The balance of local and distributed excitation shapes brain stability and reflects aging- and Alzheimer's disease-related alterations

The human brain's function arises from the complex interplay between local activity and inter-regional interactions. Yet, a clear framework to measure this balance between these two factors across the entire brain has been missing. In this study, researchers built upon an existing biophysical model to quantify inter-regional excitation and introduced a new metric called the recurrent ratio (R-ratio).

This ratio reflects the relative balance between excitation that occurs within specific brain regions (intra-regional) and between different regions (inter-regional).

Through dynamical analyses, the researchers found that an optimal R-ratio helps maintain a balance between network stability and flexibility. When they applied this framework to study healthy aging and Alzheimer's disease, they observed a trend of progressively higher R-ratios in both conditions as age increased or disease severity progressed.

In healthy individuals, a higher R-ratio correlated with changes in brain morphology, molecular pathology, and cognitive abilities that are commonly associated with aging. In contrast, Alzheimer's disease was marked by elevated R-ratios combined with reduced dynamical persistence, indicating a loss of stability in brain network dynamics.

Overall, these findings present the R-ratio as a biologically meaningful indicator of the balance between excitation within and between brain regions. This new metric not only enhances our understanding of the underlying mechanisms at play but also offers a valuable tool for linking large-scale brain dynamics with the processes of aging and neurodegeneration.