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Leveraging Technology

Wide-shot shot (5) of MRI Machine in imaging center. Door shows.

The complex, sophisticated human brain contains 100 billion neurons, each of which is connected to an average of 7,000 other neurons. They pass signals via 500 trillion synaptic connections.

Unsurprisingly, the brain's secrets have been difficult to uncover. However, we finally have the technology that allows us to see into the living brain. With this capability, we can gather and analyze terabytes of data with a fidelity that was previously impossible.

In 2019, the Center for BrainHealth® opened The University of Texas at Dallas BrainHealth Imaging Center, which is uniquely focused on the discovery of composite brain health metrics to measure the brain's positive response to interventions. In addition, The BrainHealth Project is generating vast amounts of data from our technology platform, the training modules and our multimodal brain imaging paradigms. These anonymized data will be shared openly with collaborating researchers to uncover new insights and pave the way for precision brain health.

Group photo of Sergey C, Bart R, Angela P, and Jason G standing in front of MRI machine in the imaging center

UTD BrainHealth Imaging Center staff: Sergey Cheshkov, PhD – Research Scientist; Bart Rypma, PhD – Director of UTD BrainHealth Imaging Center; Angela Plata – Administrative Coordinator; Jason Grubb - MRI Technology Manager

UTD BrainHealth Imaging Center

OPTIMIZED FOR FUNCTIONAL IMAGING

The University of Texas at Dallas BrainHealth® Imaging Center is a one-of-a-kind facility completely focused on human brain imaging to measure changes in brain health and function. The two 3-tesla MRI scanners enable exciting, leading-edge research to advance the measurement of brain improvement. By leveraging imaging and other technology, we can objectively measure if, how and to what extent someone's brain is getting healthier and fitter over time.

Dr. Jeffrey Spence, director of biostatistics at the Center for BrainHealth, and Dr. Asha Vas worked together on the gist reasoning test research.  Vas was a postdoctoral fellow during the time of the study.

Machine Learning

Individualized Precision Health

Machine learning will allow us to take very large volumes of data and help identify the most important markers of brain health, validate indices, and choose targeted training strategies for individualized, precision brain health. Scaling these evidence-based brain health protocols will ultimately move global public health to an entirely new level.

Jeffrey S. Spence, PhD Director of Biostatistics

Virtual Social Learning Platform

Researched Here – Developed Here

Center for BrainHealth developed Charisma™, a flexible, virtual simulation platform that is used in combination with a clinician-led cognitive social learning protocol to help users increase their social adeptness. Charisma leverages cutting-edge game development software to allow repeated – but novel – practice with real-time simulation of authentic, dynamic social interactions at varying levels of complexity.

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