(A) novel method for quantification of cognitive reserve using multi-modal neuroimaging

Abstract

The concept of cognitive reserve (CR) originated from discrepancies between brain pathology and the severity of clinical manifestations. CR has been characterized through CR proxies

however, such approaches have inherent limitations. Although several methods have been developed to overcome these limitations, they fail to reflect the entire Alzheimer’s disease neuropathology. Meanwhile, graph theoretic analysis has established remarkable network features of the brain. In neurodegenerative disease like AD, the functional and structural brain networks are damaged. Here, using multimodal neuroimaging, we developed a novel model to estimate CR based on the relationship between AD pathology and cognitive function. We hypothesize CR as a residual of actual performance and expected performance from AD pathology, demographics and genetic factor. Then, we correlated this marker with conventional CR proxies. We validated this marker by testing whether it would modulate the effect of brain pathology on memory function. Furthermore, we verified the proposed method through external validation using another dataset. Finally, we investigated how the CR marker affected clinical progression in AD spectrum and cognitively unimpaired group. To identify the neural substrates associated with CR, we performed graph analysis to explore the relationship between CR and network measures at different granularities. We identified that these local network parameters would modulate the effect of brain pathology on cognition. This study demonstrates that proposed CR model using multimodal neuroimaging captures CR comprehensively, representing the paradoxical phenomenon of CR. These findings will foster understanding of AD and be useful to help identify individuals with vulnerability or resistance to AD pathology, and characterize patients for intervention or pharmacologic trials.