Frontiers in Computational Neuroscience

Papers
(The H4-Index of Frontiers in Computational Neuroscience is 23. 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 2020-03-01 to 2024-03-01.)
ArticleCitations
Brain Tumor Segmentation Using an Ensemble of 3D U-Nets and Overall Survival Prediction Using Radiomic Features121
Attention in Psychology, Neuroscience, and Machine Learning96
A Study on Arrhythmia via ECG Signal Classification Using the Convolutional Neural Network71
A Deep Learning Approach for Automatic Seizure Detection in Children With Epilepsy70
Transfer Entropy as a Measure of Brain Connectivity: A Critical Analysis With the Help of Neural Mass Models65
Overall Survival Prediction in Glioblastoma With Radiomic Features Using Machine Learning62
ASD-SAENet: A Sparse Autoencoder, and Deep-Neural Network Model for Detecting Autism Spectrum Disorder (ASD) Using fMRI Data49
An Active Inference Approach to Modeling Structure Learning: Concept Learning as an Example Case43
Review on Emotion Recognition Based on Electroencephalography43
Theta-Nested Gamma Oscillations in Next Generation Neural Mass Models43
Unsupervised Domain Adaptation With Optimal Transport in Multi-Site Segmentation of Multiple Sclerosis Lesions From MRI Data36
Spiking Neural Network (SNN) With Memristor Synapses Having Non-linear Weight Update32
The Neuroscience of Spatial Navigation and the Relationship to Artificial Intelligence30
Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation30
GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity29
An Investigation of the Free Energy Principle for Emotion Recognition29
EEG-based emotion recognition using hybrid CNN and LSTM classification29
Optimal Self-Induced Stochastic Resonance in Multiplex Neural Networks: Electrical vs. Chemical Synapses27
Serotonergic Axons as Fractional Brownian Motion Paths: Insights Into the Self-Organization of Regional Densities26
Fast Simulations of Highly-Connected Spiking Cortical Models Using GPUs25
Stochastic Resonance Based Visual Perception Using Spiking Neural Networks24
Learning Generative State Space Models for Active Inference24
Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation23
Unsupervised Few-Shot Feature Learning via Self-Supervised Training23
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