Graph theory in paediatric epilepsy: A systematic review.

Dialogues Clin Neurosci

Unit of Rare Diseases of the Nervous System in Childhood, Department of Clinical and Experimental Medicine, Section of Pediatrics and Child Neuropsychiatry, University of Catania, Catania, Italy.

Published: July 2022

Graph theoretical studies have been designed to investigate network topologies during life. Network science and graph theory methods may contribute to a better understanding of brain function, both normal and abnormal, throughout developmental stages. The degree to which childhood epilepsies exert a significant effect on brain network organisation and cognition remains unclear. The hypothesis suggests that the formation of abnormal networks associated with epileptogenesis early in life causes a disruption in normal brain network development and cognition, reflecting abnormalities in later life. Neurological diseases with onset during critical stages of brain maturation, including childhood epilepsy, may threaten this orderly neurodevelopmental process. According to the hypothesis that the formation of abnormal networks associated with epileptogenesis in early life causes a disruption in normal brain network development, it is then mandatory to perform a proper examination of children with new-onset epilepsy early in the disease course and a deep study of their brain network organisation over time. In regards, graph theoretical analysis could add more information. In order to facilitate further development of graph theory in childhood, we performed a systematic review to describe its application in functional dynamic connectivity using electroencephalographic (EEG) analysis, focussing on paediatric epilepsy.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286734PMC
http://dx.doi.org/10.1080/19585969.2022.2043128DOI Listing

Publication Analysis

Top Keywords

brain network
16
graph theory
12
paediatric epilepsy
8
systematic review
8
graph theoretical
8
network organisation
8
formation abnormal
8
abnormal networks
8
networks associated
8
associated epileptogenesis
8

Similar Publications

A 3D decoupling Alzheimer's disease prediction network based on structural MRI.

Health Inf Sci Syst

December 2025

School of Mathematics and Computing, University of Southern Queensland, 487-535 West Street, Toowoomba, QLD 4350 Australia.

Purpose: This paper aims to develop a three-dimensional (3D) Alzheimer's disease (AD) prediction method, thereby bettering current predictive methods, which struggle to fully harness the potential of structural magnetic resonance imaging (sMRI) data.

Methods: Traditional convolutional neural networks encounter pressing difficulties in accurately focusing on the AD lesion structure. To address this issue, a 3D decoupling, self-attention network for AD prediction is proposed.

View Article and Find Full Text PDF

Background: Recent years have seen persistently poor prognoses for glioma patients. Therefore, exploring the molecular subtyping of gliomas, identifying novel prognostic biomarkers, and understanding the characteristics of their immune microenvironments are crucial for improving treatment strategies and patient outcomes.

Methods: We integrated glioma datasets from multiple sources, employing Non-negative Matrix Factorization (NMF) to cluster samples and filter for differentially expressed metabolic genes.

View Article and Find Full Text PDF

Interaction between Th17 and central nervous system in multiple sclerosis.

Brain Behav Immun Health

February 2025

Centre for Infection and Immunity Studies, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, 518107, China.

Image 1.

View Article and Find Full Text PDF

Traumatic brain injury is widely viewed as a risk factor for dementia, but the biological mechanisms underlying this association are still unclear. In previous studies, traumatic brain injury has been associated with the hallmark pathologies of Alzheimer's disease, i.e.

View Article and Find Full Text PDF

Brain network control theory (NCT) is a groundbreaking field in neuroscience that employs system engineering and cybernetics principles to elucidate and manipulate brain dynamics. This review examined the development and applications of NCT over the past decade. We highlighted how NCT has been effectively utilized to model brain dynamics, offering new insights into cognitive control, brain development, the pathophysiology of neurological and psychiatric disorders, and neuromodulation.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!