ReviewBrain topography2022
Computational Models in Electroencephalography.
Review in Brain topography, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed.
- Diffusion Inverse Filtering: Enhancing Functional Connectivity-Based Pattern Recognition by Counteracting Spatial Smoothing.Brain sciences · 2026Article
- A Precision Computational Framework for sLORETA Neurofeedback in Mild Cognitive Impairment: Integration of qEEG Biomarkers and Neuropsychological Metrics.International journal of environmental research and public health · 2026Article
- EEG biomarkers for Alzheimer's disease: A novel automated pipeline for detecting and monitoring disease progression.Journal of Alzheimer's disease : JAD · 2025Article
- Topographic Variation in Human Neurotransmitter Receptor Densities Explains Differences in Intracranial EEG Spectra.Human brain mapping · 2025Article
- Application of Electroencephalography (EEG) in Combat Sports-Review of Findings, Perspectives, and Limitations.Journal of clinical medicine · 2025Review
- Digital twins and non-invasive recordings enable early diagnosis of Alzheimer's disease.Alzheimer's research & therapy · 2025Observational
- On the validity of electric brain signal predictions based on population firing rates.PLoS computational biology · 2025Article
- A comprehensive investigation of intracortical and corticothalamic models of the alpha rhythm.PLoS computational biology · 2025Article
- Decoding Imagined Speech from EEG Data: A Hybrid Deep Learning Approach to Capturing Spatial and Temporal Features.Life (Basel, Switzerland) · 2024Article
- Article
- A tutorial on fitting joint models of M/EEG and behavior to understand cognition.Behavior research methods · 2024Article
- Simultaneous oscillatory encoding of "hot" and "cold" information during social interactions in the monkey medial prefrontal cortex.iScience · 2024Article
- Research on the pathogenesis of Alzheimer's disease based on thalamocortical computational model.Frontiers in neurology · 2024Article
- Bayesian inference of frequency-specific functional connectivity in MEG imaging using a spectral graph model.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Increased noise relates to abnormal excitation-inhibition balance in schizophrenia: a combined empirical and computational study.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Investigation of frequency components embedded in EEG recordings underlying neuronal mechanism of cognitive control and attentional functions.Cognitive neurodynamics · 2023Article
- Multi-modal and multi-model interrogation of large-scale functional brain networks.NeuroImage · 2023Article
- Excitation-Inhibition Imbalance in Migraine: From Neurotransmitters to Brain Oscillations.International journal of molecular sciences · 2023Review
- Advanced Modeling and Signal Processing Methods in Brain-Computer Interfaces Based on a Vector of Cyclic Rhythmically Connected Random Processes.Sensors (Basel, Switzerland) · 2023Article
- Bi-sinusoidal light stimulation reveals an enhanced response power and reduced phase coherence at the visual cortex in migraine.Frontiers in neurology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses in silico and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by "computational model" is understood in many different ways by researchers in different fields of neuroscience and psychology, hindering communication and collaboration. In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level models, and behavior. On the one hand, computational models serve to investigate the mechanisms that generate brain activity, for example measured with EEG, such as the transient emergence of oscillations at different frequency bands and/or with different spatial topographies. On the other hand, computational models serve to design experiments and test hypotheses in silico. The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal. This is crucial for an accurate interpretation of EEG measurements that may ultimately serve in the development of novel clinical applications.
Indexed as
Identifiers
What OpenQuestion holds
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.