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UID:10000834-1760711400-1760716800@micde.umich.edu
SUMMARY:Graduate Opportunities in Computational and Data Science Information Session
DESCRIPTION:The educational programs represented will be: \n\nPhD in Scientific Computing (MICDE)\nGraduate Certificate in Computational Discovery & Engineering (MICDE)\nGraduate Certificate in Computational Neuroscience (MICDE)\nGraduate Certificate in Data Science (MIDAS)\n\nThese programs are open to U-M graduate students with an interest in scientific computing or data science. If you have any questions about these programs or about the information session\, please reach out to MICDE (micde-contact@umich.edu) or MIDAS (midas-contact@umich.edu). \nPlease register to attend
URL:https://micde.umich.edu/event/workshop-seminargraduate-opportunities-in-computational-and-data-science/
LOCATION:Weiser Hall\, Room 555\, 500 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Info Session,Sessions
ATTACH;FMTTYPE=image/png:https://micde.umich.edu/wp-content/uploads/2025/09/2025-Happening@UMich-graphic.png
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DTSTAMP:20230905T171405Z
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UID:10000245-1569841200-1569844800@micde.umich.edu
SUMMARY:MICDE Seminar: Jason MacLean\, Associate Professor\, Neurobiology\, University of Chicago
DESCRIPTION:Bio: Jason MacLean is an Associate Professor in the Department of Neurobiology and director of undergraduate studies in neuroscience at the University of Chicago.  His research aims to define how information is encoded in the brain by large groups of synaptically interconnected neurons using a range of analytical approaches. He complements this work by simulating and training spiking neuronal networks. Jason completed his Ph.D. at the University of Manitoba in Canada\, and worked at Cornell University and Columbia University before establishing his own group at the University of Chicago in 2008. He and his wife have two children and he no longer has time for hobbies. \nRecurrent interactions can explain the variance in single trial responses\nTo develop a complete description of sensory encoding\, it is necessary to account for trial-to-trial variability in cortical neurons. Using a generalized linear model with terms corresponding to the visual stimulus\, mouse running speed\, and experimentally measured neuronal correlations\, we modeled short term dynamics of L2/3 murine visual cortical neurons to evaluate the relative importance of each factor to neuronal variability within single trials. We find single trial predictions improve most when conditioning on the experimentally measured local correlations in comparison to predictions based on the stimulus or running speed. Specifically\, accurate predictions are driven by positively co-varying and synchronously active functional groups of neurons. Including functional groups in the model enhances decoding accuracy of sensory information compared to a model that assumes neuronal independence. Functional groups\, in encoding and decoding frameworks\, provide an operational definition of Hebbian assemblies in which local correlations largely explain neuronal responses on individual trials. \nProf. MacLean is being hosted by Prof. Watson (Psychiatry). If you would like to meet with him during his visit\, please send an email to micde-events@umich.edu. If you are an MICDE student and would like to join Prof. MacLean for lunch please RSVP by Saturday\, September 28th. 
URL:https://micde.umich.edu/event/fall2019-maclean-uchicago/
LOCATION:Weiser Hall\, Room 555\, 500 Church St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Featured Events,MICDE Seminar Series
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