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


Chen, C C; Henson, R N; Stephan, K E; Kilner, J M; Friston, K J (2009). Forward and backward connections in the brain: A DCM study of functional asymmetries. NeuroImage, 45(2):453-462.

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.

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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39 citations in Web of Science®
42 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Economics
Dewey Decimal Classification:330 Economics
Language:English
Date:2009
Deposited On:06 Jul 2009 05:50
Last Modified:05 Apr 2016 13:17
Publisher:Elsevier
ISSN:1053-8119
Publisher DOI:https://doi.org/10.1016/j.neuroimage.2008.12.041
PubMed ID:19162203

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