Genetic factors have been proven to be one of the major determinants in shaping the neonatal cerebral cortex. Previous research has demonstrated distinct genetic influences on the spatial patterns of cortical thickness (CT) and surface area (SA) in neonates, leading to their unique genetically informed parcellation maps. However, these parcellation maps were derived at coarse scales and only reliant on single cortical properties, making them unable to comprehensively characterize the fine-grained genetically regulated patterns of the neonatal cerebral cortex. To fill this knowledge gap, by combining genetic correlations of multiple cortical properties (CT and SA) based on 202 twin neonates' brain magnetic resonance (MR) images, we performed multi-view spectral clustering and revealed the first joint, fine-grained, genetically informed parcellation map of the neonatal cerebral cortex. The discovered parcellation maps comprehensively reflect genetically regulated detailed patterns of the neonatal brain.
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http://dx.doi.org/10.1109/EMBC53108.2024.10782296 | DOI Listing |
Annu Int Conf IEEE Eng Med Biol Soc
July 2024
Spatiotemporal brain dynamism is a complex phenomenon, characterized by dynamic patterns of neural activity that unfold across both space and time. However, capturing these dynamic patterns poses a formidable challenge due to the sheer complexity of neural interactions and the demand for advanced computational models. In this context, we have harnessed advances in computer vision and formulated this challenging issue as the weakly supervised spatiotemporal dense prediction of dynamic brain networks.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2024
Genetic factors have been proven to be one of the major determinants in shaping the neonatal cerebral cortex. Previous research has demonstrated distinct genetic influences on the spatial patterns of cortical thickness (CT) and surface area (SA) in neonates, leading to their unique genetically informed parcellation maps. However, these parcellation maps were derived at coarse scales and only reliant on single cortical properties, making them unable to comprehensively characterize the fine-grained genetically regulated patterns of the neonatal cerebral cortex.
View Article and Find Full Text PDFbioRxiv
February 2025
School of Psychological Sciences, The Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
The mammalian brain is comprised of anatomically and functionally distinct regions. Substantial work over the past century has pursued the generation of ever-more accurate maps of regional boundaries, using either expert judgement or data-driven clustering of functional, connectional, and/or architectonic properties. However, these approaches are often purely descriptive, have limited generalizability, and do not elucidate the underlying generative mechanisms that shape the regional organization of the brain.
View Article and Find Full Text PDFNeuroimage
April 2025
Department of Artificial Intelligence, Korea University, Seoul 02841, Republic of Korea. Electronic address:
Deep learning (DL) for predicting Alzheimer's disease (AD) has provided timely intervention in disease progression yet still demands attentive interpretability to explain how their DL models make definitive decisions. Counterfactual reasoning has recently gained increasing attention in medical research because of its ability to provide a refined visual explanatory map. However, such visual explanatory maps based on visual inspection alone are insufficient unless we intuitively demonstrate their medical or neuroscientific validity via quantitative features.
View Article and Find Full Text PDFHum Brain Mapp
February 2025
Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Alcohol Use Disorder (AUD), a prevalent and potentially severe psychiatric condition, is one of the leading causes of morbidity and mortality. This systematic review investigates the relationship between AUD and resting-state functional connectivity (rsFC) derived from functional magnetic resonance imaging data. Following the PRISMA guidelines, a comprehensive search yielded 248 papers, and a screening process identified 39 studies with 73 relevant analyses.
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