Gyrus Cinguli

The goal of this work was to create a large dataset of consistently and accurately labeled cortices. To do so we adopted a modification of the DK protocol (Desikan et al., 2006 (link)). We modified the protocol for two reasons: (i) to make the region definitions as consistent and as unambiguous as possible, and (ii) to rely on region boundaries that are well suited to FreeSurfer’s classifier algorithm, such as sulcal fundi that are approximated by surface depth and curvature. This would make it easier for experienced raters to assess and edit automatically generated labels, and to minimize errors introduced by the automatic labeling algorithm. We also sought to retain major region divisions that are of interest to the neuroimaging community. In some cases, this necessitated the inclusion of anatomically variable sulci as boundary markers (such as subdivisions of the inferior frontal gyrus) or use of gyral crowns (such as the pericalarine cortex). Alternatively, common subdivisions of gyri that were not based on cortical surface curvature features (such as subdivisions of the cingulate gyrus and the middle frontal gyrus) were retained if the subdivision was wholly within the surface curvature features that defined the gyrus.
The DKT protocol has 31 cortical regions per hemisphere, one less than the DK protocol. We have also created a variant of the DKT protocol with 25 cortical regions per hemisphere to combine regions that are subdivisions of a larger gyral formation and whose divisions are not based on sulcal landmarks or are formed by sulci that are highly variable. The regions we combined include subdivisions of the cingulate gyrus, the middle frontal gyrus, and the inferior frontal gyrus. Since fewer regions means larger regions that lead to higher overlap measures when registering images to each other, note that comparisons should be made using the same labeling protocol. We refer to these two variants as the DKT31 and DKT25 cortical labeling protocols.
Figure 1 shows cortical regions in the DKT labeling protocol. We retained the coloring scheme and naming conventions of Desikan et al. (2006 (link)) for ease of comparison. The Appendix contains detailed definitions of the regions but we summarize modifications to the original DK protocol in Table 2. Table 3 lists the names and abbreviations for the bounding sulci used by the DKT protocol; the locations of these sulci are demonstrated in Figure 2. Three regions were eliminated from the original DK protocol: the frontal and temporal poles and the banks of the superior temporal sulcus. The poles were eliminated because their boundaries were comprised primarily of segments that “jumped” across gyri rather than along sulci. By redistributing these regions to surrounding gyri we have increased the portion of region boundaries that along similar curvature values, that is, along sulci and gyri rather than across them, which improves automatic labeling and the reliability of manual edits. The banks of the superior temporal sulcus region was eliminated because its anterior and posterior definitions were unclear and it spanned a major sulcus.
Additional, more minor, modifications took the form of establishing distinct sulcal boundaries when they approximated a boundary in the original protocol that was not clearly defined. For instance, the lateral boundary of the middle temporal gyrus anterior to the inferior frontal sulcus was defined explicitly as the lateral H-shaped orbital sulcus and the frontomarginal sulcus more anteriorly. Similarly, the boundary between the superior parietal and the lateral occipital regions was assigned to the medial segment of the transverse occipital sulcus. Other examples include establishing the rhinal sulcus and the temporal incisure as the lateral and anterior borders of the entorhinal cortex, and adding the first segment of the caudal superior temporal sulcus (Petrides, 2011 ) as part of the posterior border of the supramarginal gyrus. Several popular atlases informed these modifications, including Ono et al. (1990 ), Damasio (2005 ), Duvernoy (1999 ), and Mai et al. (2008 ). The recent sulcus and gyrus atlas from Petrides (2011 ) proved particularly useful because of its exhaustive catalog of small but common sulci.

Roadmap Epigenomic Project (18 (link)) chromHMM segmentations across 127 tissues and cell types were used to define brain-specific enhancers. We selected all genic (intronic) and intergenic enhancers (6_EnhG and 7_Enh) from a male (E081) and a female fetal brain (E082). This was accomplished using genome-wide chromHMM chromatin state classification in rolling 200-bp windows. All consecutive 200-bp windows assigned as an enhancer in the fetal brain were merged to obtain enhancer boundaries. A score was assigned to each enhancer based on the total number of 200-bp windows covered by each enhancer. Next, for each fetal brain enhancer, we counted the number of 200-bp segments assigned as an enhancer in the remaining 125 tissues and cell types. This provided enhancer scores across 127 tissues and cell types for all fetal brain enhancers. To identify FBSEs, Z scores were calculated for each fetal brain enhancer using the enhancer scores. Z scores were calculated independently for male and female fetal brain enhancers. Independent Z scores cutoffs were used for both male and female fetal brain enhancers such that ∼35% of enhancers were selected. To define open accessible chromatin regions within brain-specific enhancers, we intersected enhancers with DNAse-seq data from the Roadmap Epigenomic Project (18 (link)) from a male (E081) and a female fetal brain (E082), respectively. Next, the male and female FBSEs were merged to get a final set of 27,420 FBSEs. We used a similar approach to identify enhancers that were specifically active in adult brain subsections, which include angular gyrus (E067), anterior caudate (E068), cingulate gyrus (E069), germinal matrix (E070), hippocampus middle (E071), inferior temporal lobe (E072), dorsolateral prefrontal cortex (E073), and substantia nigra (E074).

White matter hyperintensities in cholinergic pathways were graded visually using the Cholinergic Pathways HyperIntensity Scale (CHIPS) by the first author on a single-rater basis. First reported by Bocti et al. (24 (link)), CHIPS is a visual rating scale developed based on published immunohistochemical tracings of the cholinergic pathways in humans (24 (link), 31 (link)), and was previously used by some studies for the relationship between WMH and cognition (12 (link), 13 (link)). According to Selden (31 (link)), the cholinergic pathways include the medial pathway and lateral pathway. The medial pathway is closely associated with the adjacent cingulate gyrus and rostrum of the corpus callosum; the lateral pathway courses through the external capsule and claustrum within the white matter (31 (link)). Accordingly, four axial planes of T2-FLAIR images were identified by major anatomical landmarks—low external capsule, high external capsule, corona radiata, and centrum semiovale (Figure 1). Medial pathway is included in two of the axial planes as anterior cingulate gyrus and posterior cingulate gyrus. A total of 10 regions are illustrated in Figures 1A–D. White matter hyperintensity of each region was determined visually on a 3-point scale for each region (0 = normal; 1 = minimal; 2 = confluent or moderate to severe). To account for the decreasing concentration of cholinergic fibers, each slice was weighted sequentially from 1 to 4 with one being the centrum semiovale and four being the lower external capsules (Table 1). The total CHIPS score (both hemispheres) ranged from 1 to 100. The lowest CHIPS score is 0, indicating no burden of WMH in cholinergic pathways, and the highest CHIPS score is 100 (24 (link)). The corresponding author independently rated CHIPS scores of random 65 participants to ascertain the inter-rater reliability of CHIPS. Controversial images were rated based on the consensus of the first author, the corresponding author, and a radiologist (Cheng-Feng Ho). The consensus CHIPS scores were used in our regression analyses. Intra-rater reliability was calculated by two independent ratings of the first author. The inter-rater reliability and intra-rater reliability were analyzed by inter-class correlation coefficient (ICC).

The brain structures were identified according to Paxinos and Watson (2007), as described above (Section 2.1). Measurements were carried out in the dorsal and ventral striatum, cingulate (Cg), motor (M), and somatosensory (S) cortex. Somatosensory, motor, and cingulate areas of the neocortex were measured without division into the primary and secondary cortex. The dorsal and ventral striatum were divided into subregions (Figure 2). The CPu was virtually divided into nine subregions, as shown in Figure 2. NAcb was divided into shell and core parts (abbreviated below as NAcbC and NAcbSh), further parcellated as shown on Figure 2. The obtained values of optical densities were converted into pmol/g of tissue by using the microscale standards (see Section 2.1). The obtained values of optical densities were converted into pmol/g of tissue by using the microscale standards (see Section 2.1).