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Open Access Publications from the University of California
Cover page of Creativity and Disability and Difference

Creativity and Disability and Difference

(2024)

Creativity is a cornerstone of human innovation, influencing numerous disciplines and captivating both academics and practitioners. Despite extensive research, the connection between creativity and disability has been relatively unexplored. This paper seeks to bridge this gap by investigating the interplay between creativity, disability, and difference through the lens of "mental foraging." This conceptual framework compares cognitive exploration to how animals forage for food, suggesting that disabilities and differences can act as catalysts rather than barriers to creative thought and breakthroughs. By combining qualitative case studies with a thorough literature review, the study delves into the complex interactions between mental health conditions such as schizophrenia and ADHD, and physical disabilities like deafness and blindness, with creativity. It aims to provide new insights into the experiences and challenges faced by individuals with disabilities in their creative endeavors, highlighting how these unique cognitive landscapes can foster novel problem-solving approaches and innovation. Through understanding how disabilities influence creative processes, the paper underscores the importance of embracing cognitive and experiential diversity to enrich the creative landscape.

Cover page of A Review of Attractor Neural Networks and Their Use in Cognitive Science

A Review of Attractor Neural Networks and Their Use in Cognitive Science

(2024)

This literature review explores the role of attractor neural networks (ANNs) in modeling psychological processes in artificial and biological systems. By synthesizing research from dynamical systems theory, psychology, and computational neuroscience, the review provides an overview of the current understanding of ANN function in memory formation, memory reinforcement, retrieval, and forgetting. Key mathematical foundations of ANNs, including dynamical systems theory and energy functions, are discussed to explain the behavior and stability of these networks. The review also examines empirical applications of ANNs in cognitive processes such as semantic memory and episodic recall, as well as highlighting the hippocampus' role in pattern separation and completion. The review addresses challenges like catastrophic forgetting and noise effects on memory retrieval. By identifying gaps between theoretical models and empirical findings, it highlights the interdisciplinary nature of ANN research and suggests future areas for exploration.

Cover page of Outlining the Diverse Etiologies of Autism Spectrum Disorder

Outlining the Diverse Etiologies of Autism Spectrum Disorder

(2022)

Autism Spectrum Disorder (ASD) is a disorder defined by the heterogeneity of its presentations, making diagnosis and treatment for those who need it difficult. Here I examine a set of causal mechanisms which lead to the development of ASD. I support the idea that within and between those mechanisms, what may look like a singular causal tale may instead account for a large variety of individual presentations. I examine how an understanding of the low-level neurobiological mechanisms underlying ASD allows us to begin unraveling the nature of the heterogeneity found in individual and sub-group presentations of ASD.

Understanding the diverse etiologies of ASD can facilitate diagnosis and treatment. It is therefore critical that our understanding of ASD is as nuanced as possible. Here I explore three precipitants of ASD: SHANK3 haploinsufficiency, pre-natal organophosphate exposure, and pre-natal neonicotinoid exposure. I explore why the precipitant is important, how disruption in the mechanisms relevant to the precipitant can lead to ASD, and how mitigating or agitating ancillary factors affect the likelihood of precipitation, severity of effect, and phenotype of presentation of ASD within subgroups and individuals.

Cover page of User Experience Evaluation of the Simbrain Neural Network Simulator

User Experience Evaluation of the Simbrain Neural Network Simulator

(2022)

Don Norman, the author of The Design of Everyday Things, once said, “everything is designed.” Our world is surrounded by many physical and digital products, each with its own purpose. The study of design emphasizes making advancements to products and keeping in mind the ease of users' experience. User experience design provides a way to improve products while also creating better usability. This article will provide an overview of user experience and its different applications, along with a review of an educational application called Simbrain. Simbrain was used to teach a summer program called Frontier of Science at the University of Northern Colorado in Summer 2022.  Experiences from this program will be described here.

Cover page of Industry User Experience Research: A Detailed Account at a Social Media Startup

Industry User Experience Research: A Detailed Account at a Social Media Startup

(2022)

The field of industry User Experience (UX) Research is applied by large scale companies, small startups, and all in between. Companies rely on this research to understand their target audience and determine how to make their product successful in the hands of the consumer. The present work details the projects completed during a UX Research internship for a startup company developing a social media app and relates these experiences to both the coursework within UC Merced’s Cognitive and Information Sciences’ graduate program and cognitive science as a field. These projects include an analysis regarding a mood tracking feature and comparisons to competitor apps, literature reviews on conflict related to friend groups and teenager/young adult social environments, and beta testing of the app in development.

Cover page of Exploratory Data Analysis: Bias in The Media

Exploratory Data Analysis: Bias in The Media

(2022)

The sharing of biased information has become an increasingly pervasive issue. This is quite dangerous considering how the exchange of information can influence perceptions, decision-making, and, most importantly, how well we coexist. Accordingly, as our access to information and interactions grow in the wake of the digital age, we must reestablish control for how information is shared and increase accountability for those sharing information. Unfortunately, this is seemingly impossible given the scale of interactions and the complexity of information passed around. Thus, researchers in an experiment by Westmark et al., suggest that gauging people’s ability to detect biased information at the lower group level is where to start to accomplish these initiatives. The present work is an exploratory data analysis of the results from a survey deployed during this experiment, which was used to assess participants’ ability to detect bias correctly. The analysis was designed to provide researchers with different perspectives of the original hypothesis to consider. Although no significant relationships were found, comparisons based on gender and party affiliation displayed interesting information about how well these groups deal with the media information they receive and pass on to others.