supFunSim: spatial filtering toolbox for EEG

Recognition and interpretation of brain activity patterns from EEG or MEG signals is one of the most important tasks in cognitive neuroscience, requiring sophisticated methods of signal processing. The O_SCPLOWSUPC_SCPLOWFO_SCPLOWUNC_SCPLOWSO_SCPLOWIMC_SCPLOW library is a new MO_SCPLOWATLABC_SCPLOW toolbox which generates accurate EEG forward models and implements a collection of spatial filters for EEG source reconstruction, including linearly constrained minimum-variance (LCMV), eigenspace LCMV, nulling (NL), and minimum-variance pseudo-unbiased reduced-rank (MV-PURE) filters in various versions. It also enables source-level directed connectivity analysis using partial directed coherence (PDC) and directed transfer function (DTF) measures. The O_SCPLOWSUPC_SCPLOWFO_SCPLOWUNC_SCPLOWSO_SCPLOWIMC_SCPLOW library is based on the well-known FO_SCPLOWIELDC_SCPLOW-TO_SCPLOWRIPC_SCPLOW toolbox for EEG and MEG analysis and is written using object-oriented programming paradigm. The resulting modularity of the toolbox enables its simple extensibility. This paper gives a complete overview of the toolbox from both developer and end-user perspectives, including description of the installation process and some use cases.