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Single-Trial Multi-channel N170 Estimation Using Linear Discriminant Analysis (LDA)

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Neural Information Processing (ICONIP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7666))

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Abstract

N170 is one of the event-related potentials (ERPs) that have been extensively used to study the neurological response of a subject when presented with a visual face stimulus. Although many N170 experiments have been performed with multi-channel EEG recordings, most of the N170 analyses are still based on trial-averaged signals from one or a few selected electrodes. Not only does this method under utilise the information from all available electrodes, it inhibits a trial-to-trial analysis of N170. We address this issue by proposing a single-trial multi-channel N170 estimation method that estimates the latency, amplitude and scalp projection of N170 using a linear classifier-based approach.

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© 2012 Springer-Verlag Berlin Heidelberg

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Lee, W.L., Tan, T., Falkmer, T., Leung, Y.H. (2012). Single-Trial Multi-channel N170 Estimation Using Linear Discriminant Analysis (LDA). In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7666. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34478-7_43

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  • DOI: https://doi.org/10.1007/978-3-642-34478-7_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34477-0

  • Online ISBN: 978-3-642-34478-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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