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 "Serial correlation"

Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Item
    Melodies in space: neural processing of musical features
    (2013-03) Dumas, Roger Edward
    With modern digital technology, it is now possible to capture, store and describe the brain's response to musical stimuli with some degree of confidence. Increasing financial and materiel resources are being made available to music-brain researchers and, as a result, the number of music perception and cognition publications is expanding exponentially (Levitin & Tirovolas, 2011). Many neuro-musicologists have access to at least one of the two most popular brain-imaging technologies, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). EEG measures the electric brain signal passing through soft tissues, which becomes 'smeared' and difficult to separate from signals measured elsewhere on the scalp. fMRI measure the blood-oxygen level dependent (BOLD) signal, however this signal develops too slowly (2-5 seconds) to accurately capture the brain's swift processing of individual melodic notes. In contrast, magneto-encephalography (MEG) affords high temporal resolution (1 ms) and high fidelity (i.e. the clean, direct measurement of undistorted electromagnetic fluctuations in neural populations) and is therefore the most suitable method for matching the brain's dynamic, interacting sub-networks to the processing of melodies played at normal tempos. To explore my idea that this evolving process is both observable and quantifiable, I have performed a series of MEG experiments involving human subjects listening to melodic stimuli. This dissertation details my examination of the brain's response to melodic pitch, contour, interval distance and next-note probability.

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