| Perceptual contributions to racial biases in pain recognition | Perceptual contributions to racial biases in pain recognition | There are pervasive racial and ethnic disparities in medical treatment in the United States. For instance, the pain of Black patients is systematically under-diagnosed and under-treated, compared to the pain of Whites. While other research has examined higher-level factors fueling such biases (e.g., perceptions of status, stereotypes about biological differences between Blacks and Whites), we're interested in examining whether racial biases in pain recognition might also stem from a perceptual basis. We've observed that pain on Black faces is less readily perceived than pain on White faces, stemming from a disruption in configural processing associated with other-race faces. Further, these biases in perception predict biases in treatment behavior. Currently, we're exploring the neural bases of these biases, examining whether these biases are observable in medical health professionals, and beginning to develop interventions designed to attenuate these perceptual contributions to racial biases in pain recognition. | Mende-Siedlecki, Peter | pmendesiedlecki | | <img alt="" src="/content-sub-site/PublishingImages/RacialBiasPain_Pic3.png" style="BORDER:0px solid;" /> | | | | | |
| Neural dynamics supporting impression updating | Neural dynamics supporting impression updating | How does the brain support our ability to change our minds about other people? Using fMRI, we've observed that impression updating is supported neurally by a distributed network of brain regions and that activity in a subset of these regions (in particular, vlPFC & IFG) is preferential for diagnostic changes in behavior, beyond mere moment-to-moment inconsistencies. Critically, we've observed that perceptions of behavioral frequency are a critical factor in the updating process: behaviors that are perceived to be more rare (e.g., highly immoral or highly competent behaviors) drive updating on both behavioral and neural levels. We're currently using computational modeling approaches to better characterize the neural dynamics supporting updating -- for example, to examine how this sort of complex social learning is contextualized and generalized. | Mende-Siedlecki, Peter | pmendesiedlecki | | <img alt="" src="/content-sub-site/PublishingImages/NeuralDynamics_Pic1.png" style="BORDER:0px solid;" /> | | | | | |
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