Vince Calhoun, PhD
Jane and Bud Smith Chair
Technology is opening new windows of understanding about the brain’s incredible ability to change, grow and adapt, putting us on the cusp of major advances. Dr. Vince Calhoun leverages data in unprecedented ways to help improve individual cognitive function and optimize the performance of the human brain.
As one of the world’s foremost experts in human brain imaging and analysis, Dr. Calhoun’s research focuses on such areas as: image and signal processing, data fusion, multimodal brain imaging (MRI, EEG, MEG, etc.), identification of biomarkers for brain health and disease, machine learning/deep learning, neuroinformatics, and imaging genomics/epigenomics.
A Decade of Intrinsic Networks, Default Mode, and Neurodiagnostic Discovery
Dr. Calhoun developed a widely used approach for estimating brain networks from fMRI data and creating a data-driven functional "connectome" of the brain.
Feature-based Fusion of Medical Imaging Data
This study presents a novel framework for combining information from multiple types of neuroimaging data – a way to ‘fuse’ the data to provide something that is greater than the sum of the parts.
COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets
COINS is a neuroinformatics platform used by researchers around the world which provides a comprehensive system for capture, management and analysis of multiple types of neuroimaging and assessment data.
Deep Learning for Neuroimaging: A Validation Study
This paper was one of the first that developed and applied deep learning approaches to neuroimaging data. The use of deep learning/AI tools to study the brain has since exploded, with exciting new research findings coming out all the time.
Dr. Calhoun delivered the talk "Brain-Based Biomarkers: A Focus on the Heterogeneous by Enhancing Sensitivity to Brain Disorders and Change" during the 2021 season of Frontiers of BrainHealth.
The use of neuroimaging to study mental and neurological disorders has shown to be a powerful tool to capture information on underlying brain changes. However, diagnostic heterogeneity has become a major issue as leaders in the field continue to learn from brain imaging data. One important aspect which has not been well explored is the use of rich, high-dimensional brain data to guide researchers through this complex territory. By focusing on more similar subsets of data, identified via advanced algorithmic strategies, studies can facilitate an apples-to-apples comparison, enhance sensitivity to mental illness, and provide a framework for improved stratification.
Vince Calhoun, author of “The Promise of Big Data Imaging for Mental Health,” published in the Dana Foundation's Cerebrum magazine, discusses his pioneering research with Cerebrum podcast host Bill Glovin.
Knowledge gleaned from big data and advances in neuroimaging have provided new insights into the workings of the brain. In this conversation, Dr. Calhoun explores these two evolving fields and their potential to impact of both mental health and neurodegenerative treatment.