scholarly journals Altered Regional Homogeneity in Rolandic Epilepsy: A Resting-State fMRI Study

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Ye-Lei Tang ◽  
Gong-Jun Ji ◽  
Yang Yu ◽  
Jue Wang ◽  
Zhong-Jin Wang ◽  
...  
Keyword(s):  
Behavioral Problems ◽  
Orbitofrontal Cortex ◽  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Regional Homogeneity ◽  
Healthy Children ◽  
Rolandic Epilepsy ◽  
Performance Intelligence Quotient ◽  
Local Synchronization

Children with rolandic epilepsy (RE) are often associated with cognitive deficits and behavioral problems. Findings from neurophysiological and neuroimaging studies in RE have now demonstrated dysfunction not only in rolandic focus, but also in distant neuronal circuits. Little is known, however, about whether there is distributed abnormal spontaneous brain activity in RE. Using resting-state functional magnetic resonance imaging (RS-fMRI), the present study aimed to determine whether children with RE show abnormal local synchronization during resting state and, if so, whether these changes could be associated with the behavioral/clinical characteristics of RE. Regional homogeneity (ReHo) in children with RE(n=30)and healthy children(n=20)was computed on resting-state functional MRI data. In comparison with healthy children, children with RE showed increased ReHo in the central, premotor, and prefrontal regions, while they showed decreased ReHo in bilateral orbitofrontal cortex and temporal pole. In addition, the ReHo value in the left orbitofrontal cortex negatively was corrected with performance intelligence quotient in the children with RE. The aberrant local synchronization, not strictly related to primary site of the typical rolandic focus, indicates the neuropathophysiological mechanism of RE. The study findings may shed new light on the understanding of neural correlation of neuropsychological deficiencies in the children with RE.

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.

ALTERED BRAIN ACTIVITY IN PATIENTS WITH DIABETIC RETINOPATHY USING REGIONAL HOMOGENEITY: A RESTING-STATE fMRI STUDY

2019 ◽  
Vol 25 (4) ◽  
pp. 320-327 ◽  
Author(s):  
Xu-Lin Liao ◽  
Qing Yuan ◽  
Wen-Qing Shi ◽  
Biao Li ◽  
Ting Su ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Regional Homogeneity ◽  
Fmri Study

scholarly journals Gender Differences in Cerebral Regional Homogeneity of Adult Healthy Volunteers: A Resting-State fMRI Study

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Chunsheng Xu ◽  
Chuanfu Li ◽  
Hongli Wu ◽  
Yuanyuan Wu ◽  
Sheng Hu ◽  
...  
Keyword(s):  
Gender Differences ◽  
Cerebral Cortex ◽  
Healthy Volunteers ◽  
Resting State ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Regional Homogeneity ◽  
Female Group ◽  
Precentral Gyrus ◽  
Sensorimotor Network

Objective.We sought to use the regional homogeneity (ReHo) approach as an index in the resting-state functional MRI to investigate the gender differences of spontaneous brain activity within cerebral cortex and resting-state networks (RSNs) in young adult healthy volunteers.Methods.One hundred and twelve healthy volunteers (56 males, 56 females) participated in the resting-state fMRI scan. The ReHo mappings in the cerebral cortex and twelve RSNs of the male and female groups were compared.Results.We found statistically significant gender differences in the primary visual network (PVN) (P<0.004, with Bonferroni correction) and left attention network (LAtN), default mode network (DMN), sensorimotor network (SMN), executive network (EN), and dorsal medial prefrontal network (DMPFC) as well (P<0.05, uncorrected). The male group showed higher ReHo in the left precuneus, while the female group showed higher ReHo in the right middle cingulate gyrus, fusiform gyrus, left inferior parietal lobule, precentral gyrus, supramarginal gyrus, and postcentral gyrus.Conclusions.Our results suggested that men and women had regional specific differences during the resting-state. The findings may improve our understanding of the gender differences in behavior and cognition from the perspective of resting-state brain function.

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.

Sign in / Sign up

Export Citation Format

Share Document