Repository logo
Log In

University Digital Conservancy

University Digital Conservancy

Communities & Collections
Browse
About
AboutHow to depositPolicies
Contact

Browse by Subject

  1. Home
  2. Browse by Subject

Browsing by Subject "fMRI data"

Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Item
    Bayesian spatiotemporal modeling using spatial hierarchical priors with applications to functional magnetic resonance imaging
    (2015-01) Bezener, Martin Andrew
    Functional magnetic resonance imaging (fMRI) has recently become a popular tool for studying human brain activity. Despite its widespread use, most existing statistical methods for analyzing fMRI data are problematic. Many methodologies oversimplify the problem for the sake of computational efficiency, often not providing a full statistical model as a result. Other methods are too computationally inefficient to use on large data sets. In this paper, we propose a Bayesian method for analyzing fMRI data that is computationally efficient and provides a full statistical model.

UDC Services

  • About
  • How to Deposit
  • Policies
  • Contact

Related Services

  • University Archives
  • U of M Web Archive
  • UMedia Archive
  • Copyright Services
  • Digital Library Services

Libraries

  • Hours
  • News & Events
  • Staff Directory
  • Subject Librarians
  • Vision, Mission, & Goals
University Libraries

© 2025 Regents of the University of Minnesota. All rights reserved. The University of Minnesota is an equal opportunity educator and employer.
Policy statement | Acceptable Use of IT Resources | Report web accessibility issues