Project:	Online and lab experiments, and webscraping to understand upernormal stimuli and human perception
Disciplines:	Multidisciplinary, psychology
Mentor:	Colin Camerer, Prof , (HSS), camerer@caltech.edu, Phone: 3232521752
AO Contact:	diana bohler, dbohler@caltech.edu
Background:	Supernormal stimuli refer to exaggerated versions of natural stimuli that elicit stronger responses than the original stimulus. This concept, originally studied in ethology, has profound implications for human perception, decision-making, media consumption, and aesthetics. Early research by Nikolaas Tinbergen demonstrated that animals often prefer artificial stimuli that are hyper-exaggerated versions of their natural counterparts. In humans, similar principles apply to many aspects of cognition and behavior, influencing everything from food consumption to advertising and media design. Modern technology, including AI-generated images, virtual reality, and enhanced visual effects, has intensified the presence and impact of supernormal stimuli in daily life. This research aims to uncover how these artificially amplified features shape human perception, drive preferences, and influence decision-making processes. By integrating behavioral experiments, computational modeling, and AI-generated stimuli, we seek to explore the underlying mechanisms that govern responses to supernormal stimuli, shedding light on their role in domains such as marketing, entertainment, social media, and human-computer interaction.
Description:	The student will contribute to a project investigating how supernormal stimuli shape human preferences and decision-making. This will involve a combination of data collection, analysis, and experimental design. The student will employ web scraping techniques to collect datasets related to exaggerated stimuli, followed by statistical analysis using Python, R, or Stata to identify trends in perception and preference. They will also design and run behavioral experiments on online platforms like Prolific to assess how different populations respond to these stimuli. Additionally, the project may involve developing machine learning models to analyze large-scale datasets and classify image properties associated with exaggerated stimuli. Depending on interest and expertise, the student may also work on AI-generated image synthesis, modifying visual elements to study their impact on human perception. This research will be conducted in person at the Caltech campus, providing the student with direct mentorship and access to campus resources. Through this work, the student will gain valuable experience in data science, experimental psychology, and computational modeling, contributing to a deeper understanding of how artificially amplified stimuli influence human behavior. This project offers an opportunity to work at the intersection of psychology, neuroscience, and data science, gaining hands-on experience in behavioral research, computational analysis, and experimental design. If you are interested in understanding how exaggerated stimuli shape human perception and decision-making, this is an exciting chance to contribute to cutting-edge research.
References:	References: 1. Tinbergen, N. (1951). The Study of Instinct. Oxford University Press. 2. Lynn, Spencer. (2010). Decision-Making and Learning: The Peak Shift Behavioral Response. 3. Barrett, Deirdre. (2010). Supernormal Stimuli: How Primal Urges Overran Their Evolutionary Purpose. 4. Dunbar R. I. (2009). The social brain hypothesis and its implications for social evolution. Annals of human biology, 36(5), 562–572. 5. Cunningham, C. A., & Egeth, H. E. (2018). The capture of attention by entirely irrelevant pictures of calorie-dense foods. Psychonomic bulletin & review, 25(2), 586–595.
Student Requirements:	This SURF AO will be technically demanding Experience in programming (Python, R, or Stata) and web scraping (BeautifulSoup, Scrapy, or Selenium). Familiarity and/or strong interest in statistical analysis, machine learning (TensorFlow, PyTorch, or Scikit-learn), online experimentation (Prolific), and image processing (OpenCV, Photoshop, or AI-based generation) is a plus.
Programs:	This AO can be done under the following programs:   Program    Available To        Amgen Scholars    Non-Caltech students only          SURF    both Caltech and non-Caltech students  Click on a program name for program info and application requirements.