performed for all subjects. Thirty-one firefighters over 40 years of age without PTSD (31 men; mean age, 49.8 ± 4.7 years) were included. Twenty-six non-traumatized healthy controls (HCs) (26 men; mean age, 65.3 ± 7.84 years) were also included. Voxel-based morphometry was performed to investigate focal differences in the brain anatomy. Seed-based functional connectivity analysis was performed to investigate differences in spontaneous brain characteristics. Results The mean z-scores of the Seoul Verbal Learning Test for immediate and delayed recall, Controlled Oral Word Association Test (COWAT) score for animals, and COWAT phonemic fluency were significantly lower in the firefighter group than in the HCs, indicating decreased neurocognitive function. Compared to HCs, firefighters showed reduced gray matter volume in the left superior parietal gyrus and left inferior temporal gyrus. Further, in contrast to HCs, firefighters showed alterations in rsfMRI values in multiple regions, including the fusiform gyrus and cerebellum. Conclusion Structural and resting-state functional abnormalities in the brain may be useful imaging biomarkers for identifying alterations in trauma-exposed firefighters without PTSD.

• Sleep Medicine and Psychophysiology
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• v.25 no.2
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• pp.82-91
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• 2018

Objectives: Synchronous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) has been used to explore sleep stage dependent functional brain networks. Despite a growing number of sleep studies using EEG-fMRI, few studies have conducted network analysis on whole night sleep due to difficulty in data acquisition, artifacts, and sleep management within the MRI scanner. Methods: In order to perform network analysis for whole night sleep, we proposed experimental procedures and data processing techniques for EEG-fMRI. We acquired 6-7 hours of EEG-fMRI data per participant and conducted signal processing to reduce artifacts in both EEG and fMRI. We then generated a functional brain atlas with 68 brain regions using independent component analysis of sleep fMRI data. Using this functional atlas, we constructed sleep level dependent functional brain networks. Results: When we evaluated functional connectivity distribution, sleep showed significantly reduced functional connectivity for the whole brain compared to that during wakefulness. REM sleep showed statistically different connectivity patterns compared to non-REM sleep in sleep-related subcortical brain circuits. Conclusion: This study suggests the feasibility of exploring functional brain networks using sleep EEG-fMRI for whole night sleep via appropriate experimental procedures and signal processing techniques for fMRI and EEG.

• Journal of Biomedical Engineering Research
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• v.45 no.1
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• pp.26-36
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• 2024

Functional brain imaging techniques have been used to diagnose psychiatric disorders such as dementia, depression, and autism. Recently, these techniques have also been actively used to study hearing loss. The present study reviewed the application of the functional brain imaging techniques in auditory research, especially those focusing on hearing loss, over the past decade. EEG, fMRI, fNIRS, MEG, and PET have been utilized in auditory research, and the number of research studies using these techniques has been increasing. In particular, fMRI and EEG were the most frequently used technique in auditory research. EEG studies mostly used event-related designs to analyze the direct relationship between stimulus and the related response, and in fMRI studies, resting-state functional connectivity and block designs were utilized to analyze alterations in brain functionality in hearing-related areas. In terms of age, while studies involving children mainly focused on congenital and pre- and post-lingual hearing loss to analyze developmental characteristics with and without hearing loss, those involving adults focused on age-related hearing loss to investigate changes in the characteristics of the brain based on the presence of hearing loss and the use of a hearing device. Overall, ranging from EEG to PET, various functional brain imaging techniques have been used in auditory research, but it is difficult to perform a comprehensive analysis due to the lack of consistency in experimental designs, analysis methods, and participant characteristics. Thus, it is necessary to develop standardized research protocols to obtain high-quality clinical and research evidence.

• Korean Journal of Biological Psychiatry
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• v.21 no.1
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• pp.1-13
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• 2014

Normal aging causes changes in the brain volume, connection, function and cognition. The brain changes with increases in age and difference of gender varies at all levels. Studies about normal brain aging using various brain magnetic resonance imaging (MRI) variables such as gray and white matter structural imaging, proton spectroscopy, apparent diffusion coefficient, diffusion tensor imaging and functional MRI are reviewed. Total volume of brain increases after birth but decreases after 9 years old. During adulthood, total volume of brain is relatively stable. After 35 years old, brain shrinks gradually. The changes of gray and white matters by aging show different features. N-acetylaspartate decreases or remains unchanged but choline, creatine and myo-inositol increase with aging. Apparent diffusion coefficient decreases till 20 years old and then becomes stable during adulthood and increase after 60 years old. Diffusion tensor properties in white matter tissue are variable during aging. Resting-state functional connectivity decreases after middle age. Structural and functional brain changes with normal aging are important for studying various psychiatric diseases such as dementia, schizophrenia and bipolar disorder. Our review may be helpful for studying longitudinal changes of these diseases and successful aging.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.2052-2061
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• 2021

Objective: The role of preoperative overt hepatic encephalopathy (OHE) in the neurophysiological mechanism of cognitive improvement after liver transplantation (LT) remains elusive. This study aimed to explore changes in sub-regional thalamic functional connectivity (FC) after LT and their relationship with neuropsychological improvement using resting-state functional MRI (rs-fMRI) data in cirrhotic patients with and without a history of OHE. Materials and Methods: A total of 51 cirrhotic patients, divided into the OHE group (n = 21) and no-OHE group (n = 30), and 30 healthy controls were enrolled in this prospective study. Each patient underwent rs-fMRI before and 1 month after LT. Using 16 bilateral thalamic subregions as seeds, we conducted a seed-to-voxel FC analysis to compare the thalamic FC alterations before and after LT between the OHE and no-OHE groups, as well as differences in FC between the two groups of cirrhotic patients and the control group. Correction for multiple comparisons was conducted using the false discovery rate (p < 0.05). Results: We found abnormally increased FC between the thalamic sub-region and prefrontal cortex, as well as an abnormally decreased FC between the bilateral thalamus in both OHE and no-OHE cirrhotic patients before LT, which returned to normal levels after LT. Compared with the no-OHE group, the OHE group exhibited more extensive abnormalities prior to LT, and the increased FC between the right thalamic subregions and right inferior parietal lobe was markedly reduced to normal levels after LT. Conclusion: The renormalization of FC in the cortico-thalamic loop might be a neuro-substrate for the recovery of cognitive function after LT in cirrhotic patients. In addition, hyperconnectivity between thalamic subregions and the inferior parietal lobe might be an important feature of OHE. Changes in FC in the thalamus might be used as potential biomarkers for recovery of cognitive function after LT in cirrhotic patients.

• Journal of Physiology & Pathology in Korean Medicine
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• v.38 no.1
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• pp.1-9
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• 2024

Cognitive reserve (CR) is a concept that can explain the discrepancies between the pathologic burden of the disease and clinical manifestations. It refers to the individual susceptibility to age-related brain changes and pathologies related to Alzheimer's disease, thus recognized as a factor affecting the trajectories of the disease. The purpose of this study was to explore the current states of clinical studies on neural substrates of CR in Alzheimer's disease using functional magnetic resonance imaging. We searched for clinical studies on CR using fMRI in the Pubmed, Cochrane library, RISS, KISS and ScienceON on August 14, 2023. Once the online search was finished, studies were selected manually by the inclusion criteria. Finally, we analyzed the characteristics of selected articles and reviewed the neural substrates of CR. Total thirty-four studies were included in this study. As surrogate markers of CR, not only education and occupational complexity, but also composite score and questionnaire-based method, which cover various areas of life, were mainly used. The most utilized methods in resting-state fMRI were independent component analysis, seed-based analysis, and graph theory analysis. Through the analysis, we demonstrated that neuroimaging techniques could capture the neural substrates associated with cognitive reserve. Moreover, functional connectivity of brain regions centered on prefrontal and parietal cortex and network areas such as default mode network showed a significant correlation with CR, which indicated a significant association with cognitive performance. CR may induce differential effects according to the disease status. We hope that this perspective on cognitive reserve would be helpful when conducting clinical researches on the mechanisms of traditional Korean medicine for Alzheimer's disease in the future.

• 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.