Dynamic synergetic configurations of resting-state networks in ADHD
Author(s) -
Neda Kaboodvand,
Behzad Iravani,
Peter Fransson
Publication year - 2019
Publication title -
neuroimage
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.259
H-Index - 364
eISSN - 1095-9572
pISSN - 1053-8119
DOI - 10.1016/j.neuroimage.2019.116347
Subject(s) - default mode network , resting state fmri , stroop effect , cognition , dynamic functional connectivity , psychology , cognitive psychology , task (project management) , attention deficit hyperactivity disorder , perspective (graphical) , neuroscience , network topology , task positive network , computer science , artificial intelligence , clinical psychology , computer network , economics , management
Attention deficit hyperactivity disorder (ADHD) is characterized by high distractibility and impaired executive functions. Notably, there is mounting evidence suggesting that ADHD could be regarded as a default mode network (DMN) disorder. In particular, failure in regulating the dynamics of activity and interactions of the DMN and cognitive control networks have been hypothesized as the main source of task interference causing attentional problems. On the other hand, previous studies indicated pronounced fluctuations in the strength of functional connections over time, particularly for the inter-network connections between the DMN and fronto-parietal control networks. Hence, characterization of connectivity disturbances in ADHD requires a thorough assessment of time-varying functional connectivity (FC). In this study, we proposed a dynamical systems perspective to assess how the DMN over time recruits different configurations of network segregation and integration. Specifically, we were interested in configurations for which both intra- and inter-network connections are retained, as opposed to commonly used methods which assess network segregation as a single measure. From resting-state fMRI data, we extracted three different stable configurations of FC patterns for the DMN, namely synergies. We provided evidence supporting our hypothesis that ADHD differs compared to controls, both in terms of recruitment rate and topology of specific synergies between resting-state networks. In addition, we found a relationship between synergetic cooperation patterns of the DMN with cognitive control networks and a behavioral measure which is sensitive to ADHD-related symptoms, namely the Stroop color-word task.
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