Author ORCID Identifier
https://orcid.org/0009-0008-0217-3163
Date of Award
12-2024
Degree Type
Closed Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
First Advisor
Armin Iraji
Second Advisor
Vince Calhoun
Third Advisor
Jingyu Liu
Abstract
Psychotic disorders have a great amount of biological heterogeneity within diagnoses. This study explores this heterogeneity by leveraging multiscale functional network connectivity (msFNC) to identify distinct neurobiological psychosis biotypes to improve our understanding of the psychosis spectrum. Resting-State fMRI data from B-SNIP consortium (2103 participants: 626 controls, 1127 with psychosis, and 350 of their relatives) were analyzed. msFNC and its Latent Network Connectivity subspace were computed. Projections of psychosis participants revealed three neurobiology-based PSY biotypes with unique connectivity and cognitive characteristics. Biotype-1 characterized as the most cognitively impaired, and Biotype-2 is cognitively preserved psychosis group. First–degree relatives of psychosis participants were classified under psychosis biotypes as their family members, exhibiting shared neurobiological traits. These neurobiological distinct biotypes, sharing common brain and behavior patterns may promise a more homogenous therapeutic response, guiding future targeted treatment development and aiding in prognosis and enhancing diagnoses efforts.
Recommended Citation
Ballem, Adithya Ram, "Human Brain Latent Connectivity Independent Subspace Identifies Neurobiology Based Psychosis Biotypes." Thesis, Georgia State University, 2024.
https://scholarworks.gsu.edu/cs_theses/118
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