Cerebral Cortex Advance Access originally published online on October 5, 2007
Cerebral Cortex 2008 18(6):1415-1420; doi:10.1093/cercor/bhm174
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Deep Sulcal Landmarks Provide an Organizing Framework for Human Cortical Folding
1 Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, 04103 Leipzig, Germany, 2 Kent Institute of Medicine and Health Sciences, Canterbury CT2 7PD, UK
Address correspondence to Gabriele Lohmann, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr. 1a, 04103 Leipzig, Germany. Email: lohmann{at}cbs.mpg.de
| Abstract |
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The folding pattern of the cerebral cortex and its relation to functional areas is notoriously variable and there is a need to identify more consistent 3-dimensional (3D) topographical cortical features. We analyzed magnetic resonance brain images of 96 normal adult human volunteers using automated 3D image analysis methods. We examined the deeper parts of the sulci because they generally show less interindividual variability than more superficial parts, especially in monozygotic twins, and deepest parts of primary sulci are the first to develop embryologically and change least as the cortex expands. Along the length of each sulcus we found that there is generally one well-defined zone where depth is maximal, which we term the sulcal pit. Long sulci may have 2 or 3 pits. The spatial arrangement of pits is strikingly regular, forming alternating chains of deeper and shallower pits. We hypothesize that the pits are encoded in the protomap described in Rakic (1988. Specification of cerebral cortical areas. Science. 241:170–176) and are under closer genetic control than the rest of the cortex and are likely to have a more consistent relationship to functional areas.
Key Words: cortical sulci human cortical folding magnetic resonance imaging sulcal pits
| Introduction |
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The high variability of the topography of the cerebral cortex and its relationship to functional areas continues to present challenges for research into cyto- and fiber architecture, neurophysiology, functional activation, and lesion effects as well as for clinical applications (Rademacher et al. 1993
From a functional point of view, the cortex can be viewed as a 2D processing manifold and this has led to the development of approaches to improve visualization of the manifold and of surface-based coordinate systems to express the spatial relationship of functional or anatomical features on the manifold (van Essen 2005
). The variable relation of many 3-dimensional (3D) topographical features (gyri and sulci) to functional areas is well shown on such maps, although the precision of the different methods involved places clear limits on detailed interpretation (van Essen et al. 1998
).
It would greatly assist the mapping of function to structure if 3D topographical cortical features could be identified, which were more consistent between individuals than the majority of the folding pattern and which bore a more consistent relationship to functional areas. For 2 reasons, we hypothesized that the deepest parts of the sulcal fundi would be the most likely to satisfy these requirements. Firstly, quantitative studies of intersubject variation revealed that the sulcal pattern becomes more consistent at increasing depths below the surface (Le Goualher et al. 1999
; Lohmann et al. 1999
), particularly in monozygotic twins (Lohmann et al. 1999
), indicating increasing genetic influence with depth. Secondly, the deepest parts of sulci form early and retain their identity during development; the more complex (and variable) superficial folds form later (Smart and McSherry 1986
; Welker 1990
). There is abundant evidence that the basic functional organization of the cortical manifold is laid down in the fetal ventricular zone (the "protomap" of Rakic [Rakic 1988
, 2004
; Piao et al. 2004
]), where cortical neurones are formed from progenitor cells before they migrate superficially along a radial glial scaffolding to form the cortical surface. Therefore, it is likely that the deepest parts of the sulci have a specific spatial relationship to functional areas as well as having ontogenetic importance.
In the present study, we developed a method for extracting the deepest parts of the sulcal fundi, which we term the sulcal "pits," and examined their spatial distribution in a large group of individuals.
| Materials and Methods |
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Data Acquisition and Initial Processing
Our data pool consisted of 48 female and 48 male right-handed normal human subjects aged between 18 and 60 years (mean 29.2). The data were acquired in the context of various functional magnetic resonance imaging (MRI) experiments conducted at the Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, between January 2001 and August 2002. All subjects gave informed consent. All subjects received a high-resolution T1-weighted MRI scan acquired on a 3-T magnetic resonance scanner (Bruker Medspec 300, Ettlingen, Germany) using a modified driven equilibrium Fourier transform pulse sequence. Resolution was set to 1 x 1 mm within plane and 1.5 mm between planes. All datasets were initially coregistered using a standard approach based on the AC and PC (Talairach and Tournoux 1988
). For this, the upper rim of AC in the median sagittal plane was taken as the origin and trilinear scaling (derived separately in antero–posterior, lateral, and supero–inferior directions from the bounding box on the outer cerebral surface) was applied to each dataset. At the same time, the datasets were resampled to produce isotropic 1 x 1 x 1 mm voxels. In addition to the affine linear registration to the AC/PC–based coordinate system, we performed a nonlinear registration to the generic gyral model (GGM) as introduced in (Lohmann et al. 2005
, 2006
). The GGM contains a polygonal line–based representation of 6 major cortical gyri obtained as a population average. The registration caused those 6 major gyri to be geometrically aligned in all 96 datasets. The images were then segmented to extract the cerebral white matter, removing nonbrain structures and cortical gray matter, to make sulcal indentations easier to describe and analyze. All subsequent image analysis procedures were based on these coregistered datasets in which the white matter was segmented. The automated segmentation procedures are less reliable for orbital, basal, medial, and insular cortices, and we have restricted the current study to the lateral cortex.
Data Analysis
Our experimental results are based upon automatic image analysis methods applied to the preprocessed MRI data. We extracted a smooth superficial white matter surface with a morphological closing operation using a spherical structuring element of radius 15 mm and referred to this as the "closed" surface. This would correspond to the arachnoid surface if the gray matter were included. Similarly, we extracted a deep white matter surface resembling a primitive unfolded or lissencephalic brain with a morphological opening operation using a spherical structuring element of radius 5 mm and referred to this as the "opened" surface. A distance transform was then computed inside the closed surface, giving the absolute depth of any point measured from this surface (Fig. 1). We automatically segmented all major sulci in an individual and extracted their depth profiles along their entire length (see Fig. 2). We also calculated the depth of points in sulci as a percentage of the distance between the closed (superficial) and opened (deep) white matter surfaces at any point and referred to this as the "relative depth" (Fig. 1).
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Segmentation of Sulcal Pits
To investigate the spatial distribution of the deepest parts of the sulci across individuals, while eliminating minor local variations in the depth profile, we carried out the following steps. We first located all local relative depth maxima on the white matter surface, defined by there being no deeper voxel within a diameter of 5 mm. Starting from each local maximum, we created a small region by linking all voxels that shared a common face (26-connected) with the starting point and that were no more than 5% relative depth shallower than the local maximum. This procedure had the effect of "flooding" the neighborhood of each local maximum, filling a small local region, which we refer to as the "sulcal pit."
| Results |
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We analyzed several properties of sulci as a function of depth as measured from the outer brain surface. When the sulci fundi were examined along their full length, and local fluctuations over a scale of a few millimeters are removed, most sulci had only one depth minimum or pit (Fig. 2). However, for certain major sulci, there may be more than one: the central sulcus usually has 2 and the superior frontal sulcus usually has 3 or 4. Note that a sulcal pit is a locally deepest part of a sulcal base or fundus, the fundus extending along the full length of the sulcus. The longer sulci, mostly corresponding to the traditional primary sulci, extend down to the closed (deep) white matter surface, and we refer to any such sulcus as "major" and to shallower pits as "minor." We have avoided the terms "primary" and "secondary," which are not used consistently in the literature.
The sulci have fewer branches at deeper levels than they do superficially. Their pattern becomes notably more consistent across subjects, and it is much easier to identify interindividual homologies of sulcal pits rather than homologies of entire sulci. Figure 3 shows the sulcal pattern of 2 individuals at 4 different levels of depth. The superficial sulcal pattern in the region of the angular gyrus in the left hemisphere differs markedly in the 2 individuals, but at increasing levels of depth (rows 2 and 3), it becomes clear that the sulcal pattern becomes simpler and progressively more similar and at depth levels between about 50% and 60% reduces to a pit in a similar location. The pit has disappeared by the 86% depth level (bottom row of Fig. 3), and we therefore classify the pit as minor.
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Using the center of gravity of a pit as a point marker for sulcus locations, we analyzed the variation of pits across all 96 subjects. Figure 4 shows that the pit locations form significant clusters not only for major but also for minor sulci. This regularity of minor and major sulci only became apparent when we investigated their deepest regions represented as points in 3D space.
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Table 1 gives the loci of centers of major pit clusters and their densities and the anatomical names of the sulci to which they usually correspond. Similarly, Table 2 gives the loci and densities of minor pit clusters. Note that pits in some clusters may belong to sulci with different names in different individuals because of the variation of superficial folding patterns (Fig. 3), and for minor clusters, we have omitted possible sulcus names. Supplementary Figures 1–4 and their accompanying videos provide further views of the original data.
The clusters form chains stretching from the anterior pole toward the posterior pole and from the temporal pole toward the intraparietal lobe, shown diagrammatically in Figure 5. A prominent chain of clusters of minor sulcal pits is located along the frontal and parietal opercula extending further posterior into the posterior parietal and parietal–occipital cortex (clusters b, c, d, and e of Fig. 5 and Table 1). The general arrangement of the chains of pits seems to follow the alignment of the underlying lateral ventricles (Fig. 6). Minor chains are interleaved with major chains. Further clusters can be found within the middle temporal gyrus and the lateral occipital gyri and at the occipital polar cap.
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| Discussion |
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We have shown that when the extended space curves constituting sulcal fundi are reduced to the locally deepest points or sulcal pits, the spatial relationship between sulci becomes much clearer and forms striking alternating major and minor chains of pits. The chains correspond well with the distribution of areas of highest heritability of gray matter density described by Thompson (Thompson et al. 2001
We hypothesize that the pits are encoded in the protomap of prospective cytoarchitectonic areas (Rakic 1988
) and are under closer genetic control than the rest of the cortex. This leads to predictions that should be tested in future research. Because the broad arrangement of functional areas is also encoded in the protomap, we predict that the spatial correlation between sulcal pits and functional areas should be much clearer than with other sulcal features. This could be examined in several ways. We would expect that the pits have a more consistent relationship to cytoarchitectonic areas than is generally the case for sulcal fundi (Amunts et al. 2000
)—even though the relationship between sulcal features and cytoarchitectonic areas may be nonlinearly distorted during the process of gyrogenesis and therefore difficult to identify in adult brains. The location of pits in relation to data from functional activation, neurophysiology, and fiber architecture studies should also be examined.
Although this evidence indicates the importance of genetic factors in explaining relative consistency of pit locations across individuals, the ontogenetic determinants of the more variable, later-developing superficial cortical folds need further consideration. There is a growing body of evidence that axonal tension forces are important in the formation of cortical folds (gyrogenesis) (Scannell 1997
; van Essen 1997
; Hilgetag and Barbas 2006
). The timing of development of cortical connections is consistent with a causal role, and disruption of connections during development has a marked effect on the gyral pattern (Goldman-Rakic 1980
). Thus, it seems likely that the density of axonal connections is important in determining the location of many sulci and gyri, and variation in axonal density could explain the variations in the pattern of superficial sulci.
If pits are confirmed as having a clearer relation to functional areas than other geometrically defined features, important applications will follow. In particular, the sulcal pits can be used as landmarks to refine the current methods for interindividual and atlas-to-individual coregistration, both for traditional 3D methods that are based on deep landmarks and the outer (arachnoid) brain surface, and in the newer surface-based approaches (van Essen 2005
).
| Acknowledgments |
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Conflict of Interest: None declared.
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= 2. Note that most of the profiles have a focused central region. The sulcal pits are in the center of these deepest regions.



