Journal of Data Science logo


Login Register

  1. Home
  2. Issues
  3. Volume 6, Issue 1 (2008)
  4. Identifying Multisubject Cortical Activa ...

Journal of Data Science

Submit your article Information
  • Article info
  • More
    Article info

Identifying Multisubject Cortical Activation in Functional MRI: A Frequency Domain Approach
Volume 6, Issue 1 (2008), pp. 89–103
Joao Ricardo Sato  

Authors

 
Placeholder
https://doi.org/10.6339/JDS.2008.06(1).375
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

Abstract: Functional magnetic resonance imaging (fMRI) has, since its de scription fifteen years ago, become the most common in-vivo neuroimaging technique. FMRI allows the identification of brain areas which are related to specific tasks, by statistical analysis of the BOLD (blood oxigenation level dependent) signal. Classically, the observed BOLD signal is compared to an expected haemodynamic response function (HRF) using a general linear model (GLM). However, the results of GLM rely on the HRF specification, which is usually determined in an ad hoc fashion. For periodic experimental designs, we propose a multisubject frequency domain brain mapping, which requires only the stimulation frequency, and consequently avoids subjective choices of HRF. We present some computational simulations, which demon strate a good performance of the proposed approach in short length time series. In addition, an application to real fMRI datasets is also presented.

PDF XML
PDF XML

Copyright
No copyright data available.

Metrics
since February 2021
515

Article info
views

268

PDF
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

Journal of data science

  • Online ISSN: 1683-8602
  • Print ISSN: 1680-743X

About

  • About journal

For contributors

  • Submit
  • OA Policy
  • Become a Peer-reviewer

Contact us

  • JDS@ruc.edu.cn
  • No. 59 Zhongguancun Street, Haidian District Beijing, 100872, P.R. China
Powered by PubliMill  •  Privacy policy