ReviewCognitive neurodynamics2014
A review of EEG and MEG for brainnetome research.
Review in Cognitive neurodynamics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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.
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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
14 citing papers in PubMed, 39 citations in OpenAlex.
- Domain-generalized Deep Learning for Improved Subject-independent Emotion Recognition Based on Electroencephalography.Experimental neurobiology · 2025Article
- Optimal graph representations and neural networks for multichannel time series data in seizure phase classification.Scientific reports · 2025Article
- Low-Rank Tensor Fusion for Enhanced Deep Learning-Based Multimodal Brain Age Estimation.Brain sciences · 2024Article
- High-altitude exposure leads to increased modularity of brain functional network with the increased occupation of attention resources in early processing of visual working memory.Cognitive neurodynamics · 2024Article
- Brain Functional Connectivity inFrontiers in neurology · 2022Article
- Ant Colony System Optimization for Spatiotemporal Modelling of Combined EEG and MEG Data.Entropy (Basel, Switzerland) · 2021Article
- Research on Recognition of Motor Imagination Based on Connectivity Features of Brain Functional Network.Neural plasticity · 2021Article
- Resting-State Electroencephalography Functional Connectivity Networks Relate to Pre- and Postoperative Language Functioning in Low-Grade Glioma and Meningioma Patients.Frontiers in neuroscience · 2021Article
- Electroencephalographic correlates of body shape concerns: an eLORETA functional connectivity study.Cognitive neurodynamics · 2020Article
- IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG).Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2018Review
- Children with well controlled epilepsy possess different spatio-temporal patterns of causal network connectivity during a visual working memory task.Cognitive neurodynamics · 2016Article
- Cortical activities of heat-sensitization responses in suspended moxibustion: an EEG source analysis with sLORETA.Cognitive neurodynamics · 2015Article
- The graph theoretical analysis of the SSVEP harmonic response networks.Cognitive neurodynamics · 2015Article
- Power spectral density and coherence analysis of Alzheimer's EEG.Cognitive neurodynamics · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The majority of brain activities are performed by functionally integrating separate regions of the brain. Therefore, the synchronous operation of the brain's multiple regions or neuronal assemblies can be represented as a network with nodes that are interconnected by links. Because of the complexity of brain interactions and their varying effects at different levels of complexity, one of the corresponding authors of this paper recently proposed the brainnetome as a new -ome to explore and integrate the brain network at different scales. Because electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive and have outstanding temporal resolution and because they are the primary clinical techniques used to capture the dynamics of neuronal connections, they lend themselves to the analysis of the neural networks comprising the brainnetome. Because of EEG/MEG's applicability to brainnetome analyses, the aim of this review is to identify the procedures that can be used to form a network using EEG/MEG data in sensor or source space and to promote EEG/MEG network analysis for either neuroscience or clinical applications. To accomplish this aim, we show the relationship of the brainnetome to brain networks at the macroscale and provide a systematic review of network construction using EEG and MEG. Some potential applications of the EEG/MEG brainnetome are to use newly developed methods to associate the properties of a brainnetome with indices of cognition or disease conditions. Associations based on EEG/MEG brainnetome analysis may improve the comprehension of the functioning of the brain in neuroscience research or the recognition of abnormal patterns in neurological disease.
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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.