Aptitude tests are commonly used to measure an individual’s potential to learn a new skill or succeed in a new domain. However, psychometric measures of aptitude are constrained by issues of measurement validity and are susceptible to systemic biases. An alternate neuropsychometric approach is to leverage individual differences in task-free brain characteristics to measure aptitude. Previous researchers have employed this approach using task-free electroencephalography (EEG). Specifically, their work has provided evidence that higher power in the beta frequency band (~13-29.5 Hz), particularly over the right hemisphere, predicts as much as 60% of the variance in the rate at which individuals learn a second-language or a programming language. However, it is unclear what drives this observed relation between beta power and learning rate. The current study explores the mechanistic explanation of this relation, and hypothesizes that this relation is driven by either individual differences in motor control or cognitive control more generally. To test these hypotheses, we tested if individual differences in behavioral measures of motor control (i.e., the Stop Signal task) and/or cognitive control (i.e., the Simon task) mediate the relation between task-free beta power and language learning rate. Contrary to our hypotheses, neither measure of cognitive or motor control mediated the relation between beta power and learning rate. The results of the present study extend previous work relating beta power and learning rate, but future work is needed to elucidate the mechanism driving this relation.

There is great interest in understanding how experiences of adversity impact mental health. In particular, adverse childhood experiences (ACEs) can have long-term negative effects on a wide range of adult health and mental health outcomes. One mechanism of this effect might be the impact of adversity on cardiac functioning via regulation of the parasympathetic nervous system by the prefrontal cortex. This regulation is measured using respiratory sinus arrhythmia (RSA), or regular variation in heart rate with respiration. Higher baseline RSA indicates better trait emotional regulation, while lower baseline RSA indicates reduced emotional regulation and greater risk of psychopathology. This project explores the pathways from mothers' ACEs to infants’ RSA, highlighting the potential for intergenerational transmission of experiences of adversity. Data were obtained from 120 mothers and their infants living in low-income contexts. Baseline RSA is calculated using electrocardiogram recordings taken as the mother sits quietly with the infant on her lap. Mothers completed questionnaires related to stress, mental health, financial security, and adversity. Data was collected at two time-points: when the infant was 2-4 months of age (T1) and 4-6 months of age (T2). The results from multiple regression analyses showed that higher current economic insecurity predicted lower baseline RSA in infants at T1 (Β=.299, p=.004) but not in mothers, whereas mothers’ report of ACEs predicted lower maternal baseline RSA at T1 (Β=-.226, p=.032). Higher maternal baseline RSA at T1 predicted increases in infant RSA from T1 to T2 (Β=.306, p=.024). Exploring impacts of maternal RSA and risk context on infant RSA is significant as low infant RSA can impact growth, coping, and mental health outcomes. The findings also indicate a pathway from maternal experiences of adversity as a child to emotional regulation in mothers, and in turn, to subsequent psychophysiological functioning of infants. 

Metaphors are used continuously in everyday language and they can subtly shift how we perceive and respond to stimuli. Metaphors can also be used in the media to frame complicated topics. For example, describing climate change as a war (“combat excessive energy use”), instead of a race (“get in front of this challenging problem”), can lead to the perception of greater urgency and risk. There have been previous studies that have looked at metaphors surrounding current events but they have primarily relied on manual metaphor identification methods. The purpose of this project is to develop an automated system to identify metaphorical language. The data we are using are New York Times articles about COVID-19 from February through August 2020. We are using the tidyverse and corpus packages in the programming language R to create this pipeline. First, we created a corpus of articles in R, then we created a process to filter and analyze the text. So far, we have identified multiple metaphors used when writing about COVID, such as the “war” metaphor and the “journey” metaphor. The media discusses our “invisible enemy” and our “path forward” during the pandemic. Currently, our pipeline maintains sentences that use our target metaphors while filtering out sentences that contain literal or non-metaphorical language (such as “culture war” or “World War II”). Creating an automated process for analyzing corpora (a collection of texts) for metaphorical language in the COVID articles will allow us to gain a deeper understanding of how the usage of metaphors has changed throughout the pandemic. This pipeline will also allow us to analyze other texts and media for metaphors which will give us greater insight into how culture, language, and perception interact.

Because rates of sexual activity increase significantly during adolescence, young people are at an especially high risk for negative sexual health outcomes including sexually transmitted infection (STI) transmission, early pregnancy, and sexual violence. Current research reveals the effectiveness of comprehensive sex education (CSE) programs in combatting these outcomes, with students who participate in CSE reporting having better knowledge and feeling more prepared to face important decisions regarding their health. Research also shows that knowledge of sexual health resources impacts self-efficacy and benefits overall sexual health, with sexual resourcefulness showing direct ties to learned resourcefulness and sexual self-efficacy. The present study looks at how an individual’s sex education experience (e.g. topics discussed, depth of discussion) may impact their ability to communicate their sexual health needs and their willingness to access resources. In addition, this study aims to understand the link between sex education experience and relationship satisfaction later in life, a phenomenon which very few existing studies address. Our findings showed significant positive relationships and differences in communication comfort, self-efficacy, and relationship satisfaction such that people who perceived their sexual education experiences to be more inclusive also demonstrated higher scores in the aforementioned areas of focus.

Harmful myths are widely circulated about the cognitive effects of bilingualism on children. Studies tend to focus on bilingualism’s effects on overall executive functioning, but looking at preschoolers’ metaphor comprehension allows us to explore a specific, challenging area. Preschoolers struggle to comprehend metaphors, possibly because the mutual exclusivity bias inhibits their understanding that there can be multiple labels for one concept. However, this may not apply to bilingual children, as they were raised with the understanding that there are multiple words for the same meaning. Additionally, examining different types of metaphors and seeing which are harder for children (with fixed factors of age and language exposure), informs us further of this development. In the present study, we aim to understand if early language exposure affects metaphor comprehension and if the metaphor type affects children’s comprehension ability. I run 2.5-4.5 year-old subjects through our study every week by asking them to choose which of two pictures answers my question. Half of my questions are perceptual metaphors, where children can compare visual components to understand the metaphor (e.g. “Which dog is wearing socks?” about two photos of dogs, one with white paws). The other half are abstract metaphors, where children must apply conceptual mapping between two discrete domains (e.g. “Which kid is having a bumpy day” about two photos of kids, one dropping his books and frowning while the other holds his books and smiles). We hypothesize that bilingual children will perform better on the metaphor comprehension tasks because they lack the mutual exclusivity bias. We also predict that perceptual metaphors will be easier because they only require visual comparison. The results of our study can be used to provide clarity on the bilingualism controversy and illuminate challenges and areas of future research in language development.

My project is about automated classification of vicarious trial and error (VTE), a behavior observed in rats when they pause and look around before making decisions during a spatial memory task. During delayed spatial alternation (DSA) tasks, a rat is randomly placed on one of two start arms of a plus maze, with reward delivered on alternating arms for each trial. The movements of rats are recorded as position data while they perform the task.

Since our lab don’t have a commonly agreed upon criteria for VTE classification with our maze, manual scoring of VTE with recorded behavioral data has been time consuming, requiring many people to do the same work. Thus, my mentor and I decided to make a machine learning program to achieve automated and highly efficient VTE classification.

I first produced a representative data set with trials that were manually scored and commonly agreed by our lab members. Then, my mentor and I figured out several quantifiable features of VTEs and non-VTEs based on the representative data set. My mentor and I used machine learning algorithms to let our program learn those features that separate VTEs from not VTEs and help us accomplish automatic classification of VTEs with raw behavioral data from the DSA task. Preliminary result indicates that the supervised classification by the program aligns well with manual scoring, with roughly the same degree of agreement. Thus, I am currently transiting from a fully supervised method to a semi-supervised method, which allows almost full automation and minimal manual oversight. This work will provide insights for the behavioral strategy of rats throughout learning and guide us to find the connection between VTE behavior and neural circuitry.