Retinotopic maps and hemodynamic delays in the human visual cortex measured using arterial spin labeling
Introduction
The human visual cortex is partitioned into a number of functional areas with specific local neuronal properties (DeYoe et al., 1996, Engel et al., 1997, Sereno et al., 1995, Wandell et al., 2007, Watson et al., 1993, Zeki et al., 1991). That is, adjacent neurons have receptive fields covering adjacent points in the visual field (Brewer et al., 2005, Wandell et al., 2007). This spatial organization of the neuronal properties is called retinotopy. Functional magnetic resonance imaging (fMRI) has been used for over a decade to identify the visual field maps in the human cortex (DeYoe et al., 1996, Engel et al., 1997, Engel et al., 1994, Hasson et al., 2003, Huk et al., 2002, Sereno, 1998, Sereno et al., 1995, Sereno et al., 2001, Silver et al., 2005, Swisher et al., 2007, Tootell and Taylor, 1995, Tootell et al., 1997). Many studies have used blood oxygenation level-dependent (BOLD) fMRI to non-invasively visualize retinotopic maps, e.g. for intersubject comparisons of the human visual system (Tootell and Hadjikhani, 2001, Wade et al., 2002), for measuring the position, surface area and visual field representations of the visual cortex (Dougherty et al., 2003, Endo et al., 1997, Engel et al., 1997), for quantitative estimation of cortical magnification factor (Sereno et al., 1995) and receptive field size (Smith et al., 2001) and in numerous cognitive experiments (e.g. Boynton, 2005, Brefczynski and DeYoe, 1999, Saygin and Sereno, 2008, Tootell et al., 1998, Wandell, 1999).
Although measuring the BOLD signal is the main fMRI tool for mapping studies and has been widely used to create visual field maps and delineate visual areas, it has potential limitations due to the underlying physiological and physical processes giving rise to the BOLD signal. BOLD contrast relies on changes of local magnetic susceptibility induced by the changes in paramagnetic deoxyhemoglobin, reflecting the increased metabolic demands of enhanced neural activity (Logothetis, 2008). In addition, the fMRI signal also directly depends on cerebral blood volume changes altering the balance of intra- and extra-vascular MRI signal contributions (Uludag et al., 2009, and references therein). Many studies have shown that such changes not only occur in brain parenchyma (e.g., gray matter) but also in the draining veins on the surface of the parenchyma. It has been experimentally and theoretically shown that at 1.5 and 3 T magnetic field strength, using the gradient-echo and spin-echo MRI acquisition schemes, most of the BOLD signal originates from veins (Boxerman et al., 1995, Buxton et al., 1998, Lai et al., 1993, Song et al., 1996, Uludag et al., 2009). As a result, the spatial location of the BOLD signal change at 3 T fails to define exactly where the neuronal activity occurs. Hence, the BOLD signal might show a spatial displacement from the actual site of neuronal activation, thereby reducing the specificity of the functional localization (Ugurbil et al., 2003). In addition, the BOLD signal delays can vary considerably depending on the local vasculature. Signals originating near large draining veins have been shown to have delays of several seconds longer compared to those originating from the capillary bed (Birn et al., 2001, Lee et al., 1995, Saad et al., 2001). This is substantial for retinotopic mapping studies even if the rotation direction of phase-encoding stimuli is systematically reversed, as the noise in their averaged signal can increase the more the assumed global BOLD signal delay differs from the actual BOLD signal delay.
Several alternative fMRI methods to BOLD contrast were proposed in the last decade. These assess different physiological processes and have different sensitivities such as contrast agent methods, vascular space occupancy (VASO) and nuclear medicine. Direct measurement of CBF using arterial spin labeling (ASL) MRI is a promising alternative for functional activation and baseline studies. Perfusion imaging using ASL allows noninvasive measurement of CBF by assessing the inflow of magnetically tagged arterial water into an imaging slice (Detre et al., 1992, Wong et al., 1998). The CBF signal arises from labeled water spins that have passed through the capillary walls into the tissue or are still within the capillaries (Silva et al., 1997), as the amount of tagged water in humans at 3 T reaching the veins is negligible (Wong et al., 1997). Therefore, CBF signal is more tightly linked to the capillary bed whose vascular properties are directly modulated by the surrounding nervous tissue. In accordance with this, a number of fMRI studies that compared BOLD and CBF signals reported that CBF measurements provide better functional localization than the BOLD signal (Aguirre et al., 2002, Duong et al., 2001, Luh et al., 2000, Tjandra et al., 2005, Wang et al., 2003). In addition, several authors have reported that CBF changes have lower intersubject variability and are more reproducible compared to BOLD signals (Aguirre et al., 2002, Tjandra et al., 2005, Wang et al., 2003). On the other hand, ASL has relatively lower SNR than BOLD signal and has a number of systematic confounding factors such as transit delay, magnetization transfer and relaxation artifacts.
The current study was therefore driven by two main motivations: firstly, to demonstrate, for the first time, delineation of visual areas using CBF weighted retinotopic maps and secondly the systematic characterization of BOLD signal delays relative to those of CBF across human visual areas. To this end, we exposed five human volunteers to visual displays of rotating wedge and expanding ring stimuli utilizing an ASL sequence that enabled simultaneous acquisition of BOLD- and perfusion-weighted images. We calculated the phase maps for the polar angle and eccentricity across their occipital cortices for each of the two fMRI imaging modalities. The visual areas were then determined for each of the fMRI imaging modalities and the overlap of the resulting visual areas V1, V2, V3, hV4, and V3A/B was compared. Furthermore, the general approach in retinotopic mapping is assuming that the hemodynamic delay of the response remains fixed at each cortical position. Here, we calculated the hemodynamic delays for each voxel separately and used the corresponding values for phase calculations. We assessed the potential sources for the discrepancies between the BOLD signal and perfusion-based retinotopic maps from the aspect of both calculation methods and underlying physiology. Finally, we assessed the reproducibility of the retinotopic maps created from BOLD signal and perfusion-weighted images. A preliminary version of this work has been previously presented in abstract form (Cavusoglu et al., 2010).
Section snippets
Subjects
Five healthy subjects participated in the experiments (mean age 26 ± 6 years). They were familiarized with the stimuli outside the scanner, and practiced each task for 4–6 min in the scanner. Written consent from the participants was obtained before the experiments began and the experimental protocol was approved by the ethics committee of the University of Tübingen.
Stimulus paradigm
Phase-encoded retinotopic maps were calculated from measurements obtained using standard rotating wedge and expanding ring stimuli
Retinotopic mapping with perfusion contrast
Fig. 2 shows a color plot of the CBF responses to the rotating wedge and expanding ring stimuli on the inflated and flattened cortical surface representations from the right hemisphere of a representative subject. The color scale indicates the raw phase values between 0 and 2π for polar angle and eccentricity. Similar to the well-established BOLD signal retinotopy, CBF activation led to reliable maps throughout the early visual areas.
In the eccentricity map (Figs. 2A, B, C), where the fovea is
Discussion
In this study, we used arterial spin labeling (ASL) fMRI that enables the simultaneous acquisition of BOLD- and perfusion-weighted images (Cavusoglu et al., 2009, Wong et al., 1997) to i) determine the delineations of early visual areas for retinotopic mapping of the human brain using perfusion data, ii) investigate the variations in hemodynamic delay times across the visual areas, iii) explore the uncertainties in retinotopic maps caused by the measurement artifacts particularly due to the
Acknowledgments
We thank Dr. Douglas Greve from the A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, for helpful comments in analyzing the retinotopy data.
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