Schedule | CONNECTOMICS IN NEUROIMAGING - WORKSHOP |
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12:30 - 12:40 | Welcome and Opening remarks | 12:40 - 13:25 | Keynote: Consistent white matter tractography parcellation across the lifespan to study the brain's connections in health and disease Dr Fan Zhang Laboratory of Mathematics in Imaging, Harvard Medical School, USA Abstract: Diffusion MRI (dMRI) is the only modality that can non-invasively trace the human brain's white matter connections. dMRI allows the analysis of individual white matter fiber tracts in the brain via a process called tractography, which has been widely used for understanding neurological development, brain function, and brain disease. White matter tract parcellation, i.e. dividing the massive number of tractography fibers into multiple fiber parcels (or fiber fascicles), is the first and essential step to enable tract quantification and visualization. This talk will focus on an introduction to dMRI tractography parcellation and describe our recent work, including computational methods to enable consistent white matter parcellation across the lifespan and tractography analysis of the brain's connections in health and disease. |
13:25 - 13:37 | Oral 1: Covariance Shrinkage for Dynamic Functional Connectivity Nicolas Honnorat, Ehsan Adeli, Qingyu Zhao, Adolf Pfefferbaum, Edith V. Sullivan, Kilian Pohl |
13:37 - 13.49 | Oral 2: Rapid Acceleration of the Permutation Test via Transpositions Moo Chung, Linhui Xie, Shih-Gu Huang, Yixian Wang, Jingwen Yan, Li Shen |
13.49 - 14.01 | Oral 3: A Machine Learning Framework for Accurate Functional Connectome Fingerprinting and an Application of a Siamese Network Ali Shojaee, Kendrick Li, Gowtham Atluri |
14.01 - 14:13 | Oral 4: Unsupervised Feature Selection via Adaptive Embedding and Sparse Learning for Parkinson’s Disease Diagnosis Zhongwei Huang, Haijun Lei, Guoliang Chen, Shiqi Li, Hancong Li, Ahmed Elazab, Baiying Lei |
14:13 - 14:25 | Oral 5: A Novel Graph Neural Network to Localize Eloquent Cortex in Brain Tumor Patients from Resting-State fMRI Connectivity Naresh Nandakumar, Komal Manzoor, Jay J. Pillai, Sachin K. Gujar, Haris I. Sair, Archana Venkataraman |
14:25 - 15:10 | Keynote: Developmental Connectomics from Infancy through Early Childhood Prof. Yong He Beijing Key Laboratory of Brain Imaging & Connectomics, Beijing Normal University, China Abstract: The human brain undergoes rapid growth in both structure and function from infancy through early childhood, and this significantly influences cognitive and behavioral development in later life. Developmental connectomics provides unprecedented opportunities for exploring the developing brain through non-invasive mapping of structural and functional connectivity patterns. In this talk, I will describe the methodological framework of developmental connectomics and our recent works in connectome development from infancy to early childhood. Specifically, I will highlight five fundamental principles of brain network development during the critical first years of life, emphasizing strengthened segregation and integration balance, a remarkable hierarchical order from primary to higher-order regions, unparalleled structural and functional maturations, substantial individual variability, and high vulnerability to developmental disorders. |
15:10 - 16:00 | Posters and Coffee break |
CONNECTOMICS IN NEUROIMAGING - TRANSFER LEARNING CHALLENGE | |
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18:00 - 18:30 | CNI-Transfer Learning Challenge Opening remarks |
18:30 - 18:33 | Participant 1: Linear support vector machine framework to predict abnormal functional connectivity Team MEINTERNATIONAL - Hassna Irzan; Michael Hütel, Sebastien Ourselin, Neil Marlow, Andrew Melbourne |
18:33 - 18:36 | Participant 2: Classification ADHD disorder against healthy based on spectra of the normalized Laplacians Egor Levchenko |
18:36 - 18:39 | Participant 3: Domain Independent SVM for CNI challenge Shuo Zhou, Mwiza Kunda, Haiping Lu |
18:39 - 18:42 | Participant 4: Ensemble model for CNI Challenge Shuo Zhou, Mwiza Kunda, Haiping Lu |
18:42 - 18:45 | Participant 5: Learning generalizable recurrent neural networks from small task-fMRI datasets Nicha C. Dvornek, Juntang Zhuang |
18:45 - 19:45 | CNI-Evaluation & Discussion |
19:45 - 20:00 | Awards and Closing remarks |