The field of Magnetoencephalography (MEG) and Electroencephalography (EEG) source imaging is maturing rapidly. This scientific growth is accompanied by a variety of complementary and/or concurrent software solutions from the academic world.

The objective of this CIN Special Issue is to help the neuroimaging obtain an overview of state-of-the-art academic software applications for MEG/EEG data analysis, how they differ and interact, and of upcoming methodological trends and technical developments; the topics to be covered include, but are not limited to, academic software solutions for:

• MEG and EEG data acquisition
• Data preprocessing, that is, filtering, artifact detection, rejection or correction, trial sorting, averaging
• Segmentation and geometrical modeling of head tissues
• Computational electromagnetics for MEG/EEG forward modeling
• MEG/EEG source analysis
• Statistical appraisal and inference: confidence intervals on measures and hypothesis testing
• Identification and evaluation of evoked, induced event-related brain responses and ongoing brain activity
• Time-frequency decompositions, advanced spectral analysis, time series modeling
• Estimation of functional and effective connectivity

Authors should provide detailed information regarding their software toolbox or application by addressing the following topics: open source software (yes/no), i/o file formats available, operating system, Matlab required (yes/no), interoperability with other software, and so forth.

Further, the software needs to be available for download free of charge at the time of manuscript submission, with sufficient documentation provided online to be able to reproduce the data analysis featured in the manuscript.