Krysta Chauncey
Tufts University
18 Papers
149 Citations
Krysta Chauncey is an academic researcher from Tufts University. The author has contributed to research in topics: Computer science & Priming (psychology). The author has an hindex of 13, co-authored 18 publications. Previous affiliations of Krysta Chauncey include United States Department of the Army & Charles River Laboratories.
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Papers
Effects of stimulus font and size on masked repetition priming: An event-related potentials (ERP) investigation.
TL;DR: The results confirm the interpretation of the N/P150 as a component sensitive to feature-level processing, and suggest that the type of prelexical and lexical processing reflected in the N250, P325, and N400 components is performed on representations that are invariant to changes in both font and size.
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Code-switching effects in bilingual word recognition: A masked priming study with event-related potentials ☆
TL;DR: Evidence is presented for fast-acting language-switching effects occurring in the absence of overt task switching, and for target words in L1 and L2 primed by unrelated words from the same or the other language.
106
Distinguishing Difficulty Levels with Non-invasive Brain Activity Measurements
Audrey Girouard,Erin Treacy Solovey,Leanne M. Hirshfield,Krysta Chauncey,Angelo Sassaroli,Sergio Fantini,Robert J. K. Jacob +6 more
- 24 Aug 2009
TL;DR: In this article, the authors used functional near-infrared spectroscopy (fNIRS) to distinguish between different levels of game difficulty using non-invasive brain activity measurement.
Predictive text encourages predictable writing
Kenneth C. Arnold,Krysta Chauncey,Krzysztof Z. Gajos +2 more
- 17 Mar 2020
TL;DR: Key findings were that captions written with suggestions were shorter and that they included fewer words that that the system did not predict, which implies that text entry systems should be evaluated not just by speed and accuracy but also by their effect on the content written.
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Combining Electroencephalograph and Functional Near Infrared Spectroscopy to Explore Users' Mental Workload
Leanne M. Hirshfield,Krysta Chauncey,Rebecca Gulotta,Audrey Girouard,Erin Treacy Solovey,Robert J. K. Jacob,Angelo Sassaroli,Sergio Fantini +7 more
- 15 Jul 2009
TL;DR: While the fNIRS machine learning results showed promise for the measurement of workload states in HCI, the EEG results indicate that more research must be done in order to combine these two devices in practice.