Brain signaling becomes less integrated and more segregated with age
Rostam M Razban1, Botond B Antal2,3, Ken A Dill1,4,5
1Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA.
Brain activity shows decreased integration and increased segregation with age. This shift, observed in functional MRI data, reflects weakened regional connections, not changes in brain structure.
Area of Science:
- Neuroscience
- Physics
- Medical Imaging
Background:
- The integration-segregation framework simplifies brain dynamics into global (integration) and local (segregation) signaling states.
- Defining these brain states lacks a standardized approach, hindering consistent analysis.
- The Ising model from physics offers a framework to define order (integration) and disorder (segregation) states.
Purpose of the Study:
- To quantitatively define and calculate brain integration and segregation probabilities (P_int, P_seg) using the Ising model.
- To investigate how these brain states change with age.
- To determine if age-related changes in brain dynamics are linked to connection strength or network topology.
Main Methods:
- Mapped integration and segregation to order and disorder states of the Ising model.
- Calculated state probabilities (P_int, P_seg) from functional MRI (fMRI) data.
- Analyzed changes across three independent databases and compared with structural and diffusion MRI data.
Main Results:
- Integration (P_int) significantly decreases with advancing age.
- Segregation (P_seg) significantly increases with advancing age across all datasets.
- Observed changes correlate with weakened functional connection strength, not alterations in structural connectivity.
Conclusions:
- Age-related decline in brain integration and rise in segregation are robust findings.
- These dynamics shifts are primarily driven by reduced connection strength between brain regions.
- Findings provide a novel physics-based method for analyzing brain dynamics and its aging trajectory.
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