Two-Dimensional Latent Space Manifold of Brain Connectomes Across the Spectrum of Clinical Cognitive Decline
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| Foilsithe in: | Bioengineering vol. 12, no. 8 (2025), p. 819-839 |
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| Príomhchruthaitheoir: | |
| Rannpháirtithe: | , , , , , |
| Foilsithe / Cruthaithe: |
MDPI AG
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| Ábhair: | |
| Rochtain ar líne: | Citation/Abstract Full Text + Graphics Full Text - PDF |
| Clibeanna: |
Níl clibeanna ann, Bí ar an gcéad duine le clib a chur leis an taifead seo!
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MARC
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| 001 | 3243983851 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2306-5354 | ||
| 024 | 7 | |a 10.3390/bioengineering12080819 |2 doi | |
| 035 | |a 3243983851 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Güneş, Bayır |u VAVlab, Department of Electrical & Electronics Engineering, Boğaziçi University, Istanbul 34342, Türkiye | |
| 245 | 1 | |a Two-Dimensional Latent Space Manifold of Brain Connectomes Across the Spectrum of Clinical Cognitive Decline | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Alzheimer’s Disease and Dementia (ADD) progresses along a continuum of cognitive decline, typically from Subjective Cognitive Impairment (SCI) to Mild Cognitive Impairment (MCI) and eventually to dementia. While many studies have focused on classifying these clinical stages, fewer have examined whether brain connectomes encode this continuum in a low-dimensional, interpretable form. Motivated by the hypothesis that structural brain connectomes undergo complex yet compact changes across cognitive decline, we propose a Graph Neural Network (GNN)-based framework that embeds these connectomes into a two-dimensional manifold to capture the evolving patterns of structural connectivity associated with cognitive deterioration. Using attention-based graph aggregation and Principal Component Analysis (PCA), we find that MCI subjects consistently occupy an intermediate position between SCI and ADD, and that the observed transitions align with known clinical biomarkers of ADD pathology. This hypothesis-driven analysis is further supported by the model’s robust separation performance, with ROC-AUC scores of 0.93 for ADD vs. SCI and 0.81 for ADD vs. MCI. These findings offer an interpretable and neurologically grounded representation of dementia progression, emphasizing structural connectome alterations as potential markers of cognitive decline. | |
| 653 | |a Alzheimer's disease | ||
| 653 | |a Deep learning | ||
| 653 | |a Principal components analysis | ||
| 653 | |a Hypotheses | ||
| 653 | |a Brain research | ||
| 653 | |a Graph neural networks | ||
| 653 | |a Dementia | ||
| 653 | |a Neural networks | ||
| 653 | |a Dementia disorders | ||
| 653 | |a Classification | ||
| 653 | |a Regions | ||
| 653 | |a Biomarkers | ||
| 653 | |a Brain | ||
| 653 | |a Cognitive ability | ||
| 653 | |a Neurodegenerative diseases | ||
| 653 | |a Survival analysis | ||
| 653 | |a Impairment | ||
| 700 | 1 | |a Yüksel Dal Demet |u Department of Electrical & Electronics Engineering, Fatih Sultan Mehmet Vakıf University, Istanbul 34015, Türkiye; dyukseldal@fsm.edu.tr | |
| 700 | 1 | |a Harı Emre |u Hulusi Behçet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, Istanbul 34093, Türkiye; emre.hari@istanbul.edu.tr (E.H.); psk.ulasay@gmail.com (U.A.) | |
| 700 | 1 | |a Ay Ulaş |u Hulusi Behçet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, Istanbul 34093, Türkiye; emre.hari@istanbul.edu.tr (E.H.); psk.ulasay@gmail.com (U.A.) | |
| 700 | 1 | |a Gurvit Hakan |u Behavioral Neurology and Movement Disorders Unit, Department of Neurology, Faculty of Medicine, Istanbul University, Istanbul 34093, Türkiye; gurvit@istanbul.edu.tr | |
| 700 | 1 | |a Alkan, Kabakçıoğlu |u Department of Physics, Koç University, Istanbul 34450, Türkiye; akabakcioglu@ku.edu.tr | |
| 700 | 1 | |a Acar Burak |u VAVlab, Department of Electrical & Electronics Engineering, Boğaziçi University, Istanbul 34342, Türkiye | |
| 773 | 0 | |t Bioengineering |g vol. 12, no. 8 (2025), p. 819-839 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3243983851/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3243983851/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3243983851/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |