Julie A. Van Dyke, Ph.D.

Grammatically related items often occur across long distances. We investigate how cues are used to retrieve the distant information needed to create meaning, and how retrieval interference leads to comprehension failure.

Reading comprehension disability has the same prevalence as 

dyslexia, but is much less studied. Our model specifies how under-specified grammatical encodings and shallow lexical representations

affect comprehension.

The response-signal Speed-Accuracy Tradeoff method provides speed measures that are not confounded by response thresholds.  These are necessary for identifying the computational properties of retrieval. 

Eye-movement models traditionally have not considered person-level factors. We provide data showing the importance of individual skills in determining eye-movements and the effects of skilled oculomotor control on fluency.

Clinical research involves datasets with many predictors and few observations. Machine learning techniques provide a means of ranking predictor importance while avoiding model overfitting and collinearity.

Eye-movement monitoring provides a realtime index of brain activations during word-by-word reading.  We are using this method to identify brain regions associated with word-by-word integrative processing. 

Fluency requires scheduling motor responses to be in sync with perceptual processes.  We examine the association between disordered predictive timing in the motor system, indexed by beta oscillations, and fluency disorders.

Cascade Reading is a reading technology that uses Natural Language Processing to reveal the syntactic structure of sentences.  It is freely available for use with any text.  Research shows this format improves reading comprehension, helps students hear phrasing, and increases reading confidence.