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Abstract #0142

Dedifferentiation of functional hierarchical axis captures individual differences in cognition performance and disease progression

Chenye Shen1, Chaoqiang Liu1, Nanguang Chen1, and Anqi Qiu1,2,3
1Biomedical Engineering, National University of Singapore, Singapore, Singapore, 2Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung hom, Hong Kong, 3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States

Synopsis

Keywords: Functional Connectivity, Aging

Motivation: The healthy aging brain exhibits functional dedifferentiation, yet a consensus on its characterization remains elusive, hindering individual-level assessment of unhealthy aging.

Goal(s): We aim to utilize the functional hierarchical axis to elucidate primary alterations in functional dedifferentiation during healthy aging.

Approach: We developed a measure to quantify the heterogeneity of network dedifferentiation along the functional hierarchical axis, and assessed its relevance to cognition and neurological diseases at an individual level.

Results: Functional dedifferentiation in attention and control networks captures substantial individual differences in aging, cognition, and diseases. The heterogeneity of functional dedifferentiation along the functional hierarchical axis predicts domain-specific disease risk.

Impact: Brain aging primarily entails association and control network integrity deterioration on the functional hierarchical axis. The individual differences of functional dedifferentiation on this axis provide risk assessments of unhealthy brain aging.

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