The purpose of this research was two-fold: (1) further validate the Virtual Reality Stroop Task HMMWV [VRST; Stroop stimuli embedded within a virtual high mobility multipurpose wheeled vehicle] via a comparison of the 3-dimensional VRST factor structure to that of a 2-dimensional computerized version of the Stroop task; and (2) model the performance of machine learning [ML] classifiers and hyper-parameters for an adaptive version of the VRST. Both the 3-D VRST and 2-D computerized Stroop tasks produced two-factor solutions: an accuracy factor and a reaction time factor. The factors had low correlations suggesting participants may be focusing on either responding to stimuli accurately or swiftly. In future studies researchers may want to consider throughput, a measure of correct responses per unit of time. The assessment of naive Bayes (NB), k-nearest neighbors (kNN), and support vector machines (SVM) machine learning classifiers found that SVM classifiers tended to have the highest accuracies and greatest areas under the curve when classifying users as high or low performers. NB also performed well but kNN algorithms did not. As such, SVM and NB may be the best candidates for creation of an adaptive version of the VRST.

Past research has provided evidence for cultural differences in episodic memory when comparing European American and East Asian samples. However, cultural cognitive neuroscience has become over-dependent on European American vs. East Asian samples, which has left very little research into groups outside of this dichotomy. The aim of this dissertation was to address the need of more diverse samples in cultural cognitive neuroscience and to address the lack of research on Latinx biculturals. In this dissertation I explored how language could serve as a priming method to activate specific cultural systems, how bicultural Latinxs may switch cultural frames through language priming, and how priming of cultural systems affects their perception and recognition memory for certain visual information. The present study was designed to include a specific technique to investigate the potential cross-modal effect of cultural priming through language on visual cognition in bicultural and bilingual Latinxs. Results suggest that language did prime bicultural Latinxs to perform differently in a behavioral task, where images encoded in Spanish were more likely to be identified as incorrect and images encoded in English were more likely to be identified as correct. Additionally, we found that Cultural Blendedness directly predicted recognition accuracy, where higher identification …