ReviewComputational intelligence and neuroscience2021
Brain Connectivity Studies on Structure-Function Relationships: A Short Survey with an Emphasis on Machine Learning.
Review in Computational intelligence and neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of the relationship between magnetic resonance imaging based resting-state and structural networks in the rodent brain.Frontiers in neuroscience · 2023Pooled it
- Gut bacteria and their metabolites may influence our decisions, intelligence, cognition, and consciousness.Gut microbes · 2026Review
- Neural self-organization during episodic encoding: deep recurrent effective connectivity from source-localized EEG.Frontiers in psychology · 2026Article
- Evaluating topological and graph-theoretical approaches to extract complex multimodal brain connectivity patterns in multiple sclerosis.Health information science and systems · 2025Article
- Navigation in brain networks is possible using only local measures.Scientific reports · 2025Article
- Biomarker Investigation Using Multiple Brain Measures from MRI Through Explainable Artificial Intelligence in Alzheimer's Disease Classification.Bioengineering (Basel, Switzerland) · 2025Article
- Novel approaches to EEG and MEG in motor neurone disease: IFCN Handbook Chapter.Clinical neurophysiology practice · 2025Review
- Fibration symmetry-breaking supports functional transitions in a brain network engaged in language.ArXiv · 2024Article
- Fibration symmetry-breaking supports functional transitions in a brain network engaged in language.Research square · 2024Article
- Early detection of Alzheimer's disease in structural and functional MRI.Frontiers in medicine · 2024Article
- Brain connectomics: time for a molecular imaging perspective?Trends in cognitive sciences · 2023Review
- Forecasting brain activity based on models of spatiotemporal brain dynamics: A comparison of graph neural network architectures.Network neuroscience (Cambridge, Mass.) · 2022Article
- Structural and functional deficits and couplings in the cortico-striato-thalamo-cerebellar circuitry in social anxiety disorder.Translational psychiatry · 2022Article
- Generative Models of Brain Dynamics.Frontiers in artificial intelligence · 2022Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This short survey reviews the recent literature on the relationship between the brain structure and its functional dynamics. Imaging techniques such as diffusion tensor imaging (DTI) make it possible to reconstruct axonal fiber tracks and describe the structural connectivity (SC) between brain regions. By measuring fluctuations in neuronal activity, functional magnetic resonance imaging (fMRI) provides insights into the dynamics within this structural network. One key for a better understanding of brain mechanisms is to investigate how these fast dynamics emerge on a relatively stable structural backbone. So far, computational simulations and methods from graph theory have been mainly used for modeling this relationship. Machine learning techniques have already been established in neuroimaging for identifying functionally independent brain networks and classifying pathological brain states. This survey focuses on methods from machine learning, which contribute to our understanding of functional interactions between brain regions and their relation to the underlying anatomical substrate.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.