Forward and backward connections in the brain: a DCM study of functional asymmetries
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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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Predictive coding holds that top-down predictions suppress prediction errors in lower levels of a hierarchy.
“Theoretically, this is consistent with predictive coding, where top-down predictions suppress prediction errors in lower levels of a hierarchy”
From Network discovery with DCM (2011) · cites this paper as Chen et al., 2009
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- Authors
- Chen, C. C., Henson, R. N., Stephan, K. E., Kilner, J. M., & Friston, K. J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- MRC Cognition and Brain Sciences Unit (GB)
- Corresponding author
- Chen, C.C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-04
- Volume
- 45
- Issue
- 2
- Pages
- 453-462
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2120182026
- Cited by
- 109
- References
- 90
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 6 · 2022: 5 · 2021: 4 · 2020: 8 · 2019: 1 · 2018: 19 · 2017: 5 · 2016: 5 · 2015: 7 · 2014: 4 · 2013: 7 · 2012: 5
- FWCI
- 4.36
- Type
- journal article
- Language
- en
- Open access
- green
- www.zora.uzh.ch
- Licence
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, other-oa)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Wellcome Trust (088130)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- functional asymmetry, effective connectivity, nonlinear coupling, face processing, MEG, perceptual inference, generative models, Bayesian model selection
- MeSH terms
- Brain Mapping, Computer Simulation, Evoked Potentials, Visual, Female, Humans, Functional Laterality, Male, Models, Neurological, Nerve Net, Pattern Recognition, Visual, Magnetoencephalography
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