August 2014
Volume 14, Issue 10
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Vision Sciences Society Annual Meeting Abstract  |   August 2014
P300 variability during target detection in natural images: Implications for single-trial classification
Author Affiliations
  • Jon Touryan
    Human Research and Engineering Directorate, U.S. Army Research Laboratory
  • Amar Marathe
    Human Research and Engineering Directorate, U.S. Army Research Laboratory
  • Anthony Ries
    Human Research and Engineering Directorate, U.S. Army Research Laboratory
Journal of Vision August 2014, Vol.14, 195. doi:10.1167/14.10.195
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      Jon Touryan, Amar Marathe, Anthony Ries; P300 variability during target detection in natural images: Implications for single-trial classification. Journal of Vision 2014;14(10):195. doi: 10.1167/14.10.195.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

The P300 is one of the most prominent and well-studied event-related potentials (ERPs) in the literature. The P300 is also a primary discriminant signal for many brain-computer interface (BCI) systems. It has been well established that the P300 amplitude and latency, along with reaction time, are directly linked to target discriminability. However, since the majority of P300 studies using an odd-ball or target-detection paradigm have a fixed or unquantified level of target discriminability, it remains unclear how the P300 is systematically modulated by the discriminability of stimulus properties affecting target detection. In this study we quantified visual properties of target objects within a large ensemble of natural images (color photographs of an office environment). Using a rapid serial visual presentation (RSVP) paradigm, we were able to systematically measure the effect of these properties on both the behavioral reaction time and P300.We evaluated how stimulus properties affected the P300 amplitude and latency while controlling for reaction time variability by using response-locked ERPs. As expected, we found that several stimulus properties, such as target size and eccentricity, had a dramatic effect on the P300 amplitude. In contrast, no effect was observed on the response-locked P300 latency. Importantly, the performance of single-trial classifiers (linear discriminant functions) was affected to a similar degree by these stimulus properties. Our results articulate the challenge for developing classification approaches that are robust to stimulus induced variability in the P300 response.

Meeting abstract presented at VSS 2014

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