Decision letter: Chimpanzee brain morphometry utilizing standardized MRI preprocessing and macroanatomical annotations

Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Chimpanzees are among the closest living relatives to humans and, as such, provide a crucial comparative model for investigating primate brain evolution. In recent years, human brain mapping has strongly benefited from enhanced computational models and image processing pipelines that could also improve data analyses in animals by using species-specific templates. In this study, we use structural MRI data from the National Chimpanzee Brain Resource (NCBR) to develop the chimpanzee brain reference template Juna.Chimp for spatial registration and the macro-anatomical brain parcellation Davi130 for standardized whole-brain analysis. Additionally, we introduce a ready-to-use image processing pipeline built upon the CAT12 toolbox in SPM12, implementing a standard human image preprocessing framework in chimpanzees. Applying this approach to data from 194 subjects, we find strong evidence for human-like age-related gray matter atrophy in multiple regions of the chimpanzee brain, as well as, a general rightward asymmetry in brain regions. Introduction Chimpanzees (Pan troglodytes) along with bonobos (Pan paniscus) represent the closest extant relatives of humans sharing a common ancestor approximately 7–8 million years ago (Langergraber et al., 2012). Experimental and observational studies, in both the field and in captivity, have documented a range of cognitive abilities that are shared with humans such as tool use and manufacturing (Shumaker et al., 2011), symbolic thought (de and Frans, 1996), mirror self-recognition (Anderson and Gallup, 2015; Hecht et al., 2017) and some basic elements of language (Savage-Rumbaugh, 1986; Savage-Rumbaugh and Lewin, 1994; Tomasello and Call, 1997) like conceptual metaphorical mapping (Dahl and Adachi, 2013). This cognitive complexity together with similar neuroanatomical features (Zilles et al., 1989; Rilling and Insel, 1999; Gómez-Robles et al., 2013; Hopkins et al., 2014; Hopkins et al., 2017) and genetic proximity (Waterson et al., 2005) renders these species unique among non-human primates to study the evolutional origins of the human condition. In view of evolutionary neurobiology, the relatively recent divergence between humans and chimpanzees explains the striking similarities in major gyri and sulci, despite profound differences in overall brain size. Numerous studies using magnetic resonance imaging (MRI) have compared relative brain size, shape, and gyrification in humans and chimpanzees (Zilles et al., 1989; Rilling and Insel, 1999; Gómez-Robles et al., 2013; Hopkins et al., 2014; Hopkins et al., 2017). Previous studies of brain aging in chimpanzees have reported minimal indications of atrophy (Herndon et al., 1999; Sherwood et al., 2011; Chen et al., 2013; Autrey et al., 2014). Nevertheless, Edler et al., 2017 recently found that brains of older chimpanzees’ exhibit both neurofibrillary tangles and amyloid plaques, the classical features of Alzheimer’s disease (AD). Neurodegeneration in the aging human brain includes marked atrophy in frontal and temporal lobes and decline in glucose metabolism even in the absence of detectable amyloid beta deposition, which increases the likelihood of cognitive decline and development of AD (Jagust, 2018). Given the strong association of brain atrophy and amyloid beta in humans, this phenomenon requires further investigation in chimpanzees. Cortical asymmetry is a prominent feature of brain organization in many primate species (Hopkins et al., 2015) and was recently shown in humans in a large-scale ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) study (Kong et al., 2018). For chimpanzees, various studies have reported population-level asymmetries in different parts of the brain associated with higher order cognitive functions like tool-use (Freeman et al., 2004; Hopkins et al., 2008; Hopkins et al., 2017; Hopkins and Nir, 2010; Lyn et al., 2011; Bogart et al., 2012; Gilissen and Hopkins, 2013) but these results are difficult to compare within and across species, due to the lack of standardized registration and parcellation techniques as found for humans. To date, there is no common reference space for the chimpanzee brain available to reliably associate and quantitatively compare neuro-anatomical evidence, nor is there a standardized image processing protocol for T1-weighted (T1w) brain images from chimpanzees that matches human imaging standards. With the introduction of voxel-based morphometry (Ashburner and Friston, 2000) and the ICBM (international consortium of brain mapping) standard human reference brain templates almost two decades ago (Mazziotta et al., 2001), MRI analyses became directly comparable and generally reproducible. In this study, we adapt state-of-the-art MRI (magnetic resonance imaging) processing methods to assess brain aging and cortical asymmetry in the chimpanzee brain. To make this possible, we rely on the largest openly available resource of chimpanzee MRI data: the National Chimpanzee Brain Resource (NCBR, http://www.chimpanzeebrain.org/), including in vivo MRI images of 223 subjects from 9 to 54 years of age (Mean age = 26.9 ± 10.2 years). The aim of this study is the creation of a chimpanzee template permitting automated and reproducible image registration, normalization, statistical analysis, and visualization to systematically investigate brain aging and hemispheric asymmetry in chimpanzees. Results Initially, we created the population-based Juna.Chimp (Forschungszentrum Juelich - University Jena) T1-template, tissue probability maps (TPM) for tissue classification and a non-linear spatial registration ‘Shooting’ templates (Figure 1) in an iterative fashion at 1 mm spatial resolution. The preprocessing pipeline and templates creation were established using the freely available Statistical Parametric Mapping (SPM12 v7487, http://www.fil.ion.ucl.ac.uk/spm/) software and Computational Anatomy Toolbox (CAT12 r1704 http://www.neuro.uni-jena.de/cat/). Juna.Chimp templates, the Davi130 parcellation, gray matter (GM) masks utilized, as well as statistical maps from our analysis are interactively accessible and downloadable via the Juna.Chimp web viewer (http://junachimp.inm7.de/). Figure 1 Download asset Open asset Juna.Chimp templates including the average. T1- template, tissue probability maps (TPM), and Geodesic Shooting template. For Shooting templates and TPM axial slices are shown of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). All templates are presented at 0.5 mm resolution. To enable more direct comparison to previous research, we manually created the Davi130 parcellation (by R.D. and S.V.), a whole brain macroanatomical annotation based on the Juna T1 template (Figure 2). The delineation of regions within the cortex was determined by following major gyri and sulci, whereby, large regions were arbitrarily split into two to three sub-regions of approximate equal size even though histological studies show that micro-anatomical borders between brain regions are rarely situated at the fundus (Sherwood et al., 2003; Schenker et al., 2010; Spocter et al., 2010; Amunts and Zilles, 2015). This process yielded 65 regions per hemisphere for a total of 130 regions for the Davi130 macro-anatomical manual parcellation (Figure 2 and Figure 2—source data 1). Figure 2 Download asset Open asset Lateral and medial aspect of the Davi130 parcellation right hemisphere. Visible regions are numbered with Davi130 parcellation region numbers and correspond to names in the figure. Even numbers correspond to regions in the right hemisphere (as shown in the figure), while left hemisphere regions are odd numbers. A list of all Davi130 labels can be found at Figure 2—source data 1. Figure 2—source data 1 Source file for Complete List of Davi130 Labels. https://cdn.elifesciences.org/articles/60136/elife-60136-fig2-data1-v2.docx Download elife-60136-fig2-data1-v2.docx Following successful CAT12 preprocessing, rigorous quality control (QC) was employed to identify individual MRI scans suitable for statistical analysis of brain aging and hemispheric asymmetry in chimpanzees. Our final sample consists of 194 chimpanzees including 130 females with an age range of 9–54 years and a mean age of 26.3 ± 9.9 years (Figure 3A). The linear regression model with GM fraction of total intracranial volume as the dependent variable and age, scanner field strength, sex, and rearing environment revealed a significant negative association between age and GM (p<0.0001) demonstrating age-related decline in overall GM density (Figure 3B). Both sex (p=0.004) and scanner field strength (p<0.0001) showed a significant effect on total GM volume. Therefore, the sample was split into male and female subjects and into 1.5T and 3T scanner, whereby, all sub-samples showed a significant age effect on GM (male: R2 = 0.17, p=0.0004; female R2 = 0.13, p<0.0001, 1.5T: R2 = 0.19, p<0.0001; 3T: R2 = 0.09, p=0.004). There were no significant sex differences of GM decline (p=0.3). The same analysis was conducted on a matched human sample from the IXI dataset (Figure 3C; https://brain-development.org/ixi-dataset/). The human sample was matched based on age, sex, and scanner field strength (n = 194, 128 females, 20–78 y/o, mean = 39.4 ± 14.0). As life span and aging processes are different between species, the human sample was matched to chimpanzees roughly by using a factor of 1.5* for age. A significant age-related decline in overall GM (p<0.0001) as well as a significant sex effect (p<0.0001) was also found in the human sample (Figure 3D). Similar to the chimpanzee sample, both males and female subjects show a significant age effect on total GM (male: R2 = 0.58, p<0.0001; female: R2 = 0.61, p<0.0001) but with no significant sex differences on GM decline (p=0.8). Although both species present a significant age-related GM decline, humans show a higher negative correlation between age and GM (chimpanzee: R2 = 0.12; human: R2 = 0.55) with less variance as compared to chimpanzees. Figure 3 with 2 supplements see all Download asset Open asset Total gray matter volume decline during aging in chimpanzees and matched human sample. (A) Distribution of age and sex in the final sample of 194 chimpanzees. (B) Linear relationship between GM and age with standard error for chimpanzee sample. (C) Distribution of age and sex in the human (IXI) matched sample of 194 humans. (D) Linear relationship between GM and age with standard error for human sample. Figure 3—figure supplement 1 presents the age and sex distribution of the whole sample (n = 223). Figure 3—figure supplement 2 presents the age and sex distribution of the whole IXI sample (n = 496). Region-based morphometry analysis was applied to test for local effect of age on GM. Linear regression analyses identified 55 of 130 brain regions in the Davi130 parcellation across both hemispheres that were significantly associated with age after family-wise error (FWE) correction for multiple testing (Figure 4 and Figure 4—source data 1). Specifically, GM decline with age was found bilaterally in the superior frontal gyrus (SFG), posterior middle frontal gyrus (pMFG), posterior inferior frontal gyrus (pIFG), lateral orbitofrontal cortex (lOFC), middle and inferior precentral gyrus (PrCG), cingulate gyrus (ACC, MCC, PCC), posterior superior temporal gyrus (pSTG), anterior middle temporal gyrus (aMTG), precuneus (PCun), and lingual gyrus (LG) as well as unilaterally in the right anterior insula (aIns) and middle inferior frontal gyrus (mIFG), in addition to the left superior precentral gyrus (sPrCG), anterior transverse temporal gyrus (aTTG), posterior transverse temporal gyrus (pTTG), paracentral lobule (PCL) and the area around the calcarine sulcus (Calc) within the cerebral cortex. Subcortically, age-related GM decline was found in the bilateral putamen (Pu), caudate nucleus (CN), and the nucleus accumbens (NA), as well as in the superior cerebellum (CerVI, CerIV, CerVA, Cer VB, CerIV and right CrusII). Finally, to test for more fine grained effects of aging independently of our macroanatomical parcellation, the same sample was analyzed with VBM revealing additional clusters of GM that are significantly affected by age in chimpanzees (Figure 5) after FWE correction using threshold-free cluster enhancement (TFCE) (Smith and Nichols, 2009). On top of the regions identified by region-wise morphometry, we found extensive voxel-wise effects throughout the orbitofrontal cortex (OFC), inferior temporal gyrus (ITG), transverse temporal gyrus (TTG), frontal operculum (FOP), parietal operculum (POP), postcentral gyrus (PoCG), supramarginal gyrus (SMG), angular gyrus (AnG), and in parts of the superior parietal lobule (SPL), superior occipital gyrus (sOG), and in inferior parts of the cerebellum. Figure 4 Download asset Open asset Region-wise morphometry in the Davi130 parcellation age regression. Red regions represent Davi130 regions that remained significant at p≤0.05 following FWE correction (Holm method). The T-statistic and p-value for all Davi130 labels can be found in Figure 4—source data 1. 1 and 2 – aSFG, 3 and 4 – mSFG, 5 and 6 – pSFG, 9 and 10 – pMFG, 14 – mIFG, 15 and 16 – pIFG, 19 and 20 – lOFC, 21 and 22 – ACC, 23 and 24 – MCC, 25 and 26 – PCC, 27 – sPrCG, 29 and 30 – mPrCG, 31 and 32 – iPrCG, 33 – PCL, 40 – aIns, 43 – aTTG, 49 and 50 – pSTG, 51 and 52 – aMTG, 83 and 84 – PCun, 85 – Cun, 87 and 88 – LG, 89 and 90 – Calc, 97 and 98 – CN, 99 and 100 – NA, 103 and 104 – Pu, 118 – CrusII, 119 and 120 – CerVI, 121 and 122 – CerVB, 123 and 124 – CerVB, 125 and 126 – CerIV. Figure 4—source data 1 Aging effect on gray matter in complete Davi130 Labels. https://cdn.elifesciences.org/articles/60136/elife-60136-fig4-data1-v2.docx Download elife-60136-fig4-data1-v2.docx Figure 5 with 1 supplement see all Download asset Open asset Voxel-based morphometry of aging on GM volume. The significant clusters are found using TFCE with FWE correction at p≤0.05. Hemispheric asymmetry of the chimpanzee brain was assessed for each cortical Davi130 region with a total of 68% (44/65) exhibiting significant cortical asymmetry after FWE correction (Figure 6 and Figure 6—source data 1). The majority of regions were found with greater GM volume in the right hemisphere (n = 32) as compared to the left (n = 12). In the left hemisphere, we found more GM in the SFG, pMFG, insula, anterior TTG, and PCun within the cortex. Rightward cortical asymmetry was located in the anterior MFG, middle and posterior IFG, medial OFC, cingulate gyrus, amygdala, STG, MTG, posterior TTG, anterior and posterior fusiform gyrus (FFG), FOP, POP, middle PrCG, middle and inferior PoCG, SMG, AnG, Calc, as well as the middle occipital gyrus. Within the basal ganglia, leftward GM asymmetry was observed in the Pu, nucleus accumbens (NA), basal forebrain nucleus (BF), and globus pallidus (GP), while, rightward asymmetry in the caudate nucleus (CN) and thalamus (Th). The cerebellum exclusively showed rightward GM asymmetry in the posterior cerebellar lobe (CerIX, CerVIII, CrusI, CrusII, CerVI). The hemispheric asymmetry did not show a decipherable pattern. Figure 6 Download asset Open asset Hemispheric asymmetry of Davi130 regions within the chimpanzee sample. Significant leftward (red) and rightward (green) asymmetrical regions are those with a p≤0.05 after FWE correction. The T-statistic and p-value for all Davi130 labels can be found in Figure 6—source data 1. 1 – aSFG, 3 – mSFG, 5 – pSFG, 8 – aMFG, 9 – pMFG, 12 – aIFG, 14 – mIFG, 16 – pIFG, 18 – mOFC, 22 – ACC, 24 – MCC, 26 – PCC, 30 – mPrCG, 36 – FOP, 38 – POP, 39 – aIns, 41 – pIns, 43 – aTTG, 46 – pTTG, 48 – aSTG, 50 – pSTG, 52 – aMTG, 54 – pMTG, 62 – aFFG, 64 – pFFG, 74 – mPoCG, 76 – iPoCG, 80 – SMG, 82, AnG, 83 – PCun, 90 – Calc, 94 – mOG, 98 – CN, 101 – BF, 103 – Pu, 108 – Th, 112 – CerIX, 114 – CerVIII, 115 –CrusI, 118 –CrusII, 120 – CerVI. Figure 6—source data 1 Complete Davi130 labels hemispheric asymmetry. https://cdn.elifesciences.org/articles/60136/elife-60136-fig6-data1-v2.docx Download elife-60136-fig6-data1-v2.docx Discussion As a common reference space for the analysis of chimpanzee brain data, we created the Juna.Chimp template, constructed from a large heterogeneous sample of T1w MRI’s from the NCBR. The Juna.Chimp template includes a reference T1-template, along with probability maps of brain and head tissues accompanied by a Geodesic Shooting template for the publicly available SPM12/CAT12 preprocessing pipeline to efficiently segment and accurately spatially normalize individual chimpanzee T1w images. The T1-template and TPM can also be used as the target for image registration with other popular software packages, such as FSL (https://fsl.fmrib.ox.ac.uk/fsl) or ANTs (http://stnava.github.io/ANTs/). Furthermore, our processing pipeline and templates can be utilized for data-driven approaches to create connectivity-based and structural covariance parcellations of the chimpanzee brain (Alexander-Bloch et al., 2013; Eickhoff et al., 2015). Additionally, we provide the manually segmented, macro-anatomical Davi130 whole-brain parcellation comprising 130 cortical, sub-cortical and cerebellar brain regions, which enables systematic extraction of volumes-of-interest from chimpanzee MRI data. The image processing pipeline and Davi130 parcellation were used to investigate ageing and interhemispheric asymmetry in the chimpanzee brain. The Davi130 parcellation was realized by utilizing macroscopic gyral and sulcal features such as peaks, fundi, and bends to represent the chimpanzee brain in a reduced dimensional space based on macro-anatomical landmarks. Despite the evidence that true microanatomical borders between brain areas rarely coincide with macro-anatomical patterns (Amunts and Zilles, 2015), macroscopic brain parcellations like human et al., have utilized in many studies our of brain and disease (Kong et al., et al., The Davi130 parcellation of the chimpanzee brain two regions in Juna.Chimp template space enable and of analyses and between studies, even our manual the statistical of multiple testing for approaches like VBM to brain - Furthermore, our macroscopic parcellation the of for methods to be applied to the relatively like the NCBR. found evidence of and local GM decline in the aging chimpanzee brain even though previous into age-related in chimpanzee brain organization has shown to no effect (Herndon et al., 1999; Sherwood et al., 2011; Chen et al., 2013; Autrey et al., 2014). (Herndon et al., 1999; Sherwood et al., 2011; Chen et al., 2013; Autrey et al., 2014). This can be on the to the of MRI scans available via the including of older subjects with 55 30 and 12 years of age, which is crucial for the effect of aging et al., 2013; Autrey et al., 2014). On the other state-of-the-art image processing the creation of the species-specific Juna.Chimp templates, which tissue and registration (Ashburner and Friston, registration was also by the large heterogeneous sample utilized for the creation of the templates a of used the structural brain imaging toolbox CAT12 to a chimpanzee preprocessing pipeline local as with T1w The region-wise and the voxel-wise morphometry analysis showed GM decline in lateral frontal lOFC, precentral gyrus, cingulate gyrus, PCun, medial parietal and occipital the basal ganglia, and superior cerebellum. The VBM approach evidence for age effects in bilateral mOFC, PoCG, inferior temporal regions, inferior and superior lateral parietal and throughout the cerebellum. additional effects can be as VBM is more to GM due to aging et al., 2009). The multiple brain regions revealing GM decline reported in both approaches have also shown to exhibit GM atrophy during aging in humans et al., et al., et al., 2014; et al., 2017). Additionally, there was no significant in the age-related decline between humans and chimpanzee (Figure even though a negative correlation with less variance was found in the matched human sample, which a in the aging process of chimpanzees that was thought to be to humans. In GM atrophy in chimpanzees across the sub-cortical regions, and local areas decline at a relative within the and parietal lobes et al., 2014). Davi130 regions within the frontal lobe MFG, IFG, and have reported in human in to GM volume decline due to aging et al., et al., 2014; et al., 2014; et al., 2017). Furthermore, aging effects in temporal and parietal AnG, regions in chimpanzees have revealed in human areas et al., et al., et al., 2014; et al., 2014; et al., 2017). The same is true for the superior occipital gyrus and caudate nucleus et al., 2014). Similar age-related total GM decline along with in brain areas common processes in humans and chimpanzees due to shared primate evolution. has shown that with age in chimpanzees, a process thought to in humans, which can GM volume decline et al., This further the that age-related GM decline is also shared by humans closest the Furthermore, Edler et al., 2017 found Alzheimer’s of amyloid beta and neurofibrillary tangles located in and temporal in a sample of chimpanzees between and 62 years of age. As the of these is associated with and cortical atrophy in humans et al., 2012; et al., the age-related decline in GM volume shown is well in with the by GM atrophy with amyloid provide a for GM in and temporal found in chimpanzees. In show GM volume decline the of neurofibrillary tangles et al., 2008; et al., GM atrophy to be a common aspect of the primate brain aging observed in chimpanzees, and humans. To make a for the of Alzheimer’s disease in chimpanzees, cognitive for cognitive decline in non-human primates are to test for direct between cognitive decline with and brain To further the effects on we the of the sample, with to the rearing The majority of chimpanzees 40 years were in the and at a age, chimpanzees 40 were The from and to the can be a with effects on brain development and In captivity, different by or in a has shown to brain et al., 2014; and Hopkins, 2018). The same be in comparison of and chimpanzees. The distribution of rearing and life our analyses of the effect of aging on GM volume. we have some to be that the aging effect shown is not by these as rearing environment was as a to all age regression models and the VBM age regression model with and rearing as a are almost (Figure 5 and Figure supplement 1 the GM decline we found is and also present in chimpanzees 30 years of age are Hemispheric asymmetry was found in 68% (44/65) of all regions of the Davi130 parcellation, reported in previous studies using image processing methods as well as population-level Previous studies utilizing a region-wise approach based on or regions to asymmetry in cortical also reported leftward asymmetry of the insula (Hopkins et al., 2017) and rightward of cortical of the (Hopkins et al., 2017) as well as STG, MTG, and (Hopkins and 2013). Previous VBM also revealed leftward asymmetry in the anterior (Hopkins et al., along with rightward of the MFG, PrCG, PoCG, mOG, and (Hopkins et al., 2008; Hopkins and 2013). In the study, regions of GM volume in the left hemisphere were found in frontal mSFG, temporal (aTTG), and parietal as well as in the basal rightward asymmetries could also be in the frontal mOFC, temporal parietal and occipital (Calc) the basal and the cerebellum CerIX, CerVI, The region which the presented significant rightward while previous studies of the have shown leftward asymmetry in chimpanzee GM area (Hopkins and Nir, and (Zilles et al., et al., Spocter et al., A for the divergence in this is that the anterior of (Hopkins and Nir, posterior from the anterior posterior split of the Davi130 Additionally, the left lateral sulcus in the Juna.Chimp template to further and compared to the which is with previous in asymmetrical of the in chimpanzees and Hopkins, 2013) and in et al., 2011; et al., 2018). asymmetries in the in chimpanzees were documented almost two decades ago by and Hopkins, reported a leftward asymmetry in volume in a sample of In studies, this could not be GM volume (Hopkins et al., 2008; et al., or et al., also to find a leftward asymmetry in GM volume for the pIFG, in to asymmetries found in humans (Amunts et al., 1999; et al., et al., 2009). A of regions significant differences of local in chimpanzees has also shown in humans et al., et al., 2014; et al., 2018). Specifically, leftward has found in human regions of the and insula utilizing GM and volume in voxel-wise and region-wise approaches et al., et al., 2011; et al., 2014; et al., 2018). Rightward asymmetry in the Davi130 regions IFG, STG, MTG, AnG, mOG, Calc, in addition to the thalamus and lateral cerebellum is documented in the human brain also using both VBM and et al., et al., 2011; et al., 2014; et al., 2018). hemispheric asymmetry in humans a general of frontal rightward and occipital leftward asymmetry as the and This general of asymmetry was not in the chimpanzee et al., 2018). The the largest and openly available dataset of chimpanzee brain MRI scans a with 1.5T and 3T MRI at two in large heterogeneous sample. To for the scanner effect on GM field strength was as a of no for the age effect on GM volume. The of this study was the analysis of GM even though the

Topic: Primate Behavior and Ecology
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences