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
Unsupervised method for representation transfer from one brain to another24
SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies24
Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN23
Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies23
Erratum: Mapping and validating a point neuron model on Intel's neuromorphic hardware Loihi22
0.13582396507263