Abstract
Event-related potentials (ERP) are usually studied by means of their grand averages, or, like in brain-machine interfaces (BMI), classified on a single-trial level. Both approaches do not offer a detailed insight into the individual, qualitative variations of the ERP occurring between single trials. These variations, however, convey valuable information on subtle but relevant differences in the neural processes that generate these potentials. Understanding these differences is even more important when ERP are studied in more complex, natural and real-life scenarios, which is essential to improve and extend current BMI. We propose an approach for assessing these variations, namely amplitude, latency and morphology, in a recently introduced ERP, fixation-related potentials (FRP). To this end, we conducted a study with a complex, real-world like choice task to acquire FRP data. Then, we present our method based on multiple-linear regression and outline, how this method may be used for a detailed, qualitative analysis of single-trial FRP data.
Keywords
- Fixation-related Potentials (FRP)
- Choice Task Complexity
- Single-trial Level
- Grand Average
- Brain Machine Interface (BMI)
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Acknowledgments
This research/work was supported by the Cluster of Excellence Cognitive Interaction Technology ‘CITEC’ (EXC 277) at Bielefeld University, which is funded by the German Research Foundation (DFG).
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Wobrock, D., Finke, A., Schack, T., Ritter, H. (2016). Assessing the Properties of Single-Trial Fixation-Related Potentials in a Complex Choice Task. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9948. Springer, Cham. https://doi.org/10.1007/978-3-319-46672-9_62
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DOI: https://doi.org/10.1007/978-3-319-46672-9_62
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