Literature DB >> 29284140

Effective connectivity during working memory and resting states: A DCM study.

Kyesam Jung1, Karl J Friston2, Chongwon Pae3, Hanseul H Choi1, Sungho Tak4, Yoon Kyoung Choi5, Bumhee Park6, Chan-A Park4, Chaejoon Cheong7, Hae-Jeong Park8.   

Abstract

Although the relationship between resting-state functional connectivity and task-related activity has been addressed, the relationship between task and resting-state directed or effective connectivity - and its behavioral concomitants - remains elusive. We evaluated effective connectivity under an N-back working memory task in 24 participants using stochastic dynamic causal modelling (DCM) of 7 T fMRI data. We repeated the analysis using resting-state data, from the same subjects, to model connectivity among the same brain regions engaged by the N-back task. This allowed us to: (i) examine the relationship between intrinsic (task-independent) effective connectivity during resting (Arest) and task states (Atask), (ii) cluster phenotypes of task-related changes in effective connectivity (Btask) across participants, (iii) identify edges (Btask) showing high inter-individual effective connectivity differences and (iv) associate reaction times with the similarity between Btask and Arest in these edges. We found a strong correlation between Arest and Atask over subjects but a marked difference between Btask and Arest. We further observed a strong clustering of individuals in terms of Btask, which was not apparent in Arest. The task-related effective connectivity Btask varied highly in the edges from the parietal to the frontal lobes across individuals, so the three groups were clustered mainly by the effective connectivity within these networks. The similarity between Btask and Arest at the edges from the parietal to the frontal lobes was positively correlated with 2-back reaction times. This result implies that a greater change in context-sensitive coupling - from resting-state connectivity - is associated with faster reaction times. In summary, task-dependent connectivity endows resting-state connectivity with a context sensitivity, which predicts the speed of information processing during the N-back task.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 29284140     DOI: 10.1016/j.neuroimage.2017.12.067

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  10 in total

1.  A Computational Framework for Controlling the Self-Restorative Brain Based on the Free Energy and Degeneracy Principles.

Authors:  Hae-Jeong Park; Jiyoung Kang
Journal:  Front Comput Neurosci       Date:  2021-04-14       Impact factor: 2.380

2.  Parietal-Prefrontal Feedforward Connectivity in Association With Schizophrenia Genetic Risk and Delusions.

Authors:  Danielle L B Greenman; Michelle A N La; Shefali Shah; Qiang Chen; Karen F Berman; Daniel R Weinberger; Hao Yang Tan
Journal:  Am J Psychiatry       Date:  2020-05-27       Impact factor: 18.112

3.  A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI.

Authors:  Peter Zeidman; Amirhossein Jafarian; Nadège Corbin; Mohamed L Seghier; Adeel Razi; Cathy J Price; Karl J Friston
Journal:  Neuroimage       Date:  2019-06-19       Impact factor: 6.556

4.  A guide to group effective connectivity analysis, part 2: Second level analysis with PEB.

Authors:  Peter Zeidman; Amirhossein Jafarian; Mohamed L Seghier; Vladimir Litvak; Hayriye Cagnan; Cathy J Price; Karl J Friston
Journal:  Neuroimage       Date:  2019-06-18       Impact factor: 6.556

Review 5.  From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis.

Authors:  Guoshi Li; Pew-Thian Yap
Journal:  Front Hum Neurosci       Date:  2022-08-17       Impact factor: 3.473

6.  Effective brain connectivity at rest is associated with choice-induced preference formation.

Authors:  Katharina Voigt; Carsten Murawski; Sebastian Speer; Stefan Bode
Journal:  Hum Brain Mapp       Date:  2020-04-03       Impact factor: 5.038

7.  Novelty modulates human striatal activation and prefrontal-striatal effective connectivity during working memory encoding.

Authors:  Lena S Geiger; Carolin Moessnang; Axel Schäfer; Zhenxiang Zang; Maria Zangl; Hengyi Cao; Tamar R van Raalten; Andreas Meyer-Lindenberg; Heike Tost
Journal:  Brain Struct Funct       Date:  2018-05-11       Impact factor: 3.270

8.  The neurophysiological architecture of semantic dementia: spectral dynamic causal modelling of a neurodegenerative proteinopathy.

Authors:  Elia Benhamou; Charles R Marshall; Lucy L Russell; Chris J D Hardy; Rebecca L Bond; Harri Sivasathiaseelan; Caroline V Greaves; Karl J Friston; Jonathan D Rohrer; Jason D Warren; Adeel Razi
Journal:  Sci Rep       Date:  2020-10-01       Impact factor: 4.379

9.  Increased functional interaction within frontoparietal network during working memory task in major depressive disorder.

Authors:  Wanyi Cao; Haiyan Liao; Sainan Cai; Wanrong Peng; Zhaoxia Liu; Kaili Zheng; Jinyu Liu; Mingtian Zhong; Changlian Tan; Jinyao Yi
Journal:  Hum Brain Mapp       Date:  2021-07-30       Impact factor: 5.038

10.  Neural network modelling reveals changes in directional connectivity between cortical and hypothalamic regions with increased BMI.

Authors:  Katharina Voigt; Adeel Razi; Ian H Harding; Zane B Andrews; Antonio Verdejo-Garcia
Journal:  Int J Obes (Lond)       Date:  2021-08-02       Impact factor: 5.095

  10 in total

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