Here is a gallery of projects that have been developed by Dartmouth undergraduates for the dartbrains course.
In Spring 2019, students developed an experiment to study the neural basis of how Dartmouth undergraduates process viewing memes. Twelve Dartmouth undergraduates were scanned using functional magnetic resonance imaging (fMRI) while viewing 76 memes. After viewing each meme, participants made a decision about whether they would likely share this meme with a friend or not. After the scanning session, participants rated each meme on a number of dimensions using a Qualtrics survey (e.g., relatability, enjoyment, type of meme, etc.).
Unfortunately, we discovered that was a between run scanner artifact, which negatively impacted the results of all of the projects. Nevertheless, the questions and analytic approaches are very interesting and highlight the talent of Dartmouth undergraduates.
Self-Referencing With Memes
Sarah Eger, Taylor Walsh, Serena Zhu
Memes have become a major phenomenon in recent years, due to individuals of all ages sharingthem across social media platforms. However, no study to date has evaluated the self-referential processing that occurs in response to relatable memes. Our research undertakes this topic through the analysis of functional MRI (fMRI) scans and behavioral data gathered from ten undergraduate students at Dartmouth College. The behavioral data facilitate the conclusion that 9 of the 76 memes presented in the study directly reference Dartmouth. These data also confirm that there is a statistically significant difference in relatability between these two categories of memes. The differences in activation to stimuli belonging to each of these classes were then evaluated using a univariate analysis of the fMRI scans. This analysis showed that some activation in the dmPFC and hypothalamus survived after thresholding the contrast between Dartmouth and non-Dartmouth memes. A Multivariate Pattern Analysis (MVPA) was also implemented to determine if a Support Vector Machine (SVM) could predict which stimulus class a participant was processing, based on activation patterns in the entire brain or individual regions of interest (ROI). Both the whole-brain and 50 ROI MVPAs suggest that no particular voxel or region of the brain accounts for the classification of the two types of memes more than others. However, this pilot study was limited by a small number of subjects and some flaws in the data collection. Therefore, the findings presented in this paper should be considered only as exploratory results that merit additional inquiry through future studies of self-referential processing in relation to relatable memes, Dartmouth or otherwise.
See their presentation of this project here.
FFA Activation While Viewing Memes
Shivesh Shah, Hana Nazir, Huy Dang, Matthew Yuen
Human face perception is an evolutionary adaptation in humans that has become specialized because of the social nature of human life. The ability to quickly and accurately identify faces facilitates social bonding and the creation of social networks by allowing humans to gauge each other’s emotions and engage in social behavior. Contemporarily, socialization has taken the form of sharing memes, or pieces of social media that convey messages that are passed on from one person to another. Understanding how viewing memes affects the brain will allow us to understand how memes provide us an avenue to socialize with each other and share commonalities. The fusiform face area (FFA) is one area that has been found to highly activate in response to faces. How this area is activated during meme-viewing has been virtually unstudied. Thus, we endeavor to uncover how the brain, specifically the FFA, reacts when viewing memes with faces and memes without faces. Our study used fMRI data when participants were exposed to memes with and without faces. We ran a univariate contrast to identify whether there was an increase in activation of the FFA in response to Face vs NoFace memes. Then, we performed a prediction analysis to see whether activation in the FFA of our participants could predict whether they perceived faces in the memes. Finally, we performed a univariate contrast of brain activation when participants viewed memes for which they perceived faces and for which they were unsure. We found that there was non-significantly more activation of the FFA when participants perceived faces than when they did not. Additionally, our model for prediction was unable to reliably predict whether participants perceived faces or not based on their brain activation. And interestingly, we found that activation was significantly greater when participants were sure they saw a face than when they were unsure. Our results provide first steps toward using memes as a way to answer broader questions on what types of materials we like, how we decide what to share, and how memes can serve as a method of strengthening social networks.
See their presentation of this project here.