Modeling the outcome of structural disconnection on resting-state functional connectivity
Abstract
A growing body of experimental evidence suggests that functional connectivity at rest is shaped by the underlying anatomical structure. Furthermore, the organizational properties of resting-state functional networks are thought to serve as the basis for an optimal cognitive integration. A disconnection at the structural level, as occurring in some brain diseases, would then lead to functional and presumably cognitive impairments. In this work, we propose a computational model to investigate the role of a structural disconnection (encompassing putative local/global and axonal/synaptic mechanisms) on the organizational properties of emergent functional networks. The brain's spontaneous neural activity and the corresponding hemodynamic response were simulated using a large-scale network model, consisting of local neural populations coupled through white matter fibers. For a certain coupling strength, simulations reproduced healthy resting-state functional connectivity with graph properties in the range of the ones reported experimentally. When the structural connectivity is decreased, either globally or locally, the resultant simulated functional connectivity exhibited a network reorganization characterized by an increase in hierarchy, efficiency and robustness, a decrease in small-worldness and clustering and a narrower degree distribution, in the same way as recently reported for schizophrenia patients. Theoretical results indicate that most disconnection-related neuropathologies should induce the same qualitative changes in resting-state brain activity.
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The pattern of altered network dynamics was similar to that found in patients with schizophrenia.
“This pattern of altered network dynamics was found to be similar to that found in patients with schizophrenia”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [21]
Randomly removing links or decreasing global coupling strength resulted in increased hierarchy, efficiency, and robustness, but reduced small-worldness and clustering and a narrower degree distribution.
“Randomly removing links or decreasing the global coupling strength resulted in characteristic patterns of increased hierarchy, efficiency, and robustness, but reduced small-worldness and clustering and generated a narrower degree distribution.21”
From Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery (2016) · cites this paper as [21]
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- Authors
- Cabral, J., Hugues, E., Kringelbach, M. L., & Deco, G.
- Affiliations
- Universitat Pompeu Fabra (ES)
- Aarhus University (DK)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Corresponding author
- Cabral, Joana
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-09
- Volume
- 62
- Issue
- 3
- Pages
- 1342-1353
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2016188209
- Cited by
- 182
- References
- 10
- Citations by year
- 2026: 7 · 2025: 11 · 2024: 11 · 2023: 10 · 2022: 16 · 2021: 14 · 2020: 18 · 2019: 7 · 2018: 10 · 2017: 13 · 2016: 15 · 2015: 15 · 2014: 14 · 2013: 19 · 2012: 2
- FWCI
- 8.17
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- resting-state functional connectivity, structural disconnection, spontaneous neuronal activity, hemodynamic response, network reorganization, network hierarchy, small-worldness, network robustness, schizophrenia
- MeSH terms
- Brain, Humans, Models, Neurological, Nerve Net, Neural Pathways, Schizophrenia
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