ArticleCognitive neurodynamics2021
Construction of embedded fMRI resting-state functional connectivity networks using manifold learning.
Article in Cognitive neurodynamics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-analysis and systematic review of single vs. multimodal neuroimaging techniques in the classification of psychosis.Molecular psychiatry · 2023Pooled it
- Brain Connectivity Modelling Through Joint Estimation of Parcels and Gradients.bioRxiv : the preprint server for biology · 2026Article
- Mapping Functional Brain Organization Using Artificial Intelligence.Chemical & biomedical imaging · 2026Review
- Connectivity Regression.Biostatistics (Oxford, England) · 2025Article
- Exploring Nonlinear Dynamics In Brain Functionality Through Phase Portraits And Fuzzy Recurrence Plots.bioRxiv : the preprint server for biology · 2024Article
- Advancing Colorectal Cancer Diagnosis with AI-Powered Breathomics: Navigating Challenges and Future Directions.Diagnostics (Basel, Switzerland) · 2023Review
- Nursing students' learning flow, self-efficacy and satisfaction in virtual clinical simulation and clinical case seminar.BMC nursing · 2023Article
- Manifold Learning for fMRI time-varying FC.bioRxiv : the preprint server for biology · 2023Article
- Prediction and analysis of time series data based on granular computing.Frontiers in computational neuroscience · 2023Article
- Application of machine learning in predicting aggressive behaviors from hospitalized patients with schizophrenia.Frontiers in psychiatry · 2023Article
- Manifold learning for fMRI time-varying functional connectivity.Frontiers in human neuroscience · 2023Article
- An efficient functional magnetic resonance imaging data reduction strategy using neighborhood preserving embedding algorithm.Human brain mapping · 2022Article
- Aberrant resting-state functional connectivity and topological properties of the subcortical network in functional dyspepsia patients.Frontiers in molecular neuroscience · 2022Article
- Synergy Factorized Bilinear Network with a Dual Suppression Strategy for Brain Tumor Classification in MRI.Micromachines · 2021Article
- Article
- Recognition of Electroencephalography-Related Features of Neuronal Network Organization in Patients With Schizophrenia Using the Generalized Choquet Integrals.Frontiers in neuroinformatics · 2021Article
- ISOMAP and machine learning algorithms for the construction of embedded functional connectivity networks of anatomically separated brain regions from resting state fMRI data of patients with Schizophrenia.AIMS neuroscience · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We construct embedded functional connectivity networks (FCN) from benchmark resting-state functional magnetic resonance imaging (rsfMRI) data acquired from patients with schizophrenia and healthy controls based on linear and nonlinear manifold learning algorithms, namely, Multidimensional Scaling, Isometric Feature Mapping, Diffusion Maps, Locally Linear Embedding and kernel PCA. Furthermore, based on key global graph-theoretic properties of the embedded FCN, we compare their classification potential using machine learning. We also assess the performance of two metrics that are widely used for the construction of FCN from fMRI, namely the Euclidean distance and the cross correlation metric. We show that diffusion maps with the cross correlation metric outperform the other combinations.
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