Functional MRI (fMRI) is a technique that utilizes time-series collection of rapidly-obtained magnetic resonance images that are sensitive to brain activation-induced changes in blood flow, oxygenation, and volume. The most common functional contrast used in fMRI is blood oxygenation level-dependent (BOLD) contrast. Since this technique was developed in 1992, it has continued to advance in methodology sophistication, sensitivity, temporal and spatial resolution, interpretability, and applications.
My Section on Functional Imaging Methods (SFIM), aims to develop and refine novel approaches to fMRI acquisition, brain activation paradigms, neuronal modulation, and processing methods that leverage in-depth and nuanced understanding functional MRI (fMRI) signal and noise so that more precise and interpretable information about human neuronal function and physiology can be extracted. Our ultimate goals are to advance multimodal neuroimaging to both gain insight about the brain and to contribute to health care approaches.
Major subfields of fMRI that my group focus on are ultra-high-resolution fMRI, time-series dynamics, resting-state fMRI, and naturalistic stimuli approaches.
Our Functional MRI Core Facility was started in 1999 and has grown to include 5 MRI scanners, one of which is a 7T scanner for high resolution and high sensitivity functional imaging. Over 30 Principle Investigators throughout the NIH utilize the center.
Our Data Sharing and Science Team supports investigators within the NIMH intramural program in creating, distributing, and leveraging large, open datasets to accelerate discovery. They provide tools and training to help the IRP embrace open science and stay on the cutting edge of novel datasets, tools, and platforms.
Our Machine Learning Team supports researchers in the NIMH intramural research program who want to address research problems in clinical and cognitive neuroscience using machine learning approaches. They do this by consulting with individual researchers and guiding them in the use of the appropriate tools and methods, or by taking on the analysis process themselves. In parallel, they develop new methods and analysis approaches, motivated by the needs of researchers or by the practical possibilities arising from advances in the field.
The Center for Multimodal Neuroimaging brings together NIMH neuroimaging, processing, and neuromodulation expertise so that communication channels are further enhanced between cores, sections, units, individual staff scientists, and, importantly, users. The goals of this level of integration are to foster collaborative bridges, create a centralized view of what is available to users, generate questions that lend themselves to cross-modal investigation and integration, and allow efficient exchange of practical information and new ideas.
More information can be found here for:
Section on Functional Imaging Methods https://fim.nimh.nih.gov
Functional MRI Facility https://fmrif.nimh.nih.gov
Data Sharing and Science Team https://cmn.nimh.nih.gov/dsst
Machine Learning Team https://cmn.nimh.nih.gov/mlt
Center for Multimodal Neuroimaging https://cmn.nimh.nih.gov