AIMC Topic: Connectome
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Separating group- and individual-level brain signatures in the newborn functional connectome: A deep learning approach.
NeuroImage
Aug 22, 2024
Recent studies indicate that differences in cognition among individuals may be partially attributed to unique brain wiring patterns. While functional connectivity (FC)-based fingerprinting has demonstrated high accuracy in identifying adults, early s...
Unveiling the core functional networks of cognition: An ontology-guided machine learning approach.
NeuroImage
Aug 20, 2024
Deciphering the functional architecture that underpins diverse cognitive functions is fundamental quest in neuroscience. In this study, we employed an innovative machine learning framework that integrated cognitive ontology with functional connectivi...
Predicting treatment outcomes in patients with panic disorder: Cross-sectional and two-year longitudinal structural connectome analysis using machine learning methods.
Journal of anxiety disorders
Jul 26, 2024
PURPOSE: This study examined the relationship between structural brain networks and long-term treatment outcomes in patients with panic disorder (PD) using machine learning methods.
Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach.
NeuroImage
Jun 14, 2024
Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed...
Recovering high-quality fiber orientation distributions from a reduced number of diffusion-weighted images using a model-driven deep learning architecture.
Magnetic resonance in medicine
Jun 9, 2024
PURPOSE: The aim of this study was to develop a model-based deep learning architecture to accurately reconstruct fiber orientation distributions (FODs) from a reduced number of diffusion-weighted images (DWIs), facilitating accurate analysis with red...
Contrastive Brain Network Learning via Hierarchical Signed Graph Pooling Model.
IEEE transactions on neural networks and learning systems
Jun 4, 2024
Recently, brain networks have been widely adopted to study brain dynamics, brain development, and brain diseases. Graph representation learning techniques on brain functional networks can facilitate the discovery of novel biomarkers for clinical phen...
BAI-Net: Individualized Anatomical Cerebral Cartography Using Graph Neural Network.
IEEE transactions on neural networks and learning systems
Jun 3, 2024
Brain atlas is an important tool in the diagnosis and treatment of neurological disorders. However, due to large variations in the organizational principles of individual brains, many challenges remain in clinical applications. Brain atlas individual...
Anatomy-Guided Spatio-Temporal Graph Convolutional Networks (AG-STGCNs) for Modeling Functional Connectivity Between Gyri and Sulci Across Multiple Task Domains.
IEEE transactions on neural networks and learning systems
Jun 3, 2024
The cerebral cortex is folded as gyri and sulci, which provide the foundation to unveil anatomo-functional relationship of brain. Previous studies have extensively demonstrated that gyri and sulci exhibit intrinsic functional difference, which is fur...
A machine-learning approach for differentiating borderline personality disorder from community participants with brain-wide functional connectivity.
Journal of affective disorders
May 26, 2024
BACKGROUND: Functional connectivity has garnered interest as a potential biomarker of psychiatric disorders including borderline personality disorder (BPD). However, small sample sizes and lack of within-study replications have led to divergent findi...
Oral ketamine effects on dynamics of functional network connectivity in patients treated for chronic suicidality.
European archives of psychiatry and clinical neuroscience
May 21, 2024
The underlying brain mechanisms of ketamine in treating chronic suicidality and the characteristics of patients who will benefit from ketamine treatment remain unclear. To address these gaps, we investigated temporal variations of brain functional sy...
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