A Systematic Review of the Brain Frontal Lobe Parcellation Techniques in Magnetic Resonance

Abstract

The domestic canine (canis familiaris) is a growing novel model for human neuroscientific research. Unlike rodents and primates, they demonstrate unique convergent sociocognitive skills with humans, are highly trainable and able to undergo not-invasive experimental procedures without restraint, including fMRI. In add-on, the gyrencephalic structure of the canine encephalon is more similar to that of human than rodent models. The increasing employ of dogs for not-invasive neuroscience studies has generating a need for a standard canine cortical atlas that provides common spatial referencing and cortical segmentation for avant-garde neuroimaging data processing and analysis. In this manuscript we create and make available a detailed MRI-based cortical atlas for the canine brain. This atlas includes a population template generated from xxx neurologically and clinically normal not-brachycephalic dogs, tissue sectionalisation maps and a cortical atlas generated from Jerzy Kreiner'south myeloarchitectonic-based histology atlas. The provided cortical parcellation includes 234 priors from frontal, sensorimotor, parietal, temporal, occipital, cingular and subcortical regions. The atlas was validated using an boosted canine accomplice with variable cranial conformations. This comprehensive cortical atlas provides a reference standard for canine brain inquiry and volition improve and standardize processing and data analysis and interpretation in functional and structural MRI research.

Introduction

There is continual demand to develop novel beast models for neurobiological and neuropsychological research. The domestic canine (canis familiaris) shows multiple advantages over more standard rodent and primate models and in that location is growing utilize of the dog as a model in neurocognitive, aging and clinical inquiry. Unlike rodents and primates, dogs are highly-trainable and able to undergo not-invasive experimental procedures without restraint, including functional magnetic resonance imaging (fMRI)^i,2. In add-on, the canine brain has the advantage of being gyrencephalic, making it more similar to the human brain than rodent and avian models. Neurocognitively the canine shares like behavioral and emotional responses to humans and are highly integrated into homo club. These convergent sociocognitive skills places the canis familiaris in a unique position to increase our understanding of sociocognition in humans³. The aging canine is beingness routinely used as model for crumbling research due to its unique similarities to human brain aging and ability to link aging with learning memory and other cerebral functions^four,5,6,7. The canine as well suffers from some spontaneous neurological diseases analogous to that of humans, and as such can serve as a unique model for these disease processes including glioma⁸ and amyotrophic lateral sclerosis^nine. This growing use of the domestic dog in non-invasive neuroscience, aging and neuropathogical research has generated a need for a standard canine brain atlas that provides mutual spatial referencing and architectonic based cortical partitioning for standardized data processing, analysis and interpretation^three.

Several brain atlases have been made available for the canine^10,11,12, even so these atlases have limitations, being created from a depression number of subjects¹⁰, using not-isovolumetric clinical magnetic resonance imaging (MRI) data¹², or utilizing dogs that were not neurologically or clinically healthy¹¹. In improver, in that location is no cortical atlas that provides a microarchitectonic based cortical parcellation for the canine encephalon¹². Cortical brain atlases allow for standardized referencing of brain regions within a item species and assistance in the correlation of function and structural encephalon regions between species. Digital cortical atlases can be viewed three-dimensionally and can be used for computational processing and transformation, a critical component for quantitative assay of MRI data¹³.

Atlases of the cerebral cortex have been historically created by partitioning into regions with distinct laminar structures using histologically defined criteria. The virtually ordinarily used homo MRI cortical atlases were created based on cytoarchitectonic maps created by the High german anatomist Korbinian Brodmann^xiv which separated areas of the cortex according to cytoarchitectural organization. Although used commonly, in that location is a concern that these atlases do not provide sufficient neuroanatomical item for the caste of cortical segregation more than recently identified in neuroimaging research^15,sixteen. Though more fine-grained cytoarchitectonic atlases exist, such as Economo and Koskinas, 1925 atlas¹⁷ and Sarkisov, 1949 atlas¹⁸ they have non been widely utilized. For this reason there has been growing, interest in using a different component of neuronal organization, myeloarchitecture, to create a human cortical atlases such equally the one generated by anatomists Oskar and Cecile Vogt^16,19,twenty and Flechsig²¹. The atlases by Vogt^17,20,21 divide the cortex according myeloarchitecture using the density, orientation and configuration of myelinated axons resulting in the division of the human cortex into 185 regions. These regions are thought to be complementary to cytoarchitectonic based cortical divisions. Currently, a "supermap" of the human neocortex is being created using myeloarchitectonics from the Vogt-Vogt School and has the potential to exist a tool that is more detailed and morphologically more than authentic than currently available cytoarchitectonic atlases^sixteen. Similarly research past Walters²² have shown have shown a direct correlation between the myeloarchitecture of the human cortex and MRI signal intensities could be applied to other species.

The canine cortex has been intricately studied by Jerzy Kreiner who generated a comprehensive myeloarchitectonic-based cortical atlas^{23,24,25,26,27,28}. These document the parcellation of the cortex co-ordinate to the size, staining, advent, and system of radial and tangential myelinated fibers and the appearance of myelinated fibers in the superficial plexus²⁴. These manuscripts provide detailed surface and cross-sectional illustrations to prove the exact margins of each region, facilitating sectionalization^{23,24,25,26,27,28}. They intricately segment the cortex into regions, similar to that described by the Vogt-Vogt school^sixteen.

In this manuscript we create a stereotactic cortical atlas for the mesaticephalic canine encephalon based on data from Kreiner's myeloarchitectonic parcellations. This cortical atlas is created with a population boilerplate template generate from high-resolution 3-dimensional T1-weighted information obtained from 30 neurologically normal dogs. This quality assured and validated atlas includes tissue segmentation maps and a total of 234 cortical and subcortical priors. The atlas is provided in mutual neuroimaging computer science engineering science initiative (NIfTI) format and tin can exist integrated into standard neuroscience tools and pipelines for information assay and processing. This comprehensive cortical atlas provides a reference standard for canine brain enquiry and volition better and standardize processing and data assay and interpretation in functional and structural MRI research.

Materials and Methods

Written report population

For template creation, nosotros recruited thirty dogs from research populations (Cornell University Higher of Veterinary Medicine). In order to limit the diversity of brain structure betwixt subjects secondary to cranial conformation, we included only non-brachycephalic dogs considered clinically and neurological normal. The population was composed of 22 females and eight males aged between 2 and 11 years of age (median 5.5, interquartile range 7.5). Ten of these subjects were beagles and twenty were of mixed brood, weighing between seven and 30 kgs (median thirteen, interquartile range 12.75). All dogs were imaged for research purposes and the Cornell University Institutional Animal Care and Use Committee (IACUC protocol number: 2015–0115) canonical their use (Table 1). All procedures were performed in accordance with the relevant guidelines and regulations.

Table 1 Signalment and brain characteristics of subjects included in the final template. F = female person, Fs = female spayed, M = male, Mn= male neutered.

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For skull conformation compatibility testing, data sets from twelve dogs were recruited from a neurologically normal clinical research population (University of Sydney Higher of Veterinary Science). Five subjects were clinically healthy and 7 were previously diagnosed with glaucoma affecting a unmarried or both eyes. All dogs were female aged between 5 and 11 years of age (median 9, interquartile range 3.v). The cohort weighed between 4.7–35.3 kg (median eight.iv, interquartile range seven.48) and included the following breeds, apartment-glaze retriever (n = 1), cocker spaniel (north = ii) and cattle domestic dog (n = 1), Maltese crossbreed (n = 3), labradoodle (n = three) and terrier crossbreed (northward = 2) (Table 2). All dogs were imaged for research purposes and the University of Sydney Ideals Commission approved their use (Protocol no. 2017/1156).

Table ii Signalment and encephalon characteristics of subjects included in the testing cohort. Fs = female spayed.

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MRI examination

Dogs imaged for template creation were imaged under general anesthesia performed by a lath-certified veterinary anesthesiologist. Dogs were premedicated with dexmedetomidine (three mcg/kg Dexdomitor 0.5 mg/ml, Zoetis Inc, Kalamazoo, MI), induced to general anesthesia with propofol to effect (iii.2–v.iv mg/kg Sagent Pharmaceuticals, Schaumburg, III) and intubated. They were maintained under anesthesia with inhalant isoflurane and oxygen with a dexmedetomidine continuous rate infusion (1 mcg/kg/hr Dexdomitor 0.5 mg/ml, Zoetis Inc, Kalamazoo, MI). MRI was performed in a iii.0T General Electric (GE) Discovery MR750 (GE Healthcare, Milwaukee, WI) whole trunk scanner (sixty cm bore bore), operating at 50mT/grand aamplitude and 200T/m/south slew-rate. Subjects were placed in dorsal recumbency with their head centered in a 16-channel medium flex radio-frequency coil (NeoCoil, Pewaukee, WI 53072 United states). A high-resolution T1-weighted 3D inversion-recovery fast spoiled gradient echo sequence (Bravo) was performed in each subject with the following parameters; isotropic voxels 0.v mm³, TE = 3.6 ms, TR = 8.4 ms, TI = 450 ms, excitations = 3, a flip angle of 12°, acquisition matrix size = 256 ×256.

Dogs imaged for skull shape compatibility validation were imaged under full general anesthesia performed by a trained veterinarian anesthesiologist. All animals were premedicated with methadone (0.1–0.4 mg/kg IM; Physeptone, Aspen Pharma Pty Ltd, St Leonards NSW) with or without acepromazine (0–0.03 mg/kg IM; ACP-2, Ceva Beast Health Pty Ltd, Glenorie NSW). Full general anesthesia was induced with propofol (4–half-dozen mg/kg IV; Propofol, Sandoz Pty Ltd, Pyrmont NSW) or thiopentone (4 mg/kg IV; Pentothal, Link Medical Products Pty Ltd, Warriewood NSW) to event and intubated. Inhalational isoflurane and oxygen maintained full general anesthesia. Imaging was performed in a 3.0T GE Discovery MR750 (GE Healthcare, Milwaukee, WI) whole body scanner using an 8-channel extremity curl (Hard disk drive Pes Ankle array, Invivo) with the canis familiaris positioned in dorsal recumbency. A T1-weighted 3D fast spoiled gradient recalled echo (FSPGR) pulse sequence was performed with the following parameters; isotropic voxels 0.6 mm^three, TE = ii.eight ms, TR = 6 ms, TI = 450 ms, excitations = 1, flip bending = 12°, acquisition matrix size = 192 × 192, piece thickness = 0.vi mm.

Data processing

Preprocessing

Isovolumetric T1-weighted data from the template group were used to create a population boilerplate atlas template. MRI data were corrected for low-frequency inhomogeneity²⁹. A manual removal of non-encephalon tissues was practical prior to registration and spatial normalization³⁰. The origin of images were manually set to the rostral commissure using SPM12³¹ and reoriented to a standard FMRI Software Library (FSL) orientation for inter-subject consistency where the 10-axis contains right-left orientation, the y-axis contains the caudal-rostral orientation and the z-centrality contains the ventral-dorsal orienation³². A flow chart depicts the steps nosotros undertook during data processing and template validation (Effigy 1).

Figure 1

Method menses chart: Flow chart demonstrating the pre-processing, template creation and cranial conformation compatibility testing steps that were performed. (n = number of subjects, ANTs = avant-garde normalization tools, FAST = FMRIB's automatic segmentation tool, MNI = Montreal Neurological Found). This effigy was created using FSLeyes (version ii.one https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes), OsiriX MD (version eleven.0 https://www.osirix-viewer.com/osirix/osirix-physician/) and Microsoft Powerpoint (version 16.sixteen.19. www.microsoft.com).

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Template cosmos

Previous atlas literature take tested linear and not-linear methods for template creation and consistently establish not-linear registration using Avant-garde Normalization Tools (ANTs) to provide templates with the all-time contrast and bespeak to racket ratios^12,33,34. For this reason, we opted to apply non-linear registration methods to create our population average template. The individual subjects T1s were averaged and transformed into a common infinite population template using Advanced Normalization Tools (ANTs) which applied affine registration and diffeomorphic registration via the symmetric normalization (SyN) algorithm using the ANTs multivariate template creation script (Avants et al.^35,36, 2010). This template was generated with a stereotaxic coordinate system co-ordinate to the Montreal Neurological Institute (MNI) template specifications and in line with other animate being templates^12,37. The origin of the Cartesian system (10,y,z; 0,0,0) was centered on the mid-line over the dorsal aspect of the rostral commissure. The zero x-axis value sagittal plane extended through the center of the brain in line with the falx cerebri, the cypher y-centrality value transverse plane was parallel to the anterior commissure and transected the encephalon symmetrically and the aught z axis value dorsal plane ran from the dorsal rostral commissure to the mesencephalic aqueduct, ventral to the caudal commissure. Sagittal airplane 10-axis values increased left to right, transverse aeroplane y-axis values increased caudal to rostral and dorsal plane z-axis values increased ventral to dorsal. All co-ordinates are provided in millimeters. A neuroanatomical adept evaluated the final template and compared to anatomic specimens for appropriate anatomical item. Tissue segmentation maps (TSMs) were created from the template using FMRIB's Automated Partition Tool (FAST) which segments encephalon affair into cerebral spinal fluid (CSF), greyness matter (GM), and white matter (WM) while correcting for spatial intensity variations³⁸. FAST was used to create partial volume maps, TSMs of each tissue blazon, binary division masks and bias field maps. These maps were evaluated and manually corrected to ensure anatomical coherence with the T1 weighted browse. The corrected partial volume masks were used to calculate the tissue volume to account for partial volume effects and increase sensitivity. Effigy 1 documents the template creation steps undertaken.

Determination of cranial conformation

Canine cranial conformation is highly variable between animals of different breed and genetic make-ups. There is currently no clear consensus on how to categorize dogs into brachycephalic (brusque-faced), mesaticephalic (medium-faced) and dolichocephalic (long-faced) groups. Milne et al. (2016) explored multiple dissimilar techniques and found that brain length correlated most strongly with a subjective categorization of encephalon conformation. For this reason, we utilized encephalon length parameters to place the cranial conformation of all subjects included in the encephalon template and testing cohorts. Data sets with a encephalon length <68 mm were classified every bit brachycephalic, 72–87 mm were classified every bit mesaticephalic and >88 mm were classified every bit dolichocephalic^xi. These measures confirmed that the template accomplice included 25 mesaticephalic and five dolichocephalic subjects (Table one) and the testing cohort included seven brachycephalic subjects, iv mesaticephalic and one dolichocephalic (Table 2).

Skull conformation compatibility

In society to test the impact of registration on brains with differing cranial conformation the testing accomplice, made up of five mesaticephalic, i dolichocephalic and seven brachycephalic subjects, were registered and assessed for similarity to the template using the Jaccard similarity index and warping using the Jacobian warping metric. Individual subject area information were corrected for low-frequency inhomogeneity (Tustison et al.²⁹) and manual removal of not-brain tissues was applied. Each subject'southward brain data were registered to the population template using alignment (center of epitome 0,0,0 at the anterior commissure with anatomical alignment through the rostral commissure and ventral brain regions), rigid linear registration (registering each subject to the template with half dozen degrees of freedom) using FMRIB's Linear Registration Tool (FLIRT)³⁹ and nonlinear registration using FMRIB's Nonlinear registration (FNIRT)⁴⁰. Binary brain masks were generated for each field of study at each level of registration i.e. aligned mask, linear mask, and nonlinear mask.

Jaccard similarity index

The caste of similarity between the individual subject and template masks was tested using the Jaccard similarity index. The alphabetize was able to calculate the amount of overlapping between individual subjects at each level of registration compared to the template mask. The Jaccard similarity index between the masks (i.e., subject 1 aligned to template mask etc.) was calculated using the following commonly used formula:

$${Jaccard}\,Index=\frac{number\,of\,voxels\,in\,both\,sets}{number\,of\,voxels\,in\,either\,set}\ast 100$$

This measure of similarity was compared beyond skull shape groups and registration method to identify any significant differences betwixt skull shape and similarity to the population template⁴¹. A one-mode ANCOVA explored the differences between similarity metrics across registration techniques while controlling for interaction effects of trunk weight (kg), encephalon volume (mm³) and brain length. Similarly, an ANCOVA tested the differences in alignment similarity between brachycephalic and mesaticephalic groups while covarying for torso weight (kg), brain volume (mm³) and brain length. Statistically meaning differences or associations were considered nowadays when p < 0.05.

Jacobian warping metric

In guild to assess the degree of warping that each bailiwick underwent during non-linear registration Jacobian determinants for each voxel were calculated as a measure of nonlinear warping. In order to visualize and explore the localization and blueprint variation of warping beyond the dog cranial conformation groups, the log-demeaned absolute Jacobian warpfield images were tested for variation past one sample T-examination using FSL'due south randomize tool for permutation testing general linear models⁴² for each cranial conformation testing group, brachycephalic (n = 7) and mesaticephalic (n = 4). Since there was a single dolichocephalic subject, this group was non considered for testing. These permutations aim to exam the null hypotheses that the mean variation is symmetrical and therefore centered around zero. The output t-statistic was corrected for multiple comparisons using threshold-complimentary cluster enhancement and thresholded at p < 0.05 significance. A mail service hoc Tukey multiple comparisons of means at 95% family-wise confidence levels explored the differences between each registration method. Mean Jacobian warping metric for each bailiwick across all voxels was plotted with each cranial conformation group. For visualization purposes three subjects' (one brachycephalic, one mesaticephalic and i dolichocephalic) log demeaned Jacobian warpfields were presented in a 3D format to highlight regional variation across dogs of different skull shapes.

Cortical parcellation

Cortical parcellation into myeloarchitectonic regions was performed manually on the canine population template. Researchers divided the cortex into the following lobes; frontal, cingulate, parietal, sensori-motor, temporal (perisylvian) and occipital post-obit the myeloarhitectonic articles from Jerzy Kreiner^{23,24,25,26,27,28}. Lobe boundaries were established based on the demarcations in Kreiner's articles. Inside these lobes private regions were parcellated based on Kreiner'south detailed descriptions and depictions of cortex surfaces, sagittal and transverse slices, and referencing histological atlases^43,44. In full, 234 regions were parcellated by trained researchers (EFB and BR) and reviewed by a canine MRI anatomy practiced (PJJ).

Results

Template

The final population template exhibited surface detail that corroborated well with an anatomic specimen (Figure two). Generated tissue partitioning maps exhibited appropriate anatomic structure and correlated well to the grayness and white affair definition of the temple.

Figure 2

Gyral anatomy: Demonstrates the gyral surface anatomy of the terminal population average template and correlates that to a mesaticephalic anatomic specimen. The anatomic specimen underwent emersion fixation in 10% buffered formalin after removal from the attic (g. = gyrus, cd. = caudal, rost. = rostral). This figure was created using FSLeyes (version 2.ane https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes) and Microsoft Powerpoint (version 16.sixteen.xix. www.microsoft.com).

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Skull conformation compatibility

Jaccard similarity index

For each skull group, a one-manner ANCOVA tested the differences betwixt similarity metrics across registration techniques while decision-making for interaction furnishings of body weight (kg), encephalon book (mm³) and brain length. Within the brachycephalic grouping there was meaning departure in similarity metrics across registration techniques while controlling for covariates mentioned to a higher place (F(2,12) = 144.58, p < 0.001). Mail hoc Tukey multiple comparisons of means at 95% family unit-wise conviction levels showed a meaning difference in similarity metrics betwixt alignment and linear registration (p < 0.01) and alignment and nonlinear registration (p < 0.01) just no significant divergence in similarity metrics betwixt linear and nonlinear registration. Within the mesaticephalic group, there was a significant deviation in similarity metrics beyond registration techniques while decision-making for covariates mentioned above (F(2,viii) = 5.29, p = 0.03). Post hoc Tukey multiple comparisons of means at 95% family unit-wise confidence levels showed a significant difference in similarity metrics between alignment and nonlinear registration (p = 0.04) (Figure 3).

Jacobian warping metric

The 1 samples t-test tested the variation in warping metrics in each skull group. Within the brachycephalic group there appeared to be high levels of warping in the frontal and olfactory cortices, and a big cluster of significant voxels survived multiple comparison correction and 0.95 thresholding. While nosotros observed variations in warping in the mesaticephalic grouping, there were no significant clusters that survived correction. Variation in localization and magnitude was nowadays across the three representative subjects for brachycephalic, mesaticephalic, and dolichocephalic skull shape (Figure 3).

Figure 3

Jaccard similarity after aligned, linear and non-linear registration: Provides a visual demonstration of the overlap of an individual discipline's encephalon data to the population average template (cerise outline) afterwards alignment, linear and non-linear registration. A single sample bailiwick from each cranial conformation group is provided. The hateful similarity index for each subject field was plotted in each cranial conformation group, according to registration technique (aligned = yellowish, linear = blue, and non-linear = crimson). A mail service hoc Tukey multiple comparisons of means identified statistically significant difference in similarity index between aligned and linear and aligned and non-linear techniques in the brachycephalic grouping and between aligned and non-linear techniques in the mesaticephalic group. Jacobian warping after non-linear registration: Provides a surface heat map (range 0.0–0.8) demonstrating the degree of warping for a unmarried representative subject for each cranial conformation grouping. The warping metric used is the log demeaned accented Jacobian determinant for each voxel. The mean Jacobian warping metric for each discipline was plotted inside each cranial conformation group in the boxplot on the right side. These figures demonstrate that the highest caste of warping was present within the brachycephalic grouping. This figure was created using FSLeyes (version 2.1 https://fsl.fmrib.ox.ac.britain/fsl/fslwiki/FSLeyes), microGL (version 2.i www.mricro.com) and Microsoft Powerpoint (version 16.xvi.xix. www.microsoft.com).

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Cortical and subcortical parcellation

The brain was parcellated into 7 lobar regions (Figure 4) and a total of 234 cortical and subcortical regions. The abbreviation, full name, gyrus, lobe and volume of each region is documented in Table three. Transverse, sagittal and dorsal sliced images or the cortical parcellation with anatomic referencing is provided in Figures 5–7 and three -dimensional depictions provided in Effigy 8.

Effigy four

Lobar divisions: Depicts how the brain was divided into lobar regions according to that described by Jerzy Kriener. These regions included frontal (red), parietal (blue), sensorimotor (cian), temporal (yellow), occipital (green), cingulate (mauve), and subcortical (pink). This figure was created using FSLeyes (version two.ane https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes), ITKsnap (version 3.8.0 www.itksnap.org), Affinity designer (version 1.8 www.affinity.serif.com) and Microsoft Powerpoint (version 16.16.19. world wide web.microsoft.com).

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Tabular array iii Documents the name, abreviation, gyral and lobar location and volume of each cortical and subcortical prior.

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Figure five

Cortical atlas in transverse sections: Demonstrates the cortical atlas and a corresponding anatomic specimen in transverse department at frontal (A), caudate nuclei (B) and mid-thalamic (C) levels. The anatomic specimen underwent plasticization of the vasculature and fixation. The brain was transected and photographed in-situ within the cranium to maintain normal anatomic structure. This effigy was created using FSLeyes (version two.1 https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes), ITKsnap (version iii.8.0 www.itksnap.org), Affinity designer (version 1.8 www.affinity.serif.com) and Microsoft Powerpoint (version 16.sixteen.nineteen. world wide web.microsoft.com).

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Figure vi

Cortical atlas in transverse sections: Demonstrates the cortical atlas and a corresponding anatomic specimen in transverse section at caudal thalamic (A), hippocampal (B) and occipital (C) levels. The anatomic specimen underwent plasticization of the vasculature and fixation. The brain was transected and photographed in-situ within the cranium to maintain normal anatomic construction. This figure was created using FSLeyes (version 2.1 https://fsl.fmrib.ox.air-conditioning.united kingdom/fsl/fslwiki/FSLeyes), ITKsnap (version 3.8.0 www.itksnap.org), Affinity designer (version ane.viii www.affinity.serif.com) and Microsoft Powerpoint (version xvi.16.nineteen. www.microsoft.com).

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Effigy 7

Cortical atlas in sagittal and dorsal sections: Demonstrates the cortical atlas and a respective anatomic specimen in dorsal (A) and sagittal (B) section. The anatomic specimen encephalon underwent immersion fixation earlier transection and photography. This figure was created using FSLeyes (version two.i https://fsl.fmrib.ox.ac.united kingdom/fsl/fslwiki/FSLeyes), ITKsnap (version three.8.0 www.itksnap.org), Analogousness designer (version one.viii www.affinity.serif.com) and Microsoft Powerpoint (version 16.xvi.19. www.microsoft.com).

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Effigy 8

Cortical atlas in 3-dimensions: Demonstrates the 3-dimensional figures of the cortical atlas in lateral (A), dorsal (B) and oblique (C) and frontal (D) orientations. This figure was created using FSLeyes (version 2.1 https://fsl.fmrib.ox.air-conditioning.united kingdom of great britain and northern ireland/fsl/fslwiki/FSLeyes), ITKsnap (version iii.viii.0 world wide web.itksnap.org), Affinity designer (version 1.viii www.affinity.serif.com) and Microsoft Powerpoint (version xvi.sixteen.19. www.microsoft.com).

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Frontal parcellation

The frontal region was delineated by adapting from what Brodmann termed the "regio frontalis" in man¹⁴ and was bordered ventrally by the anterior rhinal sulcus and caudally past the sylvian and genual sulci²⁵. This region involved the orbital, pregenual, proreus and subproreus gyri and was segmented into 17 different regions per hemisphere. These regions had a mean book of 1042.4 mm³ (+/−918.1) (Table 3).

Sensori-motor parcellation

The sensori-motor region was delineated according to that described by Woosley and his associates⁴⁵ and includes the pre-cruciate, anterior composite, precentral, postcentral and coronal gyri²⁶. This region was segmented into 23 different regions per hemisphere. These regions had a mean volume of 1266.5 mm³ (+/−1037.0) (Table 3).

Cingular parcellation

The cingular cortex represents the limbic region in the dog and comprises subcallosal, genual, anterior cingulate and posterior cingulate gyri. It lies next to the callosal commissure and is borders the deep fissure splenialis dorsolaterally, genual crevice rostrally and caloso-marginalis fissure ventrally²⁴. This region was segmented into 15 different regions per hemisphere. These regions had a mean volume of 528.3 mm³ (+/−261.5) (Table 3).

Parietal parcellation

The parietal region lies caudal to the sensori-motor cortex and is bordered by the splenial fissure medially and suprasylvian fissure laterally. This surface area includes regions of the entolateral, marginal, coronal, presplenial, ectolateral and suprasylvian gyri and is divided into 16 regions per hemisphere²³. These regions had a mean volume of 544.viii mm³ (+/−440.3) (Tabular array 3).

Temporal (peri-sylvian) parcellation

This region lies laterally and includes the sylvian, ectosylvian and posterior composite gyri and functionally represents the auditory cortex²⁸. This area is divided into 13 dissimilar hemispheric regions. These regions had a hateful book of 2889.4 mmⁱⁱⁱ (+/−1618.3) (Table 3).

Occipital parcellation

This region lies caudally within the brain and its margin borders the posterior rhinal, retrosplenial and posterior suprasylvian fissures. It includes regions within the entolateral, marginal, ectolateral, medial occipital, suprasylvian, recurrens and pararecurrents gyri²⁷. This area was segmented into 24 unlike regions co-ordinate to the myeloarchitectonic structure. These regions had a mean volume of 2405.2 mm³ (+/−2274.three) (Table iii).

Subcortical parcellation

These regions were delineated according to anatomic descriptions⁴³ and included the amygdala, caudate nuclei, rostral and caudal colliculus, cerebellum, hippocampi, lateral and medial geniculate nuclei and olfactory bulbs. We included merely regions whose boundaries were readily visible on the T1-weighted atlas were included in these segmentations. These regions had a mean volume of 6906.nine mm³ (+/−11776.v) (Table 3).

Using this brain atlas

This atlas can exist used with mutual MRI toolboxes such as FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) and ANTs (http://stnava.github.io/ANTs/) to perform linear or nonlinear registration from subject'southward T1 native space to the atlas T1 population infinite or, inversely, to annals T1 population template to a subject area'south T1 native space. The authors would propose using either FSL'due south FLIRT (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FLIRT) for linear registration or ANTs SyN³⁵ for nonlinear registration, saving the transformation matrices of these registrations and applying them to the brain atlas or other masks. Visual or manual registration can be conducted with itk-SNAP⁴⁶ if necessary or desired. To view the atlas with labels users can utilise FSLeyes (https://zenodo.org/record/3530921#.Xkbq1hdKhUM). Once the atlas is loaded the atlas search tab can be used to identify and isolate specific regions by label name.

Ethics statement

All beast use associated with this study was approved by institutional ideals or animal care and use committees.

Discussion

We present a comprehensive cortical atlas for the canine brain based on cortical myeloarchitecture. This atlas includes a population boilerplate template generated from 30 neurologically normal non-brachycephalic canines and TSMs for GM, WM and CSF. Cortical parcellation resulted in the generation of 234 cortical and subcortical priors from frontal, sensorimotor, parietal, temporal (perisylvian), occipital, cingular and subcortical regions. Not-linear registration of canine brains from mesaticephalic, dolichocephalic and brachycephalic cranial conformation resulted in high levels of similarity merely pregnant warping within the brachycephalic group. The atlas is made bachelor through an online repository https://ecommons.cornell.edu/handle/1813/67018.

Importance of this brain atlas

This is the most comprehensive architectonically parcellated cortical atlas created for the dog, an essential neuroscientific animal model. Modern stereotaxic brain atlases are a vital tool for neuroimaging research with far-reaching applications in information normalization, registration, segmentation and parcellation⁴⁷. The lack of a detailed cortical atlas has, so far, limited researchers working with the domestic dog model³. Although an increasing number of studies perform fMRI on the awake and anesthetized canines, the lack of an accustomed loftier-quality canine atlas has limited grouping-level and cortical region of involvement analyses^{2,48,49,l,51,52}. Our atlas is a vital tool that will assistance standardize cortical localization of regions of functional activation improving our understanding of the functional-structural correlation of the canine brain.

Analyzing the resting-state default style network is a promising area of research in the canine^one. However, as nonetheless, only independent component analysis (ICA) and manually placed seed-based analysis take been performed⁵². Our atlas provides whole-brain architectonic based cortical priors that could standardize seed-based functional connectivity analysis and assist in interpreting ICA. Vogt and Vogt suggested that the unique nature of each cortical region'southward myeloarchitectonic structure indicated that every region has a separate and specific role⁵³. fMRI has helped to place specific regions of the brain that respond to different stimuli, including audition⁵⁴, olfaction^50,55 and visual facial processing⁴⁸. Correlating these findings to our cortical encephalon atlas could aid define the functional relevance of these architectonically distinct regions, taking us a step farther in understanding the structure-role relationship of the canine brain and how this correlates to what is already well established in humans.

Cortical parcellation tin can be performed using multiple methods, including architectonics, surface structure, connectivity, electrophysiology and function. The paucity of functional, electrophysiological and connection information for the canis familiaris precluded the employ of these techniques to create a comprehensive cortical atlas. Architectonic based cortical parcellation has historically created the nearly important and readily used atlases in the human¹⁴ and multiple animal models^56,57. Architectonics uses cellular structure and organization to delineate boundaries inside the cortex and includes both cytoarchitectonic and myeloarchitectonic methods. In the canis familiaris comprehensive histology-based atlases take been created using both cytoarchitectonic and^58,59,lx and myeloarchitectonic^{23,24,25,26,27,28} techniques. The cytoarchitectonic based atlases are relatively simple, showroom considerable variation in cortex division, and lack cross-sectional illustrations. Thus, making accurate delineation of cortical regions throughout the complex canine brain extremely challenging^58,59,sixty. Also, fMRI research raises the concern that cytoarchitectonic based atlases underestimate the caste of cortical segmentation at a functional level^{sixteen,61,62}. For these reasons, we created our cortical atlas with guidance from the comprehensive series of papers documenting cortical parcellation according to myeloarchitectonic structure past Jerzy Kreiner^{23,24,25,26,27,28}.

Kreiner divided the cortex by assessing the size, staining, appearance, and arrangement of radial and tangential fibers and the appearance of fibers in the superficial plexus²⁴. Myeloarchitectonic based cortical parcellation was the initial technique used to divide the man cortex by the anatomists Cecil and Oskar Vogt²⁰. This technique is thought to approve with cytoarchitectonic based cortical divisions and has been used to create a cortical "supermap" in man^xvi,20. When Kreiner compared his myeloarchitectonic cortical sectionalisation of the canine brain to atlases using cytoarchitectonic based parcellation, there were both similarities and apparent differences in parcellation of the cortex between techniques^{23,24,25,26,27,28,58,59,60}. In the homo brain, parcellation similarly identified disparities between the Vogt-Vogt myeloarchitectonic atlas and the cytoarchitectonic-based Brodmann atlas. However, when Vogt and Vogt, and multiple other researchers combined these techniques, they described complete cyclopedia between cytoarchitectonic and myeloarchitectonic based regions^20,63,64,65.

Myeloarchitectonic cortical parcellation identifies boundaries within the cortex according to the organization and structure of myelinated fiber layers and radial bundles¹⁹. Myelin has a specific signal intensity on MRI and recently not-invasive imaging techniques accept been used to create cortical myelin maps in vivo. These techniques accept advantage of the intensity differences between degrees of myelination within grey matter observed on T1 and T2 weighted sequences and create cortical myelin maps with distinctive patterns of light, moderate and heavy myelination⁶⁶. These in vivo maps have been found to correlate well with both cytoarchitectonic and myeloarchitectonically defined cortical boundaries^16,66,67,68. In vivo cortical myelin maps have non, as yet, been generated for the canine and our atlas serves as a useful tool for validation and estimation of time to come study in this area.

It is optimal to utilize an atlas that most closely resembles the brain construction of the study population⁴⁷. Dogs have highly variable brain construction depending on their cranial conformation and breed^69,70. Virtually importantly, brachycephalic dogs exhibit shortening of the cranium that causes ventral pitching of the encephalon'southward long-centrality and a ventral shift of the olfactory lobe⁶⁹. The degree of brain deformity associated with brachycephaly warrants a specific brachycephalic population template, as is provided by Milne et al.¹¹. With this in mind, nosotros limited differences in brain construction within our template cohort by including merely dogs with mesaticephalic or dolichocephalic cranial conformation and excluding brachycephalics. Equally a result, our atlas is most suitable for non-brachycephalic canine cohorts, which includes the nearly common pet dog breeds, the golden retriever, Labrador retriever, High german shepherd canis familiaris, and the most commonly used enquiry dog breed, the beagle. When nosotros tested the consequence of registration of subjects with brachycephalic cranial conformation to the last template, we institute that although non-linear registration resulted in a high caste of similarity betwixt the template and the subject, there was an associated high level of information warping. Excessive degrees of warping can create artifact and misclassification of tissues and structures^47,71. Because this limitation is essential when using this atlas in populations of dogs with brachycephalic cranial conformation. The evolution of parcellated cortical atlases specific to dogs with brachycephaly cranial conformation could exist a focus of farther study.

The domestic dog is condign an increasingly important animate being model for neurocognitive, translational and comparative neuroscience research; however, tools such as a cortical encephalon atlas, are required to support inquiry in this species^three. We generated this cortical brain atlas from loftier-quality isovolumetric T1-weighted information obtained from xxx neurologically and clinically healthy dogs. It includes a population average template, tissue probability maps and 234 cortical and subcortical priors from frontal, sensorimotor, parietal, temporal (perisylvian), occipital, cingular and subcortical regions. The resulting population template has been validated using additional populations of mesaticephalic, brachycephalic and dolichocephalic skull conformations. This atlas will improve tissue segmentation and cortical region delineation and represents a unique and vital tool to facilitate neuroimaging inquiry in this useful fauna model.

Data availability

The presented data fix are stored in NIFTI-1 format and can be viewed on readily available imaging software including SPM and FSL (Analysis Group, FMRIB, Oxford, UK). All data including the T1-weighted population average canine brain template, cortical and subcortical priors, tissue segmentation maps are available at the following online resource centre https://ecommons.cornell.edu/handle/1813/67018.

Change history

• 23 Feb 2021

  A Correction to this paper has been published: https://doi.org/10.1038/s41598-021-84559-1

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Acknowledgements

Nosotros would like to acknowledge the aid of Zonia Clancy, Carol Frederick and Nora Mathews for their assistance in handling and anesthesia during magnetic resonance imaging. Nosotros would also thank the Vaika foundation and the Bowman, Boesch and Cheetham Labs based at Cornell University College of Veterinary Medicine for their contributions. This piece of work was supported by The Canine Enquiry Foundation. The Foundation funded a portion of the canine magnetic resonance imaging costs.

Author information

Affiliations

1. Cornell College of Veterinary Medicine, Department of Clinical Sciences, Cornell University, Ithaca, NY, U.s.

   Philippa J. Johnson, Benjamin C. Rivard, John P. Loftus & Erica F. Barry

2. National Institute of Aging, National Institutes of Health, Baltimore, Dr., United states

   Wen-Ming Luh

3. Clinical Ophthalmology and Eye Wellness, Sydney Medical School, University of Sydney, Sydney, NSW, Commonwealth of australia

   Kathleen Fifty. Graham & Andrew White

4. Cornell College of Veterinarian Medicine, Department of Biomedical Sciences, Cornell Academy, Ithaca, NY, U.s.a.

   Marnie FitzMaurice

Contributions

Information planning and conquering was performed by P.J.J., J.P.50., Due west.L., 1000.L.Grand. and A.Due west. Data processing and sectionalisation was performed past P.J.J., B.C.R. and E.F.B. Anatomic correlation was performed by P.J.J. and Thousand.F. Manuscript text was written past P.J.J. and prototype preparation performed by P.J.J. and Eastward.F.B. Manuscript review was performed past all authors.

Corresponding author

Correspondence to Philippa J. Johnson.

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Johnson, P.J., Luh, WM., Rivard, B.C. et al. Stereotactic Cortical Atlas of the Domestic Canine Encephalon. Sci Rep 10, 4781 (2020). https://doi.org/10.1038/s41598-020-61665-0

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• Received: 22 Nov 2019

• Accustomed: 27 Feb 2020

• Published: 16 March 2020

• DOI : https://doi.org/10.1038/s41598-020-61665-0

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