Computational Intelligence and Neuroscience

Aims & Scope

The journal provides research and review papers at an interdisciplinary level, with the field of intelligent systems for computational neuroscience as its focus.

This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing.

All items relevant to building theoretical and practical systems are within its scope, including contributions in the area of applicable neural networks theory, supervised and unsupervised learning methods, algorithms, architectures, performance measures, applied statistics, software simulations, hardware implementations, benchmarks, system engineering and integration and innovative applications.

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Mathematics, Medicine and Neuroscience, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

  Citation: 8517

  Authors: Robert, Pascal, Eric, Jan-Mathijs

• Brainstorm: A User-Friendly Application for MEG/EEG Analysis

  Citation: 2996

  Authors: François, Sylvain, John C., Dimitrios, Richard M.

• Deep Learning for Computer Vision: A Brief Review

  Citation: 2331

  Authors: Athanasios, Nikolaos, Anastasios, Eftychios

• Deep Neural Networks Based Recognition of Plant Diseases by Leaf Image Classification

  Citation: 1326

  Authors: Srdjan, Marko, Andras, Dubravko, Darko

• Spatiotemporal Analysis of Multichannel EEG: CARTOOL

  Citation: 590

  Authors: Denis, Micah M., Christoph M.

• EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing

  Citation: 502

  Authors: Arnaud, Tim, Christian, Zeynep, Nima, Andrey, Scott

• Automatic Image-Based Plant Disease Severity Estimation Using Deep Learning

  Citation: 482

  Authors: Guan, Yu, Jianxin

• EEG and MEG Data Analysis in SPM8

  Citation: 475

  Authors: Vladimir, Jérémie, Stefan, Christophe, Richard, James, Gareth, Robert, Jean, Guillaume, Will, Karl

• A Survey of Stimulation Methods Used in SSVEP-Based BCIs

  Citation: 454

  Authors: Danhua, Jordi, Gary, Ronald M.

• Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning

  Citation: 423

  Authors: Rohit, Aditya, Mohammad, Gaurav, Sagar, Parneet