With the legalization of cannabis, guidelines for regulating cannabis advertisements are important to protect underage youth who are particularly susceptible to media influence. To inform these guidelines and illuminate how cannabis marketing affects the public, we presented cannabis and control ads to youth and adults (N=63; 32 female; age range: 16-36 years old; M=23.28, SD=6.0). We tracked pupil dilation as a measure of autonomic arousal while participants were shown cannabis and control ads during fMRI scanning. In the scanner, participants were asked how much they liked the ads, and after completing the fMRI task, participants were asked how much the ads made them want to use cannabis. We hypothesized that youth and those who do not regularly use cannabis would exhibit greater pupil dilation or arousal to cannabis ads compared to older adults and those who regularly use. We found that cannabis ads elicit greater autonomic arousal than control ads regardless of age (F(1,3694) = 4.454, p<0.05), suggesting that ads for cannabis generate greater engagement from their audience. Additionally, arousal was particularly heightened in younger, non-regular users (F(1,53.944) = 4.3071, p<0.05), suggesting that youth who do not regularly use cannabis may be more sensitive to cannabis-related stimuli, possibly due to the novelty of cannabis ads or enticing nature of illegal products for under-age youth. Thus, caution should be used in presenting youth with cannabis ads, and stricter guidelines should be implemented.

Intertemporal choice reflects the degree to which people weigh immediate versus delayed rewards. While research has demonstrated that aggregate influence impacts delayed reward preferences (Bixter & Rogers, 2019; Sargisson et al., 2021), little is known about the specific social factors that might drive or amplify this effect. Here we investigated how preferences are shifted by the presentation of visual social cues (faces of other people in a group) paired with statistical information about them (e.g., “70% of prior participants chose 10 tokens today”). In a sample of undergraduate students, participants made a series of decisions for delayed rewards in an intertemporal choice task, choosing between immediate and delayed options under three possible trial conditions: (1) displaying statistical information about past participants’ choices on a given trial paired with photos of faces that participants are told belong to those past participants, (2) statistical information without photos, and (3) no social information. We hypothesize that participants exposed to social information will align their choices with the majority at a much higher rate in trials with visual cues. The findings will provide insight into how social norms shape decision making, informing efficient financial planning, health behaviors, and education. Results may guide interventions that promote long-term thinking in contexts like addiction prevention, debt management, and medical treatment adherence.

Previous research links adolescent bullying victimization to eating disorder (ED) symptoms (Copeland et al., 2015), but less is known about which subtypes of victimization contribute to this relationship. This study investigates whether reputational or relational victimization plays a stronger role in early eating disorder onset using data from the Adolescent Brain Cognitive Development (ABCD) study in 8–11 year-olds. Participants were categorized into five subclinical ED groups based on the Youth KSADS and DSM-V: Anorexia Nervosa (SAN; n=905), Bulimia Nervosa (SBN; n=247), Binge ED (SBED; n=373), ED Not Otherwise Specified (SEDNOS; n=226), and controls (C; n=350). Victimization was assessed via the Peer Experiences Questionnaire. We hypothesized reputational victimization would show a stronger association with ED symptoms, particularly in SAN/SBN. A multinomial logistic regression revealed significant associations between both victimization types and all ED groups. Post-hoc z-tests revealed reputational victimization was a stronger predictor than relational in SAN (p=0.002) and SBN (p=0.013), but not in SBED/SEDNOS. As salience–ventral attention network (VAN) connectivity supports detecting and reorienting to social cues (Seeley et al., 2007), reduced connectivity may reflect impaired social threat processing, potentially contributing to ED risk. A mediation analysis (resting-state fMRI) revealed that reduced salience-VAN connectivity significantly mediated the link between reputational victimization and SAN/SBN (p=0.042).

Learning about the linguistic abilities of primates is essential for an empirical understanding of the evolution of vocal systems. Machine-learning (ML) algorithms offer a standardized way to classify primate calls, enabling researchers to quickly analyze a species's vocal systems. With the increase of primates in captivity and the urbanization of those in the wild, anthropogenic noise (AN), or any unwanted noise created by humans that causes signal distortion, may interfere with ML’s call classification ability. Improving signal quality and having an approach for filtering AN is necessary to maximize the information obtained from animal recordings, which can be done through supervised learning methods. The MMSE Short-Time Spectral Amplitude (MMSE STSA) estimator offers a solution for bioacoustic denoising, ensuring high-quality and efficient signal retention in large datasets. However, the MMSE algorithm may be imperfect due to the unique characteristics of AN in a zoo environment compared to the wild. In this study, we focus on denoising audio files of golden-headed lion tamarins (GHLTs) collected from the Santa Ana Zoo, where some sounds overlap with AN. By comparing AN-affected calls—before and after MMSE STSA filtering—to unaffected calls, I will evaluate whether the algorithm distorts key bioacoustic features. If distortions are present, I will implement the relevant features to our current ML-based classification pipeline to improve the accuracy of call grouping.

Memory and learning occur within a broad spatial and temporal context. Event segmentation theory proposes that individuals maintain event models that help them organize daily life into units that support memory and learning. Previous studies have demonstrated that event segmentation supports episodic memory by enhancing how we encode and retrieve information from everyday experiences. In particular, memory of information that occurs at event boundaries—moments where one perceives the end of one event and the start of another—is enhanced. However, there is limited research on how event segmentation and event boundaries influence the learning of new, unfamiliar categories. The current study examines how event boundaries influence adult participants’ learning of novel categories, using a virtual learning environment designed to replicate naturalistic events. Participants watched videos of a character walking in different scenarios during which the novel categories, paired with novel names, were either at event boundaries or within the flow of an event. Then, participants were tested on their learning of novel categories using forced-choice tests. We hypothesize that objects presented at event boundaries will be better learned than those presented within an event. The findings will help us understand the ways in which event boundaries affect the learning of new concepts and provide an additional avenue to enhance current teaching methods.