Visualizing spatially distributed hemodynamic lag times in event-related functional MRI: Estimation of a characteristic visual `impulse response'

Vince D. Calhoun, Tulay Adali, Michael Kraut, Paul Rivkin, Godfrey Pearlson

Research output: Contribution to journalConference article

Abstract

Functional MRI is a technique capable of providing spatial and temporal information about the brain's hemodynamics. It has been observed that the onset of observed signal changes can vary across regions exhibiting activation. We have developed a method for extracting information about these timing differences and for observing the temporal-spatial distribution of the blood response by characterizing a typical hemodynamic response (HR) to a single flash of light repeated at 30s intervals. We anatomically locate voxels in the primary visual cortex, a region located along the calcarine sulcus, which is the main terminus of the geniculocortical visual pathways. This average response profile is correlated with the data, producing a map of `active' voxels. Next, we explore the distribution of lags by shifting the HR, correlating this signal with the data, and producing another map. We observed increased activation in non-primary visual cortex as the lag was increased to 2-3s. These results can be most effectively displayed in a time lapse movie. The described technique provides a way of determining varying hemodynamic lag times and partitioning `activated' regions in time. It also clearly demonstrates that these time lags do differ spatially.

Original languageEnglish (US)
Pages (from-to)2124-2127
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume4
StatePublished - Dec 1 1998
EventProceedings of the 1998 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 4 (of 6) - Hong Kong, China
Duration: Oct 29 1998Nov 1 1998

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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