Disrupted Energetic and Entropic Landscape in Individuals With Mild Cognitive Impairment: Insights From Network...

Area of Science:

• Neuroscience
• Cognitive Science
• Medical Imaging

Background:

• The brain's functional activity organization in mild cognitive impairment (MCI) remains incompletely understood.
• Network Control Theory (NCT) and entropy analysis offer complementary approaches to quantify brain dynamics and energy landscapes.

Purpose of the Study:

• To investigate differences in brain energetic and entropic landscapes between individuals with MCI and healthy controls (HC).
• To explore the association between brain energetics, entropy, and neuropathological markers (amyloid-beta and tau) in MCI.

Main Methods:

• Functional MRI (fMRI) data from 499 HC and 55 MCI patients were analyzed using k-means clustering to identify brain activity states.
• Network Control Theory (NCT) was applied to calculate transition energy (TE) between states.
• Entropy of fMRI time series and PET-derived amyloid-beta (Aβ) and tau deposition were measured. Linear models were used for comparisons and association analyses.

Main Results:

• MCI patients exhibited lower transition energy in the limbic network compared to HC (adjusted p = 0.028).
• A significant decrease in global entropy was observed in MCI patients versus HC (p = 7.29e-7).
• Increased global Aβ was positively associated with higher global entropy in MCI patients (ρ = 0.632, p = 0.041).

Conclusions:

• Lower limbic network transition energy in MCI may reflect neurodegeneration or compensatory mechanisms.
• Reduced global entropy in MCI suggests altered brain complexity.
• Findings highlight potential alterations in brain network dynamics and energy landscapes in early cognitive impairment.