Machine Learning Based Framework For Eeg/Erp Analysis
INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY(2016)
Abstract
Despite indications in the split-brain and lesion literatures that the right hemisphere is capable of some syntactic analysis, few studies have investigated right hemisphere contributions to syntactic processing in people with intact brains. Here we used the visual half-field paradigm in healthy adults to examine each hemisphere's processing of correct and incorrect grammatical number agreement marked either lexically, e.g., antecedent/reflexive pronoun (“The grateful niece asked herself/*themselves…”) or morphologically, e.g., subject/verb (“Industrial scientists develop/*develops…”). For reflexives, response times and accuracy of grammaticality decisions suggested similar processing regardless of visual field of presentation. In the subject/verb condition, we observed similar response times and accuracies for central and right visual field (RVF) presentations. For left visual field (LVF) presentation, response times were longer and accuracy rates were reduced relative to RVF presentation. An event-related brain potential (ERP) study using the same materials revealed similar ERP responses to the reflexive pronouns in the two visual fields, but very different ERP effects to the subject/verb violations. For lexically marked violations on reflexives, P600 was elicited by stimuli in both the LVF and RVF; for morphologically marked violations on verbs, P600 was elicited only by RVF stimuli. These data suggest that both hemispheres can process lexically marked pronoun agreement violations, and do so in a similar fashion. Morphologically marked subject/verb agreement errors, however, showed a distinct LH advantage.
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Key words
eeg/erp,machine learning,framework
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