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Relating Structure and Function in the Human Brain: Relative Contributions of Anatomy, Stationary Dynamics, and Non-stationarities
Open accessAbstract
Investigating the relationship between brain structure and function is a central endeavor for neuroscience research. Yet, the mechanisms shaping this relationship largely remain to be elucidated and are highly debated. In particular, the existence and relative contributions of anatomical constraints and dynamical physiological mechanisms of different types remain to be established. We addressed this issue by systematically comparing functional connectivity (FC) from resting-state functional magnetic resonance imaging data with simulations from increasingly complex computational models, and by manipulating anatomical connectivity obtained from fiber tractography based on diffusion-weighted imaging. We hypothesized that FC reflects the interplay of at least three types of components: (i) a backbone of anatomical connectivity, (ii) a stationary dynamical regime directly driven by the underlying anatomy, and (iii) other stationary and non-stationary dynamics not directly related to the anatomy. We showed that anatomical connectivity alone accounts for up to 15% of FC variance; that there is a stationary regime accounting for up to an additional 20% of variance and that this regime can be associated to a stationary FC; that a simple stationary model of FC better explains FC than more complex models; and that there is a large remaining variance (around 65%), which must contain the non-stationarities of FC evidenced in the literature. We also show that homotopic connections across cerebral hemispheres, which are typically improperly estimated, play a strong role in shaping all aspects of FC, notably indirect connections and the topographic organization of brain networks.
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“Interregional FC arises from anatomical projection strengths (Messe et al., 2014; Shen et al., 2012), correlated gene expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b)”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Messe et al., 2014
In the citing paper
“Models can involve highly parameterized simulations of regional activity (Hansen et al., 2015; Messe et al., 2014; Sanz-Leon et al., 2015), or sparser analytic predictions of FC using graph metrics of mutual communication (Goni et al., 2014; Grayson et al., 2016) (although, both approaches appear to be comparably effective; see Figure 1D).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Messe et al., 2014
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“Even the best-performing SC-FC models generally account for less than 50% of the variance in FC across the brain in both humans and non-human primates (Grayson et al., 2016; Messe et al., 2014; Misic et al., 2015).”
From Development of large-scale functional networks from birth to adulthood: A guide to the neuroimaging literature (2017) · cites this paper as Messe et al., 2014
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“Interregional FC arises from anatomical projection strengths (Messe et al., 2014; Shen et al., 2012), correlated gene expression (Richiardi et al., 2015), and synaptic receptor densities (Turk et al., 2016; van den Heuvel et al., 2016b) – properties that, in turn, undergo experience-dependent and…”
BackgroundInfluentialHow Local Excitation-Inhibition Ratio Impacts the Whole Brain Dynamics
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Metadata
- Authors
- Messé, A., Rudrauf, D., Benali, H., & Marrelec, G.
- Affiliations
- Inserm (FR)
- Corresponding author
- Messé, Arnaud
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-03-20
- Volume
- 10
- Issue
- 3
- Pages
- e1003530
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC3961181
- OpenAlex
- W2022159725
- Cited by
- 215
- References
- 57
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 11 · 2023: 12 · 2022: 19 · 2021: 23 · 2020: 25 · 2019: 17 · 2018: 24 · 2017: 22 · 2016: 17 · 2015: 22 · 2014: 7
- FWCI
- 12.64
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Princeton University
- Universitat Pompeu Fabra
- Institut National de la Santé et de la Recherche Médicale
- Université de Lausanne
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- structure-function relationship, functional connectivity, resting-state fMRI, structural connectivity, non-stationary dynamics, fiber tractography, interhemispheric connections, indirect connections, diffusion-weighted imaging
- MeSH terms
- Adult, Brain, Brain Mapping, Computer Simulation, Female, Hemodynamics, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Nerve Net, Neural Pathways, Reproducibility of Results, Diffusion Magnetic Resonance Imaging, Young Adult
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