Stallworthy, I. | Search bioRxiv

bioRxiv2026

Longitudinal changes in control energy of brain networks in older adults at familial risk for Alzheimers disease

The ability of structural brain networks to control neural dynamics is affected by healthy and pathological aging, including Alzheimers disease (AD). According to network control theory, transitions between functional brain states incur energetic costs. How these costs change longitudinally with aging remains unknown. Here, in 279 older adults at familial risk for AD, control energy increased longitudinally for state maintenance and transitions between sensorimotor and attentional networks, while decreasing for another sensorimotor--attentional transition. Changes in transition costs between higher-order networks were associated with cognitive performance: greater DorsAttn--Executive cost was associated with poorer immediate memory, while lower Executive--Def+Lim cost was associated with poorer attention. Higher plasma p-tau181 was associated with lower DorsAttn--Def+Lim transition cost. These findings reveal transition-specific alterations in the energetic landscape of aging and distinct relationships with cognition and AD pathology. Together, they highlight energetic constraints on brain network reconfiguration as a complementary perspective on neurocognitive aging.

neuroscience↗

bioRxiv2026

Development of the cognitive energy landscape from infancy to adolescence

Brain networks mature in a hierarchical sequence that parallels the emergence of cognitive functions. However, precisely how brain structural maturation supports the ordered development of cognitive functions remains largely unknown. Here, leveraging network control theory and 3712 developmental diffusion magnetic resonance imaging scans, we investigate how the brains structural effort to activate cognitive states -- quantified as control energy -- changes from infancy through adolescence. A total of 100 cognitive states were defined as meta-analytic activation maps from NeuroSynth, prioritized by their frequency in major neurodevelopmental behavioral assessments. We show that the control energy to drive most cognitive tasks decreases during development (for 96 out of 100 cognitive states). Ages to achieve optimal energy efficiency for each state concentrate around school age and late adolescence, whereas social and perceptual functions reach efficiency earlier (mean optimal age = 100.2 months) than higher-order cognitive functions (mean optimal age = 205.5 months). Further, we estimated the influence of molecular-level neurodevelopmental events on control energy by coupling control inputs to each events gene expression profile. We find that such influences vary in both temporal breadth and cognitive scope. Prenatal events (neuron differentiation and migration) exert effects mostly in infancy, while the prolonged process of myelination shapes the energy landscape across all developmental periods and the widest range of cognitive domains. Moreover, the transition energy architecture remains stable across development but becomes progressively modularized, such that transitions within the same category of cognitive states become increasingly favored. Together, these findings provide a comprehensive growth chart of how brain structural maturation supports the hierarchical emergence of cognitive abilities across early life, and establish a normative framework that enables systematic approaches to activate targeted brain circuits and facilitate selective cognitive transitions.

Developmental Biology↗