Modular changes in functional connectivity associated with clinical symptoms in mild traumatic brain injury (mTBI)
Radhika Madhavan1, Hariharan Ravishankar1, Suresh E Joel1, Rakesh Mullick1, Sumit Niogi2, John A Tsiouris2, Luca Marinelli3, and Teena Shetty4
1GE Global Research, Bangalore, India, 2Weill Cornell Medical College, New York, NY, United States, 3GE Global Research, Niskayuna, NY, United States, 4Hospital for Special Surgery, New York City, NY, United States
Although most mTBI patients recover by 3-6
months, they suffer serious short and long term effects. Additionally, multiple
mTBIs may have serious long-term consequences. Here, we correlated brain
network-level connectivity features derived from resting state functional
magnetic resonance imaging (rs-fMRI) with clinical symptoms, in order to identify neuroimaging
biomarkers of mTBI as patients recover over 3 months. We used a
machine-learning framework to select connectivity features associated with
symptoms and identified functional regions with altered connectivity. These
modular network-level features can be used as diagnostic tools for predicting
disease severity and recovery profiles.
This abstract and the presentation materials are available to members only;
a login is required.