Statement of Research Interests
نویسنده
چکیده
My research seeks to explain how we learn about and represent the world. I empirically examine how people learn word-object mappings (i.e., nouns) from a series of situations comprised of multiple words and objects, as an infant or a traveler may do. Using mathematical models of memory and associative learning, I seek to discover the mechanisms underlying human word-learning behavior. I also investigate how these labels generalize to other perceptually similar objects, and whether perception itself is warped by the use of labels. I plan to research how populations of neurons might learn representations that produce the observed behaviors. In this vein, collaborators and I have proposed and tested a letter-based encoding scheme for words in a holographic model trained on text. In another project, I am exploring how input topology and network structure affects the recognition, separation, and integration of multiple inputs in spiking neural networks. Finally, I have developed paradigms that track the moment-to-moment decision state in memory, learning, categorization, and decision-making tasks. Access to decision trajectories in these game-like tasks enabled me to uncover new phenomenon such as changes of mind in recognition memory, and will provide additional constraining data for cognitive process models.
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Correction: Implications of Hybridization, NUMTs, and Overlooked Diversity for DNA Barcoding of Eurasian Ground Squirrels
The Funding statement was erroneously left out of this publication. The publisher apologizes for this error. The Funding statement should read: "This research was supported by the Russian Foundation for Basic Research (RFBR; grant 14-04-00301) to SVT. Funding for DNA barcoding analysis at the Biodiversity Institute of Ontario was provided by grants from the Natural Sciences and Engineering Rese...
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