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Del Mauro, G.

Publications and source records attributed to Del Mauro, G..

3 recordsLinked to original sources

Normative Brain Entropy Across the Lifespan

Brain entropy (BEN) offers a unique perspective into brains functioning by characterizing the irregularity and randomness of brain activity. We used multiscale entropy (MSE) to estimate BEN from rs-fMRI at different timescales (from Scale 1 to Scale 5). Using a GMALSS framework, we showed that the aging trajectory of entropy differs at different timescales. Specifically, entropy increases with aging at Scale 1, the curve flattens at Scale 2, and the pattern finally reverses from Scale 3 onward, showing that entropy decreases with aging. Entropy at coarser scales (from Scale 2) showed positive correlations with measures of brain metabolism, including oxygen and glucose metabolism, whereas Scale 1 entropy displayed a trend for negative correlation. In addition, we explored the relationship between BEN and fluid intelligence (FI). Using moderated mediation models, we showed that brain entropy mediates the association between age and FI, and that the relationship between entropy and FI is itself moderated by age, indicating that entropy can either attenuate or exacerbate age-related differences in cognitive performance, depending on life stage. Finally, we used BEN to predict age. The best accuracy was achieved using the GPR (R2=0.80, MAE=7.25 years). Importantly, the difference between predicted and chronological age (brain age gap, BAG) was weakly associated with FI in an age-dependent manner, suggesting that lower entropy patterns relative to age-matched individuals may be associated with better cognitive performance during midlife, whereas higher entropy patterns may be associated with better cognition in older age.

neuroscience↗

rsfMRI-based Brain Entropy is negatively correlated with Gray Matter Volume and Surface Area

In recent years, brain entropy (BEN) has been ossociated with a number of neurocognitive, biological, and sociodemographic variables. However, its link with brain morphology is still unknown. In this study, we use resting-state fMRI (rsfMRI) data to estimate BEN maps and investigate their associations with three metrics of brain morphology: gray matter volume (GMV), surface area (SA), and cortical thickness (CT). Separate analyses will be performed on BEN maps derived from four distinct rsfMRI runs, and using both a voxelwise and a regions of interest (ROIs) approach. Our findings consistently showed that lower BEN (i.e., higher temporal coherence of brain activity) was related to increased GMV and SA in the lateral frontal and temporal lobes, inferior parietal lobules, and precuneus. We hypothesize that lower BEN and higher SA might both reflect higher brain reserve as well as increased information processing capacity.

neuroscience↗

Cross-subject brain entropy mapping

We present a method to map the regional similarity between resting state fMRI activities of different individuals. The similarity was measured using cross-entropy. Group level patterns were displayed based on the Human Connectome Project Youth data. While we only showed the cross-subject brain entropy (BEN) mapping results in this manuscript, the same concept can be directly extended to map the cross-sessional BEN and the cross-regional cross-subject or subject-session BEN.

neuroscience↗