ArticleCognitive neurodynamics2018
Estimation of effective connectivity using multi-layer perceptron artificial neural network.
Article in Cognitive neurodynamics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- A Deep Learning Framework for Spatiotemporal Modeling of Visual Task fMRI.bioRxiv : the preprint server for biology · 2026Article
- Distinct Alpha Connectivity Patterns During Response Inhibition in Alcohol Use Disorder.Human brain mapping · 2025Article
- Neural mechanisms of adaptive behavior: Dissociating local cortical modulations and interregional communication patterns.iScience · 2024Article
- Neural connectivity patterns explain why adolescents perceive the world as moving slow.Communications biology · 2024Article
- A survey of brain network analysis by electroencephalographic signals.Cognitive neurodynamics · 2022Article
- Application of Visual Recognition Based on BP Neural Network in Architectural Design Optimization.Computational intelligence and neuroscience · 2022Article
- Complex networks and deep learning for EEG signal analysis.Cognitive neurodynamics · 2021Review
- Neural mechanism of visual information degradation from retina to V1 area.Cognitive neurodynamics · 2021Article
- Frequency-specific network effective connectivity: ERP analysis of recognition memory process by directed connectivity estimators.Medical & biological engineering & computing · 2021Article
- Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators.PeerJ. Computer science · 2021Article
- Frontal-temporal functional connectivity of EEG signal by standardized permutation mutual information during anesthesia.Cognitive neurodynamics · 2019Article
- Prediction of epilepsy seizure from multi-channel electroencephalogram by effective connectivity analysis using Granger causality and directed transfer function methods.Cognitive neurodynamics · 2019Article
- Bypassing the volume conduction effect by multilayer neural network for effective connectivity estimation.Medical & biological engineering & computing · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studies on interactions between brain regions estimate effective connectivity, (usually) based on the causality inferences made on the basis of temporal precedence. In this study, the causal relationship is modeled by a multi-layer perceptron feed-forward artificial neural network, because of the ANN's ability to generate appropriate input-output mapping and to learn from training examples without the need of detailed knowledge of the underlying system. At any time instant, the past samples of data are placed in the network input, and the subsequent values are predicted at its output. To estimate the strength of interactions, the measure of "
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Registered trials
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