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Related Concept Videos

Organization of the Brain01:30

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The brain is an integral component of the nervous system and serves as the center for processing sensory inputs, making decisions, and directing bodily actions. This complex organ is organized into three primary sections: the hindbrain, midbrain, and forebrain, each responsible for a range of vital functions.
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Related Experiment Video

Updated: Jul 13, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
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Visibility graph analysis for brain: scoping review.

Sadegh Sulaimany1, Zhino Safahi1

  • 1Social and Biological Network Analysis Laboratory (SBNA), Department of Computer Engineering, University of Kurdistan, Sanandaj, Iran.

Frontiers in Neuroscience
|October 16, 2023
PubMed
Summary
This summary is machine-generated.

This review explores visibility graph (VG) methods for analyzing brain disorder time series data. It summarizes 51 studies, highlighting VG applications and suggesting future research directions.

Keywords:
EEGbrain disordersdiagnosisgraph analysisvisibility graph

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Area of Science:

  • Network science applied to neuroscience and medical data analysis.

Background:

  • Network-based analysis, particularly using visibility graphs (VG), is increasingly used for time series data.
  • VG transforms time series into networks, aiding in understanding, identifying, and predicting data characteristics across diverse fields.
  • Applications span medicine, economics, meteorology, and tourism, with growing interest in neurological and psychiatric conditions.

Purpose of the Study:

  • To conduct a scoping review of VG-based analysis methods specifically for brain disorders.
  • To establish a foundation for future research by synthesizing existing literature.
  • To introduce VG concepts and their relevance in analyzing complex medical time series.

Main Methods:

  • Systematic literature search in Google Scholar and Scopus for VG-based brain disorder studies.
  • Selection and analysis of 51 eligible English-language journal and conference articles.
  • Categorization of articles by publication year, VG type, ML algorithms, keywords, authors, institutions, metrics, network properties, and brain disorders.

Main Results:

  • The review covers various brain disorders including Epilepsy, Alzheimer's disease, Autism, Alcoholism, Sleep disorders, Fatigue, and Depression.
  • Analysis includes details on machine learning algorithms, network properties, and evaluation metrics used in VG applications.
  • Identified frequently occurring keywords, leading authors, and prominent universities in the field.

Conclusions:

  • Visibility graph analysis offers a robust framework for understanding brain disorder dynamics from time series data.
  • Future research should explore advanced techniques like graph machine learning and deep learning.
  • Expansion into understudied conditions such as ADHD and Parkinson's disease is recommended.