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Subcortical and insula functional connectivity aberrations and clinical implications in first-episode schizophrenia.

Asian journal of psychiatry
INTRODUCTION: Schizophrenia is a complex mental disorder whose pathophysiology remains elusive, particularly in the roles of subcortex. This study aims to explore the role of subcortex and insula and their relationship with symptom changes in first-e...

Estimating global phase synchronization by quantifying multivariate mutual information and detecting network structure.

Neural networks : the official journal of the International Neural Network Society
In neuroscience, phase synchronization (PS) is a crucial mechanism that facilitates information processing and transmission between different brain regions. Specifically, global phase synchronization (GPS) characterizes the degree of PS among multiva...

The efficacy of topological properties of functional brain networks in identifying major depressive disorder.

Scientific reports
Major Depressive Disorder (MDD) is a common mental disorder characterized by cognitive impairment, and its pathophysiology remains to be explored. In this study, we aimed to explore the efficacy of brain network topological properties (TPs) in identi...

Aligned and oblique dynamics in recurrent neural networks.

eLife
The relation between neural activity and behaviorally relevant variables is at the heart of neuroscience research. When strong, this relation is termed a neural representation. There is increasing evidence, however, for partial dissociations between ...

A novel approach for brain connectivity using recurrent neural networks and integrated gradients.

Computers in biology and medicine
Brain connectivity is an important tool for understanding the cognitive and perceptive neural mechanisms in the neuroimaging field. Many methods for estimating effective connectivity have relied on the linear regressive model. However, the linear reg...

Distinct connectivity patterns between perception and attention-related brain networks characterize dyslexia: Machine learning applied to resting-state fMRI.

Cortex; a journal devoted to the study of the nervous system and behavior
Diagnosis of dyslexia often occurs in late schooling years, leading to academic and psychological challenges. Furthermore, diagnosis is time-consuming, costly, and reliant on arbitrary cutoffs. On the other hand, automated algorithms hold great poten...

Deep Learning Recognition of Paroxysmal Kinesigenic Dyskinesia Based on EEG Functional Connectivity.

International journal of neural systems
Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder marked by transient involuntary movements triggered by sudden actions. Current diagnostic approaches, including genetic screening, face challenges in identifying secondary cases ...

A Machine learning classification framework using fused fractal property feature vectors for Alzheimer's disease diagnosis.

Brain research
Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topological properties of these networks helps to understand the progression of the disease. Most studies focus on single-scale brain networks, but few add...

Damage explains function in spiking neural networks representing central pattern generator.

Journal of neural engineering
Complex biological systems have evolved to control movement dynamics despite noisy and unpredictable inputs and processing delays that necessitate forward predictions. The staple example in vertebrates is the locomotor control emerging from interacti...

Hypercomplex Graph Neural Network: Towards Deep Intersection of Multi-Modal Brain Networks.

IEEE journal of biomedical and health informatics
The multi-modal neuroimage study has provided insights into understanding the heteromodal relationships between brain network organization and behavioral phenotypes. Integrating data from various modalities facilitates the characterization of the int...