Marco A. M. Prado, Ph.D. is the Tier 1 CRC in Neurochemistry of Dementia, University of Western Ontario. Dr. Prado held editorial positions in scholarly journals, including Deputy Editor in Chief and Reviews Editor for the Journal of Neurochemistry, former Editor in ASN Neuro, Associate Editor of Frontiers in Neuroscience, and Section Editor for the Brazilian Journal of Medical and Biological Research. He has also served on the board of PrioNET-Canada and in the advisory Board of the Institute of Neuroscience Mental Health and Addiction-CIHR.

Dr. Prado’s laboratory focus on generating and characterizing mouse models of dementia and understanding how neurochemical alterations in neurodegenerative diseases contribute to protein misfolding and cognitive dysfunction. His research group combines the use of sophisticated touchscreen tests of high-level cognition and detailed biochemical, imaging, and genetic analysis to reveal mechanisms regulating pathological changes relevant to human disease. Dr. Prado has received numerous awards and recognition for his research, including a Guggenheim Fellowship, Faculty Scholar Award, and Dean’s Research Excellence Award. He has been funded by several organizations, including CIHR, CFI, Networks of Centers of Excellence, NSERC, NIH, Alzheimer’s Association, Alzheimer’s Society of Canada, ALS-Canada, Brain Canada, and the Weston Family Foundation. Dr. Prado has published over 200 manuscripts that received more than 11,000 citations. Work from his lab has been critical to inform on genes that cause rare diseases (VAChT) and determined potential physiological functions for the prion protein. He has also contributed to the understanding of roles of chaperones in mammalian physiology and neurodegenerative diseases in vivo and generated multiple mouse models of dementia. Dr. Prado is currently spearheading with several colleagues an Open Science Repository (www.mousebytes.ca) for high-level cognitive, imaging and neurochemical data in mouse models of dementia, to increase the reproducibility and replicability of datasets in pre-clinical research.