Abstract
Aging brain undergoes a structural decline over lifespan accompanied by changes in neurotransmitter levels, leading to altered functional markers. Past studies have reported human resting state brain display a remarkable preservation of coordination among neural assemblies stemming from an underlying neurocomputational principles along aging trajectories, however, the true nature of which remains unknown. Here, we identify the computational mechanisms with which neurotransmitters, such as altered GABA and glutamate concentrations, can preserve functional integration across lifespan aging, despite structural decline. We employ multiscale, biophysically grounded modeling, constrained by the empirically derived anatomical connectome of the human brain, where the neurotransmitter concentrations can be free parameters that are algorithmically adjusted to maintain regional homeostasis and optimal working point. The two estimated neurotransmitters can maintain critical firing rates in the brain region and mimic age-associated functional connectivity patterns, consistent with empirical observations. We identified invariant GABA and reduced glutamate as the principle computational mechanism that can explain the topological variation of functional connectivity along lifespan, validated using graph-theoretic metrics. The results are subsequently replicated on three distinct datasets. Thus, the study offers an operational framework that integrates brain network dynamics at macroscopic and molecular scales, to gain insight into age-associated neural disorders.