scholarly journals Attribution of emotions to body postures: An independent component analysis study of functional connectivity in autism

2014 ◽  
Vol 35 (10) ◽  
pp. 5204-5218 ◽  
Author(s):  
Lauren E. Libero ◽  
Carl E. Stevens ◽  
Rajesh K. Kana
Keyword(s):  
Functional Connectivity ◽  
Independent Component Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Body Postures ◽  
Analysis Study

scholarly journals Neural Modulation in Aversive Emotion Processing: An Independent Component Analysis Study

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
César Romero-Rebollar ◽  
Luis Jiménez-Ángeles ◽  
Eduardo Antonio Dragustinovis-Ruiz ◽  
Verónica Medina-Bañuelos
Keyword(s):  
Social Interaction ◽  
Independent Component Analysis ◽  
Cognitive Processes ◽  
Emotional Processing ◽  
Component Analysis ◽  
Independent Component ◽  
Neural Dynamics ◽  
Emotional Stimuli ◽  
Analysis Study ◽  
Neural Modulation

Emotional processing has an important role in social interaction. We report the findings about the Independent Component Analysis carried out on a fMRI set obtained with a paradigm of face emotional processing. The results showed that an independent component, mainly cerebellar-medial-frontal, had a positive modulation associated with fear processing. Also, another independent component, mainly parahippocampal-prefrontal, showed a negative modulation that could be associated with implicit reappraisal of emotional stimuli. Independent Component Analysis could serve as a method to understand complex cognitive processes and their underlying neural dynamics.

Functional connectivity as revealed by independent component analysis of resting-state fNIRS measurements

NeuroImage ◽  
2010 ◽  
Vol 51 (3) ◽  
pp. 1150-1161 ◽  
Author(s):  
Han Zhang ◽  
Yu-Jin Zhang ◽  
Chun-Ming Lu ◽  
Shuang-Ye Ma ◽  
Yu-Feng Zang ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Independent Component Analysis ◽  
Resting State ◽  
Component Analysis ◽  
Independent Component

scholarly journals Abnormal Large-Scale Network Activation Present in Bipolar Mania and Bipolar Depression Under Resting State

2021 ◽  
Vol 12 ◽  
Author(s):  
Can Zeng ◽  
Brendan Ross ◽  
Zhimin Xue ◽  
Xiaojun Huang ◽  
Guowei Wu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Independent Component Analysis ◽  
Resting State ◽  
Rating Scale ◽  
Bipolar Depression ◽  
Component Analysis ◽  
Independent Component ◽  
Frontoparietal Network ◽  
Bipolar Mania ◽  
Group Independent Component Analysis

Introduction: Previous studies have primarily focused on the neuropathological mechanisms of the emotional circuit present in bipolar mania and bipolar depression. Recent studies applying resting-state functional magnetic resonance imaging (fMRI) have raise the possibility of examining brain-wide networks abnormality between the two oppositional emotion states, thus this study aimed to characterize the different functional architecture represented in mania and depression by employing group-independent component analysis (gICA).Materials and Methods: Forty-one bipolar depressive patients, 20 bipolar manic patients, and 40 healthy controls (HCs) were recruited and received resting-state fMRI scans. Group-independent component analysis was applied to the brain network functional connectivity analysis. Then, we calculated the correlation between the value of between-group differences and clinical variables.Results: Group-independent component analysis identified 15 components in all subjects, and ANOVA showed that functional connectivity (FC) differed significantly in the default mode network, central executive network, and frontoparietal network across the three groups. Further post-hoc t-tests showed a gradient descent of activity—depression > HC > mania—in all three networks, with the differences between depression and HCs, as well as between depression and mania, surviving after family wise error (FWE) correction. Moreover, central executive network and frontoparietal network activities were positively correlated with Hamilton depression rating scale (HAMD) scores and negatively correlated with Young manic rating scale (YMRS) scores.Conclusions: Three brain networks heighten activity in depression, but not mania; and the discrepancy regions mainly located in prefrontal, which may imply that the differences in cognition and emotion between the two states is associated with top–down regulation in task-independent networks.

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