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. Author manuscript; available in PMC: 2024 Jun 1.
Published in final edited form as: Neurobiol Aging. 2023 Feb 23;126:91–102. doi: 10.1016/j.neurobiolaging.2023.02.008

Age Differences in Cortical Thickness and their Association with Cognition in Chimpanzee (Pan troglodytes)

William D Hopkins 1, Xiang Li 2, Neil Roberts 2, Michele M Mullholland 1, Chet C Sherwood 3, Melissa K Edler 4, Mary Ann Raghanti 4, Steven J Schapiro 1,5
PMCID: PMC10106435  NIHMSID: NIHMS1884878  PMID: 36958104

Abstract

Humans and chimpanzees are genetically similar and share a number of life history, behavioral, cognitive and neuroanatomical similarities. Notwithstanding, our understanding of age-related changes in cognitive and motor functions in chimpanzees remains largely unstudied despite recent evident demonstrating that chimpanzees exhibit many of the same neuropathological features of Alzheimer’s disease observed in human postmortem brains. Here, we examined age-related differences in cognition and cortical thickness measured from magnetic resonance images in a sample of 215 chimpanzee ranging in age between 9 and 54 years. We found that chimpanzees showed global and region-specific thinning of cortex with increasing age. Further, within the elderly cohort, chimpanzees that performed better than average had thicker cortex in frontal, temporal and parietal regions compared to chimpanzees that performed worse than average. Independent of age, we also found sex differences in CT in four brain regions. Males had higher adjusted CT scores for the caudal anterior cingulate, rostral anterior cingulate, and medial orbital frontal while females had higher values for the inferior parietal cortex. We found no evidence that increasing age nor sex was associated with asymmetries in cortical thickness. Moreover, age-related differences in cognitive function were only weakly associated with asymmetries in cortical thickness. In summary, as has been reported in humans and other primates, elderly chimpanzees show thinner cortex and variation in cortical thickness is associated with general cognitive functions.

Keywords: Chimpanzees, Cortical Thickness, Aging, Cognition, Asymmetry

Introduction

One remarkable feature of humans is our lifespan; humans can live more than 100 years compared to approximately 50 to 60 years in one of our closet living relatives, the chimpanzee (Bronikowski et al., 2011). The duration of the post-reproductive lifespan is particularly significant, as humans can live more than 30 years beyond the period of their reproductive cessation compared to other nonhuman primates (Alvarez, 2000; Hawkes, 2003; Hawkes and Coxworth, 2013; Herndon, 2009), including chimpanzees which is estimated to be a maximum of 5 years (Havercamp et al., 2019; Judge and Carey, 2000; Levitis et al., 2013). In short, humans have remarkable potential longevity during the post-reproductive phase of life which may contribute to our species’ vulnerability to a variety of maladies associated with increasing age, notably neurodegenerative disorders including Alzheimer’s disease (AD) and related forms of dementia (Finch, 2010; Walker and Jucker, 2017).

Many studies have examined age-related changes in cognition in nonhuman primates with aged individuals generally performing significantly worse on measures of learning and memory compared to younger adult individuals (Herndon et al., 1997; Joly et al., 2014; King and Michels, 1989; LaClair and Lacreuse, 2016; Lacreuse et al., 1999; Moss et al., 1988; Munger et al., 2017; Nagahara et al., 2010; Picq, 2007; Rapp and Amaral, 1989, 1992; Workman et al., 2019). Similarly, a number of investigations of postmortem brains have described neuropathological and structural changes in the brains of aged nonhuman primates compared to those of younger individuals (Elfenbein et al., 2007; Frye et al., 2020; Hara et al., 2012; Heuer et al., 2017; Rosen et al., 2011; Schultz et al., 2000; Uno and Walker, 1993). Similarly, investigators have used in vivo neuroimaging to document age-related changes in whole brain gray and white matter volume, gyrification and cortical thickness in monkeys (Alexander et al., 2008; Chen et al., 2013; Koo et al., 2012; Matochik et al., 2000).

One group of nonhuman primates that has received considerably less attention in studies on the comparative biology of aging are great apes (chimpanzees, bonobo, gorillas and orang-utans). Besides their greater genetic similarity to humans compared to other nonhuman primate species, recent studies have documented cross-sectional and longitudinal changes in cognition and motor skill in chimpanzees (Hopkins et al., 2021a; Hopkins et al., 2015; Lacreuse et al., 2018; Lacreuse et al., 2014; Manrique and Call, 2015). Studies also have demonstrated the co-occurrence of both neurofibrillary tangles (NFT) and amyloid-beta plaques (Aβ) in elderly chimpanzee postmortem brains (Cramer et al., 2018; Edler et al., 2017; Gearing et al., 1994; Perez et al., 2013; Rosen et al., 2008). The presence of both Aβ plaques and NFT is used to definitively confirm a diagnosis of AD in humans. Though other aged nonhuman primate species develop either Aβ or NFTs, not many are jointly expressed in postmortem brains to the extent seen in chimpanzees. One important distinction between humans and chimpanzees is the absence of overt neuron loss that typically accompanies AD pathology in humans, which suggests that these lesions are not as toxic to the chimpanzee brain. Though important differences exist between humans and chimpanzees in regards to neuropathology and the brain’s astrocyte and microglial activation in response (Edler et al., 2020), chimpanzees appear to be the only known species to naturally develop a homolog to human-like AD pathology, and further studies of the similarities and differences in aged primates could lead to important findings that will help improve the efficacy of therapeutic AD models (Edler et al., 2018; Munger et al., 2018; Rosen et al., 2016).

Previous reports in chimpanzees have also identified small to moderate age-related changes in total brain volume, frontal lobe volume, white matter volume, gray matter cortical gyri and sulci thickness (Autrey et al., 2014; Chen et al., 2013; Herndon et al., 1999; Sherwood et al., 2011). Moreover, two recent reports demonstrated age-related loss in gray matter volume in elderly chimpanzees compared to middle-aged and younger individuals using voxel-based morphometry (Lacreuse et al., 2020; Vickery et al., 2020); however, to date, only a single study reported age-related changes in cortical thickness (CT) in chimpanzees. Specifically, Hopkins et al. (2019) reported that whole brain CT was negatively associated with increasing age. One limitation of the Hopkins et al. (2019) paper was the inclusion of only a few old apes (only 7 individuals over 40 years of age), and the analyses focused on whole brain rather than region-specific changes in CT with age. Here, we sought to expand on these previous findings in chimpanzees in two ways. First, we sought to examine age-related changes of CT in a larger cohort of chimpanzees with a greater number of elderly individuals. Specifically, in this study, measures of CT were obtained in an additional 138 chimpanzees and when combined with the data from Hopkins et al. (2019) resulted in a total sample of 225 subjects. Further, within the new cohort of 138 chimpanzees, there were 28 chimpanzees over the age of 40 years which was a three-fold increase in elderly chimpanzees with the total sample. Second, the previous study by Hopkins et al. (2019) focused only on whole brain measures of cortical thickness. In this study, we expanded the analyses to allow for testing of region-specific differences in CT among age groups after adjustment for whole brain cortical thickness. Based on previous studies in human and nonhuman primates, we hypothesized that older chimpanzees would show smaller CT than middle-aged and young chimpanzees.

We also tested for age group differences in CT asymmetries in the chimpanzee sample. In humans, it has been hypothesized that increasing age is associated with changes in functional and anatomical asymmetries, particularly in brain regions that play a role in cognitive and motor functions that decline in elderly populations (Dolcos et al., 2002; Donix et al., 2013; Kong et al., 2018; Roe et al., 2020; Roe et al., 2021). Whether nonhuman primates show age-related differences in CT asymmetries or any other measures of lateralization remains largely unknown and untested (Marie et al., 2018; Rogers, 2021; Spocter et al., 2020). Indeed, we know of no studies that have reported age-related changes in lateralization in cerebral structure or function in nonhuman primates, particularly between elderly individuals and adults. Thus, this analysis is the first of its kind in nonhuman primates. To test for age differences in CT, structural MRI scans were obtained in a sample of pedigreed captive chimpanzees, and following previously described methods (Hopkins et al., 2017), we used an automated pipeline program in Freesurfer to extract cortical thickness measures from 34 neocortical regions (see Figure 1). The cortical thickness for each region was then compared among chimpanzees from different age groups. Based on previous studies in human and nonhuman primates, we hypothesized that cortical thickness would differ between aged and younger adult chimpanzees. If asymmetries in CT are associated with aging, then we further hypothesized that significant differences would be found between age groups.

Figure 1:

Figure 1:

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Three-dimensional rendering of the chimpanzee brain with Desikan-Killany atlas maps projected onto the surface.

Finally, we tested for associations between CT and individual differences in general cognitive abilities in the chimpanzees. Specifically, in humans, a number of studies have reported significant associations between global and region-specific CT and general intelligence (Bajaj et al., 2018; Habeck et al., 2020; Menary et al., 2013). As noted above, previous studies in chimpanzees reported a quadratic association between age and overall cognitive performance with young and elderly chimpanzees performing more poorly than middle-aged apes (Hopkins et al., 2021a). Here, we measured general cognitive abilities using the Primate Cognition Test Battery (PCTB), a 13-item set of tasks designed to assess social and physical cognition (Herrmann et al., 2007; Herrmann et al., 2010; Hopkins et al., 2014; Lacreuse et al., 2014; Russell et al., 2011). In this study, based on their weighted average performance across all PCTB tasks, chimpanzees were classified as performing above or below average. We then compared cortical thickness measures between these two groups across age groups. We hypothesized that significant differences in CT would be found between chimpanzees based on their task performance, and these differences would be the greatest in the elderly chimpanzees.

Methods and Materials

Subjects

Magnetic resonance images (MRI) were obtained from 215 captive chimpanzees from the Emory University National Primate Research Center (ENPRC, n = 77, formerly known as Yerkes) and the National Center for Chimpanzee Care (NCCC, n = 138), which is part of The University of Texas MD Anderson Cancer Center. The study included 131 females and 84 males ranging from 9 to 54 years of age (Mean = 27.05 years, SD = 10.51). Within this sample, we operationally defined three age groups of adults including young (9 to 20 years, n = 65), middle-aged (21 to 35 years, n = 106) and geriatric (=> 36 years, n = 44) at the time of the MRI scans. Within this sample, cognition data were available in 192 individuals including 72 males and 120 females, and of these, there were 59 young, 96 middle-aged, and 37 elderly chimpanzees. All procedures performed with the chimpanzees were approved by the local Institutional Animal Care and Use Committees and followed all recommendations by the Institute of Medicine and NIH policy for the ethical treatment of chimpanzees in research.

MRI Image Collection

In vivo scans were obtained at the time the chimpanzees were surveyed for their annual physical examinations beginning in 1998 and continuing until 2014 when policy changes at the National Institutes of Health were implemented which forbid collections of MRI scans for research purposes. Subjects were first immobilized by ketamine (10 mg/kg) or telazol (3-5mg/kg) and subsequently anesthetized with propofol (40–60 mg/(kg/h)) following standard procedures at the ENPRC and NCCC facilities. ENPRC subjects were transported to the MRI facility, while NCCC subjects were wheeled to the mobile imaging unit. The subjects remained anesthetized for the duration of the scans and transport to and from their home cage and the imaging facility (~5-10 minutes) or mobile imaging unit (~5 minutes). Subjects were placed in the scanner chamber in a supine position with their head fitted inside the human-head coil. Scan duration ranged between 40 and 60 minutes as a function of brain size and scanning sequence. Seventy-seven chimpanzees were scanned using a 3.0 Tesla scanner (Siemens Trio, Siemens Medical Solutions USA, Inc., Malvern, Pennsylvania, USA) at ENPRC. T1-weighted images were collected using a three-dimensional gradient echo sequence (pulse repetition= 2300 ms, echo time = 4.4 ms, number of signals averaged = 3, matrix size = 320 X 320). The remaining 138 chimpanzees from NCCC were scanned using a 1.5T G.E. echo-speed Horizon LX MR scanner (GE Medical Systems, Milwaukee, Wisconsin, USA). T1-weighted images were collected in the transverse plane using a gradient echo protocol (pulse repetition = 19.0 ms, echo time = 8.5 ms, number of signals averaged = 8, matrix size = 256 x 256, with 0.7 x 0.7 x 1.2 resolution).

Post-Image Processing

A pipeline integrating FSL (version 5.0.9, http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/) and FreeSurfer (version 6.0, https://surfer.nmr.mgh.harvard.edu/) was performed to all MR images. First, the brain volume images were skull stripped, bias field corrected and normalized using 7 degrees of freedom (7 DOF) transformation including 3 translations, 3 rotations, and 1 uniform scaling in FSL. The normalization step registered all chimpanzee brain volume images to the standard human MNI152 template while preserving the morphology of the brain. Second, the pre-processed brain scans were subsequently put through the standard FreeSurfer streamline (Dale, 1999). Specifically, a volumetric analysis was performed to label the white matter respectively for the left and right cerebral hemispheres. Then, a triangular mesh that tightly covers each white matter component, also known as the white matter surface, was generated and deformed with respect to the intensity gradients between the white and gray matter. The white matter surface was further expanded along the direction of the intensity gradients between the gray matter and the cerebrospinal fluid (CSF), until it coincided with the gray matter surface (i.e., pial surface).

Region-based Brain Measurement Computation

The regional measurement of the brain was computed based on the method described by Xiang et al. (2020) which was shown to be less prone to the inherent bias in the cerebral surface parcellation atlases. In brief, the method first identified the vertex-wise inter-hemispheric correspondence by co-registering both cerebral hemisphere surfaces of individual subjects to a symmetric registration atlas (i.e., lh.fsaverage_sym) (Greve et al., 2013). Thereby, the regional label of the left side of parcellation atlas can be projected to both the left and the contralateral cerebral hemisphere. For each region-of-interest (ROI), the value of brain measurement was computed respectively for the left and right cerebral hemispheres for individual subjects. In particular, at each ROI, the cortical thickness was computed as the mean of the values of all vertices belonging to the region. To account for potential bias derived from the choice of the parcellation atlas (i.e. left or right atlas), the same procedure above was repeated but using the right side of the registration and parcellation atlases. The value of brain regional measurement for individual subjects is therefore averaged between the results obtained respectively based on both atlases. The Desikan-Killany atlas (Desikan et al., 2006; Destrieux et al., 2010) in FreeSurfer was considered as the cerebral surface parcellation atlas, because it was shown to provide high quality parcellation results for the chimpanzee brain (Hopkins et al., 2017; Xiang et al., 2020) (see Figure 1).

Primate Cognition Test Battery (PCTB)

The PCTB is a set of 13 tasks used to assess overall and domain-specific physical and social cognition abilities as previously described in detail (Herrmann et al., 2007; Herrmann et al., 2010; Hopkins et al., 2021a; Lacreuse et al., 2014). Shown in Table 1 is a brief description of each PCTB task and the cognitive constructs they presumably measure. To quantify individual variation in cognition, performance on each task was converted to a standardized z-score within the NCCC and ENPRC chimpanzee cohorts. PCTB data were standardized within each colony because, overall, the NCCC chimpanzees performed significantly better than the ENPRC apes. The z-scores were then averaged across all tasks for each subject which created a unit weighted average (UWA) score. Subjects with positive or negative UWA scores were considered performing above or below the average for all subjects within the cohort. As noted above, we have previously reported that there was a significant quadratic relationship between age and PCTB performance in the NCCC and ENPRC cohorts (Hopkins et al., 2021a). Thus, young and elderly chimpanzees performed more poorly than middle-aged individuals. To adjust the UWA performance scores to account for their age at the time they were tested (which differed from the time at which they were scanned), we regressed the chimpanzee quadratic ages on their UWA scores and saved the unstandardized residuals. These residuals reflected the extent that each chimpanzee performed better or worse than would be predicted for their chronological age. Chimpanzees with negative residuals were classified as performing worse than average (WTA), while individuals with positive residual were classified as performing better than average (BTA). In all subsequent tests, we compared CT measures between the WTA and BTA chimpanzees within each age group. We note here that the time between the acquisition of the MRI scans and when each chimpanzee was tested on the PCTB tasks differed, on average, by 2.34 years (s.d. = 1.97).

Table 1:

13 Task Comprising the PCTB, Number of Items and Trials (Based on Herrmann et al. 2007)

Physical Cognition
   Spatial Memory Location of hidden baited reward (1 item, 3 trials)
   Object Permanence Tracking of reward atter invisible displacement (3 items, 9 trials)
   Rotation Tracking location of reward after rotation (3 items,9 trials)
   Transposition Tracking rewards after location changes (3 items, 9 trials)
   Quantify Discrimination Discriminate quantity (1 item, 13 trials)
   Causality (Noise) Causal understanding of produced noise by hidden rewards (2 items, 6 trials)
   Causality (Visual) Causal understanding of appearance change by hidden rewards (2 items, 6 trials)
   Tool Use Use a lollipop stick to retrieve out of reach food (1 item, 2 trials)
   Tool Comprehension Understanding of functional and nonfunctional tool properties (5 items, 15 trials)
Social Cognition
   Comprehension Understanding communicative cues to select hidden food location (3 items, 9 trials)
   Production Producing communicative gestures in order to receive hidden food (1 item, 4 trials)
   Attention State Using communicative signals according to attention state of audience (4 items, 4 trials)
   Gaze Following Following an experimenters gaze direction toa target (3 items, 9 trials)
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Note that each chimpanzee was tested twice on the PCTB tasks; thus, for the performance measures in this study, the number of trials administered to each subjects was twice as many as reported in the Table.

Data Analysis

A preliminary analysis revealed that whole brain cortical thickness differed significantly among age groups with elderly chimpanzees (F(2, 207) = 6.343, p = 0.002; Mean = 1.299 mm, s.e. = 0.023) having thinner values than middle-aged (Mean = 1.372 mm, s.e. = 0.022) and young apes (Mean = 1.405 mm, s.e. = 0.014). To determine whether age differences in CT were region specific, independent of these whole brain values, we computed adjusted average cortical thickness (ACT) measures for each of the 34 ROIs. For this calculation, the average value for each ROI was subtracted from the mean whole brain CT value to create a difference score. Within each ROI, positive and negative difference scores reflected whether subjects had cortical thickness scores that were greater or lesser than average for their entire brain. Asymmetry quotients (AQ) were also computed following the formula [AQ=(L − R) / ((L + R) * 0.5)] where R and L reflected the right and left hemisphere raw, unadjusted CT thickness value for each ROI. Positive values indicated leftward biases and negative values indicated rightward biases. Statistical analyses were performed using multiple analysis of covariance (MANCOVA) with scanner magnet, rearing experience and the duration of time between PCTB testing and the collection of the MRI scans serving as covariates, ROI as the repeated measures, and sex and age groups as between group factors. Alpha was set to p < .05 and any post-hoc tests needed were performed using Tukey’s Honestly Significant Difference (HSD) test.

Results

Average and Asymmetry in Cortical Thickness

The mixed model analysis of covariance revealed significant two-way interactions between brain region and age group F(66,6831) = 2.773, p < 0.001 and brain region and sex F(33, 6831 )= 4.897, p < 0.001. Figures 2 and 3 show the mean adjusted cortical thickness values for each brain region between age groups and sexes. Post-hoc analysis of the age group by brain region interaction revealed significant age differences for 13 regions. For 12 brain regions (bank of STS, caudal middle frontal, isthmus of the cingulate, paracentral, pars opercularis, pars orbitalis, precentral, superior frontal, superior temporal, supramarginal, transverse temporal, and insula), elderly chimpanzees had lower adjusted CT values compared to middle-aged and young chimpanzees who did not differ significantly from each other. For one brain region (rostral middle frontal), middle-aged chimpanzees had higher values than young apes but not elderly apes. Regarding sex differences, males had higher adjusted CT scores for three brain regions (caudal anterior cingulate, rostral anterior cingulate, and medial orbital frontal), and females had higher values for one area (inferior parietal). With respect to the AQ values, the mixed model analysis of covariance failed to reveal any significant main effects or interactions, though the main effect for age group approached conventional levels of statistical significance F(2, 207) = 2.991, p = 0.052. As can be seen in Figure 4, middle-aged and elderly chimpanzees had greater rightward AQ values than young chimpanzees.

Figure 2:

Figure 2:

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Mean-adjusted cortical thickness (CT) values (+/− s.e.) in young (blue), middle-aged (red), and elderly (black) chimpanzees. ** indicates that elderly chimpanzees had significantly lower adjusted CT values compared to middle-aged and young chimpanzees who did not differ significantly from each other based on Bonferroni post-hoc test. *** indicates that Bonferroni post-hoc test revealed that middle-aged chimpanzees had significantly higher CT values than young apes but not elderly apes.

Figure 3:

Figure 3:

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Mean-adjusted cortical thickness (CT) values (+/− s.e.) in male (red) and female (blue) chimpanzees. * indicates males have significantly higher than average adjusted CT compared to females. ** indicates females have significantly higher than average adjusted CT than males.

Figure 4;

Figure 4;

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Mean cortical thickness AQ scores (+/− s.e.) in young, middle-aged and elderly chimpanzees.

Cognitive Correlates of Cortical Thickness in Different Age Groups

Two mixed model analyses of covariance were performed with sex, age group and PCTB performance (WTA, BTA) serving as between-group factors and adjusted average CT or CT AQ values for each ROI serving as the repeated measure. Scanner magnet, rearing, and difference in the number of years between administration of the PCTB tests and the acquisition of the MRI scans were the covariates. Of specific interest were any main effects or interactions that involved the PCTB variable. For analysis of the adjusted average CT values, there was a significant main effect for PCTB performance F(1,179) = 5.564, p = 0.019 with BTA chimpanzees having higher adjusted average CT values than WTA apes. There was also a significant two-way interaction between age group and PCTB performance F(2,179) = 5.039, p = 0.007. The mean adjusted average CT scores for WTA and BTA chimpanzees within each age group is shown in Figure 5. Post-hoc analysis of the interaction term indicated that BTA chimpanzees had significantly higher CT values than WTA apes within the elderly group. By contrast, no significant differences in adjusted average CT values were found between the WTA and BTA apes in the middle-aged or young cohorts.

Figure 5:

Figure 5:

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Mean-adjusted cortical thickness values (+/− s.e.) in better than average (BTA) and worse than average (WTA) chimpanzees by each age group.

For analysis of the AQ CT data, significant three-way interactions were found between age class, PCTB performance, and brain region F(66,5874) = 1.598, p = 0.002 and between sex, PCTB group, and brain region F(33,5874) = 2.597, p < 0.001. The mean CT AQ values for WTA and BTA chimpanzees within the young, middle-aged, and elderly group are shown in Table 2. Post-hoc testing indicated age group by PTCB group interactions for 4 brain regions including the isthmus of the cingulate, paracentral, precentral, and rostral anterior cingulate cortex. For the rostral anterior cingulate and paracentral cortex, elderly BTA chimpanzee had greater rightward asymmetries than WTA apes. No significant differences between BTA and WTA apes were found for these regions within the young and middle-aged groups. For the isthmus of the cingulate, elderly BTA chimpanzees showed significantly greater leftward asymmetries than WTA individuals, while no significant differences in CT values were found within the middle-aged and young apes. For the precentral gyrus, WTA chimpanzees had greater rightward asymmetries than BTA individuals within the young group, while no significant differences were found between WTA and BTA apes within the middle-aged and elderly groups.

Table 2:

Mean AQ Values (+/− s.e.) for WTA and BTA Chimpanzees in Each Age Group

Brain Region Young Middle-
Aged		 Elderly
WTA s.e. BTA s.e WTA s.e. BTA s.e. WTA s.e. BTA s.e.
Bank STS −0.01 0.02 −0.03 0.02 −0.03 0.02 −0.02 0.02 −0.07 0.03 −0.02 0.05
Caudal Anterior Cingulate 0.07 0.03 0.07 0.02 0.07 0.02 0.07 0.02 0.08 0.04 0.10 0.06
Caudal Middle Frontal 0.02 0.02 0.01 0.02 0.01 0.02 0.00 0.02 0.01 0.03 −0.01 0.04
Cuneus 0.00 0.01 −0.03 0.01 −0.03 0.01 −0.02 0.01 −0.02 0.02 −0.01 0.03
Entorhinal 0.04 0.03 −0.01 0.02 −0.01 0.02 −0.04 0.02 0.04 0.04 0.00 0.06
Fusiform −0.03 0.01 −0.02 0.01 −0.02 0.01 −0.05 0.01 −0.01 0.02 −0.03 0.03
Inferior Parietal 0.00 0.02 −0.03 0.01 −0.03 0.01 −0.02 0.01 0.00 0.02 −0.02 0.03
Inferior Temporal −0.03 0.02 −0.02 0.01 −0.02 0.01 −0.04 0.01 0.02 0.02 −0.06 0.03
Isthmus Cingulate −0.05 0.03 0.00 0.02 0.00 0.02 0.01 0.02 −0.07 0.04 0.12 0.06
Lateral Occipital −0.03 0.01 −0.04 0.01 −0.04 0.01 −0.04 0.01 −0.02 0.02 −0.03 0.03
Lateral Orbital −0.03 0.01 −0.02 0.01 −0.02 0.01 −0.03 0.01 −0.02 0.02 0.04 0.03
Lingual −0.03 0.01 0.00 0.01 0.00 0.01 −0.04 0.01 −0.02 0.02 0.01 0.03
Medial Orbital 0.04 0.02 0.01 0.02 0.01 0.02 0.03 0.02 0.06 0.03 0.00 0.05
Middle Temporal −0.01 0.01 −0.04 0.01 −0.04 0.01 −0.03 0.01 −0.05 0.02 −0.05 0.03
Parahippocampal −0.02 0.02 −0.03 0.02 −0.03 0.02 −0.04 0.02 −0.03 0.03 −0.05 0.04
Paracentral −0.01 0.01 −0.05 0.01 −0.05 0.01 −0.06 0.01 −0.01 0.02 −0.11 0.03
Pars Opercularis −0.01 0.02 0.00 0.01 0.00 0.01 0.00 0.01 −0.01 0.03 −0.05 0.04
Pars Orbitalis 0.00 0.02 −0.04 0.02 −0.04 0.02 −0.05 0.02 −0.08 0.03 −0.07 0.05
Pars Triangularis 0.01 0.02 0.00 0.02 0.00 0.02 −0.01 0.02 −0.02 0.03 0.00 0.04
Peri Calcarine 0.03 0.02 −0.02 0.01 −0.02 0.01 −0.01 0.01 −0.02 0.02 −0.05 0.04
Post Central −0.01 0.01 −0.01 0.01 −0.01 0.01 0.00 0.01 0.00 0.02 −0.05 0.03
Posterior Cingulate 0.02 0.02 0.02 0.01 0.02 0.01 0.00 0.01 0.00 0.03 0.04 0.04
Precentral −0.03 0.01 0.00 0.01 0.00 0.01 −0.01 0.01 0.00 0.02 −0.03 0.03
Precuneus 0.02 0.02 −0.01 0.02 −0.01 0.02 0.00 0.02 −0.01 0.03 0.03 0.04
Rostral Anterior Cingulate −0.05 0.04 0.06 0.03 0.06 0.03 −0.02 0.03 0.03 0.06 −0.12 0.09
Rostral Middle Frontal 0.01 0.01 0.01 0.01 0.01 0.01 0.00 0.01 0.00 0.02 −0.03 0.03
Superior Frontal 0.00 0.01 −0.01 0.01 −0.01 0.01 −0.01 0.01 −0.01 0.01 0.00 0.02
Superior Parietal 0.00 0.01 −0.02 0.01 −0.02 0.01 −0.01 0.01 0.00 0.02 0.00 0.03
Superior Temporal −0.02 0.01 −0.01 0.01 −0.01 0.01 −0.02 0.01 −0.02 0.02 −0.01 0.03
Supramarginal 0.01 0.01 −0.02 0.01 −0.02 0.01 −0.01 0.01 −0.02 0.02 −0.03 0.03
Frontal Pole 0.06 0.03 −0.02 0.03 −0.02 0.03 0.07 0.03 0.00 0.05 −0.03 0.07
Temporal Pole 0.02 0.03 −0.01 0.03 −0.01 0.03 0.03 0.03 0.11 0.05 0.07 0.08
Tranverse Temporal −0.05 0.03 −0.01 0.02 −0.01 0.02 −0.05 0.02 −0.05 0.04 0.00 0.06
Insula 0.01 0.01 −0.01 0.01 −0.01 0.01 −0.01 0.01 0.02 0.02 −0.01 0.02
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Bolded regions are significant

For the three-way sex by PCTB group by brain region interaction, when considering each region, significant two-way interactions were found for 5 brain regions including the isthmus of the cingulate, parahippocampus, paracentral and temporal pole. The mean CT AQ values (+/− s.e.) for WTA and BTA chimpanzees within males and females are shown in Table 3. For the isthmus of the cingulate, BTA males had greater leftward asymmetries than WTA males while no significant difference in CT AQ values were found within the females. For the paracentral, BTA males had greater rightward asymmetries than WTA males while no significant difference in CT AQ values were found within the females. For the temporal pole, BTA males had greater rightward asymmetries than WTA males; by contrast, WTA females had greater rightward asymmetries than BTA individuals. Finally, for the parahippocampus, BTA males had greater rightward biases than WTA apes while the opposite pattern was observed in the females.

Table 3:

Mean AQ Values (+/− s.e.) for WTA and BTA Chimpanzees in Males and Females

Brain Region Males Females
WTA s.e. BTA s.e WTA s.e. BTA s.e.
Bank STS −0.05 0.02 −0.01 0.03 −0.03 0.01 −0.01 0.02
Caudal Anterior Cingulate 0.07 0.03 0.10 0.04 0.07 0.02 0.07 0.02
Caudal Middle Frontal 0.03 0.02 0.01 0.03 0.00 0.01 −0.01 0.02
Cuneus −0.01 0.01 0.02 0.02 −0.02 0.01 −0.04 0.01
Entorhinal 0.05 0.03 −0.03 0.04 0.01 0.02 0.03 0.02
Fusiform −0.01 0.01 −0.04 0.02 −0.03 0.01 −0.05 0.01
Inferior Parietal 0.00 0.01 −0.02 0.02 −0.02 0.01 −0.02 0.01
Inferior Temporal −0.01 0.01 −0.05 0.02 −0.01 0.01 −0.02 0.01
Isthmus Cingulate −0.07 0.02 0.11 0.04 −0.01 0.02 −0.01 0.02
Lateral Occipital −0.03 0.01 −0.04 0.02 −0.03 0.01 −0.04 0.01
Lateral Orbital −0.02 0.01 0.02 0.02 −0.03 0.01 −0.02 0.01
Lingual −0.01 0.01 −0.02 0.02 −0.03 0.01 −0.01 0.01
Medial Orbital 0.05 0.02 0.01 0.03 0.01 0.02 0.02 0.02
Middle Temporal −0.03 0.01 −0.04 0.02 −0.03 0.01 −0.02 0.01
Parahippocampal 0.00 0.02 −0.05 0.03 −0.05 0.01 0.00 0.02
Paracentral −0.01 0.01 −0.08 0.02 −0.04 0.01 −0.05 0.01
Pars Opercularis −0.02 0.02 −0.03 0.03 0.01 0.01 0.00 0.02
Pars Orbitalis −0.04 0.02 −0.05 0.03 −0.03 0.02 −0.02 0.02
Pars Triangularis −0.01 0.02 −0.03 0.03 0.00 0.01 0.02 0.02
Peri Calcarine 0.00 0.02 −0.03 0.02 0.00 0.01 −0.03 0.01
Post Central 0.00 0.01 −0.01 0.02 −0.01 0.01 −0.02 0.01
Posterior Cingulate 0.01 0.02 0.02 0.03 0.02 0.01 0.00 0.02
Precentral −0.01 0.01 0.00 0.02 −0.01 0.01 −0.02 0.01
Precuneus 0.01 0.02 0.01 0.03 −0.01 0.01 0.00 0.02
Rostral Anterior Cingulate 0.03 0.04 −0.07 0.06 0.00 0.03 0.01 0.04
Rostral Middle Frontal 0.00 0.01 0.00 0.02 0.01 0.01 0.00 0.01
Superior Frontal 0.00 0.01 0.00 0.01 −0.01 0.01 −0.01 0.01
Superior Parietal 0.00 0.01 0.00 0.02 −0.01 0.01 −0.01 0.01
Superior Temporal −0.02 0.01 0.00 0.02 −0.02 0.01 −0.03 0.01
Supramarginal 0.00 0.01 −0.01 0.02 −0.02 0.01 −0.01 0.01
Frontal Pole 0.03 0.03 0.03 0.05 0.00 0.02 0.02 0.03
Temporal Pole −0.01 0.03 0.15 0.05 0.10 0.02 0.03 0.03
Tranverse Temporal −0.02 0.02 0.01 0.04 −0.05 0.02 −0.06 0.02
Insula 0.00 0.01 0.00 0.02 0.02 0.01 −0.02 0.01
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Bolded regions are significant

Discussion

The main findings from this study can be summarized as follows. First, as hypothesized, elderly chimpanzees showed thinner CT compared to middle-aged and young chimpanzees in whole brain CT and in 13 brain regions adjusted for whole brain differences. Our findings of reduced CT values in elderly individuals primarily in frontal, parietal, and temporal regions is consistent with previous reports on gray matter volume using voxel-based and source-based morphometry in these same chimpanzees (Lacreuse et al., 2020; Mulholland et al., 2021; Vickery et al., 2020). Second, small to moderate differences in adjusted average CT were found between male and female chimpanzees in 4 brain regions. Third, within the elderly cohort, chimpanzees that performed BTA had greater CT values than apes that performed WTA. By contrast, the difference in CT between BTA and WTA chimpanzees was not significant for the middle-aged or young cohorts. Finally, BTA and WTA elderly chimpanzees showed differences in asymmetries in CT for 4 brain regions.

The age group differences in CT in chimpanzees share similarities and differences with previous reports in monkeys and humans. Specifically, Koo et al. (2012) quantified age-related change in CT in 18 rhesus monkeys ranging from 6 to 27 years and reported moderate thinning associated with increasing age in primary somatosensory and motor cortices. The chimpanzees also showed age-related thinning in the precentral gyrus but not in the post-central gyrus, thereby only partially replicating their results. Moreover, the chimpanzees showed thinning associated with increasing age in several brain regions not reported by Koo et al. (2012), including the superior frontal, medial orbital, caudal middle, portions of the inferior frontal gyrus (pars opercularis) and the inferior, middle, and superior temporal gyri.

When comparing our findings on age-related thinning in CT in chimpanzees to humans, Lemaitre et al. (2012) reported that increasing age was negatively associated with CT in the pars opercularis, paracentral gyrus, posterior cingulate, precuneus, and precentral gyrus, after controlling for whole brain cortical thickness, in a sample of 216 healthy human subjects ranging between 18 to 87 years., Age-related thinning in CT values were similarly observed in the chimpanzees for the paracentral, pars opercularis, and precentral gyrus but not the posterior cingulate cortex and precuneus. Interestingly, the pars opercularis makes up a portion of the inferior frontal gyrus (Broca’s area) in humans and chimpanzees (Cantalupo and Hopkins, 2001; Hopkins et al., in press; Keller et al., 2009; Schenker et al., 2010). Chimpanzees also showed greater than average age-related decline in the superior and transverse temporal gyri, which was not reported in humans in the report by Lemaitre et al. (2012). Interestingly, the temporal cortex (MTG specifically) is the area in which we have observe the greatest levels of AD-related neuropathology as well as the convergence of both amyloid-beta and tau pathologies in chimpanzees (Edler et al., 2017). In addition, a non-significant trend of neuron loss (20-24%) was associated with Aβ42 vascular deposition in the temporal cortex of chimpanzees (Edler et al., 2020) Furthermore, Aβ plaque and vessel volumes were significantly greater in older apes, suggesting that age-related increases could contribute to neuronal toxicity in the MTG of aged chimpanzees. The functional relevance and the consequences of what these differences might be for loss in cognitive or behavioral functions is not clear and merits further investigation. Further, we would emphasize that this study was not explicitly designed to examine human and chimpanzees age-related changes in CT.

We also found a borderline significant effect of aging on CT asymmetries averaged across all brain regions. Elderly and middle-aged chimpanzees had greater rightward asymmetries than young individuals. Some have hypothesized that the right hemisphere ages more rapidly than the left, which would result in increased leftward neuroanatomical and functional asymmetries with increasing age (Dolcos et al., 2002). In chimpanzees, the findings were exactly the opposite with middle-aged and elderly chimpanzees showing increasing right hemisphere biases; this would suggest chimpanzees show a fundamentally different process in the aging of the two hemispheres compared to humans. One limitation of this interpretation is that the data are based on cross-sectional rather than longitudinal data; therefore, the results may not directly speak to longitudinal changes in brain asymmetry but rather reflect age group differences that might be attributable to cohort effects.

We also found sex differences in adjusted CT in 4 regions. Males had higher adjusted CT scores for the caudal anterior cingulate, rostral anterior cingulate, and medial orbital frontal while females had higher values for the inferior parietal cortex. With respect to the regions found to be larger in males, and somewhat consistent with the findings reported here, we have previously reported that male chimpanzees had larger surface area and deeper depths in the anterior cingulate sulcus compared to females (Hopkins et al., 2021b). By contrast, no sex differences in adjusted gray matter volumes were found for measures of the rostral and caudal anterior cingulate (Latzman et al., 2015). Thus, the CT data reported here are consistent with previous reports of sex differences in the surface area and magnitude of gyrification of the sulcus that defines the cingulate regions but not the gray matter volume. For the inferior parietal cortex, Taglialatela et al. (2007) previously reported that females had a greater rightward asymmetry in gray matter volume compared to males. In this report, females had greater bilateral cortical thickness in the inferior parietal region rather than in asymmetry. More broadly, when compared to humans, there is some evidence of sex differences in adjusted CT measures that show similar patterns to what we have observed in the chimpanzees. For instance, in a sample of 176 healthy human subjects ranging in age between 8 and 87 years of age, Sowell et al. (2007) found that females had higher CT values than males in the inferior parietal regions whereas males showed higher values in the causal and rostral cingulate. More recently, Ritchie et al. (2018) measured adjusted cortical thickness (and other measures) from 5,216 subjects within the UK biobank. Though no sex differences in adjusted CT were found for the caudal anterior cingulate, males were found to have higher values than females for the rostral anterior cingulate and medial orbital frontal cortex whereas females were found to have higher values in the inferior parietal cortex.

When considering cognition, chimpanzees that performed BTA on the PCTB had thicker CT values than individuals that performed lower than chance. Moreover, these effects were specific to the elderly group of chimpanzees. The differences in CT between BTA and WTA older chimpanzees is consistent with the previous finding reported by Mulholland et al. (2021) on gray matter covariation in chimpanzees. We also found that performance on the PCTB task and age had an interactive effect on CT asymmetry, and these effects were specific to 4 regions (see Table 3) including the isthmus of the cingulate, paracentral, precentral, and rostral anterior cingulate. For all 4 regions, differences in AQ values were greatest between BTA and WTA apes within the elderly groups, but albeit, in different directions.

Limitations

There are several limitations to this study. First, for pragmatic and technical reasons, the two chimpanzee cohorts were scanned on magnets with different field strengths which creates some challenges because this can influence image resolution and segmentation. That stated, when correlating age with average whole brain CT, significant negative correlations are found for both the NCCC (r = −.204, p = .017) and ENRPC (r = −.431, p < .001) cohorts separately. When considering each brain region, age is significantly negatively associated with CT in 9 and 28 regions within the ENPRC and NCCC cohorts, respectively (see Table 4). A significant negative association between age and CT was found in both cohorts for nine regions, all of which overlapped with12 regions found to differ between age groups in the combined sample. Thus, in general, increasing age was associated with CT thinning, and this was consistent in the two cohorts scanned on different magnets.

Table 4:

Partial Correlation Coefficients Between Age and Cortical Thickness Within the Combined, NCCC and ENPRC Cohorts While Controlling for Sex and Scanner

Brain Region Combined NCCC ENPRC
Frontal Regions
   Frontal Pole −0.122 −0.071 −0.200
   Rostral Middle Frontal −0.144 * −0.204 * −0.041
   Caudal Middle Frontal −0.421 *** −0.408 *** −0.439 ***
   Lateral Orbital Frontal −0.262 *** −0.294 *** −0.204
   Medial Orbital Frontal +0.067 −0.019 +0.199
   Paracentral −0.334 *** −0.309 *** −0.363 ***
   Pars Opercularis −0.392 *** −0.416 *** −0.341 ***
   Pars Orbitalis −0.228 *** −0.269 *** −0.143
   Pars Triangularis −.0260 *** −0.225 *** −0.260 *
   Precentral −0.456 *** −0.356 *** −0.102
   Superior Frontal −0.423 *** −0.408 *** −0.446 ***
Temporal Regions
   Entorhinal −0.105 −0.207 * +0.034
   Parahippocampus −0.250 *** −0.192 * −0.331 **
   Temporal Pole −0.149 * +0.203 * −0.023
   Inferior Temporal −0.112 −0.204 * +0.051
   Middle Temporal −0.211 ** −0.328 *** −0.051
   Superior Temporal −0.286 *** −0.354 *** −0.166
   Tranverse Temporal −0.348 *** −0.377 *** −0.286 *
   Bank of STS −0.258 *** −0.364 *** −0.056
Parietal Regions
   Postcentral −0.232 *** −0.291 *** −0.102
   Inferior Parietal −0.295 *** −0.369 *** −0.136
   Superior Parietal −0.158 * −0.262 ** +0.078
   Supramarginal −0.289 *** −0.369 *** −0.115
Occipital Regions
   Fusiform −0.125 −0.223 ** +0.047
   Lingual −0.131 −0.179 * −0.050
   Precuneus −0.123 −0.183 * +0.000
   Cuneus −0.163 −0.206 * −0.073
   Lateral Occipital −0.084 −0.151 +0.050
   Peri-calcarine −0.095 −0.055 −0.140
Cingulate and Insula
   Rostral Anterior Cingulate +0.213 +0.135 +0.322 **
   Caudal Anterior Cingulate −0.030 −0.014` −0.062
   Posterior Cingulate −0.241 *** −0.279 *** −0.171
   Isthmus Cingulate −0.360 *** −0.400 *** −0.282 *
   Insula −0.189 ** −0.243 ** −0.082
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*

p < .05

**

p < .01

***

p < .001. NCCC - National Center for chimpanzee Care (n=138), ENPRC = Emory National Primate Research Center (n = 77). Combined -= combined sample (n = 215).

Second, the chimpanzees were tested on the PCTB tasks at different time points than the collection of the MRI scans. On average, the duration of time between behavioral testing and collection of the scans was 2.5 years, but ideally these would have been obtained at the same time. Third, though we included rearing history of the chimpanzees as a covariate, it is important to recognize that all wild-born (WB) chimpanzees were elderly, as the U.S. stopped importation of chimpanzees in 1974. Thus, there are no WB middle-aged or young chimpanzees. We would point out that comparing whole brain CT between mother-reared, nursery-reared, and WB chimpanzees, while statistically controlling for their age and scanner magnet, does not reveal a significant main effect for rearing F(2,207) = 1.55, p = 0.214. Thus, rearing likely does not explain our observed aging effects though we cannot rule out this variable. Lastly, the WB chimpanzees also present challenges when determining their exact age, because they have estimated dates of birth which can create some potential error. Recent studies using DNA methylation in calculating epigenetic clocks in chimpanzees and other species may offer some potential insight or options for resolving this issue, as it may be feasible to use DNA methylation to provide additional support for the age of WB apes rather than relying solely on estimates of birthdates to determine their chronological ages (Bell et al., 2019; Guevara et al., 2020; Horvath, 2013).

Lastly, we did not consider or test for the possibility that different dimensions in cognition (physical versus social) may have impacted the brain regions found to differ between age groups. This is certainly worth consideration but we opted nto to perform these analyses because our previous studies have found that the quadratic relationship between age and overall performance on the PCTB tasks (i.e., UWA scores) were the very similar when considering only those tasks that comprised the physical and social cognition dimensions within the PCTB (Hopkins et al., 2021a). Further, there are significant positive correlations between the weighted scores derived for the physical (r = .935, p < .001) and social (r = .495, p < .001) cognition tasks and the overall UWA scores (see also Hopkins et al., 2014). Thus, in our view, we believe that the brain-behavior-aging results reported in this study based on the overall UWA scores would be similar or not change significantly if the analyses were separated out by their performance on the social and particularly the physical cognition tasks.

In conclusion, chimpanzees show increased thinning in CT as they age, and these results are evident in two separate cohorts of chimpanzees. Further, chimpanzees with BTA cognitive abilities have thicker CT, and this is particularly evident in elderly chimpanzees. To what extant variation in CT reflects neuronal or potential neuropathological changes in the cortex remains unclear but clearly merits investigation in future studies in chimpanzees and other nonhuman primate models of human aging.

Highlights.

  • Elderly chimpanzees show regional cortical thinning compared to younger individuals

  • Elderly chimpanzees show greater rightward asymmetries compared to younger apes

  • Age-related differences in cognition were associated with loss in cortical thickness

Acknowledgement

This research was supported in part by NIH grants NS-073134, AG-067419 and NS-092988 (support for the National Chimpanzee Brain Resource). Chimpanzee maintenance at the National Center for Chimpanzee Care is funded by NIH/NCRR U42-OD-011197. American Psychological Association guidelines for the ethical treatment of animals were adhered to during all aspects of this study. We are grateful to the entire veterinary staffs at the NCCC and YNPRC for their helpful assistance in collection of the MRI scans.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Credit_author_statement

WDH designed study, performed statistical analyses, wrote the manuscript. XI and Roberts performed all image processing in Freesurfer, CCS, MAR and MKE assisted in research design and manuscript preparation, MMM and SJS helped with data collection, analysis and manuscript preparation.

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