EEGLAB , MPT , NetSIFT , NFT , BCILAB , and ERICA : New tools for advanced EEG / MEG processing

We review a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience and connecting to the EEGLAB software environment (sccn.ucsd.edu/eeglab), a freely available and readily extensible processing environment running under Matlab (The Mathworks, Inc.). These new tools include: (1) a new and flexible EEGLAB STUDY.design facility for framing and performing statistical analyses on data from multiple subjects; (2) a Measure Projection Toolbox (MPT) for aggregating independent component processes across subjects; (3) a Network Source Information Flow Toolbox (NetSIFT) for modeling event-related information flow between cortical areas; (4) a Neuroelectromagnetic Forward head modeling Toolbox (NFT) for building realistic electrical head models from available data; (5) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and; (6) an Experimental Real-time Interactive Control and Analysis (ERICA) environment for real-time production and interactive coordination of multimodal experiments. A variety of new signal processing methods have been applied to EEG signal processing over the past 15 years [1]. These new methods require new tools to allow routine processing of EEG data. Here we present a collection of recent advances implemented in or connecting to the EEGLAB software environment [2]. EEGLAB is an interactive, GUI menu and commandline script-based environment for processing electrophysiological data. Since its introduction in 2001, it has become a widely used platform for time series processing of biophysical data and for sharing of new signal processing approaches. A number of new EEGLAB-associated tools have been introduced that connect to the EEGLAB environment: NFT [3] is a new toolbox for electrical head modeling, an essential first step in electrophysiological source localization. NetSIFT allows users to implement a wide range of recently published methods for assessing effective connectivity between EEG signal processes including independent component processes. MPT is an EEGLAB plug-in for aggregating and comparing ICA components across subjects. Finally the ERICA framework, composed of the Datariver, Matriver, Enactor, and Producer toolboxes, as well as the BCILAB toolbox manage real time processing of EEG data and delivery of sensory feedback to the subject(s), system, and/or experimenters [4]. Figure 1 depicts how these toolboxes interact in connection with distributed data storage solutions such as the proposed HeadIT data and tools resource [5]. Figure 1. Complete electrophysiological experiment control, data collection, analysis, archiving, and meta-analysis suite (the ERICA framework for data recording, online analysis, and stimulus control environment; EEGLAB for data analysis; BCILAB for online and offline classification and BCI; HeadIT, an archival data and tools resource for laboratory or archival data storage, retrieval and meta-analysis; NFT for source localization; NetSIFT for information flow modeling; MPT for independent component process comparison).