scholarly journals Aberrant Dynamics of Regional Coherence Measured by Resting-State fMRI in Children With Benign Epilepsy With Centrotemporal Spikes (BECTS)

2021 ◽  
Vol 12 ◽  
Author(s):  
Lin Jiang ◽  
Xuejin Ma ◽  
Heng Liu ◽  
Ji Wang ◽  
Jiaren Zhang ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Middle Temporal Gyrus ◽  
Dynamic Features ◽  
Association Analyses ◽  
Global Signal ◽  
Iq Scores ◽  
Intrinsic Brain Activity ◽  
Benign Epilepsy

Objective: To explore the dynamic features of intrinsic brain activity measured by fMRI in children with benign epilepsy with centrotemporal spikes (BECTS) and examine whether these indexes were associated with behaviors.Methods: We recruited 26 children with BECTS (10.35 ± 2.91 years) and 26 sex-, and age-matched (11.35 ± 2.51 years) healthy controls (HC) and acquired resting-state functional magnetic resonance imaging (rs-fMRI) and behavioral data. Dynamic regional homogeneity (dReHo), including mean and coefficient of variation (CV) metrics derived from the rs-fMRI data, and were compared between the BECTS and the HC groups.Results: Significantly decreased mean dReHo in bilateral supramarginal gyrus, left middle temporal gyrus (MTG.L), left postcentral gyrus and superior occipital gyrus were found in children with BECTS. Meanwhile, increased CV of dReHo in MTG.L and right fusiform in children with BECTS was revealed compared with HC. Further analyses of functional connectivity revealed decreased global signal FC existed in similar regions, linked with linguistic, social cognition, and sensorimotor processes, in children with BECTS compared with HCs. Moreover, the association analyses showed that the CV of dReHo in MTG.L was positively associated with age and a negative correlation was found between mean dReHo of MTG.L and disease duration. Besides, the CV of dReHo in MTG.L was found positively associated with the intelligence quotient (IQ) language scores and full IQ scores in children with BECTS, and the CV of dReHo in the left inferior temporal gyrus and Rolandic operculum were positively correlated with IQ operation scores and full IQ scores.Conclusion: Aberrant dynamic regional coherence in sensorimotor, linguistic, and lateral temporal regions suggests dynamical interplay that underlying cognitive performance in children with BECTS, suggesting an intrinsic dynamic mechanism for BECTS.

scholarly journals Altered brain network centrality in patients with retinal vein occlusion: a resting-state fMRI study

2021 ◽  
Vol 14 (11) ◽  
pp. 1741-1747
Author(s):  
Wen-Jia Dong ◽  
◽  
Chu-Qi Li ◽  
Yong-Qiang Shu ◽  
Wen-Qing Shi ◽  
...  
Keyword(s):  
Retinal Vein Occlusion ◽  
Resting State ◽  
Brain Activity ◽  
Activity Patterns ◽  
Depression Scale ◽  
Resting State Fmri ◽  
Brain Network ◽  
Middle Temporal Gyrus ◽  
Vein Occlusion ◽  
Intrinsic Brain Activity

AIM: To explore the intrinsic brain activity variations in retinal vein occlusion (RVO) subjects by using the voxel-wise degree centrality (DC) technique. METHODS: Twenty-one subjects with RVO and twenty-one healthy controls (HCs) were enlisted and underwent the resting-state functional magnetic resonance imaging (rs-fMRI) examination. The spontaneous cerebrum activity variations were inspected using the DC technology. The receiver operating characteristic (ROC) curve was implemented to distinguish the DC values of RVOs from HCs. The relationships between DC signal of definite regions of interest and the clinical characteristics in RVO group were evaluated by Pearson’s correlation analysis. RESULTS: RVOs showed notably higher DC signals in right superior parietal lobule, middle frontal gyrus and left precuneus, but decreased DC signals in left middle temporal gyrus and bilateral anterior cingulated (BAC) when comparing with HCs. The mean DC value of RVOs in the BAC were negatively correlated with the anxiety and depression scale. CONCLUSION: RVO is associated aberrant intrinsic brain activity patterns in several brain areas including pain-related as well as visual-related regions, which might assist to reveal the latent neural mechanisms.

Distinguishing hypochondriasis and schizophrenia using regional homogeneity: a resting-state fMRI study and support vector machine analysis

2021 ◽  
pp. 1-29
Author(s):  
Kangyu Jin ◽  
Zhe Shen ◽  
Guoxun Feng ◽  
Zhiyong Zhao ◽  
Jing Lu ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Resting State ◽  
Parietal Lobe ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Middle Temporal Gyrus ◽  
Support Vector ◽  
Fmri Study

Abstract Objective: A few former studies suggested there are partial overlaps in abnormal brain structure and cognitive function between Hypochondriasis (HS) and schizophrenia (SZ). But their differences in brain activity and cognitive function were unclear. Methods: 21 HS patients, 23 SZ patients, and 24 healthy controls (HC) underwent Resting-state functional magnetic resonance imaging (rs-fMRI) with the regional homogeneity analysis (ReHo), subsequently exploring the relationship between ReHo value and cognitive functions. The support vector machines (SVM) were used on effectiveness evaluation of ReHo for differentiating HS from SZ. Results: Compared with HC, HS showed significantly increased ReHo values in right middle temporal gyrus (MTG), left inferior parietal lobe (IPL) and right fusiform gyrus (FG), while SZ showed increased ReHo in left insula, decreased ReHo values in right paracentral lobule. Additionally, HS showed significantly higher ReHo values in FG, MTG and left paracentral lobule but lower in insula than SZ. The higher ReHo values in insula were associated with worse performance in MCCB in HS group. SVM analysis showed a combination of the ReHo values in insula and FG was able to satisfactorily distinguish the HS and SZ patients. Conclusion: our results suggested the altered default mode network (DMN), of which abnormal spontaneous neural activity occurs in multiple brain regions, might play a key role in the pathogenesis of HS, and the resting-state alterations of insula closely related to cognitive dysfunction in HS. Furthermore, the combination of the ReHo in FG and insula was a relatively ideal indicator to distinguish HS from SZ.

scholarly journals The organization of intrinsic brain activity differs between genders: A resting-state fMRI study in a large cohort of young healthy subjects

2012 ◽  
Vol 34 (6) ◽  
pp. 1330-1343 ◽  
Author(s):  
Massimo Filippi ◽  
Paola Valsasina ◽  
Paolo Misci ◽  
Andrea Falini ◽  
Giancarlo Comi ◽  
...  
Keyword(s):  
Resting State ◽  
Healthy Subjects ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Large Cohort ◽  
Fmri Study ◽  
Intrinsic Brain Activity

scholarly journals Lag threads organize the brain’s intrinsic activity

2015 ◽  
Vol 112 (17) ◽  
pp. E2235-E2244 ◽  
Author(s):  
Anish Mitra ◽  
Abraham Z. Snyder ◽  
Tyler Blazey ◽  
Marcus E. Raichle
Keyword(s):  
Spontaneous Activity ◽  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Intrinsic Activity ◽  
Resting State Networks ◽  
Slow Activity ◽  
Intrinsic Brain Activity ◽  
Temporal Sequences ◽  
The Brain

It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals.

scholarly journals Propagated infra-slow intrinsic brain activity reorganizes across wake and slow wave sleep

eLife ◽  
2015 ◽  
Vol 4 ◽  
Author(s):  
Anish Mitra ◽  
Abraham Z Snyder ◽  
Enzo Tagliazucchi ◽  
Helmut Laufs ◽  
Marcus E Raichle
Keyword(s):  
Slow Wave ◽  
Resting State ◽  
Slow Wave Sleep ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Blood Oxygen Level Dependent ◽  
Intrinsic Activity ◽  
Subcortical Structures ◽  
Blood Oxygen Level ◽  
Intrinsic Brain Activity

Propagation of slow intrinsic brain activity has been widely observed in electrophysiogical studies of slow wave sleep (SWS). However, in human resting state fMRI (rs-fMRI), intrinsic activity has been understood predominantly in terms of zero-lag temporal synchrony (functional connectivity) within systems known as resting state networks (RSNs). Prior rs-fMRI studies have found that RSNs are generally preserved across wake and sleep. Here, we use a recently developed analysis technique to study propagation of infra-slow intrinsic blood oxygen level dependent (BOLD) signals in normal adults during wake and SWS. This analysis reveals marked changes in propagation patterns in SWS vs. wake. Broadly, ordered propagation is preserved within traditionally defined RSNs but lost between RSNs. Additionally, propagation between cerebral cortex and subcortical structures reverses directions, and intra-cortical propagation becomes reorganized, especially in visual and sensorimotor cortices. These findings show that propagated rs-fMRI activity informs theoretical accounts of the neural functions of sleep.

scholarly journals Jumping over baselines with new methods to predict activation maps from resting-state fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Lacosse ◽  
Klaus Scheffler ◽  
Gabriele Lohmann ◽  
Georg Martius
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Behavioral Differences ◽  
Large Variability ◽  
Single Vertex ◽  
Spontaneous Brain Activity ◽  
New Methods ◽  
Group Averaging ◽  
Proposed Modification

AbstractCognitive fMRI research primarily relies on task-averaged responses over many subjects to describe general principles of brain function. Nonetheless, there exists a large variability between subjects that is also reflected in spontaneous brain activity as measured by resting state fMRI (rsfMRI). Leveraging this fact, several recent studies have therefore aimed at predicting task activation from rsfMRI using various machine learning methods within a growing literature on ‘connectome fingerprinting’. In reviewing these results, we found lack of an evaluation against robust baselines that reliably supports a novelty of predictions for this task. On closer examination to reported methods, we found most underperform against trivial baseline model performances based on massive group averaging when whole-cortex prediction is considered. Here we present a modification to published methods that remedies this problem to large extent. Our proposed modification is based on a single-vertex approach that replaces commonly used brain parcellations. We further provide a summary of this model evaluation by characterizing empirical properties of where prediction for this task appears possible, explaining why some predictions largely fail for certain targets. Finally, with these empirical observations we investigate whether individual prediction scores explain individual behavioral differences in a task.

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