Accelerating the pace of scientific discovery will take more than data generation alone. Innovation is required in the analytic tools and frameworks employed by scientists. This is especially true for efforts to unravel the mysteries of the web of connections in the human brain, increasingly referred to as the “Human Connectome.” The Computational Neuroimaging Lab is dedicated to finding useful solutions to complex problems and sharing them with the scientific community.
The lab’s research agenda involves the development of novel computational analysis and experimental techniques for determining how brain function and structure are impacted by mental illness and development. Our researchers are developing real-time fMRI experiments to evaluate the interaction between brain networks, and are applying machine learning and signal processing methods to describe how individual brains differ. Lab staff are also optimizing MRI techniques to better include more of the pediatric and psychiatric populations in research, a critical necessity if we are to focus on developing solutions for children.
The NIH BRAIN Initiative recently awarded the Computational Neuroimaging Lab a grant to extend its C-PAC open-source software to handle nonhuman imaging data. C-PAC is open-source software for MRI analysis that can be used by researchers with limited computer skills, providing automated preprocessing and analysis of resting-state fMRI data.