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.