Improved localization of language areas using single voxel signal analysis of unprocessed fMRI data

Leonard Fetscher; Marion Batra; Uwe Klose

doi:10.3389/fradi.2022.997330

Improved localization of language areas using single voxel signal analysis of unprocessed fMRI data

Front Radiol. 2022 Sep 22:2:997330. doi: 10.3389/fradi.2022.997330. eCollection 2022.

Authors

Leonard Fetscher¹, Marion Batra¹, Uwe Klose¹

Affiliation

¹ Department of Diagnostic and Interventional Neuroradiology, University Clinic of Tuebingen, Radiological Clinic, Tuebingen, Germany.

Abstract

Activated brain regions can be visualized and localized with the use of fMRI (functional magnetic imaging). This is based on changes in the blood flow in activated regions, or more precisely on the hemodynamic response function (HRF) and the Blood-Oxygen-Level-Dependent (BOLD) effect. This study used a task-based fMRI examination with language paradigms in order to stimulate the language areas. The measured fMRI data are frequently altered by different preprocessing steps for the analysis and the display of activations. These changes can lead to discrepancies between the displayed and the truly measured location of the activations. Simple t-maps were created with unprocessed fMRI data, to provide a more realistic representation of the language areas. HRF-dependent single-voxel fMRI signal analysis was performed to improve the analyzability of these activation maps.

Keywords: HRF-dependent parameters; filter; hemodynamic response function (HRF); language fMRI; t-Map; task-based fMRI; unprocessed fMRI.

Grants and funding

This research was funded by “Interdisziplinäres Promotionskolleg Medizin” (IZKF) of the University of Tübingen. Furthermore, we acknowledge support by Open Access Publishing Fund of University of Tübingen.