Assessment of nonlinear changes in functional brain connectivity during aging using deep learning

Jiawei Sun; Blanca Zufiria Gerbolés; Daniel Vereb; Mite Mijalkov; Jesus Pineda Castro; Giovanni Volpe; Joana B. Pereira

doi:10.1117/12.2677365

6 October 2023 Assessment of nonlinear changes in functional brain connectivity during aging using deep learning

Jiawei Sun, Blanca Zufiria Gerbolés, Daniel Vereb, Mite Mijalkov, Jesus Pineda Castro, Giovanni Volpe, Joana B. Pereira

Proceedings Volume PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023; PC1265519 (2023) https://doi.org/10.1117/12.2677365
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States

Conference Poster

Abstract

The study focuses on the complex relationship between aging and functional brain connectivity, and the need for advanced artificial intelligence approaches to understanding them. To identify the underlying mechanisms that drive cognitive decline in aging, we present a novel graph attention network model to detect nonlinear changes in functional brain connections across the aging process. The results have the potential to improve our understanding of the complexities of aging-related diseases, such as Alzheimer's disease, and aid in the development of effective diagnostic tools and treatments.

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Jiawei Sun, Blanca Zufiria Gerbolés, Daniel Vereb, Mite Mijalkov, Jesus Pineda Castro, Giovanni Volpe, and Joana B. Pereira "Assessment of nonlinear changes in functional brain connectivity during aging using deep learning", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC1265519 (6 October 2023); https://doi.org/10.1117/12.2677365

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