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. 2022 Apr 7;33(4):1230–1245. doi: 10.1093/cercor/bhac132

Morphological patterns and spatial probability maps of the superior parietal sulcus in the human brain

Kristina Drudik 1,2,✉, Veronika Zlatkina 3,4, Michael Petrides 5,6
PMCID: PMC9930623  PMID: 35388402

Abstract

The superior parietal sulcus (SPS) is the defining sulcus within the superior parietal lobule (SPL). The morphological variability of the SPS was examined in individual magnetic resonance imaging (MRI) scans of the human brain that were registered to the Montreal Neurological Institute (MNI) standard stereotaxic space. Two primary morphological patterns were consistently identified across hemispheres: (i) the SPS was identified as a single sulcus, separating the anterior from the posterior part of the SPL and (ii) the SPS was found as a complex of multiple sulcal segments. These morphological patterns were subdivided based on whether the SPS or SPS complex remained distinct or merged with surrounding parietal sulci. The morphological variability and spatial extent of the SPS were quantified using volumetric and surface spatial probabilistic mapping. The current investigation established consistent morphological patterns in a common anatomical space, the MNI stereotaxic space, to facilitate structural and functional analyses within the SPL.

Keywords: MRI, superior parietal sulcus, MNI space, sulcal morphology, probability maps

Introduction

The superior parietal sulcus (SPS) lies within the lateral surface of the superior parietal lobule (SPL) in the human brain, separating the anterior from the posterior part of the SPL (see Fig. 1 for the lateral surface and Fig. 2 for the medial surface of the human brain; Economo and Koskinas 1925; Petrides 2012, 2014, 2019). As with all sulci in the human brain, there are variations in the morphological patterns of this sulcus (Cunningham 1892; Retzius 1896; Connolly 1950). In recent years, several studies have demonstrated that a detailed understanding of the variations in local sulcal morphology is necessary when specific anatomical landmarks must be related to functional activation (e.g. Amiez et al. 2006; Segal and Petrides 2013; Amiez and Petrides 2014; Zlatkina and Petrides 2014; Huntgeburth and Petrides 2016; Zlatkina et al. 2021). In addition, a thorough understanding of the individual patterns of sulci and gyri is critical for neurosurgical interventions that rely on these intrinsic neuroanatomical landmarks (e.g. Sampath et al. 2014; Tomaiuolo and Giordano 2016; Koutsarnakis et al. 2017).

Fig. 1.

Fig. 1

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Sulcal map of the lateral surface of the human brain a) by Petrides (2012, 2014, 2019) and cytoarchitectonic map b) by Economo and Koskinas (1925). For the sulcal map of Petrides, please see Petrides (2019) for abbreviations not found in the text. Figure 1a reproduced with permission by Elsevier. Note the location of areas PEm and PEp anterior and posterior to the SPS in the Economo and Koskinas (1925) map. Abbreviations: IPL, inferior parietal lobule; IPS, intraparietal sulcus.

Fig. 2.

Fig. 2

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Sulcal map of the medial surface of the human brain a) by Petrides (2012, 2014, 2019) and cytoarchitectonic map b) by Economo and Koskinas (1925). Figure 2a reproduced with permission by Elsevier. Note the location of areas PEm and PEp anterior and posterior to the SPS in the Economo and Koskinas (1925) map. Abbreviations: mcgs, marginal ramus of the cingulate sulcus; PrCu, precuneus; prcus, precuneal sulcus.

A recent examination of the spatial organization of the precuneus, the medial portion of the SPL, has demonstrated the importance of examining local cortical morphology in the posterior parietal cortex (Bruner and Pereira-Pedro 2020). Indeed, individual morphological variation may be related to real cortical variability and not brain-volume constraints. Thus, individual differences in the precuneus—and by virtue of their similar cytoarchitecture, the lateral SPL—may be a result of localized cortical variations, which are influenced independently by the anterior and posterior parts of the parietal cortex (Bruner and Pereira-Pedro 2020). By defining and quantifying the consistent patterns of the SPS, which separates the SPL into its anterior and posterior portions, the present investigation will aid in the examination of structure-to-function relationships in the parietal cortex and in relating these variations in sulci to cytoarchitectonic areas.

The functional organization of the posterior parietal cortex has been examined extensively in the macaque monkey and in the human brain (e.g. Mountcastle et al. 1975; Blatt et al. 1990; Kalaska 1996; Andersen et al. 1997; Galletti et al. 2003, 2010; Filimon 2010; Sereno and Huang 2014; Caminiti et al. 2015; Hadjidimitrakis et al. 2015, 2019; Pitzalis et al. 2015, 2019; Galletti and Fattori 2018; Gamberini et al. 2018, 2020). Although the exact homologues in the human brain of several areas established in the macaque using electrophysiological methods have yet to be identified, functional neuroimaging suggests that the SPL in the human brain is involved in the multimodal integration of information for limb coordination and visually guided action, such as reaching and cognitive traversing in space (e.g. Sereno et al. 2001; Medendorp et al. 2003; Culham et al. 2006). Specifically, it has been shown in functional neuroimaging studies of the human brain that activity in the SPL codes the directions in cognitive navigation within a maze (Gourtzelidis et al. 2005; Jerde et al. 2008) and responds selectively to spatial shifts in the focus of attention: the activity in the SPL correlates with the distance between the original and the new foci of attention (Vandenberghe et al. 2001; Molenberghs et al. 2007; Caspari et al. 2018). Functional neuroimaging studies raise the question of how functional regions relate to the SPS given that the cortex of the SPL is composed of 2 cytoarchitectonically distinct areas, namely magnocellular part of area PE (PEm) in the anterior part of the SPL and parvocellular part of area PE (PEp) in its posterior part (Figs. 1b and 2b; Economo and Koskinas 1925). Thus, the SPS is the morphological structure of the SPL around and within which occur functional activities involved in guided movements and reaching, as well as cognitive attentional moves in space (Galati et al. 2011; Huang et al. 2012; Gamberini et al. 2018; Bruner and Pereira-Pedro 2020; Passarelli et al. 2021).

The present investigation examined the morphological variability of the SPS to quantify the spatial extent of this sulcus in the Montreal Neurological Institute (MNI) standard stereotaxic space that is used worldwide to report anatomical and functional data related to the human brain. The exact morphology of the SPS in individual subjects was examined and quantified with volumetric and surface spatial probability maps in continuous serial 2D magnetic resonance imaging (MRI) sections and 3D surface reconstructions of the brain. The aim was to document the pattern of local morphological variability of the SPS to improve the interpretation of functional activity in neuroimaging studies investigating motor and higher order cognitive processing within the posterior parietal cortex.

Materials and methods

Subjects

The morphology of the SPS in the human brain was examined in 40 MRI scans (i.e. a total of 80 hemispheres) from the International Consortium for Brain Mapping project (Mazziotta et al. 1995a, 1995b, 2001; www.loni.usc.edu/ICBM). The subset of scans consisted of 24 males (mean age 24.6 years, standard deviation (SD) 3.18) and 16 females (mean age 24.6 years, SD 4.33). All subjects were right-handed, had no history of neurological and/or psychiatric illness, and gave informed consent. The same subset of subjects was used in a previous anatomical study by Zlatkina and Petrides (2014).

Magnetic resonance imaging

All MRI scans were acquired using a 1.5 T Phillips Gyroscan superconducting magnet system. A fast-field echo 3D acquisition sequence collected 160 contiguous 1 mm T1-weighted images in the sagittal plane (Tr = 18 msec, Te = 10 msec, flip angle 30o). An intensity correction for nonuniformity was performed (Sled et al. 1998). Following this correction, a 9-parameter linear transformation was used to register each MRI volume to the asymmetric version of the most recent MNI stereotaxic template, namely the MNI152 2009c asymmetric template (Fonov et al. 2011). This normalization accounted for interindividual differences in gross brain size and was carried out using MINC Toolkit (Collins et al. 1994). The transformed brain volumes were then resampled on a 1-mm3 isotropic grid (1 mm × 1 mm × 1 mm voxel size). The thickness of the obtained coronal, sagittal, and horizontal sections was 1 mm.

Sulcal identification and labelling

Identification of the SPS was based on criteria established in atlases of the sulcal morphology of the human cerebral cortex in MNI stereotaxic space (Petrides 2012, 2014, 2019). The SPS has been traditionally described as the single sulcus that separates the anterior from the posterior part of the SPL (Economo and Koskinas 1925; Petrides 2012, 2014, 2019). In the present study, the following criteria were used to identify the SPS with respect to its neighboring parietal sulci. The SPS was identified as the dorsal parietal sulcus that is found within the SPL, posterior to the superior postcentral sulcus (SPCS) and anterior to the paroccipital segment of the intraparietal sulcus (IPS-PO) (Petrides 2012, 2014, 2019; Zlatkina and Petrides 2014). When more than one branch was found in the SPL, posterior to the SPCS and anterior to the IPS-PO, all segments were identified as part of the SPS and were named the SPS complex. The one exception to this rule was that, in cases where a sulcal branch merged with the IPS-PO, this branch was excluded and not identified as part of the SPS. A sulcal branch that merged with the IPS-PO was excluded from the analyses because the morphological patterns of the IPS-PO have yet to be examined. The reader should note that in some cases the SPS extended onto the medial surface, sometimes merging with the dorsal end of a precuneal sulcus (Fig. 1a and Fig. 2a; Petrides 2012, 2014, 2019).

An interactive 3D imaging software package, DISPLAY (MacDonald 1996; Vincent et al. 2016), was used to label the SPS in individual MRI brain scans. DISPLAY allows the MRI scans to be viewed simultaneously in the coronal, horizontal, and sagittal planes of section that are updated automatically as the cursor, controlled by the mouse, moves within a given plane. The intensity and gray–white matter contrast of the MRI scans was adjusted in DISPLAY so that all sulci could be identified and followed, from the surface of the brain to the fundus of the sulcus. Using a virtual pen tool, the sulcus of interest was manually identified by labelling the cerebrospinal fluid voxels between the banks of the sulcus. The brush diameter was set to 1 mm. The SPS was examined at 1-mm intervals in all 3 planes of section to determine its direction, extent, and pattern with respect to neighboring sulci. The SPS was marked until its termination point, i.e. until it could no longer be identified in any of the 3 planes.

Surface renderings

Three-dimensional surface renderings of each individual brain were acquired using 2 types of software. First, the cortical surfaces were reconstructed to visualize the outer surface of the brain using an automated, surface-deformation algorithm (MacDonald et al. 1994). After the SPS had been labeled in 2 dimensions (i.e. labeled in each plane of section of the MRI volumes), the labels were projected onto the 3D reconstructed surface of each of the 40 MRI brain volumes. Second, the open-access pipeline FreeSurfer (Dale et al. 1999; Fischl et al. 1999a, 1999b) was used to extract the pial and white matter surfaces of all 40 MRI scans. The FreeSurfer 3D reconstructions revealed the submerged parts of the sulci, which are not usually visible on the cortical surface. The FreeSurfer surface reconstructions were visually inspected along with the MRI volumes to ensure accurate identification of the morphological patterns of the SPS.

Probability maps

Volumetric and surface spatial probability maps were used to determine the average location and to quantify the morphological variability of the SPS. Both types of probability maps were generated with methodology similar to that used in the studies of Sprung-Much and Petrides (2018, 2020). The reader should note that the presentation of both types of probability maps was not to compare the volumetric and spatial surface registration methods, but rather to provide the reader with a thorough understanding of the location and extent of the sulcus of interest.

Volumetric probability maps

Volumetric probability maps quantify the likelihood that a voxel belongs to the sulcus of interest from 0 to 100% along the x-, y-, z-axes, where the x-axis represents the sagittal plane, the y-axis represents the coronal plane, and the z-axis represents the horizontal plane (Sprung-Much and Petrides 2018). After sulcal labelling, MINC Toolkit (Collins et al. 1994) was used to estimate a nonlinear transformation of each MRI scan to the asymmetric version of the most recent MNI template (MNI152 2009c asymmetric; Fonov et al. 2011). Then, volumetric probability maps were generated for the left and right hemispheres separately by dividing the number of times each voxel in stereotaxic space belonged to the SPS by the total number of subjects in which that morphological type could be identified. In other words, the volumetric maps represent the probability that any given voxel in MNI standard proportional stereotaxic space belongs to a particular morphological pattern of the SPS.

The maps were then blurred using a Gaussian kernel with a full width at half maximum (FWHM) of 2 mm, an FWHM that was found to enhance the maps optimally without excessive smoothing (Sprung-Much and Petrides 2018, 2020). The volumetric probability maps were superimposed onto the MNI152 2009c template that was used for registration and the probability values of the voxels are depicted by means of a color scale (Figs. 4 and 5). For the purpose of illustration, the threshold for the volumetric maps has been set to a minimum 7%. The stereotaxic coordinates in MNI152 space with the highest probability value of belonging to the SPS are provided in Table 2.

Fig. 4.

Fig. 4

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Volumetric probability maps of the Type I SPS from left and right hemispheres superimposed onto coronal and horizontal sections of the MNI152 2009c asymmetric template that was used for registration. For the coronal sections, the y-coordinate is indicated in the upper right corner of each section; the x- and z-coordinates are shown on the appropriate axes. For the horizontal sections, the z-coordinate is indicated in the upper right corner of each section; the x- and y-coordinates are shown on the appropriate axes. The color bar indicates the extent of overlap of the labeled voxels.

Fig. 5.

Fig. 5

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Volumetric probability maps of the Type II SPS from left and right hemispheres superimposed onto coronal and horizontal sections of the MNI152 2009c asymmetric template that was used for registration. For the coronal sections, the y-coordinate is indicated in the upper right corner of each section; the x- and z-coordinates are shown on the appropriate axes. For the horizontal sections, the z-coordinate is indicated in the upper right corner of each section; the x- and y-coordinates are shown on the appropriate axes. The color bar indicates the extent of the overlap.

Table 2.

MNI152 stereotaxic coordinates (x, y, z) of the SPS with the highest probability value: volumetric spatial probability maps.

x y z Probability (%)
Type I  
LH
−19
−55
+67
28

RH
Type II
LH
RH		 +13

−25
+14		 −58

−62
−58		 +65

+59
+66		 33

31
36
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Coordinates are in MNI152 stereotaxic space. The probability values represent the maximum overlap of the labeled voxels from 0 to 100%.

Surface probability maps

Surface probability maps quantify the likelihood that a vertex on the reconstructed cortical surface belongs to the sulcus of interest from 0 to 100% (Sprung-Much and Petrides 2018, 2020). Surface probability maps were created using the open-access pipeline FreeSurfer (Dale et al. 1999; Fischl et al. 1999a, 1999b). First, surfaces were reconstructed for each linearly registered MRI scan using FreeSurfer 7.0. Second, the labeled voxels from the MRI volumes were converted to surface overlays in FreeSurfer. The overlays of the labeled voxels were registered to the surface template, fsaverage. Fsaverage is the FreeSurfer pipeline’s default average surface template, which was created by averaging 40 individual surfaces that were nonlinearly registered to one another (Fischl et al. 1999a, 1999b). Thus, interindividual differences in cortical morphology between each subject’s cortical surface were accounted for by registering to the average surface. Next, the average of the labels for each morphological pattern of the SPS was calculated separately for the left and right hemispheres. Finally, the average of the labels was blurred using a Gaussian kernel with a FWHM of 3 mm, which was found to enhance optimally without excessive smoothing (Sprung-Much and Petrides 2018, 2020). The surface spatial probability maps were overlaid onto the fsaverage template that was used for registration (Fig. 6). Again, probability values of each vertex are depicted by means of a color scale. For the purpose of illustration, the threshold for the maps has been set to a minimum of 10%. The stereotaxic coordinates of the vertex with the highest probability value of belonging to the SPS is provided in MNI305 (Evans et al. 1993), as the default volumetric space used by the FreeSurfer pipeline (Table 3).

Fig. 6.

Fig. 6

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Surface probability maps of the SPS from a) Type I left hemispheres, b) Type I right hemispheres, c) Type II left hemispheres, d) Type II right hemispheres. All probability maps have been overlaid onto the surface template, fsaverage, used for registration. The color bar indicates the extent of overlap of the labeled vertices. The x-, y-, z-coordinates below each surface indicate the position, in MNI305 stereotaxic space, of the vertex with the maximum overlap. Abbreviations: A, anterior; D, dorsal; CS, central sulcus; PCS, postcentral sulcus.

Table 3.

MNI305 stereotaxic coordinates (x, y, z) of the SPS with the highest probability value: surface spatial probability maps.

x y z Probability (%)
Type I  
LH
−16
−56
+61
22
RH
Type II
LH
RH		 +17

−24
+16		 −54

−61
−52		 +61

+55
+60		 15

30
47
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Coordinates are in MNI305 stereotaxic space, which is the default volumetric space of the fsaverage template in FreeSurfer. The probability values represent the maximum overlap of the labeled vertices from 0 to 100%.

All volumetric and surface spatial probability maps are made freely available in the Dryad database (https://doi.org/10.5061/dryad.zcrjdfncx). The figures were created using the graphical design software packages Adobe Photoshop and Adobe Illustrator.

Results

Morphological patterns

The SPS is classically described as the main sulcus on the lateral surface of the SPL, separating the SPL into anterior and posterior parts. A systematic examination of the SPS in 2D MRI sections, in conjunction with visual inspection of 3D reconstructed pial and white matter surfaces of the brain, identified the SPS in 100% of left and right hemispheres. The morphological patterns of the SPS were classified into 2 main types and a third, less frequent type (Table 1). A sulcus was categorized as a Type I SPS (Fig. 3a–e) when it was a single sulcus, separating the anterior from the posterior part of the SPL. A Type II SPS (Fig. 3f–g) was identified when it was not a single sulcus, but rather a complex consisting of more than one sulcal segment. Finally, in the least frequent pattern observed, Type III, the SPS complex consisted of a group of dimples occupying the dorsal part of the SPL, rather than well-defined sulci that are part of the sulcal complex.

Table 1.

Frequency of the SPS and its morphological patterns in the left and right hemispheres of the human brain.

Total no. hemispheres % Total hemispheres Total no. LH % Total LH Total no. RH % Total RH
Type I 60 75 29 72.5 31 77.5
Subtype Ia 42 52.5 20 50 22 55
Subtype Ib
Subtype Ic
Subtype Id
Subtype Ie
Unknown lateral		 7
5
2
2
2		 8.75
6.25
2.5
2.5
2.5		 5
2
0
1
1		 12.5
5
0
2.5
2.5		 2
3
2
1
1		 5
7.5
5
2.5
2.5
Type II 18 22.5 9 22.5 9 22.5
Subtype IIa
Subtype IIb		 7
3		 8.75
3.75		 3
2		 7.5
5		 4
1		 10
2.5
Subtype IIc 3 3.75 1 2.5 2 5
Subtype IId
Subtype IIe
Unknown lateral		 2
4
2		 2.5
5
2.5		 2
3
1		 5
7.5
2.5		 0
1
1		 0
2.5
2.5
Type III 2 2.5 2 5 0 0
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The morphological patterns of the SPS were examined in 40 MRI volumes (i.e. 80 hemispheres). Three morphological patterns were identified (Types I–III). Refer to the Morphological patterns section of the Results for an explanation of the different classifications. LH, left hemisphere; RH, right hemisphere.

Fig. 3.

Fig. 3

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Schematic drawing illustrating the 2 main morphological patterns of the SPS, drawn in orange, in relation to its neighboring parietal sulci. a) Subtype Ia: The SPS is a single, distinct sulcus that does not blend with any neighboring sulci; b) Sutype Ib: The SPS is a single sulcus that merges with the SPCS; c) Subtype Ic: The SPS is a single sulcus that merges with the IPSa; d) Subtype Id: The SPS is a single sulcus that merges with the IPSp; e) Subtype Ie: The SPS is a single sulcus and extends over the midline and merges with a precuneal sulcus (prcus) on the medial surface of the brain; f) Subtype IIa: The SPS is found in 2 or more separate branches that do not merge with any neighboring parietal sulci; g) Subtype IIb–e: The SPS is found in 2 or more separate branches and at least one branch merges with a neighboring parietal sulcus. Abbreviations: IPSC, inferior postcentral sulcus; pof, parieto-occipital fissure.

Type I SPS was found in the majority of hemispheres (75% of all hemispheres, 72.5% of left hemispheres, 77.5% of right hemispheres). Within this category, the SPS was sometimes a single sulcus that was branched (12.5% of all hemispheres, 10% of left hemispheres, 15% of right hemispheres). Type II SPS constituted 22.5% of cases in all hemispheres (22.5% of left and right hemispheres) and Type III SPS was observed in only 2 left hemispheres from the sample, representing 2.5% of the total hemispheres examined (5% of left hemispheres).

Types I and II were further subdivided based on the interaction of the SPS with nearby sulci. In Subtype a, the SPS was found as a distinct sulcus, separating the anterior part from the posterior part of the SPL, and did not merge with any of the surrounding parietal sulci. Subtype Ia was, therefore, the type illustrated in the classic sulcal maps—that is, a single and distinct sulcus, separate from the surrounding parietal sulci visible on the surface of the brain or by way of any deep or submerged parts of the sulcus, not visible from the surface of the brain (i.e. a submerged gyral bridge or pli de passage) (Fig. 3a; Eberstaller 1890; Economo and Koskinas 1925; Petrides 2012, 2014, 2019). This pattern was observed in 52.5% of all hemispheres examined (50% of left hemispheres and 55% of right hemispheres). In contrast, in Subtype IIa, the SPS was found in 2 or more segments, but in this case, the segments did not merge with each other or surrounding parietal sulci and were entirely distinct (Fig. 3f) (8.75% of all hemispheres, 7.5 of left hemispheres, 10% of right hemispheres).

Frequently, the SPS was found to merge with a surrounding parietal sulcus. Thus, Types I and II were subdivided on the basis of the parietal sulcus with which it merged. A parietal sulcus was considered to merge with the SPS in the absence of a visible gyrus, detectable from or below the surface of the cortex. In the cases of Type II, the SPS was found as 2 or more segments, where at least one of the segments merged with another parietal sulcus. Subtype b refers to cases in which the SPS merged with the SPCS. Subtype Ib was observed in 8.75% of all hemispheres (Fig. 3b) (12.5% of left hemispheres, 5% of right hemispheres) and Subtype IIb occurred in 3.75% of all hemispheres (5% of left hemispheres, 2.5% of right hemispheres).

Subtype c was defined as the SPS merging with the anterior ramus of the intraparietal sulcus (IPSa). Subtype Ic occurred in 6.25% of hemispheres (Fig. 3c) (5% of left hemispheres, 7.5% of right hemispheres) and Subtype IIc was observed in 3.75% of all hemispheres (2.5% of left hemispheres, 5% of right hemispheres). Further, Subtype d was categorized as the SPS merging with the posterior ramus of the intraparietal sulcus (IPSp) (Fig. 3d), which occurred in 2.5% of hemispheres for Subtype Id (5% of right hemispheres) and 2.5% of hemispheres for Subtype IId (5% of left hemispheres).

Subtype e was the case of the SPS extending over the midline to merge with a medial precuneal sulcus. Subtype Ie was observed in 2.5% of all hemispheres (Fig. 3e) (2.5% of left and right hemispheres), while Subtype IIe was found in 5% of all hemispheres (7.5% of left hemispheres and 2.5% of right hemispheres). Finally, in 4 hemispheres, the SPS merged with a sulcus on the lateral surface that was difficult to identify (2.5% of all hemispheres, 2.5% of left and right hemispheres). Consequently, these hemispheres were excluded from the spatial probability maps. The reader should note that 2 left hemispheres categorized as Type II were classified as belonging to multiple subtypes because the SPS complex was found to merge with more than one parietal sulcus (the results of which are reflected in Table 1).

Morphological comparison between the 2 hemispheres in the same brain

When 2 hemispheres of the same brain were compared with respect to the morphological patterns of the SPS, more than half of all brains (55% or 22 brains) demonstrated the same sulcal morphological pattern in both hemispheres (i.e. both hemispheres were either Type I or Type II). Of these brains, 21 brains (42 hemispheres) were classified as Type I SPS. Further, when both hemispheres were classified as Type I, 12 of these brains (24 hemispheres) were classified according to the same subtype as well (30% of all brains examined in the present study). Specifically, it was observed that 11 of the 12 brains (22 hemispheres) were classified as a single and distinct sulcus, separating the anterior from the posterior part of the SPL (Subtype Ia), whereas 1 brain (2 hemispheres) was classified as a single sulcus merging with a medial precuneal sulcus (Subtype Ie). Finally, both hemispheres of 1 brain was classified as Type II, where the subtypes of each hemisphere were not the same.

Thus, when comparing the morphology of the SPS between 2 hemispheres of the same brain, the results indicated that, in approximately half of all brains examined, the same morphological pattern was observed across hemispheres. Of these brains, approximately half maintained the same type and subtype across hemispheres (Subtype Ia), which represented nearly a third of the brains from the sample.

Spatial probability maps

Volumetric maps

Volumetric spatial probability maps were created to demonstrate the morphological variability and spatial extent of the SPS in MNI stereotaxic space. These maps indicate the likelihood that any voxel in standard MNI stereotaxic space belongs to the SPS. Figure 4 shows the volumetric probability maps for the Type I SPS and Fig. 5 for Type II SPS. The volumetric probability maps are overlaid onto a series of coronal (y coordinate) and horizontal (z coordinate) sections of the MNI asymmetric template used for registration (Fonov et al. 2011). The coronal sections demonstrate the spatial extent of the SPS, from its most anterior to its most posterior position, and the horizontal sections show the extent of the SPS, from its most dorsal to its most ventral position. A grid has been superimposed onto each section to demonstrate the x (medial–lateral), y (anterior–posterior), and z (dorsal–ventral) axes. The color bar in each figure indicates the extent of overlap of the labeled voxels. The probability maps for each morphological type are presented separately to demonstrate the different morphological patterns.

In Fig. 4, the morphological variability and spatial extent of the SPS was quantified for Type I SPS (see Morphological patterns in Results for description). The volumetric probability map for Type I SPS demonstrates a maximum probability value for left hemispheres of 28%, found at MNI coordinates x − 19, y − 55, z + 67. In other words, the maximum overlap of painted voxels, indicating the location with the highest probability of belonging to the SPS is common across ~28% of Type I left hemispheres. The maximum overlap quantified using only the right hemispheres categorized as Type I reaches 34%, which was found at the MNI coordinates x + 13, y − 58, z + 65. Table 2 summarizes the stereotaxic coordinates found with the highest probability values.

In Fig. 5, maps are presented of only the hemispheres in which the SPS was a sulcal complex, i.e. consisting of more than one segment (classified as Type II). The results for left hemispheres show a maximum probability peak of 31% at MNI coordinate x − 25, y − 62, z + 59. For right hemispheres, the results demonstrate the highest probability voxel occurring at MNI coordinate x + 14, y − 58, z + 66, with a maximum overlap of 36% (see Table 2 for summary of stereotaxic coordinates).

Surface maps

In addition to volumetric probability maps, surface spatial probability maps were generated on the basis of the morphological types of the SPS. The spatial probability maps have been overlaid onto the surface template, fsaverage, which was used for registration (Fischl et al. 1999a, 1999b). These maps indicate the likelihood that any point on the surface of the brain belongs to the SPS. The probability values of all maps are presented by means of a color bar, indicating the extent of the overlap of the labeled vertices.

In Fig. 6, the surface spatial probability map of Type I SPS is shown. The maximum overlap across left hemispheres defined as Type I reaches 22% and occurs at the MNI coordinates x − 16, y − 56, z + 61 (Fig. 6a, Table 3). For Type I SPS in the right hemisphere, the maximum overlap is 15% and occurs at coordinates x + 17, y − 54, z + 61 (Fig. 6b, Table 3). Figure 6 also displays the probability maps for the Type II SPS. For the surface probability maps of Type II in the left hemisphere, a maximum overlap of 30% occurs at MNI stereotaxic coordinate x − 24, y − 61, z + 55 (Fig. 6c, Table 3), and in the right hemisphere, a maximum overlap of 47% occurs at stereotaxic coordinate x + 16, y − 52, z + 60 (Fig. 6d, Table 3).

Discussion

The present study examined the morphological variations of the SPS in the human brain, i.e. the sulcus within the SPL. Forty MRI volumes (80 hemispheres) were registered to the MNI standard stereotaxic space and were subsequently labeled in 3 planes of section to determine the morphological patterns of the SPS. The location and spatial variability of these patterns of the SPS were quantified using volumetric and surface spatial probabilistic mapping. The probability maps presented here contribute, not only to our understanding of the anatomical topography of this sulcus, but also provide critical information for the reporting and interpreting of the location of functional activity in the SPL.

Morphology

The SPS was identified in all hemispheres within the SPL and standard criteria were developed for the identification of the SPS complex. The SPS is found between the SPCS and the IPS-PO. Based on our criteria, the SPS does not merge with the IPS-PO, and therefore, any sulci within the region of interest that merged with the IPS-PO were excluded from categorization. Although the SPS is a lateral parietal sulcus, it will often extend onto the medial surface of the hemisphere, sometimes merging with one of the medial precuneal sulci.

Two primary morphological variations were identified consistently within the SPL of the hemispheres examined. The most common pattern observed (Type I), in approximately three-quarters of all hemispheres, was the SPS as a single sulcus, separating the anterior from the posterior part of the SPL. In the second pattern (Type II), which was observed in approximately a quarter of hemispheres, the SPS was found as a complex consisting of multiple sulcal segments. In the third pattern (Type III), which was least frequently observed, the SPS was identified as a group of dimples rather than as a well-defined sulcus. These patterns could be further subdivided on the basis of whether the SPS or SPS complex remained distinct or merged with surrounding parietal sulci. When the SPS or SPS complex merged with a neighboring parietal sulcus, it merged most frequently with the SPCS, followed by the anterior and posterior rami of the intraparietal sulcus, and least frequently with a medial precuneal sulcus.

The results of the morphological analysis of the SPS are akin to those reported by neuroanatomists of the 20th century. Connolly (1950) examined the fissural patterns of the primate brain and reported that, in most primates, a well-developed SPS is observed. Further, he reported that there are usually 2–3 superior parietal sulci found in the SPL and identified them as the superior parietal sulcus (ps, see Fig. 189 p. 206 in Connolly 1950), the superior transverse parietal sulcus (pst, see Fig. 203 p. 215 in Connolly 1950), and the transverse parietal sulcus (pt, see Fig. 209 p. 218 in Connolly 1950). These observations are reflected in the current study (Fig. 3). A close inspection of the figures by Connolly demonstrates that what was defined as the ps corresponds to the Subtype Ia defined in the present investigation; that is, a distinct or branched sulcus, separating the SPL into 2 parts (see Fig. 201 p. 215 in Connolly 1950, for an example of what the present investigation categorizes as Subtype Ia SPS that is branched). In addition, Connolly described the pst as a secondary branch of the SPS, often found together with the ps. Thus, Connolly’s pst can be considered comparable to what is defined as Type II in the present investigation, where the SPS is found as a complex with multiple branches (see Fig. 206, p. 217 in Connolly 1950, for an example of Subtype IIa SPS). Further, in his descriptions of the superior postcentral sulcus (pts) and the intraparietal proper (ip), Connolly states that the caudal branch of the pts sometimes joins with the ps, and that the dorsal branches of the ip occasionally merge with the ps or pts. Such descriptions are consistent with the data reported in the present study, namely the Subtype Ib (see Fig. 191, p. 206 in Connolly 1950, for an example of the SPS merging with the SPCS) and Subtype Ic (see Fig. 192 p. 206 in Connolly 1950, for an example of the SPS merging with the IPSa), i.e. the patterns of the SPS merging with another parietal sulcus. In addition, the 2 types of merging patterns observed by Connolly—that is, the SPS merging with the pts and the dorsal ip—were the 2 most frequent merging patterns observed in the current study as well.

More recently, Ono et al. (1990) examined the sulcal patterns of the human cerebral cortex. As in the current study, the SPS was defined as the sulcus in the superior margin of the hemisphere between the postcentral and the parieto-occipital sulci, extending across the midline onto the medial precuneal surface. The morphological patterns reported by these researchers included the absence (20% right hemisphere, 40% left hemisphere), the presence in one branch (72% right hemisphere, 56% left hemisphere), or the presence in 2 branches (8% right hemisphere, 4% left hemisphere) of the SPS. Although their incidence rates differ slightly from those reported in the present study (Table 1), it is notable that these researchers reported the presence of a second branch of the SPS, further validating the results obtained from the current investigation. Such variability in the incidence rates is likely due to the difference in the number of hemispheres analyzed, i.e. Ono et al. (1990) examined only 25 brains, whereas the present study evaluated almost double that number. In addition, Ono et al. (1990) carried out their investigation solely by analysis of the cortical surface of postmortem brains, limiting their ability to interpret the pattern of cortical sulci—which can be submerged, convoluted, and significantly more complex than what can be seen on the surface of the brain.

Spatial probability maps

In the present study, the morphological variability and spatial extent of the SPS were quantified by means of volumetric and surface spatial probability maps (Figs. 4–6). Volumetric probability maps were generated by registering and averaging the labeled voxels of each individual subject volume to the MNI stereotaxic space. The purpose of presenting volumetric maps is to facilitate the identification of the SPS in MRI volumes since functional neuroimaging studies generally overlay their activity peaks onto an average MRI template. In addition to volumetric maps, surface probability maps of the SPS were generated using a novel method with increased accuracy for the surface registration of cortical folds (Fischl et al. 1999a, 1999b; Fischl et al. 2007). Here, individual surface patterns of cortical morphology are mapped onto an average surface where they can be subsequently described volumetrically in MNI stereotaxic space (Sprung-Much and Petrides 2018, 2020).

An interesting pattern emerges when the spatial probability maps across morphological types of the SPS are compared. As expected, the spatial probability maps for the Type I SPS reflect the classic representation of the SPS with few interhemispheric differences. In Type I, the SPS begins at its most dorsal point and ends at its most ventral point around the same z-coordinates in both the left and right hemispheres. Further, the MNI152 stereotaxic coordinates of the voxel with the maximum probability of belonging to the SPS is comparable across hemispheres, as are the maximum probability values representing similar overlap (Table 2 and Fig. 4).

In contrast, the spatial probability maps for those cases that were found in multiple segments demonstrate different trends. For Type II SPS (Figs. 5 and 6c–d), the spatial probability maps demonstrate a higher probability of merging with an anterior parietal sulcus in the right hemisphere, whereas the SPS of the left hemisphere shows a higher probability of merging with a parietal sulcus found more posteriorly. In addition, visual inspection of both volumetric and surface spatial probability maps indicates that the SPS in the right hemisphere is less variable than in the left hemisphere. Specifically, the surface probability maps demonstrate more probability clusters in the left hemisphere (Fig. 6) and the volumetric probability maps demonstrate 2 distinct probability clusters in the left hemisphere and not the right hemisphere (Fig. 5).

A trend that is specifically observed in the surface spatial probability maps of both Type I and Type II SPS is that the left hemisphere shows multiple probability clusters, in contrast to the right hemisphere which reveals only a single probability cluster (Fig. 6). Interestingly, in the volumetric probability maps for both Type I and Type II, the right hemisphere demonstrates a higher maximum overlap compared to the left hemisphere (Figs. 4 and 5). In contrast, the surface spatial probability maps demonstrate a higher maximum overlap in the left hemisphere of Type I SPS, but in the right hemisphere of Type II SPS (Fig. 6).

The trends observed in the present study are consistent with observations suggesting that the cerebral hemispheres are asymmetric at the population level (Toga and Thompson 2003). Almost three-quarters of individuals without any history of neurological or psychological illness demonstrate an expansion of the cortex along the Sylvian fissure in the left hemisphere, thus displacing, in the left hemisphere, structures around the Sylvian fissure in comparison with the right hemisphere (LeMay 1976; Toga and Thompson 2003; Mock et al. 2012; Eichert et al. 2021; Zlatkina et al. 2021). With respect to the present investigation, this trend is illustrated in the spatial probability maps of Type II morphological patterns, where the SPS of the left hemisphere: (i) lies more posteriorly because of the asymmetry of the Sylvian fissure across hemispheres and (ii) takes a less uniform shape, likely as a result of the increased surface area of the left occipital lobe (Toga and Thompson 2003).

Cytoarchitecture and cortico-cortical connectivity of the SPL

Cytoarchitectonic analysis has separated the SPL into distinct parts based on the type, size, and distribution of neurons within the cortical layers. In the most commonly used cytoarchitectonic map, Brodmann (1909) parcellated the SPL into anterior area 5 (BA 5) and posterior area 7 (BA 7), which he later subdivided into anterior area 7a and posterior area 7b (Brodmann 1914). In the cytoarchitectonic map by Economo and Koskinas (1925), the cortex that lies anterior and superior to the SPS is labeled as area PEm and the cortex that lies below and posterior to the SPS is labeled as PEp and these areas continue onto the adjacent medial part of the SPL (Figs. 1b and 2b). More recently, Scheperjans et al. (2008) confirmed 2 large, cytoarchitectonically distinct areas within the SPL, namely anterior (7A) and posterior (7P) areas, including 2 smaller areas medially (7M) and laterally (7PC). Thus, despite methodological differences in the study of the cytoarchitecture of the SPL, the results obtained provide evidence for 2 distinct anterior and posterior cytoarchitectonic areas within the SPL.

Petrides and Pandya (1984) examined the connections to the frontal cortex from the various subdivisions of the posterior parietal region in the macaque monkey using autoradiography. The anterior and posterior parts of the cortex in the SPL are connected with the dorsal premotor area 6, the supplementary motor area on the medial frontal lobe, and the upper bank of the cingulate sulcus via a distinct branch of the superior longitudinal fasciculus (SLF), referred to as SLF I (Petrides and Pandya 1984). Thus, the cortex of the SPL via SLF I can influence motor activity (Mateli et al. 1998; Tanne-Gariepy et al. 2002; Bakola et al. 2010, 2013; Gamberini et al. 2020; Passarelli et al. 2021). Future functional investigations can examine the SPS, the anterior, and posterior parts of the SPL in relation to specific aspects of motor and cognitive activity. The quantitative morphological description of the SPS in the standard MNI stereotaxic space that is provided by the present investigation makes such explorations possible.

Anatomo-functional relationship between sulci and functional peaks

In the macaque monkey, research has demonstrated that the SPL is involved in the integration of somatosensory, visuomotor, and oculomotor activities for goal-directed arm and eye movements (e.g. Kalaska 1996; Andersen et al. 1997; Galletti et al. 2003, 2010; Caminiti et al. 2015; Hadjidimitrakis et al. 2015, 2019; Galletti and Fattori 2018; Gamberini et al. 2018, 2020). Specifically, the cortex of the SPL has been defined as a region with a general topographic representation of the body (e.g. Sakata et al. 1973; Mountcastle et al. 1975; Seelke et al. 2012; Baldwin et al. 2018), the caudal part exhibiting visual and partial somatotopic receptive fields (e.g. Breveglieri et al. 2008; Bakola et al. 2010, 2013; Revechkis et al. 2014; Gamberini et al. 2018, 2020). Further, area V6A, which is found posterior and medial to the caudal part of area PE, demonstrates both visual and somatic neurons for reach-to-grasp actions and spatial encoding of visual stimuli (Gamberini et al. 2011, 2018, 2020; Fattori et al. 2012, 2017; Breveglieri et al. 2016, 2018; Galletti and Fattori 2018; Passarelli et al. 2021). Similarly in the human brain, research has identified a second somatotopic representation of the body found within the postcentral gyrus of the SPL (Huang et al. 2012; Huang and Sereno 2018; Pitzalis et al. 2019). The SPL in the human brain has also been shown to be involved both in physical and cognitive actions in space, such as the mental traversing of mazes (Gourtzelidis et al. 2005; Jerde et al. 2008) and spatial shifts in the focus of attention (Vandenberghe et al. 2001; Molenberghs et al. 2007; Caspari et al. 2018). Thus, based on the aforementioned structural similarities, research has hypothesized functional correspondence between the macaque and the human SPL. Although a comprehensive understanding of the functional properties of the SPL remains to be established, in both human and monkey brains, a comparable dichotomy is observed with the anterior part of the SPL involved in somatotopic processing and the posterior part involved in visually guided attention and somatotopic processing (Passarelli et al. 2021). Consequently, the results from the present study provide an anatomical framework to establish links between the structural and functional properties of the posterior parietal cortex.

In recent years, several functional neuroimaging studies have investigated the varied tactile, visuomotor, and attentional functions of the SPL in the human brain. The present spatial probability maps can be used to provide a more precise localization of activity within the SPL. For instance, in a study by Huang et al. (2012), certain activity peaks related to the general somatotopic map of the body were located anterior to the SPS (x − 29, y − 48, z + 64). Thus, the activity peak associated with the parietal body area is interpreted as being in cytoarchitectonic area PEm (Economo and Koskinas 1925). In contrast, in tasks where participants alternated between overt and covert shifts in attention based on the presentation of a target (Vandenberghe et al. 2001), the activity associated with the shifting focus of spatial attention was found posterior to the SPS (x − 23, y − 61, z + 63). Further, when participants performed a visual task, commonly used to locate human extrastriate area V6, functional activity responding to optic flow is found posterior to the SPS, near the parieto-occipital fissure (x − 21, y − 58, z + 52; Pitzalis et al. 2019). Accordingly, activity associated with spatial attention and movement of the eyes can be inferred to be in cytoarchitectonic area PEp (Economo and Koskinas 1925). These examples illustrate how the spatial probability maps can inform structure-to-function relationships. The reader should note that the coordinates presented above from Vandenberghe et al. (2001) and Huang et al. (2012) were converted from the older Talairach stereotaxic space to the current MNI stereotaxic space using the BioImage Suite graphical user interface (Papademetris et al. 2006; www.bioimagesuite.org).

The interindividual variability of the SPS within the SPL and its relation to goal-directed arm and eye movements is not yet fully understood. However, the SPS has the potential to act as an important functional landmark distinguishing functional activation peaks of these higher order cognitive processes found rostral and caudal to it. The spatial probability maps provided by the present examination can help establish new links between the morphological features of the SPS and the planning of action in the posterior parietal cortex.

Applications and concluding remarks

Damage to the SPL, and the adjacent intraparietal sulcus, is often associated with the neuropsychological deficit known as optic ataxia. Here, patients demonstrate impaired reaching towards visual objects in the absence of primary visual or motor deficits (Perenin and Vighetto 1988; Rossetti et al. 2005; Vallar 2007; Vesia and Crawford 2012). It has been suggested that an online disruption of visuomotor control occurs because of a disconnection between the alignment of hand and eye targets. In other words, errors of reaching may be due to errors in communication between the visual targets and the proprioception of the ataxic arm in space (Pisella et al. 2006; Blangero et al. 2007; Rossetti and Pisella 2018). In order to develop targeted rehabilitation programs for individuals with severe optic ataxia, a thorough understanding of the underlying anatomy is necessary to discriminate between the higher order visual, motor, and multisensory processing areas in the posterior parietal cortex.

The spatial probability maps are freely available in the Dryad database (https://doi.org/10.5061/dryad.zcrjdfncx). The volumetric and surface probability maps, generated on the basis of the 2 primary morphological patterns (Types I and II), are made available. Researchers can superimpose individual subject functional activity peaks on the probability maps to facilitate the identification of sulci found within the SPL.

The results of the present study will aid research investigating anatomo-functional relationships in the posterior parietal cortex. The SPL and its defining sulcus, the SPS, have been studied much less than its related counterparts in the frontal lobe. In defining consistent morphological patterns of the SPS, as well as providing access to both volumetric and surface spatial probability maps, the results of the present investigation can be used to improve the anatomical interpretation of results obtained from functional neuroimaging, as well as functional neurorehabilitation for cognitive deficits associated with posterior parietal cortex.

Acknowledgments

We would like to thank Dr. Trisanna Sprung-Much for sharing her wealth of knowledge related to MINC Toolkit and FreeSurfer. Her input helped in creating the figures. We would also like to thank the 3 anonymous reviewers for their comments and suggestions.

Contributor Information

Kristina Drudik, Department of Neurology and Neurosurgery, McGill University, Montreal Neurological Institute, 3801 University Street, Montreal, Quebec, Canada H3A 2B4; Department of Psychology, McGill University, 2001 McGill College, Montreal, Quebec, Canada H3A 1G1.

Veronika Zlatkina, Department of Neurology and Neurosurgery, McGill University, Montreal Neurological Institute, 3801 University Street, Montreal, Quebec, Canada H3A 2B4; Department of Psychology, McGill University, 2001 McGill College, Montreal, Quebec, Canada H3A 1G1.

Michael Petrides, Department of Neurology and Neurosurgery, McGill University, Montreal Neurological Institute, 3801 University Street, Montreal, Quebec, Canada H3A 2B4; Department of Psychology, McGill University, 2001 McGill College, Montreal, Quebec, Canada H3A 1G1.

Funding

This work was supported by the Canadian Institutes of Health Research (CIHR) Foundation Grant (FDN-143212) awarded to MP and a scholarship awarded to KD from the Natural Sciences and Engineering Research Council (NSERC).

Conflict of interest statement. None declared.

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