Abstract: Population aging has led to an increasing prevalence of cognitive decline and neurodegenerative disorders, creating an urgent need for effective intervention strategies. Non-pharmacological interventions, such as cognitive training and physical exercise, have consistently shown beneficial effects on cognitive functioning in older adults. However, existing studies largely focus on intervention-specific neural changes and lack a unified framework explaining whether different intervention modalities share common neurobiological mechanisms. To address this gap, the present work proposes the hypothesis that diverse non-pharmacological interventions may converge on a common large-scale brain network that mediates intervention-induced neuroplasticity and cognitive benefits. To identify and causally validate such a network, three complementary studies are proposed.
The first study aims to identify a core unifying biomarker underlying the beneficial effects of different interventions. Multimodal datasets collected from cognitively normal older adults who participated in cognitive training, exercise training, and multimodal intervention programs will be integrated into a unified intervention database. Resting-state functional MRI data will be harmonized using standardized preprocessing and site-effect correction procedures. To characterize large-scale functional organization, functional gradients will be derived from whole-brain connectivity matrices, while intrinsic timescales will be calculated to quantify hierarchical temporal processing across brain networks. Changes in these measures before and after intervention in the training group will be compared with those observed in control participants. Computational virtual-lesion analyses will then be employed to determine which large-scale network contributes most critically to intervention-related maintenance of youthful brain organization. Furthermore, structural and functional asymmetry measures will be used to distinguish whether intervention-related plasticity reflects compensatory recruitment or optimization of neural efficiency. This multidimensional framework integrates spatial hierarchy, temporal dynamics, and hemispheric specialization to identify convergent neural mechanisms shared across intervention modalities. The study is expected to reveal the dorsal attention network (DAN) as a candidate common brain network whose enhancement is associated with improved cognitive performance following intervention.
The second study provides causal validation of the identified network in cognitively normal older adults. Participants will be randomly assigned to active or sham stimulation groups and receive a two-week intervention using repetitive transcranial magnetic stimulation (rTMS). Based on findings from Study 1, stimulation will target a core hub of the DAN located in the superior parietal lobule. Behavioral performance will be assessed using the mnemonic similarity task, a sensitive measure of age-related memory decline. In addition, task-based functional magnetic resonance imaging will be conducted before and after intervention to examine neural activity and functional connectivity changes associated with memory discrimination. By directly modulating a network hub identified through large-scale neuroimaging analyses, this study tests whether enhancing DAN function improves cognitive performance and alters memory-related brain activity. Demonstrating such effects would provide causal evidence that the DAN represents a key neural substrate underlying the effectiveness of diverse non-pharmacological interventions.
The third study extends causal validation to older adults with subjective cognitive decline, a population widely considered to represent a preclinical stage of cognitive impairment. Using the same randomized sham-controlled rTMS protocol, participants will undergo stimulation targeting the DAN and complete standardized neuropsychological assessments together with the mnemonic similarity task before and after intervention. Unlike Study 2, the primary focus in Study 3 is behavioral improvement in a population at elevated risk for future cognitive decline. If stimulation-induced enhancement of DAN function produces measurable cognitive benefits in this group, the findings would demonstrate that the identified network contributes not only to healthy cognitive aging but also to resilience against pathological aging processes.
The present work contains two major innovations. The first is a theoretical innovation: it moves beyond intervention-specific explanations and introduces the concept of a common brain network shared across heterogeneous intervention modalities. This framework provides a unified account of how different interventions may promote cognitive resilience through convergent neuroplastic mechanisms. The second is a methodological innovation: by integrating functional gradients, intrinsic timescales, brain asymmetry measures, computational virtual-lesion analyses, task-based fMRI, and noninvasive brain stimulation, the study establishes a multidimensional and multimodal approach for investigating aging-related neuroplasticity. Importantly, the combination of large-scale neuroimaging analyses and randomized rTMS experiments creates a complete research pathway from mechanism discovery to causal verification across both healthy and pathological aging populations.
Overall, this work aims to establish a core unifying biomarker for evaluating intervention effectiveness, provide mechanistic insight into how non-pharmacological interventions delay cognitive decline, and identify potential neuromodulation targets for future precision interventions. These findings are expected to advance theoretical understanding of neuroplasticity in aging and contribute to the development of evidence-based strategies for promoting healthy aging and preventing dementia.

Key words: cognitive aging, non-pharmacological intervention, neural plasticity, unifying biomarker, multimodal neuroimaging