Author: Meaghan Moody

Understanding how experience and exposure to trauma changes the brain could improve diagnosis and targeted care for conditions like anxiety and post-traumatic stress disorder (PTSD). Benjamin Suarez-Jimenez, Ph.D., assistant professor of Neuroscience, has been studying this topic for the past several years and was awarded a new $3.5 million grant to use virtual reality and MRI to look into the circuitry of threat, reward, and cognitive mapping in PTSD, trauma, and resilience.

For the next five years, this funding from the National Institute of Mental Health will allow the ZVR lab to build upon work that investigates brain areas that build spatial maps, specifically to discriminate between areas of an environment associated with emotions. Suarez-Jimenez’s most recent research identified changes in the salience network – a mechanism in the brain used for learning and survival – in people exposed to trauma (with and without psychopathologies, including PTSD, depression, and anxiety). His prior research has revealed people with anxiety have increased insula and dorsomedial prefrontal cortex activation – indicating their brain was associating a known safe area to danger or threat.

“This project the RO1 will support will probe whether the neural processes we have identified in the past are specific to threat or if they expand to reward processing,” Suarez-Jimenez said. “We are also looking at how attention allocation to some visual cues of the virtual reality tasks changes from pre- to post-task experience. We are hoping that understanding these brain processes can help us identify better ways to diagnose PTSD and to improve treatment.”

Suarez-Jimenez came to the University in January 2021. He is an active member of the Neuroscience Diversity Commission and has served as a mentor for the NEUROCITY program.

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The University’s Goergen Institute for Data Science supports collaborative projects across all disciplines.

Ten projects supported with seed funding from the Goergen Institute for Data Science this year demonstrate how machine learning, artificial intelligence (AI), and augmented and virtual reality (AR/VR) are transforming the way University of Rochester researchers—across all disciplines—address challenging problems.

“I’m very excited about the wide range of collaborative projects we are able to support this year,” says Mujdat Cetin, the Robin and Tim Wentworth Director of the institute. “These projects tackle important and timely problems on data science methods and applications, and I am confident they will lead to significant research contributions and attract external funding.”

The awards, approximately $20,000 each, help researchers generate sufficient proof-of-concept findings to then attract major external funding.

This year’s projects involve collaborations among engineers, computer scientists, a historian, a biostatistician, and experts in brain and cognitive sciences, earth and environmental science, and palliative care. Their projects include a totally new kind of computing platform, new virtual reality technologies to improve doctor-patient conversations and help people overcome color vision deficiency, and machine learning techniques to make it easier for people to add music to their videos and to enhance AR/VR immersive experiences based on the unique geometry of each user’s anatomy.

The 2022–23 funded projects and their principal investigators are:

• Ising Boltzmann Substrate for Energy-Based Models
  Co-PIs: Michael Huang, professor of electrical and computer engineering and of computer science, and Gonzalo Mateos, associate professor of electrical and computer engineering and of computer science and the Asaro Biggar Family Fellow in Data Science
• A Data-Driven, Virtual Reality-based Approach to Enhance Deficient Color Vision
  Co-PIs: Yuhao Zhu, assistant professor of computer science, and Gaurav Sharma, professor of electrical and computer engineering, of computer science, and of biostatistics and computational biology
• Audiovisual Integration in Virtual Reality Renderings of Real Physical Spaces
  Co-PIs: Duje Tadin, professor and chair of brain and cognitive sciences and professor of ophthalmology and of neuroscience; Ming-Lun Lee, associate professor of electrical and computer engineering; and Michael Jarvis, associate professor of history
• Personalized Immersive Spatial Audio with Physics Informed Neural Field
  Co-PIs: Zhiyao Duan, associate professor of electrical and computer engineering and of computer science, and Mark Bocko, Distinguished Professor of Electrical and Computer Engineering and professor of physics and astronomy
• Computational Earth Imaging with Machine Learning
  Co-PIs: Tolulope Olugboji, assistant professor of earth and environmental sciences, and Mujdat Cetin, professor of electrical and computer engineering and of computer science, and the Robin and Tim Wentworth Director of the Goergen Institute for Data Science
• Improving Deconvolution Estimates through Bayesian Shrinkage
  PI: Matthew McCall, associate professor of biostatistics
• Building a Multi-Step Commonsense Reasoning System for Story Understanding
  Co-PIs: Zhen Bai, assistant professor of computer science, and Lenhart Schubert, professor of computer science
• Versatile and Customizable Virtual Patients to Improve Doctor-Patient Communication
  Co-PIs: Ehsan Hoque, associate professor of computer science, and Ronald Epstein, professor of family medicine and palliative care
• Machine Learning Assisted Femtosecond Laser Fabrication of Efficient Solar Absorbers
  Co-PIs: Chunlei Guo, professor of optics, and Jiebo Luo, Albert Arendt Hopeman Professor of Engineering
  Rhythm-Aware and Emotion-Aware Video Background Music Generation
  PI: Jiebo Luo, Albert Arendt Hopeman Professor of Engineering

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