scholarly journals Disclosing Default Mode Network on Euthymic Bipolar Patients and Healthy Controls: A Combined Approach to Resting State fMRI Data

2021 ◽  
Vol 168 ◽  
pp. S38-S39
Author(s):  
Chiara Spironelli
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Healthy Controls ◽  
Combined Approach ◽  
Default Mode ◽  
Bipolar Patients

scholarly journals Neurophysiology (fMRI)

2015 ◽  
Vol 42 (S1) ◽  
pp. S38-S38
Author(s):  
ST Lang ◽  
B Goodyear ◽  
J Kelly ◽  
P Federico
Keyword(s):  
Cognitive Functioning ◽  
Default Mode Network ◽  
Resting State ◽  
Attentional Control ◽  
Brain Tumours ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Resting State Networks ◽  
Default Mode ◽  
Eloquent Cortex

Background: Resting state functional MRI (rs-fMRI) provides many advantages to task-based fMRI in neurosurgical populations, foremost of which is the lack of the need to perform a task. Many networks can be identified by rs-fMRI in a single period of scanning. Despite the advantages, there is a paucity of literature on rs-fMRI in neurosurgical populations. Methods: Eight patients with tumours near areas traditionally considered as eloquent cortex participated in a five minute rs-fMRI scan. Resting-state fMRI data underwent Independent Component Analysis (ICA) using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) toolbox in FSL. Resting state networks (RSNs) were identified on a visual basis. Results: Several RSNs, including language (N=7), sensorimotor (N=7), visual (N=7), default mode network (N=8) and frontoparietal attentional control (n=7) networks were readily identifiable using ICA of rs-fMRI data. Conclusion: These pilot data suggest that ICA applied to rs-fMRI data can be used to identify motor and language networks in patients with brain tumours. We have also shown that RSNs associated with cognitive functioning, including the default mode network and the frontoparietal attentional control network can be identified in individual subjects with brain tumours. While preliminary, this suggests that rs-fMRI may be used pre-operatively to localize areas of cortex important for higher order cognitive functioning.

scholarly journals Effective Connectivity within the Default Mode Network: Dynamic Causal Modeling of Resting-State fMRI Data

2016 ◽  
Vol 10 ◽  
Author(s):  
Maksim G. Sharaev ◽  
Viktoria V. Zavyalova ◽  
Vadim L. Ushakov ◽  
Sergey I. Kartashov ◽  
Boris M. Velichkovsky
Keyword(s):  
Default Mode Network ◽  
Resting State ◽  
Effective Connectivity ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Fmri Data ◽  
Network Dynamic ◽  
Dynamic Causal Modeling ◽  
Default Mode

Abstract 19: Default Mode Network Alterations in Cerebral Amyloid Angiopathy: A Resting State FMRI Study

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Mitchell J Horn ◽  
Elif Gokcal ◽  
Aina Frau-Pascual ◽  
Kristin M Schwab ◽  
Anand Viswanathan ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cerebral Amyloid Angiopathy ◽  
Default Mode Network ◽  
Resting State ◽  
Resting State Fmri ◽  
Amyloid Angiopathy ◽  
Healthy Controls ◽  
Default Mode ◽  
Posterior Cingulate ◽  
Cerebral Amyloid

Introduction: Cerebral amyloid angiopathy (CAA) is an established cause of intracerebral hemorrhage and vascular dysfunction leading to ischemia. Functional connectivity analysis using MRI is becoming an important tool to analyze the brain activity during resting state, the default mode network (DMN) representing the prototypical set of connections. As CAA pathology has a posterior predominance, we sought to characterize the functional connectivity of the posterior DMN at resting state in patients with CAA. Methods: Patients with probable CAA diagnosed using Boston Criteria and healthy controls (HC) were prospectively enrolled and received high resolution 3T MRI scans including dedicated resting-state fMRI sequences. Functional seed-to-seed analyses were done using the default processing pipeline in the CONN Toolbox. Correlation maps between the established DMN and specific regions of the posterior DMN, the precuneus and posterior cingulate, were averaged within groups and compared in an ANCOVA model. Results: Study participants consisted of 60 patients with probable CAA and 20 healthy controls [aged 69 ± 7.5 vs 72.3 ± 8 years, P = 0.108]. Seed-to-seed analysis revealed a significantly lower strength of DMN connectivity in CAA when compared to controls in the precuneus [ P = 0.009] and posterior cingulate [ P = 0.003] adjusted for age and sex (Fig 1). Conclusion: Patients with CAA exhibited significant loss of connectivity in the posterior regions of the DMN when compared to controls. The precuneus and posterior cingulate are core regions of the DMN with reportedly high metabolic rates at rest. Disruption of these posterior DMN regions might occur due to vascular amyloid pathology that shows a predominantly posterior distribution.

scholarly journals Impact of physiological noise in characterizing the functional MRI default-mode network in Alzheimer’s disease

2020 ◽  
Vol 41 (1) ◽  
pp. 166-181 ◽  
Author(s):  
Yi-Tien Li ◽  
Chun-Yuan Chang ◽  
Yi-Cheng Hsu ◽  
Jong-Ling Fuh ◽  
Wen-Jui Kuo ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Default Mode Network ◽  
Resting State ◽  
Physiological Responses ◽  
Resting State Fmri ◽  
Fmri Data ◽  
Physiological Noise ◽  
Default Mode ◽  
Heart Beating ◽  
Healthy Participants

The functional connectivity of the default-mode network (DMN) monitored by functional magnetic resonance imaging (fMRI) in Alzheimer's disease (AD) patients has been found weaker than that in healthy participants. Since breathing and heart beating can cause fluctuations in the fMRI signal, these physiological activities may affect the fMRI data differently between AD patients and healthy participants. We collected resting-state fMRI data from AD patients and age-matched healthy participants. With concurrent cardiac and respiratory recordings, we estimated both physiological responses phase-locked and non-phase-locked to heart beating and breathing. We found that the cardiac and respiratory physiological responses in AD patients were 3.00 ± 0.51 s and 3.96 ± 0.52 s later (both p <  0.0001) than those in healthy participants, respectively. After correcting the physiological noise in the resting-state fMRI data by population-specific physiological response functions, the DMN estimated by seed-correlation was more localized to the seed region. The DMN difference between AD patients and healthy controls became insignificant after suppressing physiological noise. Our results indicate the importance of controlling physiological noise in the resting-state fMRI analysis to obtain clinically related characterizations in AD.

scholarly journals Effects of escitalopram therapy on resting-state functional connectivity of subsystems of the default mode network in unmedicated patients with major depressive disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jian Cui ◽  
Yun Wang ◽  
Rui Liu ◽  
Xiongying Chen ◽  
Zhifang Zhang ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Functional Connectivity ◽  
Depressive Disorder ◽  
Default Mode Network ◽  
Resting State ◽  
Fmri Data ◽  
Healthy Controls ◽  
Resting State Functional Connectivity ◽  
Major Depressive ◽  
Default Mode

AbstractAntidepressants are often the first-line medications prescribed for patients with major depressive disorder (MDD). Given the critical role of the default mode network (DMN) in the physiopathology of MDD, the current study aimed to investigate the effects of antidepressants on the resting-state functional connectivity (rsFC) within and between the DMN subsystems. We collected resting-state functional magnetic resonance imaging (rs-fMRI) data from 36 unmedicated MDD patients at baseline and after escitalopram treatment for 12 weeks. The rs-fMRI data were also collected from 61 matched healthy controls at the time point with the same interval. Then, we decomposed the DMN into three subsystems based on a template from previous studies and computed the rsFC within and between the three subsystems. Finally, repeated measures analysis of covariance was conducted to identify the main effect of group and time and their interaction effect. We found that the significantly reduced within-subsystem rsFC in the DMN core subsystem in patients with MDD at baseline was increased after escitalopram treatment and became comparable with that in the healthy controls, whereas the reduced within-subsystem rsFC persisted in the DMN dorsal medial prefrontal cortex (dMPFC) and medial temporal subsystems in patients with MDD following escitalopram treatment. In addition, the reduced between-subsystem rsFC between the core and dMPFC subsystem showed a similar trend of change after treatment in patients with MDD. Moreover, our main results were confirmed using the DMN regions from another brain atlas. In the current study, we found different effects of escitalopram on the rsFC of the DMN subsystems. These findings deepened our understanding of the neuronal basis of antidepressants’ effect on brain function in patients with MDD. The trial name: appropriate technology study of MDD diagnosis and treatment based on objective indicators and measurement. URL: http://www.chictr.org.cn/showproj.aspx?proj=21377. Registration number: ChiCTR-OOC-17012566.

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