Correlation analysis of electrical and optical low frequency fluctuation in organic device degradation

2009 ◽  
Vol 105 (6) ◽  
pp. 064504 ◽  
Author(s):  
Ke Lin ◽  
Lai Szu Cheng ◽  
Adelia Ramam ◽  
Chua Soo Jin
2021 ◽  
Author(s):  
Wenfeng Liu ◽  
Chen-Yu Yu ◽  
Yi-Cong Pan ◽  
Hui-Ye Shu ◽  
Li-Juan Zhang ◽  
...  

Abstract The present study was to assess the spontaneous changes in brain activity in patients with DON using functional magnetic resonance imaging (fMRI). 14 DON patients and 14 healthy controls (HCs) were enrolled. All participants underwent resting-state fMRI (rs-fMRI). The fractional amplitude of low-frequency fluctuation (fALFF) method was applied to evaluate neural activity changes. The Hospital Anxiety and Depression Scale (HADS) was used to assess the anxiety and depression status of participants. The independent sample t test and chi-squared test were applied to analyze demographics of DON patients and HCs. Receiver operating characteristic (ROC) curves were applied to analyze the variation in mean fALFF values between DON patients and HCs. The relationships between the fALFF values of brain regions and clinical behaviors in the DON group were analyzed using Pearson’s correlation analysis. In contrast to HCs, the fALFF value of DON patients was significantly higher in the right precentral gyrus (RPCG). However, the fALFF values in right anterior cingulate gyrus (RACG) and left middle cingulate gyrus (LMCG) were markedly decreased in DON patients. The area under the curve (AUC) of ROCs for each brain region showed high accuracy. Pearson's correlation analysis showed that fALFF values of the right anterior cingulate gyrus and left middle cingulate gyrus were negatively correlated with HADS scores, while fALFF values of the left middle cingulate gyrus were negatively correlated with DON disease duration. To sum up, we found abnormal spontaneous brain activities in regions related to cognitive and emotional dysfunction, eye movement disorder, and vision loss in patients with DON. These results may indicate the underlying neuropathological mechanisms of DON, and show that fALFF may be an effective method by which to distinguish patients with DON from healthy individuals.


2021 ◽  
pp. 028418512110324
Author(s):  
Xiao-Dong Zhang ◽  
Jun Ke ◽  
Jing-Li Li ◽  
Yun-Yan Su ◽  
Jia-Min Zhou ◽  
...  

Background Sjögren’s syndrome (SjS) associated with systemic lupus erythematosus (SjS-SLE) was considered a standalone but often-overlooked entity. Purpose To assess altered spontaneous brain activity in SjS-SLE and SjS using amplitude of low-frequency fluctuation (ALFF). Material and Methods Sixteen patients with SjS-SLE, 17 patients with SjS, and 17 matched controls underwent neuropsychological tests and subsequent resting-state functional magnetic resonance imaging (fMRI) examinations. The ALFF value was calculated based on blood oxygen level dependent (BOLD) fMRI. Statistical parametric mapping was utilized to analyze between-group differences and multiple comparison was corrected with Analysis of Functional NeuroImages 3dClustSim. Then, the ALFFs of brain regions with significant differences among the three groups were correlated to corresponding clinical and neuropsychological variables by Pearson correlation. Results ALFF differences in the bilateral precuneus/posterior cingulate cortex (PCC), right parahippocampal gyrus/caudate/insula, and left insula were found among the three groups. Both SjS-SLE and SjS displayed decreased ALFF in the right parahippocampal gyrus, right insula, and left insula than HC. Moreover, SjS-SLE showed wider decreased ALFF in the bilateral precuneus and right caudate, while the SjS group exhibited increased ALFF in the bilateral PCC. Additionally, patients with SjS-SLE exhibited lower ALFF values in the bilateral PCC and precuneus than SjS. Moreover, ALFF values in the right parahippocampal gyrus and PCC were negatively correlated to fatigue score and disease duration, respectively, in SjS-SLE. Conclusion SjS-SLE and SjS exhibited common and different alteration of cerebral functional segregation revealed by AlFF analysis. This result appeared to indicate that SjS-SLE might be different from SjS with a neuroimaging standpoint.


2008 ◽  
Vol 29 (2) ◽  
pp. 142-156 ◽  
Author(s):  
Kendrick N. Kay ◽  
Stephen V. David ◽  
Ryan J. Prenger ◽  
Kathleen A. Hansen ◽  
Jack L. Gallant

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Min Deng ◽  
Xing Zhang ◽  
Xiaoyan Bi ◽  
Chunhai Gao

Abstract Background Attachment theory demonstrates that early attachment experience shapes internal working models with mental representations of self and close relationships, which affects personality traits and interpersonal relationships in adulthood. Although research has focused on brain structural and functional underpinnings to disentangle attachment styles in healthy individuals, little is known about the spontaneous brain activity associated with self-reported attachment anxiety and avoidance during the resting state. Methods One hundred and nineteen individuals participated in the study, completing the Experience in Close Relationship scale immediately after an 8-min fMRI scanning. We used the resting-state functional magnetic resonance imaging (rs-fMRI) signal of the amplitude of low-frequency fluctuation and resting-state functional connectivity to identify attachment-related regions and networks. Results Consequently, attachment anxiety is closely associated with the amplitude of low-frequency fluctuations in the right posterior cingulate cortex, over-estimating emotional intensity and exaggerating outcomes. Moreover, the functional connectivity between the posterior cingulate cortex and fusiform gyrus increases detection ability for potential threat or separation information, facilitating behavior motivation. The attachment avoidance is positively correlated with the amplitude of low-frequency fluctuation in the bilateral lingual gyrus and right postcentral and negatively correlated with the bilateral orbital frontal cortex and inferior temporal gyrus. Functional connection with attachment avoidance contains critical nodes in the medial temporal lobe memory system, frontal-parietal network, social cognition, and default mode network necessary to deactivate the attachment system and inhibit attachment-related behavior. Conclusion and implications These findings clarify the amplitude of low-frequency fluctuation and resting-state functional connectivity neural signature of attachment style, associated with attachment strategies in attachment anxiety and attachment avoidance individuals. These findings may improve our understanding of the pathophysiology of the attachment-related disorder.


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