Keynote series Dr. Sharna Jamadar — Seeing the aging brain in a new light: “The power of fPET imaging”
By Alejandra Lopez-Castro
The human brain’s journey through time is marked by profound transformations that extend beyond the visible wrinkles of cortical atrophy or the gradual slowing of synaptic transmission. At the core of these changes lies a fundamental shift in how neural circuits fuel their operations and coordinate activity. Recent advances in neuroimaging have begun to illuminate the metabolic underpinnings of cognitive aging, revealing patterns of energetic reorganization that may hold the key to understanding why some minds remain sharp while others falter. Two pivotal studies, one published in Brain Communications by Dr. Deery and Dr. Jamadar and them colleagues and another in Nature Communications Biology, have converged on a groundbreaking insight: the brain’s metabolic connectivity, its intricate web of energy-dependent communication pathways, may offer superior predictive power for age-related cognitive decline compared to traditional measures of functional connectivity.
Deciphering Cognitive Aging Through Metabolic Connectivity
The Brain Communications study represents a methodological tour de force, employing both functional magnetic resonance imaging (fMRI) and functional positron emission tomography (fPET) in a carefully matched cohort of younger and older adults. While both imaging modalities detected age-related alterations in network organization, fPET’s metabolic measurements revealed more pronounced and clinically relevant changes. Older participants exhibited a marked decline in glucose-dependent coordination between higher-order cognitive regions, particularly within the prefrontal cortex and its connections to the default mode network. This metabolic decoupling was strongly correlated with diminished performance across multiple cognitive domains, including episodic memory, processing speed, and executive function. Intriguingly, the predictive power of metabolic connectivity remained robust even after accounting for structural brain changes, suggesting that energetic factors contribute independently to cognitive aging.
A Strategic Reorganization of Energy Utilization
Complementing these findings, the Nature Communications Biology study provides compelling evidence that age-related metabolic changes represent more than simple network degradation. Through sophisticated graph theoretical analyses of whole-brain metabolic patterns, researchers uncovered a systematic reorganization of energy utilization pathways. The aging brain appears to strategically redistribute its metabolic resources, preserving function in primary sensory and motor regions while sacrificing efficiency in association cortices. This metabolic shift follows principles of neuroeconomic adaptation, where the brain prioritizes the maintenance of basic operations at the expense of more energetically demanding higher cognitive functions. Longitudinal data suggest that this metabolic rewiring begins in midlife and accelerates with age, potentially serving as an early biomarker for future cognitive decline.
At the cellular level, these imaging findings align with emerging understandings of age-related mitochondrial dysfunction and oxidative stress. Neurons in the aging brain face increasing challenges in maintaining their energy budgets, particularly in regions with high metabolic demands. fPET data reveal that this energetic compromise does not manifest as uniform decline but rather as a selective redistribution of resources, reshaping the brain’s functional architecture. This explains why certain cognitive abilities, especially those dependent on prefrontal integration and rapid information transfer, show disproportionate vulnerability to aging, while more automated processes remain relatively intact.
Clinical Implications: A Shift Toward Energetic Biomarkers
The clinical significance of these discoveries is profound. Current diagnostic approaches to age-related cognitive impairment often focus on structural changes or amyloid deposition, potentially overlooking earlier metabolic warning signs. The strong correlation between metabolic connectivity patterns and cognitive performance suggests that fPET could serve as a highly sensitive tool for detecting preclinical decline. Moreover, the dynamic nature of metabolic reorganization opens the door for targeted interventions aimed at preserving or restoring energetic efficiency. Potential strategies might include metabolic modulators, ketogenic interventions, or precision neuromodulation techniques designed to optimize network energetics.
A Paradigm Shift in Cognitive Aging Research
Looking ahead, these studies call for a fundamental reconsideration of how we conceptualize and investigate brain aging. The traditional emphasis on structural integrity and functional activation patterns may need to be augmented, or even subordinated, to deeper analyses of metabolic networks. Future research directions could explore the genetic determinants of metabolic connectivity, its relationship to cerebrovascular health, and its potential as a therapeutic target. As neuroimaging technologies advance, enabling ever more precise measurements of brain metabolism in vivo, we may be standing at the threshold of a new era in cognitive aging research—one where supporting the brain’s energetic infrastructure becomes central to preserving cognitive vitality across the lifespan.
Ultimately, this metabolic perspective suggests that the resilience of the aging brain depends not merely on the preservation of its structural components or the stability of its activation patterns but on the ongoing optimization of its energy economy. The extent to which neural networks maintain efficient, flexible metabolic communication despite accumulating molecular damage and cellular stress may determine the trajectory of cognitive aging. By shifting our focus to these fundamental energetic processes, we may uncover new opportunities for early detection, prevention, and intervention in age-related cognitive decline, potentially transforming how we approach brain health in an aging population.
Don't miss the interview with Dr. Jamadar that you'll find in the blog post. And don't miss the keynote talk this June at the OHBM Annual Meeting 2025
Sources :
Deery, H.A., Liang, E.X., Siddiqui, M.N. et al. Reconfiguration of metabolic connectivity in ageing. Commun Biol 7, 1600 (2024). https://doi.org/10.1038/s42003-024-07223-0
Deery, H. A., Liang, E. X., Moran, C., Egan, G. F., & Jamadar, S. D. (2025). Metabolic connectivity has greater predictive utility for age and cognition than functional connectivity. Brain Communications, 7(1), fcaf075.
