Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
The cognitive reserve (CR) hypothesis posits that individuals can differ in how their brain function is disrupted by pathology associated with aging and neurodegeneration. Here, we test this hypothesis in the continuum from cognitively normal to at-risk stages for Alzheimer's Disease (AD) to AD dementia using longitudinal data from 490 participants of the DELCODE multicentric observational study. Brain function is measured using task fMRI of visual memory encoding. Using a multivariate moderation analysis, we identify a CR-related activity pattern underlying successful memory encoding that moderates the detrimental effect of AD pathological load on cognitive performance. CR is mainly represented by a more pronounced expression of the task-active network encompassing deactivation of the default mode network (DMN) and activation of inferior temporal regions including the fusiform gyrus. We devise personalized fMRI-based CR scores that moderate the impact of AD pathology on cognitive performance and are positively associated with years of education. Furthermore, higher CR scores attenuate the effect of AD pathology on cognitive decline over time. Our findings primarily provide evidence for the maintenance of core cognitive circuits including the DMN as the neural basis of CR. Individual brain activity levels of these areas during memory encoding have prognostic value for future cognitive decline.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11561234 | PMC |
| http://dx.doi.org/10.1038/s41467-024-53360-9 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Role of CPEBs in Learning and Memory.
J Neurochem
September 2025
Astbury Centre for Structural Molecular Biology, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, UK.
Memory formation involves a complex interplay of molecular and cellular processes, including synaptic plasticity mechanisms such as long-term potentiation (LTP) and long-term depression (LTD). These processes rely on activity-dependent gene expression and local protein synthesis at synapses. A central unresolved question in neuroscience is how memories can be stably maintained over time, despite the transient nature of the proteins involved in their initial encoding.
View Article and Find Full Text PDFEngrams Formed in Virtual Reality Exhibit Reduced Familiarity Upon Retrieval: Electrophysiological Correlates of Source Memory Retrieval Indicate Modality-Dependent Differences in Recognition Memory.
Eur J Neurosci
September 2025
Experimental Psychology I, Institute of Psychology, Osnabrück University, Osnabrück, Germany.
Initial findings linking Virtual Reality (VR)-based encoding to increased recollection at retrieval remain inconclusive due to heterogeneous study designs and dependence on behavioral data. To clarify under which circumstances VR-based encoding affects or enhances episodic memory retrieval, the fundamental question remains whether the encoding modality, i.e.
View Article and Find Full Text PDFMulti-voxel pattern analysis of face and word encoding fMRI in people with temporal lobe epilepsy and healthy individuals.
Epilepsy Behav
September 2025
Department of Clinical and Experimental Epilepsy, University College London, London the United Kingdom of Great Britain and Northern Ireland; MRI Unit, Chalfont Centre for Epilepsy, Bucks, the United Kingdom of Great Britain and Northern Ireland. Electronic address:
Memory functional MRI (fMRI) has been used to explore cognitive processing in people with refractory temporal lobe epilepsy (TLE) to predict memory decline after anterior temporal lobe resection (ATLR). Traditional studies employed univariate analysis (UVA), focusing on isolated voxel activity in mesial temporal regions. By contrast, multivariate pattern analysis (MVPA), examines distributed activity patterns , offering deeper insight into neural networks supporting cognitive functions.
View Article and Find Full Text PDFPreRBP: Interpretable Deep Learning for RNA-Protein Binding Site Prediction with Attention Mechanism.
Anal Biochem
September 2025
School of Computer Science and Engineering, Southeast University, Nanjing 210000, China.
In the complex process of gene expression and regulation, RNA-binding proteins occupy a pivotal position for RNA. Accurate prediction of RNA-protein binding sites can help researchers better understand RNA-binding proteins and their related mechanisms. And prediction techniques based on machine learning algorithms are both cost-effective and efficient in identifying these binding sites.
View Article and Find Full Text PDFChromatin-associated condensates as an inspiration for the system architecture of future DNA computers.
Ann N Y Acad Sci
September 2025
Institute of Biological and Chemical Systems, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany.
The genome stores and processes approximately 1.5 gigabytes of encoded information. In this article, we propose that the eukaryotic genome and its adaptable three-dimensional packing in the form of chromatin offer a valuable template for the system architecture of DNA-based digital computers.
View Article and Find Full Text PDF