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Neuromarkers of Adaptive Neuroplasticity and Cognitive Resilience Across Aging: A Multimodal Integrative Review
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Facultad de Medicina, Universidad Autónoma de Guadalajara, Guadalajara 45129, Mexico
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Facultad de Medicina, Universidad Autónoma del Estado de México, Toluca 50180, Mexico
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Facultad de Medicina, Universidad Lamar, Guadalajara 44110, Mexico
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Facultad de Medicina, Universidad Autónoma de Tamaulipas, Victoria 87149, Mexico
Abstract
Background: Aging is traditionally characterized by progressive structural and cognitive decline; however, increasing evidence shows that the aging brain retains a remarkable capacity for reorganization. This adaptive neuroplasticity supports cognitive resilience—defined as the ability to maintain efficient cognitive performance despite age-related neural vulnerability. Objective: To synthesize current molecular, cellular, neuroimaging, and electrophysiological neuromarkers that characterize adaptive neuroplasticity and to examine how these mechanisms contribute to cognitive resilience across aging. Methods: This narrative review integrates findings from molecular neuroscience, multimodal neuroimaging (fMRI, DTI, PET), electrophysiology (EEG, MEG, TMS), and behavioral research to outline multiscale biomarkers associated with compensatory and efficient neural reorganization in older adults. Results: Adaptive neuroplasticity emerges from the coordinated interaction of neurotrophic signaling (BDNF, CREB, IGF-1), glial modulation (astrocytic lactate metabolism, regulated microglial activity), synaptic remodeling, and neurovascular support (VEGF, nitric oxide). Multimodal neuromarkers—including preserved frontoparietal connectivity, DMN–FPCN coupling, synaptic density (SV2A-PET), theta–gamma coherence, and LTP-like excitability—consistently correlate with resilience in executive functions, memory, and processing speed. Behavioral enrichment, physical activity, and cognitive training further enhance these biomarkers, creating a bidirectional loop between experience and neural adaptability. Conclusions: Adaptive neuroplasticity represents a fundamental mechanism through which older adults maintain cognitive function despite biological aging. Integrating molecular, imaging, electrophysiological, and behavioral neuromarkers provides a comprehensive framework to identify resilience trajectories and to guide personalized interventions aimed at preserving cognition. Understanding these multilevel adaptive mechanisms reframes aging not as passive decline but as a dynamic continuum of biological compensation and cognitive preservation.
Keywords:
aging; neuroplasticity; cognitive resilience; neuromarkers; BDNF; fMRI; electrophysiology; neuroimaging; compensation; aging brain1. Introduction
Aging is accompanied by complex neurobiological changes that modify the structure and function of the brain. For decades, this process was primarily described in terms of decline—characterized by synaptic loss, reduced neurogenesis, and progressive cognitive impairment [1,2,3,4]. However, recent evidence challenges this unidirectional view by showing that the aging brain retains a remarkable capacity for adaptation and reorganization, a phenomenon known as adaptive neuroplasticity [1,4,5,6,7].
Neuroplasticity encompasses the brain’s ability to modify neural circuits in response to internal or external stimuli, maintaining homeostasis and optimizing cognitive performance [1,4,8,9,10,11,12]. In older adults, adaptive plasticity can manifest as compensatory recruitment of alternative neural pathways, strengthening of residual synapses, or increased functional connectivity within critical cognitive networks [2,5,6,7,10,13]. These compensatory mechanisms are thought to underlie cognitive resilience, defined as the ability to maintain functional cognition despite age-related structural or molecular changes [13,14,15,16,17,18,19].
Understanding the biological basis of this adaptive capacity has led to increasing interest in neuromarkers—objective indicators of neural processes that reflect the state or efficiency of neuroplastic mechanisms. Neuromarkers can be derived from multiple levels of analysis, including molecular signatures such as BDNF, CREB, and synapsin [20,21,22,23,24,25,26,27,28], neuroimaging correlates linked to network reorganization or connectivity [2,29,30,31,32,33,34,35,36,37,38,39], and electrophysiological measures of cortical excitability and oscillatory dynamics [40,41,42,43,44,45]. Integrating these multimodal biomarkers provides a framework for identifying how some individuals sustain high cognitive performance despite structural brain aging [17,18,19,46,47,48].
This review aims to synthesize current evidence linking neuromarkers of adaptive neuroplasticity to cognitive resilience across aging. By bridging molecular, imaging, and behavioral domains, it seeks to clarify how plasticity-related processes contribute to the preservation of cognition and to highlight emerging biomarkers that may guide early detection and preventive interventions against cognitive decline [18,19,49,50].
8. Discussion
The growing evidence summarized in this review supports a paradigm shift in the understanding of brain aging—from a model of progressive decline to one of dynamic adaptation [2,3,4,5,6,7,8,11,12,13,51,52]. Rather than a passive loss of neural resources, the aging brain displays a remarkable ability to reorganize its structure and function to preserve cognition [15,16,20,45,46,47,48,53,70,71,72,85]. This adaptive neuroplasticity, underpinned by molecular, glial, and vascular mechanisms, constitutes the biological substrate of cognitive resilience [21,22,23,24,25,26,27,28,31,55,56,57,58,59,60,61,62,63,64,65,69].
Importantly, neuromarker interpretation in aging should not rely on a simplified linear framework in which higher values are automatically equated with adaptive neuroplasticity or preserved neural health [25,26,56,57]. In older adults, increases in neuromarkers such as BDNF expression, functional connectivity strength, or regional metabolic activity may reflect compensatory responses to declining efficiency in downstream signaling pathways rather than enhanced function per se [27,28,58,59]. Evidence from neuroimaging and molecular studies indicates that such compensatory upregulation may coexist with reduced network efficiency, altered excitation–inhibition balance, or increased energetic cost during cognitive performance [60,61,62,63].
In addition, aging-related neuromarkers should not be interpreted independently of age range, cognitive status, or measurement context. Neuroimaging and electrophysiological metrics obtained during resting-state conditions may index baseline network organization, whereas task-based measures more directly reflect compensatory recruitment or neural efficiency under cognitive demand [32,33,34,35,36]. Importantly, these patterns vary across the aging spectrum, with younger-old adults often exhibiting flexible compensatory engagement, while older-old individuals may show overactivation associated with reduced performance or increased neural cost [37,38,39,40,41].
Thus, the functional meaning of a given neuromarker is context-dependent and influenced by age range, cognitive status, task demands, and interactions with other biological signals, including inflammatory and vascular factors [64,65,66,69]. As a result, similar neuromarker profiles may carry fundamentally different implications in cognitively resilient older adults compared with individuals at risk for cognitive decline, underscoring the need for cautious and integrative interpretation when evaluating biomarkers of adaptive plasticity in aging populations [29,30,31,67].
However, the heterogeneity of findings across studies underscores that neuroplasticity is not uniformly beneficial. Some compensatory activations may reflect inefficiency rather than resilience, particularly when overactivation of frontal or parietal networks accompanies declining cognitive performance [17,45,46,47,48,72,85,101]. Disentangling adaptive from maladaptive reorganization therefore remains a major conceptual challenge. Future research should integrate longitudinal designs and mechanistic approaches to distinguish compensatory recruitment that sustains function from neural responses that precede cognitive exhaustion [17,18,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,54,66,67,70,71,72,74,75,82,99,100,101,102].
Another critical point concerns the bidirectional relationship between behavior and biology. Lifestyle factors—such as physical activity, intellectual engagement, and social interaction—can modulate neurotrophic signaling, network organization, and metabolic efficiency [21,22,23,24,49,50,55,88,89,90,91,92,93,94,95], thereby creating a feedback loop between experience and brain biology. Conversely, molecular deficits, including reduced BDNF availability or impaired neurovascular coupling, may constrain the effectiveness of behavioral interventions [21,22,23,24,25,26,27,28,55,56,57,60,61,62]. This interplay highlights the necessity of multilevel models that integrate molecular, network, and behavioral dimensions to fully capture the determinants of cognitive resilience [17,18,45,46,47,48,54,72,75,85,99,100,101,102].
Beyond biological factors, environmental and experiential determinants play a critical role in shaping adaptive neuroplasticity and cognitive resilience in aging. Educational attainment, occupational complexity, physical activity, and sustained cognitive engagement have been consistently associated with more efficient network organization, preserved functional connectivity, and modulation of neurotrophic signaling pathways in older adults [21,22,23,24,49,50,55,88,89,90,91,92,93,94,95]. These factors contribute to cognitive reserve, influencing how neural systems respond to age-related stressors and modifying the functional expression of neuromarkers observed in neuroimaging and molecular studies.
Consequently, similar neuromarker profiles may therefore reflect distinct underlying mechanisms depending on an individual’s environmental background and life-course exposures. For example, increased functional connectivity or metabolic activity may support resilience in individuals with higher cognitive reserve, while representing compensatory strain or inefficiency in less enriched contexts [17,18,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,54,66,67,72,74,75,82,99,100,101,102]. Integrating environmental determinants into neuromarker-based models is thus essential for accurate interpretation and for advancing precision approaches to cognitive aging.
Importantly, resilience should not be conflated with resistance to aging, but rather conceptualized as adaptive recalibration in response to age-related biological change [17,18,54,70,71,72,99,100,101,102]. The presence of preserved or reorganized neural networks does not imply the absence of pathology, but instead reflects the engagement of compensatory mechanisms that maintain functional homeostasis [17,45,46,47,48,72,85,101]. Integrating multimodal neuromarkers within this framework enables a more nuanced view of brain aging—one characterized not by inevitable loss, but by the dynamic balance between degeneration and adaptation. This perspective aligns with the emerging paradigm of precision cognitive aging, which emphasizes individualized trajectories shaped by biological, environmental, and experiential factors [19,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,54,66,67,74,75,82,83,84,85,86,102].
9. Conclusions
Adaptive neuroplasticity represents a central mechanism through which the aging brain preserves cognitive function and reorganizes itself in response to biological and environmental demands [5,6,7,11,12,13,17,18,51,52,54,70,71,72,99,100,101,102]. Rather than a passive trajectory of decline, aging reflects a continuous interplay between degeneration and compensation—an evolving equilibrium shaped by molecular, glial, vascular, and network-level processes [15,16,17,18,19,20,27,28,31,44,45,46,47,48,53,54,58,59,60,61,62,63,64,65,69,70,71,72,83,84,85,86,99,100,101,102].
Neuromarkers such as BDNF, CREB, IGF-1, VEGF, indices of synaptic integrity, functional connectivity, white-matter structure, and cortical excitability provide quantifiable windows into these adaptive mechanisms [19,21,22,23,24,25,26,27,28,37,38,39,40,41,55,56,57,58,59,60,61,62,83,84]. Importantly, physiological measures of plasticity obtained through non-invasive brain stimulation—including TMS, tDCS, paired associative stimulation, and theta-burst paradigms—offer robust biomarkers of cortical adaptability across the lifespan [77,78,79,80,81,96,97,98,103,104,108,109]. These neurophysiological signatures complement molecular and imaging-based neuromarkers, strengthening multimodal models of aging [78,79,96,97,98,103,104].
Integrating neuromarkers across biological scales—from cellular metabolism and neurotrophic signaling to network reorganization and behavioral performance—provides a unified framework to understand how cognitive resilience emerges from plasticity [17,18,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,45,46,47,48,54,66,67,70,71,72,74,75,82,85,99,100,101,102]. Evidence that cortical plasticity varies across individuals, influenced by genetic, lifestyle, and neurobiological factors, further reinforces the need for personalized models of aging [80,81,103,104].
The convergence of molecular neuroscience, multimodal imaging, electrophysiology, and cognitive science demonstrates that plasticity and vulnerability coexist across the lifespan [17,18,45,46,47,48,54,70,71,72,85,99,100,101,102]. The future of aging research will depend on the development of composite biomarker signatures, incorporation of TMS- and EEG-based plasticity metrics, and implementation of personalized interventions guided by individual plasticity fingerprints [19,44,45,46,47,48,49,50,54,74,75,78,79,80,81,82,83,84,85,86,88,89,90,91,92,93,94,95,96,97,98,102,103,104].
Recognizing neuroplasticity as a lifelong capacity reframes aging not as a trajectory of inevitable decline, but as a dynamic continuum of biological adaptability and cognitive resilience [17,18,19,44,45,46,47,48,54,68,70,71,72,73,76,80,81,83,84,85,86,87,99,100,101,102,103,104,105,106,107,110,111].
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