Literature DB >> 19162203

Forward and backward connections in the brain: a DCM study of functional asymmetries.

C C Chen1, R N Henson, K E Stephan, J M Kilner, K J Friston.   

Abstract

In this paper, we provide evidence for functional asymmetries in forward and backward connections that define hierarchical architectures in the brain. We exploit the fact that modulatory or nonlinear influences of one neuronal system on another (i.e., effective connectivity) entail coupling between different frequencies. Functional asymmetry in forward and backward connections was addressed by comparing dynamic causal models of MEG responses induced by visual processing of normal and scrambled faces. We compared models with and without nonlinear (between-frequency) coupling in both forward and backward connections. Bayesian model comparison indicated that the best model had nonlinear forward and backward connections. Using the best model we then quantified frequency-specific causal influences mediating observed spectral responses. We found a striking asymmetry between forward and backward connections; in which high (gamma) frequencies in higher cortical areas suppressed low (alpha) frequencies in lower areas. This suppression was significantly greater than the homologous coupling in the forward connections. Furthermore, exactly the asymmetry was observed when we examined face-selective coupling (i.e., coupling under faces minus scrambled faces). These results highlight the importance of nonlinear coupling among brain regions and point to a functional asymmetry between forward and backward connections in the human brain that is consistent with anatomical and physiological evidence from animal studies. This asymmetry is also consistent with functional architectures implied by theories of perceptual inference in the brain, based on hierarchical generative models.

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Year:  2008        PMID: 19162203     DOI: 10.1016/j.neuroimage.2008.12.041

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


  36 in total

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Authors:  Rebecca D Ray; David H Zald
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3.  Development of effective connectivity in the core network for face perception.

Authors:  Wei He; Marta I Garrido; Paul F Sowman; Jon Brock; Blake W Johnson
Journal:  Hum Brain Mapp       Date:  2015-02-19       Impact factor: 5.038

4.  Bidirectional electric communication between the inferior occipital gyrus and the amygdala during face processing.

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Journal:  Hum Brain Mapp       Date:  2017-06-02       Impact factor: 5.038

5.  Disturbed effective connectivity patterns in an intrinsic triple network model are associated with posttraumatic stress disorder.

Authors:  Yifei Weng; Rongfeng Qi; Li Zhang; Yifeng Luo; Jun Ke; Qiang Xu; Yuan Zhong; Jianjun Li; Feng Chen; Zhihong Cao; Guangming Lu
Journal:  Neurol Sci       Date:  2018-11-17       Impact factor: 3.307

6.  Comparing families of dynamic causal models.

Authors:  Will D Penny; Klaas E Stephan; Jean Daunizeau; Maria J Rosa; Karl J Friston; Thomas M Schofield; Alex P Leff
Journal:  PLoS Comput Biol       Date:  2010-03-12       Impact factor: 4.475

Review 7.  The default-mode, ego-functions and free-energy: a neurobiological account of Freudian ideas.

Authors:  R L Carhart-Harris; K J Friston
Journal:  Brain       Date:  2010-02-28       Impact factor: 13.501

8.  Connectivity Analysis is Essential to Understand Neurological Disorders.

Authors:  James B Rowe
Journal:  Front Syst Neurosci       Date:  2010-09-17

9.  Ten simple rules for dynamic causal modeling.

Authors:  K E Stephan; W D Penny; R J Moran; H E M den Ouden; J Daunizeau; K J Friston
Journal:  Neuroimage       Date:  2009-11-12       Impact factor: 6.556

Review 10.  Computational and dynamic models in neuroimaging.

Authors:  Karl J Friston; Raymond J Dolan
Journal:  Neuroimage       Date:  2009-12-28       Impact factor: 6.556

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