Frontiers in Neuroinformatics

Papers
(The TQCC of Frontiers in Neuroinformatics is 9. 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 2022-08-01 to 2026-08-01.)
ArticleCitations
Editorial: Innovative methods for sleep staging using neuroinformatics101
The quest to share data60
Intra-V1 functional networks and classification of observed stimuli58
Epileptic brain imaging by source localization CLARA supported by ictal-based semiology and VEEG in resource-limited settings56
hvEEGNet: a novel deep learning model for high-fidelity EEG reconstruction47
Chronic jet lag-like conditions dysregulate molecular profiles of neurological disorders in nucleus accumbens and prefrontal cortex46
A multi-head self-attention deep learning approach for detection and recommendation of neuromagnetic high frequency oscillations in epilepsy45
versaFlow: a versatile pipeline for resolution adapted diffusion MRI processing and its application to studying the variability of the PRIME-DE database39
Systems Neuroscience Computing in Python (SyNCoPy): a python package for large-scale analysis of electrophysiological data35
Editorial: Neuroinformatics of large-scale brain modelling34
A standardized accelerometry method for characterizing tremor: Application and validation in an ageing population with postural and action tremor33
State-dependent modulation of thalamocortical oscillations by gamma light flicker with different frequencies, intensities, and duty cycles32
A computational model of Alzheimer's disease at the nano, micro, and macroscales30
Predicting the clinical prognosis of acute ischemic stroke using machine learning: an application of radiomic biomarkers on non-contrast CT after intravascular interventional treatment30
Detection of pulmonary embolism severity using clinical characteristics, hematological indices, and machine learning techniques30
Explainable 3D vision transformer framework for detecting brain anomalies in neuropsychiatric subtypes of Parkinson's disease28
Transdiagnostic clustering of self-schema from self-referential judgements identifies subtypes of healthy personality and depression25
Unsupervised method for representation transfer from one brain to another25
Correction: Transdiagnostic clustering of self-schema from self-referential judgements identifies subtypes of healthy personality and depression24
Erratum: Mapping and validating a point neuron model on Intel's neuromorphic hardware Loihi24
Web-based processing of physiological noise in fMRI: addition of the PhysIO toolbox to CBRAIN24
Finding the limits of deep learning clinical sensitivity with fractional anisotropy (FA) microstructure maps23
Tracking axon initial segment plasticity using high-density microelectrode arrays: A computational study23
A neuronal imaging dataset for deep learning in the reconstruction of single-neuron axons21
Multiple sclerosis and breast cancer risk: a meta-analysis of observational and Mendelian randomization studies21
QuNex—An integrative platform for reproducible neuroimaging analytics20
Multi-threshold image segmentation for melanoma based on Kapur’s entropy using enhanced ant colony optimization20
NeuroBridge ontology: computable provenance metadata to give the long tail of neuroimaging data a FAIR chance for secondary use19
Light-weight neural network for intra-voxel structure analysis19
BitBrain and Sparse Binary Coincidence (SBC) memories: Fast, robust learning and inference for neuromorphic architectures19
Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub19
Evaluating machine learning pipelines for multimodal neuroimaging in small cohorts: an ALS case study18
Alternative patterns of deep brain stimulation in neurologic and neuropsychiatric disorders17
Radiomics-driven neuro-fuzzy framework for rule generation to enhance explainability in MRI-based brain tumor segmentation17
Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute17
A review of risk concepts and models for predicting the risk of primary stroke17
Machine learning-based infection prediction model for newly diagnosed multiple myeloma patients16
A scalable implementation of the recursive least-squares algorithm for training spiking neural networks16
Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on “Frontiers in Neuroinformatics”16
Corrigendum: Mapping and validating a point neuron model on intel's neuromorphic hardware Loihi16
Editorial: Multimodal brain data integration and computational modeling16
Erratum: Advancing prediction of risk of intraoperative massive blood transfusion in liver transplantation with machine learning models. A multicenter retrospective study16
Correction: A Physics Informed Neural Network (PINN) framework for fractional order modeling of Alzheimer's disease16
Super-resolution microscopy and deep learning methods: what can they bring to neuroscience: from neuron to 3D spine segmentation15
Automatic coarse-to-fine AC-PC localization on CT using registration-guided 3D-UNets15
SynSpine: an automated workflow for the generation of longitudinal spinal cord synthetic MRI data14
Multi-omics integration reveals a six-malignant cell maker gene signature for predicting prognosis in high-risk neuroblastoma14
Recognition of MI-EEG signals using extended-LSR-based inductive transfer learning14
Editorial: Addressing large scale computing challenges in neuroscience: current advances and future directions14
Machine learning reveals interhemispheric somatosensory coherence as indicator of anesthetic depth13
2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data13
A systematic comparison of deep learning methods for EEG time series analysis13
Discovering optimal features for neuron-type identification from extracellular recordings13
Long-range temporal correlations in resting state alpha oscillations in major depressive disorder and obsessive-compulsive disorder13
Feature Selection Techniques for a Machine Learning Model to Detect Autonomic Dysreflexia12
Translating single-neuron axonal reconstructions into meso-scale connectivity statistics in the mouse somatosensory thalamus12
Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks12
Reliability and diagnostic performance of an automated MRI-based classifier compared with radiologists in Alzheimer’s disease12
The Multicentre Acute ischemic stroke imaGIng and Clinical data (MAGIC) repository: rationale and blueprint12
BrainInsights: a comprehensive framework for pre-processing, analysis, and interpretation of neuroimaging data using traditional statistics and machine learning12
Brain-Computer Interface using neural network and temporal-spectral features11
Editorial: Weakly supervised deep learning-based methods for brain image analysis11
Contrastive self-supervised learning for neurodegenerative disorder classification11
STEPS 4.0: Fast and memory-efficient molecular simulations of neurons at the nanoscale11
SDA: a data-driven algorithm that detects functional states applied to the EEG of Guhyasamaja meditation11
Power spectral analysis of voltage-gated channels in neurons11
Neuroimaging article reexecution and reproduction assessment system10
Enhanced heart sound anomaly detection via WCOS: a semi-supervised framework integrating wavelet, autoencoder and SVM10
Events in context—The HED framework for the study of brain, experience and behavior10
Editorial: Reproducible analysis in neuroscience10
PyDapsys: an open-source library for accessing electrophysiology data recorded with DAPSYS10
Investigating cortical complexity and connectivity in rats with schizophrenia10
Dynamic topological data analysis: a novel fractal dimension-based testing framework with application to brain signals10
Brain structural alterations in young girls with Rett syndrome: A voxel-based morphometry and tract-based spatial statistics study10
Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset9
Can micro-expressions be used as a biomarker for autism spectrum disorder?9
Editorial: Physical neuromorphic computing and its industrial applications9
Editorial: Navigating the landscape of FAIR data sharing and reuse: repositories, standards, and resources9
Multiscale co-simulation design pattern for neuroscience applications9
Building a realistic, scalable memory model with independent engrams using a homeostatic mechanism9
Classification of ROI-based fMRI data in short-term memory tasks using discriminant analysis and neural networks9
Identifying discriminative features of brain network for prediction of Alzheimer’s disease using graph theory and machine learning9
EPAT: a user-friendly MATLAB toolbox for EEG/ERP data processing and analysis9
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