Frontiers in Computational Neuroscience

Papers
(The H4-Index of Frontiers in Computational Neuroscience is 21. 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 2020-11-01 to 2024-11-01.)
ArticleCitations
A Study on Arrhythmia via ECG Signal Classification Using the Convolutional Neural Network95
A Deep Learning Approach for Automatic Seizure Detection in Children With Epilepsy92
ASD-SAENet: A Sparse Autoencoder, and Deep-Neural Network Model for Detecting Autism Spectrum Disorder (ASD) Using fMRI Data73
Review on Emotion Recognition Based on Electroencephalography61
EEG-based emotion recognition using hybrid CNN and LSTM classification57
Spiking Neural Network (SNN) With Memristor Synapses Having Non-linear Weight Update42
Ensemble deep learning for brain tumor detection40
Conventional machine learning and deep learning in Alzheimer's disease diagnosis using neuroimaging: A review40
GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity36
Whole-Brain Network Models: From Physics to Bedside28
Fast Simulations of Highly-Connected Spiking Cortical Models Using GPUs28
Learning Generative State Space Models for Active Inference27
Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation26
Status of deep learning for EEG-based brain–computer interface applications26
RETRACTED: Deep Learning for Autism Diagnosis and Facial Analysis in Children25
A comprehensive neural simulation of slow-wave sleep and highly responsive wakefulness dynamics24
Will We Ever Have Conscious Machines?23
Toward Reflective Spiking Neural Networks Exploiting Memristive Devices23
Learning Invariant Object and Spatial View Representations in the Brain Using Slow Unsupervised Learning22
Fano Factor: A Potentially Useful Information22
Evaluation of Synergy Extrapolation for Predicting Unmeasured Muscle Excitations from Measured Muscle Synergies21
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