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EEG decoding of semantic category reveals distributed representations for single concepts

Murphy, B. and Poesio, M. and Bovolo, F. and Bruzzone, L. and Dalponte, M. and Lakany, H. (2011) EEG decoding of semantic category reveals distributed representations for single concepts. Brain and Language, 117 (1). pp. 12-22.

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    Abstract

    Here we present a collection of advanced data-mining techniques that allows the semantics of individual concepts to be decoded from single trials of EEG data. Neural activity was recorded while participants silently named images of mammals and tools, and category could be detected in single trials with an accuracy well above chance, both when considering data from single participants, and when group-training across participants. The pattern of classifications made by the algorithm confirmed that the neural patterns identified are due to conceptual category, and not any of a series of processing-related confounds. The time intervals, frequency bands and scalp locations that proved most informative for prediction permit physiological interpretation: the widespread activation shortly after appearance of the stimulus (from 100ms) is consistent both with accounts of multi-pass processing, and distributed representations of categories. These methods provide a new alternative to fMRI for fine-grained investigations of the conceptual lexicon.

    Item type: Article
    ID code: 28507
    Keywords: semantics , single concepts , neuroimaging, brain damage, data mining, machine learning, Bioengineering, Engineering (General). Civil engineering (General)
    Subjects: Technology > Engineering (General). Civil engineering (General) > Bioengineering
    Technology > Engineering (General). Civil engineering (General)
    Department: Faculty of Engineering > Bioengineering
    Related URLs:
      Depositing user: Ms Ashley Urie
      Date Deposited: 28 Oct 2010 11:24
      Last modified: 22 Nov 2012 14:45
      URI: http://strathprints.strath.ac.uk/id/eprint/28507

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