Mark Reimers

About Mark Reimers

Dr. Mark Reimers uses advanced data analysis and computational modeling to study brain function. His research work focuses on analyzing and interpreting the very large data sets now being generated in neuroscience especially using the high-throughput technologies developed by the BRAIN Initiative. He obtained his MSc in scientific computing, and his PhD in probability theory from the University of British Columbia in Canada. He has worked at several start-up companies, at Memorial University in Canada, the Karolinska Institute in Stockholm, the National Institutes of Health in Maryland, the Virginia Institute for Psychiatric and Behavioral Genetics in Richmond, and since January 2015 in the Neuroscience Program at MSU. He supervised the data analysis for the BrainSpan paper on the development of gene expression in the human brain in Nature in 2011, and assisted in data analysis for a paper analyzing cortical dynamics on the surface of mouse brain in Nature Neuroscience in 2013.

Are FMRI Data Analysis Methods Reliable?

There’s been a lot of discussion on social media of a recent paper in PNAS by Anders Eklund, Tom Nichols, and Hans Knutsson.
Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates
Even Science magazine felt they needed to address it. What is this fuss all about?

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What are Computational and Systems Neuroscience?

One of the fundamental questions motivating neuroscientists is to understand the relationship between brain activity and lived experience: how the different parts of the brain work together to produce the key ingredients for behavior: memory, feeling, thinking and imagination. These motivating issues have been pretty much inaccessible for most of the history of neuroscience, because we could not observe very much of the brain in action in enough detail to identify individual circuits or on the time scale on which they work. That is starting to change.

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