Somatosensory anticipatory alpha activity increases to suppress distracting input
Journal of Cognitive Neuroscience
CUDAICA: GPU optimization of infomax-ICA EEG analysis
Computational Intelligence and Neuroscience - Special issue on Advanced Computational Techniques and Tools for Neuroscience
mfERG_LAB: Software for processing multifocal electroretinography signals
Computer Methods and Programs in Biomedicine
Journal of Cognitive Neuroscience
Decoding attended information in short-term memory: An eeg study
Journal of Cognitive Neuroscience
Dissociating n400 effects of prediction from association in single-word contexts
Journal of Cognitive Neuroscience
Context-dependent semantic processing in the human brain: Evidence from idiom comprehension
Journal of Cognitive Neuroscience
Working memory processes are mediated by local and long-range synchronization of alpha oscillations
Journal of Cognitive Neuroscience
Attention-modulated alpha-band oscillations protect against intrusion of irrelevant information
Journal of Cognitive Neuroscience
Erps and neural oscillations during volitional suppression of memory retrieval
Journal of Cognitive Neuroscience
Journal of Cognitive Neuroscience
Time course of shape and category selectivity revealed by eeg rapid adaptation
Journal of Cognitive Neuroscience
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This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.