Alexandre Coimbra1,2, Richard Baumgartner, 2,3, Dai Feng, 2,3, Shubing Wang3, Jaymin Upadhyay, 2,4, Adam Schwarz, 2,5, Julie Anderson, 2,4, Lauren Nutile, 2,4, Gautam Pendse, 2,4, James Bishop, 2,4, Ed George, 2,4, Smiriti Iyengar, 2,5, David Bleakman, 2,5, Richard Hargreaves, 2,6, Jeff Evelhoch1,2, David Borsook, 2,4, Lino Becerra, 2,4
1Imaging, Merck Research Laboratories, West Point, PA, United States; 2Imaging Consortium for Drug Development, Belmont, MA, United States; 3Biometrics, Merck Research Laboratories, Rahway, NJ, United States; 4PAIN, McLean Group, Belmont, MA, United States; 5Lilly Research Laboratories, Indianapolis, IN, United States; 6Neurosciences, Merck Research Laboratories, West Point, PA, United States
It has been suggested that fMRI functional connectivity metrics may be useful tools to test efficacy of CNS therapeuticals. This work provides initial exploration of functional connectivity approaches based on Independent Component Analysis. This is done in the context of a Placebo Controlled study of Buprenorphine, a partial opioid agonist and antagonist. A set of previously reported fundamental resting state networks (RSNs) were examined comprising of medial visual, lateral visual, auditory system, sensory motor system, default mode network, executive control, dorsal visual stream. Treatment effects of Buprenorphine on functional connectivity metrics associated with each of these fundamental RSNs were examined.