title: MoBILAB: an open source toolbox for analysis and visualization of mobile brain/body imaging data.
abstract: A new paradigm for human brain imaging, mobile brain/body imaging (MoBI), involves synchronous collection of human brain activity (via electroencephalography, EEG) and behavior (via body motion capture, eye tracking, etc.), plus environmental events (scene and event recording) to study joint brain/body dynamics supporting natural human cognition supporting performance of naturally motivated human actions and interactions in 3-D environments (Makeig et al., 2009). Processing complex, concurrent, multi-modal, multi-rate data streams requires a signal-processing environment quite different from one designed to process single-modality time series data. Here we describe MoBILAB (more details available at sccn.ucsd.edu/wiki/MoBILAB), an open source, cross platform toolbox running on MATLAB (The Mathworks, Inc.) that supports analysis and visualization of any mixture of synchronously recorded brain, behavioral, and environmental time series plus time-marked event stream data. MoBILAB can serve as a pre-processing environment for adding behavioral and other event markers to EEG data for further processing, and/or as a development platform for expanded analysis of simultaneously recorded data streams.
authors.affiliation: Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego La Jolla, CA, USA.
authors.forename: Alejandro
authors.initials: A
authors.lastname: Ojeda
authors.affiliation: Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego La Jolla, CA, USA.
authors.forename: Nima
authors.initials: N
authors.lastname: Bigdely-Shamlo
authors.affiliation: Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego La Jolla, CA, USA.
authors.forename: Scott
authors.initials: S
authors.lastname: Makeig
keywords: EEG; EEGLAB; MoBI; mobile brain/body imaging; motion capture; multimodal neuroimaging