Dr. Martin Lindquist, a professor in the department of biostatistics at the Johns Hopkins Bloomberg School of Public Health, recently received a $2.74 million four-year grant from the National Institute of Biomedical Imaging to study individualized spatial topology in functional neuroimaging.
In the past, Dr. Lindquist’s team has used functional Magnetic Resonance Imaging (fMRI) data and modern statistical methods to create population-based models that identify patterns of brain activity, which they call “signatures,” that can predict behavior and decode mental states in new individuals, previously not studied. These signatures are limited by neuroanatomical constraints, particularly a varying in brain anatomy in individuals.
While current approaches look to work around this problem by forcing participants’ data into anatomical reference spaces that do not respect their varying neurological topology, this grant will help Dr. Lindquist and his team model the functional topology of individual participants and integrate that into population-level models. Dr. Lindquist believes this will help advance the accuracy and understanding of representations of the brain in cognitive and affective neurosciences, and also transform the way various fields analyze neuroimaging data.
Dr. Lindquist’s research focuses on mathematical and statistical problems related to functional Magnetic Resonance Imaging (fMRI). For the last 15 years he has been actively involved in developing new analysis methods to enhance our ability to understand brain function using human neuroimaging.