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Modeling the outcome of structural disconnection on resting-state functional connectivity
Joana Cabral1, Etienne Hugues, Morten L Kringelbach
1Center of Brain and Cognition, Theoretical and Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain. juanitacabral@hotmail.com
Structural disconnection in the brain impacts functional connectivity, altering network organization. This computational model reveals how reduced connectivity, seen in diseases like schizophrenia, leads to specific network changes, offering insights into neuropathologies.
Area of Science:
- Neuroscience
- Computational Biology
- Network Science
Background:
- Resting-state functional connectivity is influenced by anatomical structure.
- Network organization is crucial for cognitive integration.
- Structural disconnections in brain diseases can cause functional and cognitive deficits.
Purpose of the Study:
- To model the impact of structural disconnection on functional network organization.
- To investigate local/global and axonal/synaptic disconnection mechanisms.
- To understand how neuropathologies affect resting-state brain activity.
Main Methods:
- Simulated spontaneous neural activity and hemodynamic responses using a large-scale network model.
- Coupled local neural populations via white matter fibers.
- Varied structural connectivity strength to mimic disconnections.
Main Results:
- Simulations reproduced healthy resting-state functional connectivity.
- Decreased structural connectivity led to increased hierarchy, efficiency, and robustness.
- Reduced connectivity resulted in decreased small-worldness and clustering, mirroring schizophrenia patient data.
Conclusions:
- Structural disconnections qualitatively alter resting-state functional network organization.
- The model supports the hypothesis that disconnection-related neuropathologies induce similar changes in brain activity.
- Findings provide a theoretical framework for understanding brain network dysfunction in disease.
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