Accurate prediction of V1 location from cortical folds in a surface coordinate system
Introduction
The cerebral cortex can be parcellated into many distinct architectonic areas based on laminar differences in neuron and myelin density (Bolton, 1900, Smith, 1904, Campbell, 1905, Brodmann, 1909, Vogt, 1911, Flechsig, 1920, von Economo and Koskinas, 1925). These architectonic areas are thought to serve distinct functional roles, and thus a substantial amount of work has concentrated on locating areas and characterizing their features.
Directly determining the precise location of architectonic areas in a living human is not currently possible. However, observing macroscopic geometric features of the cerebral cortex in an individual is straightforward using standard structural MRI techniques. The goal of probabilistic atlases is to predict the location of cortical areas, which are difficult to image, from the easily imaged cortical geometry. In this context a probabilistic atlas refers to a map of the location of a cerebral cortical area relative to geometric features of the brain. For atlases of cortical areas to be useful, their location must be predictable from brain geometry, and the methods used to create and apply the atlas must effectively capture the relationship between areas and geometric features of the brain.
Recently, methods have been developed to generate probabilistic atlases of cortical areas in a stereotaxic coordinate system by matching the intensities of volumetric brain images via linear transformations (Talairach and Tournoux, 1988) or nonlinear transformations (Roland et al., 1994, Schormann and Zilles, 1998). These volume-based intersubject registration techniques were used to build a probabilistic atlas of human primary visual cortex (V1) (Amunts et al., 2000), as well as a number of other cortical areas (Amunts et al., 1999, Geyer et al., 1999, Grefkes et al., 2001, Morosan et al., 2001, Rademacher et al., 2001b Eickhoff et al., 2007, Amunts et al., 2005, Wilms et al., 2005, Caspers et al., 2006). These studies represent the only probabilistic atlases of cortical areas delineated anatomically. Unfortunately, these atlases exhibit substantial intersubject variability, which indicates a substantial probability of error when predicting area location. This suggests that the geometric features of cortex used to produce the atlases are poor predictors of area location.
Because the cerebral cortex has the topology of a two-dimensional sheet, it is natural to represent cortical geometry in terms of its many sulci and gyri rather than in terms of a three-dimensional volume. Historically, cortical folds have been used as a qualitative method for describing cortical geometry, and in the last two decades several methods for quantitative surface-based analysis have been developed (Schwartz and Merker, 1986, Boissonnat, 1988, Dale and Sereno, 1993, Davatzikos and Bryan, 1996, Van Essen and Drury, 1997, Dale et al., 1999, Fischl et al., 1999a, Andrade et al., 2001, Goebel et al., 2006).
Previous studies investigating the relationship between primary cortical folds and primary sensory areas have found a consistent co-location (Sanides, 1970, Welker, 1990, Rademacher et al., 1993)—especially for V1. Smith (1904) performed an early study of the relationship between V1 and the cortical folds. He claimed that location of the stria of Gennari, a stripe of highly myelinated tissue particular to layer IV of V1 (Zeki, 1970, Boyd and Matsubara, 2005), was a reliable predictor of the location of the calcarine sulcus. Later studies (Putnam, 1926, Stensaas et al., 1974, Rademacher et al., 1993, Zilles et al., 1997, Hasnain et al., 2001) supported this general conclusion, but also reported intersubject variability in the location of the V1 border in relation to nearby gyri and sulci. Thus, previous studies indicate a gross consistency between the location of cortical folds and that of V1, but the lack of quantitative analysis methods dictates that only very general conclusions can be made about the strength of this relationship, and comparison of the results between studies is difficult. A goal of the work presented here was to measure the error in the predicted location of V1 when the primary cortical folds are used to align cortical geometry.
Probabilistic atlases are created and applied using intersubject registration techniques (Talairach and Tournoux, 1988, Roland et al., 1994, Friston et al., 1995, Fischl et al., 1999b, Van Essen, 2005), which provide a method for alignment based on cortical geometry. Thus far, atlases of V1 have been created using volume-based intersubject registration methods and have reported substantial variability in the location of cortical areas. However, because folds were not used in registration, this previous work has not addressed the relationship between the cortical folds and cortical areas.
Surface-based intersubject registration methods, which have been developed to aid in analysis and visualization of functional imaging data (Drury et al., 1996, Sereno et al., 1996, Thompson and Toga, 1996, Davatzikos, 1997, Fischl et al., 1999b), use the gross cortical folding pattern to derive a correspondence between the cortical surfaces of individuals. The goal of registration is to align common functional areas across subjects, and thus these methods have been developed and used under the assumption that alignment of cortical folds results in alignment of areas. Previous studies have suggested that aligning the folds effectively aligns areas (Fischl et al., 1999b), but no direct validation has been reported.
Surface-based analysis tools have been adopted mainly for use in functional imaging studies on live human subjects and have not seen wide use in postmortem studies where histological analysis is possible. Because observation of the precise location of cortical areas has up to now required staining and slicing of the cortex postmortem–a process that complicates surface reconstruction–surface-based analysis has not been applied to studies investigating cortical areas. Recently, methods for imaging ex vivo human cortical hemispheres at high resolution using MRI (Augustinack et al., 2005, Hinds et al., 2005) have allowed investigation of microanatomical cortical features in intact hemispheres. A goal of the work presented here was to apply existing surface-based registration techniques to high-resolution structural MRI data of ex vivo human cortex.
The application of surface-based intersubject registration to the location of V1 provides a probabilistic atlas of V1, which here refers to a computational method for predicting the location of V1 in living subjects based on their particular pattern of cortical folds. The amount of error in the atlas prediction indicates the effectiveness of the registration method at creating overlap of common functional areas among a group of subjects. Because registration methods are used to enable intersubject averaging in functional or morphometric imaging experiments, the amount of overlap dictates the benefit gained by pooling data from corresponding cortical areas across subjects. Most methods for intersubject averaging use cortical geometry to compute correspondence between individual brains (Fischl et al., 1999b, Van Essen, 2005), thus assuming a particular relationship between geometry and areas that has not yet been directly established. The results of this work establish a stable relationship between the cortical folds and areas. This relationship suggests both that the location of the folds are functionally significant and that surface-based intersubject registration methods are effective tools increasing statistical power via multisubject averaging in functional for imaging studies.
Section snippets
Magnetic resonance imaging
Twenty whole, formalin-fixed ex vivo human hemispheres (ten right hemispheres and ten left hemispheres) were obtained under an Institutional Review Board-approved protocol through the autopsy service of the Massachusetts General Hospital and with the cooperation of the Massachusetts Alzheimer Disease Research Center, the Massachusetts Eye and Ear Infirmary, and the Center for Neuroimaging of Aging and Neurodegenerative Disease. Five of the right hemispheres were from individuals with no
Iterations of template generation
To determine the number of productive iterations of template generation, V1 alignment quality was computed for between one and four iterations. Fig. 2 shows the relationship between alignment quality and iteration number. Alignment quality increases for the first and second iterations of template generation for each hemisphere and similarity measure and no benefit consistent over all similarity measures is gained after the third iteration. Therefore, in the following V1 alignment was considered
Predicting V1 from folds
The results of the work presented here indicate that the primary folds serve as a good predictor for the location of V1. The degree to which this is the case has thus far been overlooked due the lack of adequate quantitation in previous studies.
Stensaas et al. (1974) investigated the relationship of V1 to the location of the lips of the calcarine sulcus in an effort to determine the best placement for electrodes as part of a potential cortical visual prosthesis. They found that on average 67%
Acknowledgments
Support for this research was provided in part by the National Institute for Biomedical Imaging and Bioengineering (R01 EB001550), Mass. ADRC grant (5P50 AG05134), the National Center for Research Resources (P41 RR14075, R01 RR16594 and the NCRR BIRN Morphometric Project BIRN002, U24 RR021382), the National Institute for Neurological Disorders and Stroke (R01 NS052585), as well as the Mental Illness and Neuroscience Discovery (MIND) Institute and is part of the National Alliance for Medical
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