Author
Marina Schmid
Bio: Marina Schmid is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 2102 citations.
Papers
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01 Jan 2016
TL;DR: This is an introduction to the event related potential technique, which can help people facing with some malicious bugs inside their laptop to read a good book with a cup of tea in the afternoon.
Abstract: Thank you for downloading an introduction to the event related potential technique. Maybe you have knowledge that, people have look hundreds times for their favorite readings like this an introduction to the event related potential technique, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some malicious bugs inside their laptop.
2,445 citations
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TL;DR: ERPLAB adds to EEGLAB’s EEG processing functions, providing additional tools for filtering, artifact detection, re-referencing, and sorting of events, among others.
Abstract: ERPLAB Toolbox is a freely available, open-source toolbox for processing and analyzing event-related potential (ERP) data in the MATLAB environment. ERPLAB is closely integrated with EEGLAB, a popular open-source toolbox that provides many EEG preprocessing steps and an excellent user interface design. ERPLAB adds to EEGLAB’s EEG processing functions, providing additional tools for filtering, artifact detection, re-referencing, and sorting of events, among others. ERPLAB also provides robust tools for averaging EEG segments together to create averaged ERPs, for creating difference waves and other recombinations of ERP waveforms through algebraic expressions, for filtering and re-referencing the averaged ERPs, for plotting ERP waveforms and scalp maps, and for quantifying several types of amplitudes and latencies. ERPLAB’s tools can be accessed either from an easy-to-learn graphical user interface or from MATLAB scripts, and a command history function makes it easy for users with no programming experience to write scripts. Consequently, ERPLAB provides both ease of use and virtually unlimited power and flexibility, making it appropriate for the analysis of both simple and complex ERP experiments. Several forms of documentation are available, including a detailed user’s guide, a step-by-step tutorial, a scripting guide, and a set of video-based demonstrations.
1,726 citations
TL;DR: It is demonstrated that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study, in contrast to the interpretation of backward model parameters.
1,105 citations
University of Florida1, University of Göttingen2, City College of New York3, Mackenzie Presbyterian University4, University of São Paulo5, Johns Hopkins University6, National Institutes of Health7, Harvard University8, University of California, Davis9, University of Brescia10, University of Lisbon11, University of Oxford12, ETH Zurich13, Ruhr University Bochum14
TL;DR: This review covers technical aspects of tES, as well as applications like exploration of brain physiology, modelling approaches, tES in cognitive neurosciences, and interventional approaches to help the reader to appropriately design and conduct studies involving these brain stimulation techniques.
942 citations
TL;DR: The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.
Abstract: Periodic visual stimulation and analysis of the resulting steady-state visual evoked potentials were first introduced over 80 years ago as a means to study visual sensation and perception. From the first single-channel recording of responses to modulated light to the present use of sophisticated digital displays composed of complex visual stimuli and high-density recording arrays, steady-state methods have been applied in a broad range of scientific and applied settings.The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.
875 citations
TL;DR: How common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant but bogus effects is demonstrated, with the likelihood of obtaining at least one bogus effect exceeding 50% in many experiments.
Abstract: ERP experiments generate massive datasets, often containing thousands of values for each participant, even after averaging. The richness of these datasets can be very useful in testing sophisticated hypotheses, but this richness also creates many opportunities to obtain effects that are statistically significant but do not reflect true differences among groups or conditions (bogus effects). The purpose of this paper is to demonstrate how common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant but bogus effects, with the likelihood of obtaining at least one such bogus effect exceeding 50% in many experiments. We focus on two specific problems: using the grand-averaged data to select the time windows and electrode sites for quantifying component amplitudes and latencies, and using one or more multifactor statistical analyses. Reanalyses of prior data and simulations of typical experimental designs are used to show how these problems can greatly increase the likelihood of significant but bogus results. Several strategies are described for avoiding these problems and for increasing the likelihood that significant effects actually reflect true differences among groups or conditions.
748 citations