ReviewNeuroscience2021
Nonlinear System Identification of Neural Systems from Neurophysiological Signals.
Review in Neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed.
- Age-Dependent Entropic Features During Propofol Anesthesia in Developing Brain.Anesthesia and analgesia · 2026Article
- Towards an informational account of interpersonal coordination.Nature reviews. Neuroscience · 2026Review
- Chronic alcohol-induced brain states limit propagation of direct cortical stimulation.Scientific reports · 2025Article
- Distinct Alpha Connectivity Patterns During Response Inhibition in Alcohol Use Disorder.Human brain mapping · 2025Article
- Uncovering the role of directed connectivity in alpha and theta band activity for sustaining perception-action links.Communications biology · 2025Article
- Contralesional recruitment and localization of EEG signal complexity in stroke: a recurrence quantification analysis of hierarchical motor tasks.Journal of neural engineering · 2025Article
- Abnormalities in brain complexity in children with autism spectrum disorder: a sleeping state functional MRI study.BMC psychiatry · 2025Article
- Electrophysiological Alterations in the Progression of Parkinson's Disease and the Therapeutic Effect of Tetrabenazine on Rats With Levodopa-Induced Dyskinesia.CNS neuroscience & therapeutics · 2025Article
- The contagion of neurologic Immersion predicts retail purchases.Frontiers in neuroscience · 2025Article
- Fusion of EEG and EMG signals for detecting pre-movement intention of sitting and standing in healthy individuals and patients with spinal cord injury.Frontiers in neuroscience · 2025Article
- Quantitative electroencephalography predicts postoperative delirium in adult cardiac surgical patients from a prospective observational study.Scientific reports · 2024Observational
- Neural mechanisms of adaptive behavior: Dissociating local cortical modulations and interregional communication patterns.iScience · 2024Article
- Modeling the cortical response elicited by wrist manipulation via a nonlinear delay differential embedding.Physical and engineering sciences in medicine · 2024Article
- Detection of quadratic phase coupling by cross-bicoherence and spectral Granger causality in bifrequencies interactions.Scientific reports · 2024Article
- Article
- Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia.Brain communications · 2024Article
- Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to differences between individuals with schizophrenia and controls.Nature. Mental health · 2024Article
- Networks extracted from nonlinear fMRI connectivity exhibit unique spatial variation and enhanced sensitivity to differences between individuals with schizophrenia and controls.bioRxiv : the preprint server for biology · 2023Article
- EEG Connectivity Diversity Differences between Children with Autism and Typically Developing Children: A Comparative Study.Bioengineering (Basel, Switzerland) · 2023Article
- Causality Analysis with Information Geometry: A Comparison.Entropy (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The human nervous system is one of the most complicated systems in nature. Complex nonlinear behaviours have been shown from the single neuron level to the system level. For decades, linear connectivity analysis methods, such as correlation, coherence and Granger causality, have been extensively used to assess the neural connectivities and input-output interconnections in neural systems. Recent studies indicate that these linear methods can only capture a certain amount of neural activities and functional relationships, and therefore cannot describe neural behaviours in a precise or complete way. In this review, we highlight recent advances in nonlinear system identification of neural systems, corresponding time and frequency domain analysis, and novel neural connectivity measures based on nonlinear system identification techniques. We argue that nonlinear modelling and analysis are necessary to study neuronal processing and signal transfer in neural systems quantitatively. These approaches can hopefully provide new insights to advance our understanding of neurophysiological mechanisms underlying neural functions. These nonlinear approaches also have the potential to produce sensitive biomarkers to facilitate the development of precision diagnostic tools for evaluating neurological disorders and the effects of targeted intervention.
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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.