Congratulations to Dr. Ruogu Fang (PI), assistant professor, Dr. Mingzhou Ding (Co-PI), distinguished professor and J. Crayton Pruitt Family Professor, and Dr. Andreas Keil (collaborator), professor of psychology for their project, “OR-DRD-AI2020: VCA-DNN: Neuroscience-Inspired Artificial Intelligence for Visual Emotion Recognition” being selected as an awardee from UF Research, Artificial Intelligence Research Catalyst Fund.
Human emotions are dynamic, multidimensional responses to challenges and opportunities, which emerge from network interactions in the brain. Disruptions of these network interactions underlie emotional dysregulation in many mental disorders, including anxiety and depression.
Creating an AI-based model system that is informed and validated by known biological findings and can be used to carry out causal manipulations and test the consequences against human imaging data will thus be a highly significant development in the short term.
The long-term goal is to understand how the human brain processes emotional information and how the process breaks down in mental disorders. NIH currently funds the team to record and analyze fMRI data from humans viewing natural images of varying emotional content. In the process of their research, they recognize that empirical studies such as theirs have significant limitations. Chief among them is the lack of ability to manipulate the system to establish the causal basis for the observed relationship between brain and behavior.
The advent of AI, especially deep neural networks (DNNs), opens a new avenue to address this problem. Creating an AI-based model system that is informed and validated by known biological findings and that can be used to carry out causal manipulations and allow the testing of the consequences against human imaging data will thus be a significant step toward achieving our long-term goal.
The researchers will utilize the university’s world-leading computing capabilities to analyze vast amounts of data and predict solutions to health, agriculture, engineering, and education challenges. A team of UF faculty reviewers evaluated 133 applications and selected 20 from the group, which were determined to have the most potential for elevating UF’s AI research profile.