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Frontiers in Neuroinformatics is a peer-reviewed journal published by Frontiers, covering Neural dynamics and brain function, Functional Brain Connectivity Studies, EEG and Brain-Computer Interfaces. Over its lifetime it has published 2,180 papers, which have received 62,110 citations.
| Publisher | Frontiers |
|---|---|
| Reference style | Author–year (Harvard) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Frontiers in Neuroinformatics, 12(3), pp. 45–58.
Formats any DOI in Frontiers in Neuroinformatics style. No sign-up. |
| Publishes research in | Neural dynamics and brain function Functional Brain Connectivity Studies EEG and Brain-Computer Interfaces Cell Image Analysis Techniques Neural Networks and Applications |
| ISSN | 1662-5196 |
| Citation impact (2-yr) | 4.83 |
| h-index | 113 |
| i10-index | 722 |
| Article processing charge | $2,950 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | Forschungszentrum Jülich |
| Journal website | www.frontiersin.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover…
Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that…
PsychoPy is a software library written in Python, using OpenGL to generate very precise visual stimuli on standard personal computers. It is designed to allow the construction of as wide a variety of neuroscience experiments as possible, with the least effort. By writing scripts in standard Python syntax users can generate an enormous variety of…
Diffusion Imaging in Python (Dipy) is a free and open source software project for the analysis of data from diffusion magnetic resonance imaging (dMRI) experiments. dMRI is an application of MRI that can be used to measure structural features of brain white matter. Many methods have been developed to use dMRI data to model the…
The technology to collect brain imaging and physiological measures has become portable and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging. By its nature, such data is large and complex, making automated processing essential. This paper shows how lack of attention to the very early stages of an EEG preprocessing pipeline can…
