Targeting Reward Pathways to Treat Depression – Neuroscience News
New research highlights how the brain’s reward-learning system can guide personalized treatments for depression.
New research highlights how the brain’s reward-learning system can guide personalized treatments for depression.
1 Translational Medical Research/International Master in Innovative Medicine Master Program, Medical Faculty of Mannheim, University of Heidelberg, Mannheim, Germany 2 Department of Psychiatry and Psychotherapy,…
1 School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China 2 School of Information Engineering, Hangzhou Medical College, Hangzhou, China 3…
Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway Hodological patterning refers to developmental mechanisms that link the location of…
When diagnosing multiple sclerosis (MS), the “central vein sign” (the presence of a vein at the center of white matter hyperintensities [WMH] on magnetic resonance…
Learn how to become an advocacy leader in your clinic, institution, or community through the AAN Palatucci Advocacy Leadership Forum.
1 School of Computer Science, Northwestern Polytechnical University, Xi’ an, China 2 School of Computer Science and Technology, Xi’ an University of Posts and Telecommunications,…
Meeting Dates: Saturday, November 15 – Wednesday, November 19 Each year, scientists from around the world congregate to discover new ideas, share their research, and…
The Friedman Brain Institute’s Research Scholars Program at Icahn Mount Sinai supports innovative research and unique collaborations among scientists.
Background and ObjectivesCerebrovascular reactivity (CVR) represents the ability of cerebral blood vessels to regulate blood flow in response to vasoactive stimuli and is related to…
Background and ObjectivesEarly presentation and acute treatment for patients presenting with ischemic stroke are associated with improved outcomes. The onset of the COVID-19 pandemic was…