scholarly journals Functional connectivity in the cognitive control network and the default mode network in late-life depression

2012 ◽  
Vol 139 (1) ◽  
pp. 56-65 ◽  
Author(s):  
George S. Alexopoulos ◽  
Matthew J. Hoptman ◽  
Dora Kanellopoulos ◽  
Christopher F. Murphy ◽  
Kelvin O. Lim ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Cognitive Control ◽  
Default Mode Network ◽  
Late Life ◽  
Control Network ◽  
Late Life Depression ◽  
Default Mode ◽  
Cognitive Control Network

scholarly journals Cognitive Control Network Homogeneity and Executive Functions in Late-Life Depression

2020 ◽  
Vol 5 (2) ◽  
pp. 213-221 ◽  
Author(s):  
Matteo Respino ◽  
Matthew J. Hoptman ◽  
Lindsay W. Victoria ◽  
George S. Alexopoulos ◽  
Nili Solomonov ◽  
...  
Keyword(s):  
Cognitive Control ◽  
Executive Functions ◽  
Late Life ◽  
Control Network ◽  
Late Life Depression ◽  
Cognitive Control Network

scholarly journals Disrupted dynamic functional network connectivity among cognitive control networks in the progression of Alzheimer’s disease

2021 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Zening Fu ◽  
Jingyu Liu ◽  
Yuhui Du ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Connectivity ◽  
Cognitive Control ◽  
Disease Progression ◽  
Brain Network ◽  
Middle Frontal Gyrus ◽  
Functional Network ◽  
Control Network ◽  
Cognitive Control Network

AbstractBackgroundAlzheimer’s disease (AD) is the most common age-related dementia that promotes a decline in memory, thinking, and social skills. The initial stages of dementia can be associated with mild symptoms, and symptom progression to a more severe state is heterogeneous across patients. Recent work has demonstrated the potential for functional network mapping to assist in the prediction of symptomatic progression. However, this work has primarily used static functional connectivity (sFC) from rs-fMRI. Recently, dynamic functional connectivity (dFC) has been recognized as a powerful advance in functional connectivity methodology to differentiate brain network dynamics between healthy and diseased populations.MethodsGroup independent component analysis was applied to extract 17 components within the cognitive control network (CCN) from 1385 individuals across varying stages of AD symptomology. We estimated dFC among 17 components within the CCN, followed by clustering the dFCs into 3 recurring brain states and then estimated a hidden Markov model and the occupancy rate for each subject. Finally, we investigated the link between CCN dFC connectivity features with AD progression.ResultsProgression of AD symptoms were associated with increases in connectivity within the middle frontal gyrus. Also, the AD with mild and severer symptoms showed less connectivity within the inferior parietal lobule and between this region with the rest of CCN. Finally, comparing with mild dementia, we found that the normal brain spends significantly more time in a state with lower within middle frontal gyrus connectivity and higher connectivity between the hippocampus and the rest of CCN, highlighting the importance of assessing the dynamics of brain connectivity in this disease.ConclusionOur results suggest that AD progress not only alters the CCN connectivity strength but also changes the temporal properties in this brain network. This suggests the temporal and spatial pattern of CCN as a biomarker that differentiates different stages of AD.Impact StatementBy assuming that functional connectivity is static over time, many of previous studies have ignored the brain dynamic in Alzheimer’s disease progression. Here, a longitudinal resting-state functional magnetic resonance imaging data are used to explore the temporal changes of functional connectivity in the cognitive control network in Alzheimer’s disease progression. The result of this study would increase our understanding about the underlying mechanisms of Alzheimer’s Disease and help in finding future treatment of this neurological disorder.

scholarly journals Default-mode network connectivity and white matter burden in late-life depression

2011 ◽  
Vol 194 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Minjie Wu ◽  
Carmen Andreescu ◽  
Meryl A. Butters ◽  
Robert Tamburo ◽  
Charles F. Reynolds ◽  
...  
Keyword(s):  
White Matter ◽  
Default Mode Network ◽  
Network Connectivity ◽  
Late Life ◽  
Late Life Depression ◽  
Default Mode

Altered brain structural and functional connectivity in schizotypy

2020 ◽  
pp. 1-10
Author(s):  
Yong-ming Wang ◽  
Xin-lu Cai ◽  
Rui-ting Zhang ◽  
Yi-jing Zhang ◽  
Han-yu Zhou ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Default Mode Network ◽  
Brain Connectivity ◽  
Structural Connectivity ◽  
Control Network ◽  
Imaging Data ◽  
Default Mode ◽  
Task Control ◽  
Brain White Matter ◽  
Functional Connectivity Strength

Abstract Background Schizotypy refers to schizophrenia-like traits below the clinical threshold in the general population. The pathological development of schizophrenia has been postulated to evolve from the initial coexistence of ‘brain disconnection’ and ‘brain connectivity compensation’ to ‘brain connectivity decompensation’. Methods In this study, we examined the brain connectivity changes associated with schizotypy by combining brain white matter structural connectivity, static and dynamic functional connectivity analysis of diffusion tensor imaging data and resting-state functional magnetic resonance imaging data. A total of 87 participants with a high level of schizotypal traits and 122 control participants completed the experiment. Group differences in whole-brain white matter structural connectivity probability, static mean functional connectivity strength, dynamic functional connectivity variability and stability among 264 brain sub-regions of interests were investigated. Results We found that individuals with high schizotypy exhibited increased structural connectivity probability within the task control network and within the default mode network; increased variability and decreased stability of functional connectivity within the default mode network and between the auditory network and the subcortical network; and decreased static mean functional connectivity strength mainly associated with the sensorimotor network, the default mode network and the task control network. Conclusions These findings highlight the specific changes in brain connectivity associated with schizotypy and indicate that both decompensatory and compensatory changes in structural connectivity within the default mode network and the task control network in the context of whole-brain functional disconnection may be an important neurobiological correlate in individuals with high schizotypy.

scholarly journals A digital intervention targeting cognitive control network dysfunction in middle age and older adults with major depression

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Faith M. Gunning ◽  
Joaquin A. Anguera ◽  
Lindsay W. Victoria ◽  
Patricia A. Areán
Keyword(s):  
Older Adults ◽  
Functional Connectivity ◽  
Cognitive Control ◽  
Video Game ◽  
Resting State ◽  
Rating Scale ◽  
Mechanistic Study ◽  
Control Network ◽  
Middle Aged ◽  
Cognitive Control Network

AbstractNonpharmacological interventions targeting putative network mechanisms of major depressive disorder (MDD) may represent novel treatments. This mechanistic study investigates how a video game-like intervention, designed to improve cognitive control network (CCN) functioning by targeting multitasking, influences the CCN of middle-aged and older adults with MDD. The sample consisted of 34 adults aged 45–75 with SCID-defined diagnosis of MDD, Hamilton depression rating scale scores ≥20, and a deficit in cognitive control. Participants were instructed to play at home for 20–25 min per day, at least 5 times per week, for 4 weeks. Evidence of target engagement was defined a priori as >2/3 of participants showing CCN improvement. CCN engagement was defined as a change in a Z score of ≥0.5 on functional magnetic resonance imaging (fMRI) in activation and functional connectivity of the CCN during task-based and resting-state fMRI, respectively. 74% of participants showed a change in activation of the CCN, and 72% showed an increase in resting-state functional connectivity. Sixty-eight percent demonstrated improved cognitive control function, measured as either improvement on sustained attention or working memory performance or reduced self-reported symptoms of apathy on the frontal systems behavioral scale (FrsBe). Participants also reported a significant reduction in mood symptoms measured by PHQ-9. A remotely deployed neuroscience-informed video game-like intervention improves both CCN functions and mood in middle-aged and older adults with MDD. This easily-disseminated intervention may rescue CCN dysfunction present in a substantial subset of middle-aged and older adults with MDD.

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