The Signiﬁcance of Chimpanzee Occipital Asymmetry to Hominin Evolution

: Little is known about how occipital lobe asymmetry, width, and height interact to contribute to the operculation of the posterior parietal lobe, despite the utility of knowing this for understanding the relative reduction in the size of the occipital lobe and the increase in the size of the posterior parietal lobe during human brain evolution. Here, we use linear measurements taken on 3D virtual brain surfaces obtained from 83 chimpanzees to study these traits as they apply to operculation of the posterior occipital parietal arcus or bridging gyrus. Asymmetry in this bridging gyrus visibility provides a unique opportunity to study both the human ancestral and human equivalently normal condition in the same individual. Our results show that all three traits (occipital lobe asymmetry, width, and height) are related to this operculation and bridging gyrus visibility but width and not height is the best predictor, against expectations, suggesting that relative reduction of the occipital lobe and exposure of the posterior parietal is a complex phenomenon.


Introduction
In addition to helping us understand the evolution of lateralization [1][2][3], asymmetries of the brain's surface seen in closely related species such as chimpanzees (Pan troglodytes) can also help us to understand the role development plays in brain evolution itself. As an example, a major shape difference in the brains of human (Homo sapiens) versus nonhuman primates is that in nonhuman primates the occipital lobe operculates part of the parietal lobe, including a buried annectant gyrus that connects these lobes, known as the 1st parieto-occipital "pli de passage" of Gratiolet or the parieto-occipital arcus [4][5][6]. The posterior portion or bridge of this gyrus is consistently seen on the brain's surface in humans but is only occasionally seen (often asymmetrically) in chimpanzees [4][5][6][7][8]. Relative reduction of the occipital operculation and expansion of the posterior parietal lobe is a major hallmark in human brain evolution, although debate on when this occurred has been contentious, and currently we have no model of what transitional states between the human ancestral and derived conditions may have looked like. Studying the presence or absence of a visible bridging gyrus in chimpanzees, who are our closest living relatives and who have brains very similar to that of the last common ancestor [7][8][9][10] allows us to understand its relationship to the size of the occipital lobe; when this trait is asymmetrical in chimpanzees (who unlike humans still show occasional asymmetry in this region) it allows us to understand this trait developmentally rather than genetically, as it occurs variably in different hemispheres of the same individual, while giving us a greater range of variation in which to build models of transitional states, and to study the evolution of asymmetries and symmetries, since it is asymmetrical in chimpanzees while it is symmetrical in humans. Such an understanding would also be very valuable for the interpretation of hominin endocranial casts, which have morphology that is difficult to interpret in this region due to Symmetry 2021, 13, 1862 2 of 12 our lack of transitional models, and so very valuable to the study of brain evolution. If this trait is only associated with occipital lobe height this would suggest that the primary factor in the exposure of the bridging gyrus is posterior movement of the occipital operculation, which retracted inferio-posteriorly during human evolution revealing buried parietal gyri which then expanded; association with asymmetry and/or width in addition to height would suggest a relative change in the size and shape of the entire occipital to the parietal lobe is a more important factor. Using preliminary data, we observed these relationships in a large sample of chimpanzees. The aim of this study is an exploratory assessment of whether the presence or absence of the occipital bridging gyrus is associated with left or right hemispheres, and how hemisphere siding is associated with occipital lobe width and height in the chimpanzee brain. Regression analysis examines the correlation between left and right hemispheres and occipital lobe width and height, where reliable predictions (±1 s.e.) determined if occipital lobe height or width was a more reliable predictor of hemisphere siding. Ultimately, we found that asymmetry, height, and width are all associated with a visible bridging gyrus, in increasing order.

Materials and Methods
This study used three-dimensional surface models of a sample of 83 chimpanzee brains. These brains were reconstructed using MRIs from the National Chimpanzee Brain Resource (https://www.chimpanzeebrain.org (accessed on 1 September 2021)) using BrainVISA software (Pune, India) and measured using MeshLab [11][12][13]. Although the measurements were able to be collected on the entire sample, the original collectors [12] could not guarantee that the left or right hemisphere siding was correctly labelled. To accommodate this uncertainty, subsample (n = 15) was obtained by one of us to allow a comparison and analysis of 'known' and 'unknown' hemisphere siding'. Each brain was rotated such that the lowest points of the left occipital and left temporal lobes both lie on a plane at right angles to the longitudinal fissure. The width of each hemispherical occipital lobe was measured as the distance in millimeters from the longitudinal fissure to the lobe's most lateral extent. Height was measured as the greatest vertical extent between points on each hemispherical lobe, barring its most medial edge if a bridging gyrus was visible; the presence of a visible bridging gyrus between the superior-medial occipital lobe and the parietal-occipital arcus was scored as a Y, while a fully operculated and thus hidden bridging gyrus was scored as an N (see Figure 1). asymmetries and symmetries, since it is asymmetrical in chimpanzees while it is symmetrical in humans. Such an understanding would also be very valuable for the interpretation of hominin endocranial casts, which have morphology that is difficult to interpret in this region due to our lack of transitional models, and so very valuable to the study of brain evolution. If this trait is only associated with occipital lobe height this would suggest that the primary factor in the exposure of the bridging gyrus is posterior movement of the occipital operculation, which retracted inferio-posteriorly during human evolution revealing buried parietal gyri which then expanded; association with asymmetry and/or width in addition to height would suggest a relative change in the size and shape of the entire occipital to the parietal lobe is a more important factor. Using preliminary data, we observed these relationships in a large sample of chimpanzees. The aim of this study is an exploratory assessment of whether the presence or absence of the occipital bridging gyrus is associated with left or right hemispheres, and how hemisphere siding is associated with occipital lobe width and height in the chimpanzee brain. Regression analysis examines the correlation between left and right hemispheres and occipital lobe width and height, where reliable predictions (±1 s.e.) determined if occipital lobe height or width was a more reliable predictor of hemisphere siding. Ultimately, we found that asymmetry, height, and width are all associated with a visible bridging gyrus, in increasing order.

Materials and Methods
This study used three-dimensional surface models of a sample of 83 chimpanzee brains. These brains were reconstructed using MRIs from the National Chimpanzee Brain Resource (https://www.chimpanzeebrain.org (accessed on 1 September 2021)) using BrainVISA software (Pune, India) and measured using MeshLab [11][12][13]. Although the measurements were able to be collected on the entire sample, the original collectors [12] could not guarantee that the left or right hemisphere siding was correctly labelled. To accommodate this uncertainty, subsample (n = 15) was obtained by one of us to allow a comparison and analysis of 'known' and 'unknown' hemisphere siding'. Each brain was rotated such that the lowest points of the left occipital and left temporal lobes both lie on a plane at right angles to the longitudinal fissure. The width of each hemispherical occipital lobe was measured as the distance in millimeters from the longitudinal fissure to the lobe's most lateral extent. Height was measured as the greatest vertical extent between points on each hemispherical lobe, barring its most medial edge if a bridging gyrus was visible; the presence of a visible bridging gyrus between the superior-medial occipital lobe and the parietal-occipital arcus was scored as a Y, while a fully operculated and thus hidden bridging gyrus was scored as an N (see Figure 1).

Statistical Analyzes
Preliminary analysis included a measurement error study. All data collection and measurements were conducted by a single operator to prevent the effects on interobserver error. Measurement error was investigated by using an analysis of variance, where measurement error was calculated as the proportion of the mean-squared differences between replicates relative to the total between-group variation [14]. The subsample (n = 15) of known hemisphere siding were measured on two separate occasions and measurement error (ME) calculated as % ME = 100 × MS (within)/MS (within) + MS (among). Measurement error ranged from 0% to 3% (results not shown), and with this low measurement error, we considered intraobserver error had a very minimal effect on further analyzes.
Canonical Correspondence Analysis (CCA) initially examined the potential association between the four metrics: occipital height, both left and right (in mm) and width, both left and right (in mm), and the presence or absence of a left, right, or no occipital bridge (Table 1). CCA is particularly suited to datasets where quantitative variables and presence/absence variables are common, such as ecological datasets [15]. Only recently has this been applied to brain evolution, specifically quantitative variables, and the presence/absence of sulcal patterns [16]. CCA allows a comparison analysis, directly testing a priori hypotheses emphasizing the variance of Y that is related to X, and where CCA combines the properties of both ordination and regression analyses to produce ordinations of Y that are linearly constrained to X [15]. Correlation analysis then tested the strength of the potential correlation between two or more variables using the most common correlation statistic (Pearson's r correlation coefficient), with a two-tailed significance that the variables were uncorrelated and a Monte Carlo permutation (using 9999 iterations) [17]. To estimate the uncertainty due to unknown hemisphere siding, a subsample (n = 15) where the hemisphere siding was known (left and right) was examined with Bivariate ordinary least-squares (OLS) regression to test the strength of association between each of the four variables and occipital lobe side (left and right hemisphere). For regression purposes, and to linearize scaling relationships [18], each variable was converted (from mm) into natural logarithmic units (base e) and a 95% confidence interval fitted to the log-log regressions.
Predicted height and width from both hemispheres was calculated using prediction equations provided by the bivariate OLS regression models, where y = (a × log[x] + b). The reliability of the predictions was calculated as the percentage of prediction errors (PPE), where PPE = (predicted − observed)/predicted × 100). PPE calculates the uncertainty in an estimate relative to its size [19]. Prediction reliability was determined by applying a bracket of uncertainty produced by the standard error (s.e.) from the bivariate OLS regression models calculating the upper and lower estimates for predicted height or width for each specimen relative to its size, where y = (a × log[x] + b ± s.e). This maintained any inherent differences between each variable allowing for changes in the range of uncertainty, where each variable is associated with differences in the standard error [20]. All statistical analyses were conducted in Past 4.0 [21].

Results
Preliminary results from summary statistics ( Table 2) detailing the differences between the left and right occipital lobes and the variation between height and width measurements. Canonical Correspondence Analysis (CCA) was used to determine the strength of the correlation between different occipital bridge types, and the left (L) and right (R) height or width of the occipital lobe. The presence or absence of bridging patterns requires assessment where the potential correlation between occipital lobe height and width could be assessed against the presence or absence of Left or Right bridging patterns, or whether those with Both patterns were associated more with Occipital lobe width or height. Consistent with CCA, the type of bridging patterns grouped specimens accordingly and the effect of occipital lobe height or width determined. Results indicated that greater occipital width was associated with both Left and Right bridging patterns (Axis 1), while occipital lobe height (Axis 2) was associated more strongly with No Bridging pattern. The correlations between variables indicated by Axis 1 (89% variance) and Axis 2 (11% variance) were statistically significant (p < 0.002) with 1000 permutations (Table 3). There were four distinct groups based on the type of bridge patterns observed with a left bridge associated with marginally shorter L lobe height and greater R lobe width, a right bridge was associated with shorter R lobe height and slightly greater R lobe width, where both L and R bridges were present, these were weakly associated with smaller L height, and no bridges was associated with greater R lobe height and width ( Figure 2). Canonical Correspondence Analysis (CCA) was used to determine the strength of the correlation between different occipital bridge types, and the left (L) and right (R) height or width of the occipital lobe. The presence or absence of bridging patterns requires assessment where the potential correlation between occipital lobe height and width could be assessed against the presence or absence of Left or Right bridging patterns, or whether those with Both patterns were associated more with Occipital lobe width or height. Consistent with CCA, the type of bridging patterns grouped specimens accordingly and the effect of occipital lobe height or width determined. Results indicated that greater occipital width was associated with both Left and Right bridging patterns (Axis 1), while occipital lobe height (Axis 2) was associated more strongly with No Bridging pattern. The correlations between variables indicated by Axis 1 (89% variance) and Axis 2 (11% variance) were statistically significant (p < 0.002) with 1000 permutations (Table 3). There were four distinct groups based on the type of bridge patterns observed with a left bridge associated with marginally shorter L lobe height and greater R lobe width, a right bridge was associated with shorter R lobe height and slightly greater R lobe width, where both L and R bridges were present, these were weakly associated with smaller L height, and no bridges was associated with greater R lobe height and width ( Figure 2).  Correlation analysis examined potential correlations between variables using Pearson's r correlation coefficient for significance and a Monte Carlo permutation (9999 iterations) with the probability of variables being uncorrelated using a two-tailed significance set to p < 0.01. Statistically significant correlations using Monte Carlo permutation are reported (Table 4) for R and L lobe height and width (p ≤ 0.0001), with slightly less robust correlations for R lobe width and right bridge (p = 0.0008), and L lobe height and L bridge (p = 0.0022). Correlations between bridging patterns are entirely due to the binary coding and do not reflect a true correlation. Caution is warranted with these initial findings where uncertainty associated with correct hemisphere siding, and the low number of individuals who possessed a bridging pattern could be obscured by the higher number of those who possessed no bridging pattern and where known siding is uncertain. However, correlation results and those reported from the CCA suggest a likely association between lobe width and bridging patterns.
Ordinary Least Squares (OLS) regression examined a subsample (n = 15) of individuals with known right and left hemisphere siding allowing a test of bridging and siding prediction and associated uncertainty. Metrics (in mm) for both right and left width and height were first transformed by natural logarithm (base e) maintaining linearity. Both height and width were predicted using Right from Left and then Left from Right to determine the potential effect of siding on prediction uncertainty. All predictions were made with a 95% confidence interval (CI) with strong correlations (r ≥ 0.86, p ≤ 0.0001). However, between the regression models, there was little observable difference whether the left or right hemisphere was used for the predictions (Table 5, Figure 3). Table 5. Parameters for ordinary least-squares regression detailing the regression statistics for the four metrics both left and right side. Statistically significant results reported in italics. All regression models showed a strong prediction overall, calculating the percentage of prediction uncertainty (PPE) allows a better comparison of the uncertainty within each model. Percentage of prediction error (PPE) was calculated for occipital height and width, respectively, and the difference between these left and right predictions compared with robust agreement between the observed and the predicted values (Table 5). Prediction reliability assessed the difference within the regression models and between left and right lobes. Greater prediction uncertainty existed for lobe height, with a disparity of 17%, than for width where the disparity was only 6%. This suggest that occipital lobe width might be a more stable variable with less prediction uncertainty than height, potentially making it more suitable for predicting occipital lobe side and hence, more reliable for assessing bridging pattern associations (Table 6).  All regression models showed a strong prediction overall, calculating the percentage of prediction uncertainty (PPE) allows a better comparison of the uncertainty within each model. Percentage of prediction error (PPE) was calculated for occipital height and width, respectively, and the difference between these left and right predictions compared with robust agreement between the observed and the predicted values (Table 5). Prediction reliability assessed the difference within the regression models and between left and right lobes. Greater prediction uncertainty existed for lobe height, with a disparity of 17%, than for width where the disparity was only 6%. This suggest that occipital lobe width might be a more stable variable with less prediction uncertainty than height, potentially making it more suitable for predicting occipital lobe side and hence, more reliable for assessing bridging pattern associations (Table 6). Table 6. Percentage of prediction errors (PPE) for four occipital metrics calculated as the difference between observed and predicted height and width, and percentage of prediction reliability calculated as difference between observed and predicted height and width (in mm) divided by observed height and width. Negative and positive values indicate an increase or decrease, respectively, in the predicted value from the observed.

Percentage Prediction Error
Height The predictions for both L and R occipital lobe width and height are provided for both known and unknown sample, with predicted values converted from log-units to metrics (in mm) by taking the inverse-log and the observed values reported in parentheses alongside the predicted values (Table 7, Figure 4). Considering there was no discernible difference in pattern of reliability between the hemispheres, only the prediction of R lobe height and width are provided. Table 6. Percentage of prediction errors (PPE) for four occipital metrics calculated as the difference between observed and predicted height and width, and percentage of prediction reliability calculated as difference between observed and predicted height and width (in mm) divided by observed height and width. Negative and positive values indicate an increase or decrease, respectively, in the predicted value from the observed.

Percentage Prediction Error
Height Width Table 6. Cont.  Abbreviations: 1 Measurements of left (L) and right (R) height and width (in mm), 2 The subsample with known hemisphere siding.

Discussion
These findings suggest greater R > L height asymmetry associated with no bridging pattern, moderate R > L height asymmetry for both R and L bridge patterns, smaller L< R height and width asymmetry with a L bridge pattern, and smaller R < L height asymmetry associated with right bridge pattern. Additionally, there was less uncertainty when predicting right and left siding using occipital lobe width rather than occipital lobe height, indicating width is a more reliable predictor than height. This has implications for the

Discussion
These findings suggest greater R > L height asymmetry associated with no bridging pattern, moderate R > L height asymmetry for both R and L bridge patterns, smaller L < R height and width asymmetry with a L bridge pattern, and smaller R < L height asymmetry associated with right bridge pattern. Additionally, there was less uncertainty when predicting right and left siding using occipital lobe width rather than occipital lobe height, indicating width is a more reliable predictor than height. This has implications for the suitability of metrics chosen to examine an association with bridging patterns, especially if the sample is unknown where width provides more reliable predictors than height for future research in modelling occipital lobe bridging patterns and possible associations. Although we suggest caution is warranted with the preliminary nature of these results, they also suggest there is a component of asymmetry for chimpanzee occipital lobe bridge patterns, and that increasing width and not simply posterior movement (or reduced height) of the occipital lobe may play an important role in exposure of the occipital-parietal bridge during human evolution, which was unexpected. Future research will compare the size of the parietal to the occipital lobe in these same subjects.
Data Availability Statement: Measurements are contained in the article. MRI data can be obtained from the National Chimpanzee Brain Resource (https://www.chimpanzeebrain.org (accessed on 1 September 2021)).