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Lecture | John Hale | Modeling Neural Time Series with Linguistic Structure
  • 04/02/2020
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Lecture | John Hale | Modeling Neural Time Series with Linguistic Structure

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Descripción de Lecture | John Hale | Modeling Neural Time Series with Linguistic Structure

It's hard to say what the physical basis of human language comprehension is.  It has something to do with the brain, but what exactly?  What is it that our brains do such that a stream of words comes together to yield a communicative or literary experience?  This scientific challenge cuts right across mind, brain and culture.

Modeling neural signals offers a particular angle from which to approach this challenge.  With functional neuroimaging, it is possible to extract a timecourse of brain activity from particular regions and ask how well alternative (psycho)linguistic theories account for the measured signal.  This approach can be carried out over prolonged periods, for instance during the spoken recitation of a literary text.  It offers the opportunity to observed quite detailed facets of linguistic information processing that are repeated many times in a naturalistic stimulus.

The talk considers four specific predictors that are motivated by longstanding theoretical ideas in cognitive science.  Formalizing these predictors and scaling them up using techniques from computational linguistics, we ask about the functional anatomy of language processing within the brain.

If there is time, I will also take up two bonus predictors that turn out to be useful in explaining human EEG signals.  The results cohere well with prior experimental findings and exemplify a quite general method for inferring processing mechanisms during ecologically natural episodes of cognition.

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linguistics University of Georgia john hale modeling neural time series linguistic structure

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