• Title/Summary/Keyword: Resting-state network

Search Result 22, Processing Time 0.028 seconds

Recent Advances on Resting State Functional Abnormalities of the Default Mode Network in Social Anxiety Disorder (사회불안장애에서 내정상태회로의 휴지기 기능 이상에 관한 최신 지견)

  • Yoon, Hyung-Jun;Seo, Eun Hyun;Kim, Seung-Gon
    • Anxiety and mood
    • /
    • v.14 no.2
    • /
    • pp.63-70
    • /
    • 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.

Accelerated Resting-State Functional Magnetic Resonance Imaging Using Multiband Echo-Planar Imaging with Controlled Aliasing

  • Seo, Hyung Suk;Jang, Kyung Eun;Wang, Dingxin;Kim, In Seong;Chang, Yongmin
    • Investigative Magnetic Resonance Imaging
    • /
    • v.21 no.4
    • /
    • pp.223-232
    • /
    • 2017
  • Purpose: To report the use of multiband accelerated echo-planar imaging (EPI) for resting-state functional MRI (rs-fMRI) to achieve rapid high temporal resolution at 3T compared to conventional EPI. Materials and Methods: rs-fMRI data were acquired from 20 healthy right-handed volunteers by using three methods: conventional single-band gradient-echo EPI acquisition (Data 1), multiband gradient-echo EPI acquisition with 240 volumes (Data 2) and 480 volumes (Data 3). Temporal signal-to-noise ratio (tSNR) maps were obtained by dividing the mean of the time course of each voxel by its temporal standard deviation. The resting-state sensorimotor network (SMN) and default mode network (DMN) were estimated using independent component analysis (ICA) and a seed-based method. One-way analysis of variance (ANOVA) was performed between the tSNR map, SMN, and DMN from the three data sets for between-group analysis. P < 0.05 with a family-wise error (FWE) correction for multiple comparisons was considered statistically significant. Results: One-way ANOVA and post-hoc two-sample t-tests showed that the tSNR was higher in Data 1 than Data 2 and 3 in white matter structures such as the striatum and medial and superior longitudinal fasciculus. One-way ANOVA revealed no differences in SMN or DMN across the three data sets. Conclusion: Within the adapted metrics estimated under specific imaging conditions employed in this study, multiband accelerated EPI, which substantially reduced scan times, provides the same quality image of functional connectivity as rs-fMRI by using conventional EPI at 3T. Under employed imaging conditions, this technique shows strong potential for clinical acceptance and translation of rs-fMRI protocols with potential advantages in spatial and/or temporal resolution. However, further study is warranted to evaluate whether the current findings can be generalized in diverse settings.

Prediction of the Following BCI Performance by Means of Spectral EEG Characteristics in the Prior Resting State (뇌신호 주파수 특성을 이용한 CNN 기반 BCI 성능 예측)

  • Kang, Jae-Hwan;Kim, Sung-Hee;Youn, Joosang;Kim, Junsuk
    • KIPS Transactions on Computer and Communication Systems
    • /
    • v.9 no.11
    • /
    • pp.265-272
    • /
    • 2020
  • In the research of brain computer interface (BCI) technology, one of the big problems encountered is how to deal with some people as called the BCI-illiteracy group who could not control the BCI system. To approach this problem efficiently, we investigated a kind of spectral EEG characteristics in the prior resting state in association with BCI performance in the following BCI tasks. First, spectral powers of EEG signals in the resting state with both eyes-open and eyes-closed conditions were respectively extracted. Second, a convolution neural network (CNN) based binary classifier discriminated the binary motor imagery intention in the BCI task. Both the linear correlation and binary prediction methods confirmed that the spectral EEG characteristics in the prior resting state were highly related to the BCI performance in the following BCI task. Linear regression analysis demonstrated that the relative ratio of the 13 Hz below and above the spectral power in the resting state with only eyes-open, not eyes-closed condition, were significantly correlated with the quantified metrics of the BCI performance (r=0.544). A binary classifier based on the linear regression with L1 regularization method was able to discriminate the high-performance group and low-performance group in the following BCI task by using the spectral-based EEG features in the precedent resting state (AUC=0.817). These results strongly support that the spectral EEG characteristics in the frontal regions during the resting state with eyes-open condition should be used as a good predictor of the following BCI task performance.

Cortical Thickness of Resting State Networks in the Brain of Male Patients with Alcohol Dependence (남성 알코올 의존 환자 대뇌의 휴지기 네트워크별 피질 두께)

  • Lee, Jun-Ki;Kim, Siekyeong
    • Korean Journal of Biological Psychiatry
    • /
    • v.24 no.2
    • /
    • pp.68-74
    • /
    • 2017
  • Objectives It is well known that problem drinking is associated with alterations of brain structures and functions. Brain functions related to alcohol consumption can be determined by the resting state functional connectivity in various resting state networks (RSNs). This study aims to ascertain the alcohol effect on the structures forming predetermined RSNs by assessing their cortical thickness. Methods Twenty-six abstinent male patients with alcohol dependence and the same number of age-matched healthy control were recruited from an inpatient mental hospital and community. All participants underwent a 3T MRI scan. Averaged cortical thickness of areas constituting 7 RSNs were determined by using FreeSurfer with Yeo atlas derived from cortical parcellation estimated by intrinsic functional connectivity. Results There were significant group differences of mean cortical thicknesses (Cohen's d, corrected p) in ventral attention (1.01, < 0.01), dorsal attention (0.93, 0.01), somatomotor (0.90, 0.01), and visual (0.88, 0.02) networks. We could not find significant group differences in the default mode network. There were also significant group differences of gray matter volumes corrected by head size across the all networks. However, there were no group differences of surface area in each network. Conclusions There are differences in degree and pattern of structural recovery after abstinence across areas forming RSNs. Considering the previous observation that group differences of functional connectivity were significant only in networks related to task-positive networks such as dorsal attention and cognitive control networks, we can explain recovery pattern of cognition and emotion related to the default mode network and the mechanisms for craving and relapse associated with task-positive networks.

Altered Functional Disconnectivity in Internet Addicts with Resting-State Functional Magnetic Resonance Imaging

  • Seok, Ji-Woo;Sohn, Jin-Hun
    • Journal of the Ergonomics Society of Korea
    • /
    • v.33 no.5
    • /
    • pp.377-386
    • /
    • 2014
  • Objective: In this study, we used resting-state fMRI data to map differences in functional connectivity between a comprehensive set of 8 distinct cortical and subcortical brain regions in healthy controls and Internet addicts. We also investigated the relationship between resting state connectivity strength and the level of psychopathology (ex. score of internet addiction scale and score of Barratt impulsiveness scale). Background: There is a lot of evidence of relationship between Internet addiction and impaired inhibitory control. Clinical evidence suggests that Internet addicts have a high level of impulsivity as measured by behavioral task of response inhibition and a self report questionnaire. Method: 15 Internet addicts and 15 demographically similar non-addicts participated in the current resting-state fMRI experiment. For the connectivity analysis, regions of interests (ROIs) were defined based on the previous studies of addictions. Functional connectivity assessment for each subject was obtained by correlating time-series across the ROIs, resulting in $8{\times}8$ matrixs for each subject. Within-group, functional connectivity patterns were observed by entering the z maps of the ROIs of each subject into second-level one sample t test. Two sample t test was also performed to examine between group differences. Results: Between group, the analysis revealed that the connectivity in between the orbito frontal cortex and inferior parietal cortex, between orbito frontal cortex and putamen, between the orbito frontal cortex and anterior cingulate cortex, between the insula and anterior cingulate cortex, and between amydgala and insula was significantly stronger in control group than in the Internet addicts, while the connectivity in between the orbito frontal cortex and insula showed stronger negative correlation in the Internet addicts relative to control group (p < 0.001, uncorrected). No significant relationship between functional connectivity strength and current degree of Internet addiction and degree of impulsitivy was seen. Conclusion: This study found that Internet addicts had declined connectivity strength in the orbitofrontal cortex (OFC) and other regions (e.g., ACC, IPC, and insula) during resting-state. It may reflect deficits in the OFC function to process information from different area in the corticostriatal reward network. Application: The results might help to develop theoretical modeling of Internet addiction for Internet addiction discrimination.

Alteration of Functional Connectivity in OCD by Resting State fMRI

  • Kim, Seungho;Lee, Sang Won;Lee, Seung Jae;Chang, Yongmin
    • Journal of Korea Multimedia Society
    • /
    • v.24 no.4
    • /
    • pp.583-592
    • /
    • 2021
  • Obsessive-compulsive disorder (OCD) is a mental disorder in which a person repeated a particular thought or feels. The domain of beliefs and guilt predicted OCD symptoms. Although there were some neuroimaging studies investigating OCD symptoms, resting-state functional magnetic resonance imaging (rs-fMRI) study investigating intra-network functional connectivity associated with guilt for OCD is not reported yet. Therefore, in the current study, we assessed the differences between intra-network functional connectivity of healthy control group and OCD group using independent component analysis (ICA) method. In addition, we also aimed to investigate the correlation between changed functional connectivity and guilt score in OCD. Total 86 participants, which consisted of 42 healthy control volunteers and 44 OCD patients, acquired rs-fMRI data using the 3T MRI. After preprocessing the fMRI data, a functional connectivity was used for group independent component analysis. The results showed that OCD patients had higher score in emotion state in beliefs and lower functional connectivity in fronto-parietal network (FPN) than control group. A decrease of functional connectivity in FPN was negatively correlated with feelings of guilt in OCD. Our results suggest excessive increase in guilt negatively affect to process emotional state and behavior or cognitive processing by influencing intrinsic brain activity.

Resting-State Functional Connectivity of Subgenual Cingulate Cortex in Major Depression (우울증 환자의 휴지기 슬밑 띠 피질의 기능적 뇌 연결성)

  • Ko, Daewook;Youn, So Young;Choi, Jean H.;Shin, Yong-Wook
    • Anxiety and mood
    • /
    • v.10 no.2
    • /
    • pp.143-150
    • /
    • 2014
  • Objective : The subgenual cingulate cortex, a part of default-mode network, has been known to playa key role in the pathophysiology of depression. The previous studies have reported abnormal functional connectivity between the subgenual cingulate cortex and other brain regions in the patients with depression. The goal of this shldy was to explore the resting-state functional connectivity of the subgenual cingulate cortex between the patients with depression and healthy subjects. Methods : Twenty patients with major depression and age- and sex-matched 20 healthy subjects underwent 5-minute resting state fMRI scans. The functional connectivity map in each subject was acquired using seed-based correlation analysis with the seed located in the subgenual cingulate cortex (Talairach coordinates; x=-10, y=5, z=-10). The functional connectivity maps were calculated using AFNI and compared between the patient and healthy subject group via two-sample T-test using 3dttest++ in AFNI package. Results : Functional connectivity was decreased between the subgenual cingulate cortex and both sides of fusiform gyrus in depressed subjects. Connectivity was also decreased between the subgenual cingulate cortex and the left cerebellum in the patient group. There was no correlation between the severity of depression and the degree of functional connectivity between the subgenual cingulate cortex and the regions showing decreased functional connectivity. Conclusion : Decreased resting-state functional connectivity between the subgenual cingulate cortex and both sides of fusiform gyrus, and decreased connectivity between the subgenual cingulate cortex and the left cerebellum found in the patients with major depression in comparison to the healthy subjects might be related to abnormal emotional and cognitive processing of depressed patients.

Combined Analysis Using Functional Connectivity of Default Mode Network Based on Independent Component Analysis of Resting State fMRI and Structural Connectivity Using Diffusion Tensor Imaging Tractography (휴지기 기능적 자기공명영상의 독립성분분석기법 기반 내정상태 네트워크 기능 연결성과 확산텐서영상의 트랙토그래피 기법을 이용한 구조 연결성의 통합적 분석)

  • Choi, Hyejeong;Chang, Yongmin
    • Journal of Korea Multimedia Society
    • /
    • v.24 no.5
    • /
    • pp.684-694
    • /
    • 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.

The Abnormality of Posterior Default Mode Network in Medication-Naïve Attention-Deficit Hyperactivity Disorder Children : Resting State fMRI Study (약물 복용력이 없는 주의력결핍 과잉행동장애 아동에서의 뒤쪽 내정상태회로 이상 : 휴식상태 기능적 뇌자기공명영상 연구)

  • Choi, Jee-Wook;Go, Hyo-Jin;Woo, Young-Sup;Song, Seung-Hoon;Yang, Po-Song;Jeong, Bum-Seok
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
    • /
    • v.23 no.2
    • /
    • pp.57-62
    • /
    • 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.

Changes in the Laterality of Functional Connectivity Associated with Tinnitus: Resting-State fMRI Study

  • Shin, Yeji;Ryu, Chang-Woo;Jahng, Geon-Ho;Park, Moon Suh;Byun, Jae Yong
    • Investigative Magnetic Resonance Imaging
    • /
    • v.23 no.1
    • /
    • pp.55-64
    • /
    • 2019
  • Purpose: One of the suggested potential mechanisms of tinnitus is an alteration in perception in the neural auditory pathway. The aim of this study was to investigate the difference in laterality in functional connectivity between tinnitus patients and healthy controls using resting state functional MRI (rs-fMRI). Materials and Methods: Thirty-eight chronic tinnitus subjects and 45 age-matched healthy controls were enrolled in this study. Connectivity was investigated using independent component analysis, and the laterality index map was calculated based on auditory (AN) and dorsal attention (DAN), default mode (DMN), sensorimotor, salience (SalN), and visual networks (VNs). The laterality index (LI) of tinnitus subjects was compared with that of normal controls using region-of-interest (ROI) and voxel-based methods and a two-sample unpaired t-test. Pearson correlation was conducted to assess the associations between the LI in each network and clinical variables. Results: The AN and VN showed significant differences in LI between the two groups in ROI analysis (P < 0.05), and the tinnitus group had clusters with significantly decreased laterality of AN, SalN, and VN in voxel-based comparisons. The AN was positively correlated with tinnitus distress (tinnitus handicap inventory), and the SalN was negatively correlated with symptom duration (P < 0.05). Conclusion: The results of this study suggest that various functional networks related to psychological distress can be modified by tinnitus, and that this interrelation can present differently on the right and left sides, according to the dominance of the network.