Frontiers in Neuroinformatics

Papers
(The H4-Index of Frontiers in Neuroinformatics is 22. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-11-01 to 2025-11-01.)
ArticleCitations
A multi-head self-attention deep learning approach for detection and recommendation of neuromagnetic high frequency oscillations in epilepsy147
hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction97
Chronic jet lag-like conditions dysregulate molecular profiles of neurological disorders in nucleus accumbens and prefrontal cortex87
Editorial: Innovative methods for sleep staging using neuroinformatics78
The quest to share data64
Epileptic brain imaging by source localization CLARA supported by ictal-based semiology and VEEG in resource-limited settings49
FN-OCT: Disease Detection Algorithm for Retinal Optical Coherence Tomography Based on a Fusion Network45
Intra-V1 functional networks and classification of observed stimuli43
versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database41
Predicting the clinical prognosis of acute ischemic stroke using machine learning: an application of radiomic biomarkers on non-contrast CT after intravascular interventional treatment37
Systems Neuroscience Computing in Python (SyNCoPy): a python package for large-scale analysis of electrophysiological data36
Editorial: Neuroinformatics of large-scale brain modelling35
State-dependent modulation of thalamocortical oscillations by gamma light flicker with different frequencies, intensities, and duty cycles33
Detection of pulmonary embolism severity using clinical characteristics, hematological indices, and machine learning techniques32
A computational model of Alzheimer's disease at the nano, micro, and macroscales29
Magnetic Resonance Imaging Sequence Identification Using a Metadata Learning Approach27
A standardized accelerometry method for characterizing tremor: Application and validation in an ageing population with postural and action tremor26
Finding the limits of deep learning clinical sensitivity with fractional anisotropy (FA) microstructure maps25
SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies24
Unsupervised method for representation transfer from one brain to another24
Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies23
Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN23
Erratum: Mapping and validating a point neuron model on Intel's neuromorphic hardware Loihi22
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