scholarly journals Lateralized Resting-State Functional Brain Network Organization Changes in Heart Failure

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0155894 ◽  
Author(s):  
Bumhee Park ◽  
Bhaswati Roy ◽  
Mary A. Woo ◽  
Jose A. Palomares ◽  
Gregg C. Fonarow ◽  
...  
2018 ◽  
Author(s):  
Marjolein Spronk ◽  
Kaustubh Kulkarni ◽  
Jie Lisa Ji ◽  
Brian P. Keane ◽  
Alan Anticevic ◽  
...  

AbstractA wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations have seemed to support various theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in broad, whole-brain perspective. Using a graph distance measure – connectome-wide correlation – we found that whole-brain resting-state functional network organization in humans is highly similar across a variety of mental diseases and healthy controls. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease those differences are informative. Such small network alterations may reflect the fact that most psychiatric patients maintain overall cognitive abilities similar to those of healthy individuals (relative to, e.g., the most severe schizophrenia cases), such that whole-brain functional network organization is expected to differ only subtly even for mental diseases with devastating effects on everyday life. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases.


2020 ◽  
Vol 31 (1) ◽  
pp. 547-561
Author(s):  
Marjolein Spronk ◽  
Brian P Keane ◽  
Takuya Ito ◽  
Kaustubh Kulkarni ◽  
Jie Lisa Ji ◽  
...  

Abstract A wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations appear to support theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in a broad, whole-brain perspective. Using a graph distance approach—connectome-wide similarity—we found that whole-brain resting-state functional network organization is highly similar across groups of individuals with and without a variety of mental diseases. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease, those differences are informative. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases. Such small network alterations suggest the possibility that small, well-targeted alterations to brain network organization may provide meaningful improvements for a variety of mental disorders.


2015 ◽  
Vol 126 (8) ◽  
pp. 1468-1481 ◽  
Author(s):  
E. van Diessen ◽  
T. Numan ◽  
E. van Dellen ◽  
A.W. van der Kooi ◽  
M. Boersma ◽  
...  

2013 ◽  
Vol 9 ◽  
pp. P670-P670 ◽  
Author(s):  
Hanneke de Waal ◽  
Cornelis Stam ◽  
Marieke Lansbergen ◽  
F. Maestú ◽  
Philip Scheltens ◽  
...  

2022 ◽  
Author(s):  
Adam B Weinberger ◽  
Robert A Cortes ◽  
Richard F Betzel ◽  
Adam E Green

The brain's modular functional organization facilitates adaptability. Modularity has been linked with a wide range of cognitive abilities such as intelligence, memory, and learning. However, much of this work has (1) considered modularity while a participant is at rest rather than during tasks conditions and/or (2) relied primarily on lab-based cognitive assessments. Thus, the extent to which modularity can provide information about real-word behavior remains largely unknown. Here, we investigated whether functional modularity during resting-state and task-based fMRI was associated with academic learning (measured by GPA) and ability (measured by PSAT) in a large sample of high school students. Additional questions concerned the extent to which modularity differs between rest and task conditions, and across spatial scales. Results indicated that whole-brain modularity during task conditions was significantly associated with academic learning. In contrast to prior work, no such associations were observed for resting-state modularity. We further showed that differences in modularity between task conditions and resting-state varied across spatial scales. Taken together, the present findings inform how functional brain network modularity - during task conditions and while at rest - relate to a range of cognitive abilities.


NeuroImage ◽  
2019 ◽  
Vol 199 ◽  
pp. 87-92
Author(s):  
Lin Shi ◽  
Wutao Lou ◽  
Adrian Wong ◽  
Fan Zhang ◽  
Jill Abrigo ◽  
...  

2020 ◽  
pp. 135245852097716
Author(s):  
Ilse M Nauta ◽  
Shanna D Kulik ◽  
Lucas C Breedt ◽  
Anand JC Eijlers ◽  
Eva MM Strijbis ◽  
...  

Background: Cognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients. Objective: To investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology. Methods: Resting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage. Results: A more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years ([Formula: see text]), independent of structural damage. Cross-sectional analyses showed that a less integrated network (e.g. lower tree hierarchy) related to worse cognition, independent of frequency band. Conclusions: The level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS.


2016 ◽  
Vol 6 (3) ◽  
Author(s):  
Bumhee Park ◽  
Jose A. Palomares ◽  
Mary A. Woo ◽  
Daniel W. Kang ◽  
Paul M. Macey ◽  
...  

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