Brain imaging shows distinct neural patterns in individuals prone to seeing hostility, according to a paper from the Motivation and Cognition Neuroscience Lab
Most people would shrug off a coworker taking too long to respond to an email as nothing more than a busy day at the office. Yet, some might see this delay as an intentional snub. Hostile attribution bias refers to the tendency to interpret ambiguous social situations as intentionally hostile, and is known to lead to aggressive behavior and interpersonal conflicts.
The study was instigated by Louisa Lyu, a fourth-year student in the College double majoring in Psychology and Statistics. Lyu approached Assistant Professor Yuan Chang Leong after the killing of UChicago graduate student Zheng Shaoxiong in November 2021 during an attempted robbery. The reports of the event, Lyu says, sparked her questions around how people interpret and react to potentially hostile social situations.
“My lab uses brain imaging to study biases in human perception and memory,” Leong says. “Louisa was working as a research assistant in our lab at that time and asked if we would be able to use similar methods to study hostility and aggression. We thought, Why not? And we pieced together this study.”
Together with project co-lead Zishan Su, a student in the Masters of Arts Program in the Social Sciences (MAPSS), Lyu used fNIRS to measure the brain activity of 58 participants as they listened to 21 hypothetical scenarios where a character’s actions resulted in a negative outcome for the listener (for example, a friend borrowing their car and then damaging it, or a professor forgetting to submit a recommendation letter by the deadline). Participants’ ratings of hostile intentions for each scenario were averaged to obtain a measure of hostile attribution bias.
The researchers found that activity in the ventromedial prefrontal cortex, a brain area implicated in decision-making, regulating emotions, and social evaluation, was more synchronized between participants with similar levels of hostile attribution bias when listening to the scenarios. This suggests that hostile attribution bias shaped the brain’s reaction to ambiguous situations, such that individuals who were “like-minded” were also “like-brained.”
Based on these findings, the team was able to identify whether a participant had high or low levels of hostile attribution bias based on their neural activity alone with 75% accuracy. For participants with particularly high levels of hostile attribution bias, accuracy reached 86%.
“Our participants were healthy college students, not a clinical population with aggressive tendencies,” Lyu says. “It was kind of surprising to see how, among all the healthy participants, there could be such a significant and distinguishable difference in terms of how people interpret social situations.”
The goal of the study, Leong says, was to delve deeper into the neural basis of hostile attribution bias, both because of its pervasiveness but also to better understand the biological mechanisms that give rise to this bias. “In doing so, we hope to inform future interventions aimed at trying to mitigate the negative impacts of this bias on our day-to-day interactions and our mental well-being,” he says.
The researchers also underscored how relatively inexpensive the fNIRS technology is, especially compared with MRIs. “Putting on an fNIRS cap is similar to placing 20 pulse oximeters on your scalp to measure the levels of blood oxygenation near the surface of the brain,” Leong says. “Once you have the device, the cost of running a study is negligible. The cost-effectiveness of fNIRS highlights the potential of wide application, enabling more accessible and inclusive brain research.”
In ongoing work, the lab is interested in developing intervention strategies to help those who have unhealthy levels of hostile attribution bias: Would there be a way to help people perceive others’ actions as less hostile? How could this change the way their brain responds to these situations? For example, the researchers are exploring the use of large language models to evaluate how much hostile attribution bias someone might have by analyzing their responses to social situations. They’re looking at how to develop a chatbot that could help rephrase people's interpretations to social situations, helping them to perceive social situations in a more positive light.
Dawn Neumann, Associate Professor at the Indiana University School of Medicine, and Kimberly Meidenbauer, Assistant Professor at Washington State University, were co-authors on the paper. The fNIRS device was supported by a Shared Equipment Award from the University of Chicago Neuroscience Institute.