Science· 2013Q1
Structural and Functional Brain Networks: From Connections to Cognition
- 2,183citations
- Q1SCImago
- 2013year
Short summary
Hierarchical modular brain networks facilitate both local neuronal operations and global integration of functions, with dynamic functional networks diverging from static structural connections during cognition tasks.
AI-generated from the title and abstract; the full text is not read.
Key points
- Hierarchical modular brain networks support both local processing and global integration.
- Functional brain networks are constrained by structural connections but diverge dynamically during cognitive tasks.
- Degenerate (many-to-one) mapping between function and structure is crucial for brain network understanding.
- A formal, computational approach is needed to resolve the structure-function dialectic.
AI-generated from the title and abstract; the full text is not read.
Abstract
How rich functionality emerges from the invariant structural architecture of the brain remains a major mystery in neuroscience. Recent applications of network theory and theoretical neuroscience to large-scale brain networks have started to dissolve this mystery. Network analyses suggest that hierarchical modular brain networks are particularly suited to facilitate local (segregated) neuronal operations and the global integration of segregated functions. Although functional networks are constrained by structural connections, context-sensitive integration during cognition tasks necessarily entails a divergence between structural and functional networks. This degenerate (many-to-one) function-structure mapping is crucial for understanding the nature of brain networks. The emergence of dynamic functional networks from static structural connections calls for a formal (computational) approach to neuronal information processing that may resolve this dialectic between structure and function.
The authors' abstract, as published at the source. Science, 2013 · DOI ↗
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Field: Cognitive Neuroscience
Cognitive NeuroscienceNeuroscience