Open AccessAn investigation of positive and inverted hemodynamic response functions across multiple visual areas
Author(s) -
Puckett Alexander M.,
Mathis Jedidiah R.,
DeYoe Edgar A.
Publication year - 2014
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.22569
Subject(s) - voxel , retinotopy , neuroscience , visual cortex , stimulus (psychology) , functional magnetic resonance imaging , deconvolution , haemodynamic response , blood oxygen level dependent , brain mapping , visual field , impulse response , photic stimulation , psychology , visual perception , artificial intelligence , pattern recognition (psychology) , computer science , biology , cognitive psychology , perception , mathematics , algorithm , heart rate , blood pressure , endocrinology , mathematical analysis
Recent studies have demonstrated significant regional variability in the hemodynamic response function (HRF), highlighting the difficulty of correctly interpreting functional MRI (fMRI) data without proper modeling of the HRF. The focus of this study was to investigate the HRF variability within visual cortex. The HRF was estimated for a number of cortical visual areas by deconvolution of fMRI blood oxygenation level dependent (BOLD) responses to brief, large‐field visual stimulation. Significant HRF variation was found across visual areas V1, V2, V3, V4, VO‐1,2, V3AB, IPS‐0,1,2,3, LO‐1,2, and TO‐1,2. Additionally, a subpopulation of voxels was identified that exhibited an impulse response waveform that was similar, but not identical, to an inverted version of the commonly described and modeled positive HRF. These voxels were found within the retinotopic confines of the stimulus and were intermixed with those showing positive responses. The spatial distribution and variability of these HRFs suggest a vascular origin for the inverted waveforms. We suggest that the polarity of the HRF is a separate factor that is independent of the suppressive or activating nature of the underlying neuronal activity. Correctly modeling the polarity of the HRF allows one to recover an estimate of the underlying neuronal activity rather than discard the responses from these voxels on the assumption that they are artifactual. We demonstrate this approach on phase‐encoded retinotopic mapping data as an example of the benefits of accurately modeling the HRF during the analysis of fMRI data. Hum Brain Mapp 35:5550–5564, 2014 . © 2014 Wiley Periodicals, Inc.