Real-time multiple linear regression for fMRI supported by time-aware acquisition and processing

Christopher Smyser, Thomas J. Grabowski, Randall J. Frank, John W. Haller, Lizann Bolinger

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Real-time parametric statistical analysis of functional MRI (fMRI) data would potentially enlarge the scope of experimentation and facilitate its application to clinical populations. A system is described that addresses the need for rapid analysis of fMRI data and lays the foundation for dealing with problems that impede the application of fMRI to clinical populations. The system, I/OWA (Input/Output time-aWare Architecture), combines a general architecture for sampling and time-stamping relevant information channels in fMRI (image acquisition, stimulation, subject responses, cardiac and respiratory monitors, etc.) and an efficient approach to manipulating these data, featuring incremental subsecond multiple linear regression. The advantages of the system are the simplification of event timing and efficient and unified data formatting. Substantial parametric analysis can be performed and displayed in realtime. Immediate (replay) and delayed off-line analysis can also be performed with the same interface. The capabilities of the system are demonstrated in normal subjects using a polar visual angle phase mapping paradigm. The system provides a time-accounting infrastructure that readily supports standard and innovative approaches to fMRI.

Original languageEnglish
Pages (from-to)289-298
Number of pages10
JournalMagnetic resonance in medicine
Volume45
Issue number2
DOIs
StatePublished - 2001

Keywords

  • Brain mapping
  • Multiple linear regression
  • Real-time
  • fMRI

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