AIMC Topic: Connectome

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Macroscale and microcircuit dissociation of focal and generalized human epilepsies.

Communications biology
Thalamo-cortical pathology plays key roles in both generalized and focal epilepsies, but there is little work directly comparing these syndromes at the level of whole-brain mechanisms. Using multimodal imaging, connectomics, and computational simulat...

Interpretable Learning Approaches in Resting-State Functional Connectivity Analysis: The Case of Autism Spectrum Disorder.

Computational and mathematical methods in medicine
Deep neural networks have recently been applied to the study of brain disorders such as autism spectrum disorder (ASD) with great success. However, the internal logics of these networks are difficult to interpret, especially with regard to how specif...

Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.

Human brain mapping
Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to ...

The NanoZoomer artificial intelligence connectomics pipeline for tracer injection studies of the marmoset brain.

Brain structure & function
We describe our connectomics pipeline for processing anterograde tracer injection data for the brain of the common marmoset (Callithrix jacchus). Brain sections were imaged using a batch slide scanner (NanoZoomer 2.0-HT) and we used artificial intell...

Ensemble Deep Learning on Large, Mixed-Site fMRI Datasets in Autism and Other Tasks.

International journal of neural systems
Deep learning models for MRI classification face two recurring problems: they are typically limited by low sample size, and are abstracted by their own complexity (the "black box problem"). In this paper, we train a convolutional neural network (CNN)...

Discriminating stress from rest based on resting-state connectivity of the human brain: A supervised machine learning study.

Human brain mapping
Acute stress induces large-scale neural reorganization with relevance to stress-related psychopathology. Here, we applied a novel supervised machine learning method, combining the strengths of a priori theoretical insights with a data-driven approach...

Alzheimer's disease, mild cognitive impairment, and normal aging distinguished by multi-modal parcellation and machine learning.

Scientific reports
A 360-area surface-based cortical parcellation is extended to study mild cognitive impairment (MCI) and Alzheimer's disease (AD) from healthy control (HC) using the joint human connectome project multi-modal parcellation (JHCPMMP) proposed by us. We ...

Bootstrapping promotes the RSFC-behavior associations: An application of individual cognitive traits prediction.

Human brain mapping
Resting-state functional connectivity (RSFC) records enormous functional interaction information between any pair of brain nodes, which enriches the individual-phenotypic prediction. To reduce high-dimensional features, correlation analysis is a comm...

Connectome-Based Propagation Model in Amyotrophic Lateral Sclerosis.

Annals of neurology
OBJECTIVE: Clinical trials in amyotrophic lateral sclerosis (ALS) continue to rely on survival or functional scales as endpoints, despite the emergence of quantitative biomarkers. Neuroimaging-based biomarkers in ALS have been shown to detect ALS-ass...

Hierarchical Organization of Functional Brain Networks Revealed by Hybrid Spatiotemporal Deep Learning.

Brain connectivity
Hierarchical organization of brain function has been an established concept in the neuroscience field for a long time, however, it has been rarely demonstrated how such hierarchical macroscale functional networks are actually organized in the human b...