SS symmetry
Article
The Significance of Chimpanzee Occipital Asymmetry to
Hominin Evolution
Shawn Hurst 1, *, Ralph Holloway 2 , Alannah Pearson 3 and Grace Bocko 1
1
2
3
*
Biology Department, University of Indianapolis, Indianapolis, IN 46227, USA; bockog@uindy.edu
Anthropology Department, Columbia University, New York, NY 10027, USA; rlh2@columbia.edu
School of Archaeology and Anthropology, The Australian National University, Canberra 2601, Australia;
alannah.pearson@anu.edu.au
Correspondence: hursts@uindy.edu; Tel.: +1-317-788-4912
Abstract: 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.
Keywords: chimpanzee; occipital; hominin
Citation: Hurst, S.; Holloway, R.;
Pearson, A.; Bocko, G. The
Significance of Chimpanzee Occipital
Asymmetry to Hominin Evolution.
1. Introduction
Symmetry 2021, 13, 1862. https://
In addition to helping us understand the evolution of lateralization [1–3], 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 [4–6]. 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 [4–8]. 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 [7–10] 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
doi.org/10.3390/sym13101862
Academic Editor: Antoine Balzeau
Received: 18 August 2021
Accepted: 29 September 2021
Published: 3 October 2021
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Symmetry 2021, 13, 1862. https://doi.org/10.3390/sym13101862
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Symmetry 2021, 13, 1862
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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.
2. 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 [11–13]. 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).
Figure 1. Occipital Measurement Definitions. W = width, H = height. The right hemisphere has
a bridging gyrus (BG) not fully operculated by the occipital lobe and was scored as a Y; in the left
hemisphere this gyrus is fully operculated, so its condition was scored as an N.
Symmetry 2021, 13, 1862
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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].
Table 1. Occipital lobe measurements and bridging pattern type.
Subject
Abby
Agatha
Ahni
Akimel
Alex *
Alpha
Amanda
Angie
Artemus
Arthur
Artifee *
Augusta
Azalea
Bahn
Barbara
Bart
Bashful *
Becca
Beleka
Bernadette
Bernie
Beta
Betty *
Billy *
Bo *
Boka
Brandy
Bria
Brodie
Height 1
Bridge 2
Width
L
R
L
R
L
R
Both
36
42
28
42
26
33
41
27
32
38
39
38
36
35
42
31
31
36
32
35
24
29
44
33
35
42
35
34
33
38
44
31
41
27
35
41
30
33
37
37
35
38
36
43
29
32
38
31
39
26
29
44
39
33
42
34
38
33
38
47
35
39
34
36
37
35
35
33
37
32
33
33
37
37
34
28
28
32
27
29
36
31
33
38
26
38
31
37
46
36
41
34
39
37
35
35
35
36
34
37
33
37
37
34
30
30
36
26
29
38
33
33
37
29
40
31
N
N
N
N
Y
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
Y
N
N
N
N
N
Y
N
N
N
Y
N
N
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
Y
N
Y
N
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
Y
N
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Table 1. Cont.
Subject
Callie
Carl *
Chechkel
Cheeta *
Cheopi
Chester
Chinook
Chip *
Christa
Chuhia
Cissie
Coco
Cybil
Dara
David *
Drew
Duff
Edwina *
Eesha
Ehsto
Elvira
Elwood *
Emily *
Eniga
Evelyne
Faye
Fiona
Foxy
Frannie
Fritz
Gaygos
Gelb
Gigi
Gimp
Gisoki
Haakid
Hannah
Helga
Heppie
Hobbes
Hodari
Huey
Hug
Huhkalig
Iyk
Jacqueline
Jadyh
Jake
Jamie
Jane
Jarred *
Jcarter
Jewelle
Jolson *
1
Height 1
Bridge 2
Width
L
R
L
R
L
R
Both
40
37
43
45
34
28
35
33
43
37
38
31
27
36
29
37
39
31
30
42
39
39
30
39
32
37
38
37
34
38
36
37
34
32
38
36
35
30
42
30
36
37
31
38
31
33
31
38
38
33
32
35
28
38
40
32
42
44
34
36
38
34
43
40
41
32
28
39
29
36
39
32
32
44
39
40
32
40
29
38
41
36
35
40
35
38
33
33
40
37
35
27
42
36
36
29
36
38
35
31
33
40
37
32
33
31
27
38
32
33
38
37
31
37
36
36
34
34
35
37
33
36
37
37
35
32
33
45
38
35
35
35
29
35
38
35
34
34
39
31
35
36
30
38
32
33
36
33
37
37
36
35
33
34
33
36
37
38
33
32
30
39
32
34
41
39
32
37
36
36
37
34
37
38
34
34
35
40
37
32
33
45
37
35
35
35
29
38
37
35
34
36
39
33
35
35
35
41
33
35
37
32
37
38
36
36
35
34
34
37
38
37
33
34
29
38
N
Y
N
N
N
Y
N
Y
N
N
N
Y
Y
N
N
N
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
N
Y
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
Y
N
N
N
Y
N
Y
N
Y
N
Y
Y
N
Y
Y
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
N
Y
N
N
N
Y
N
N
N
N
N
Y
Y
N
N
Y
N
N
N
Y
N
Y
N
N
N
Y
Y
N
N
N
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Y
N
All numbered measurements in left (L) and right (R) height and width in mm. 2 Presence (Y), absence (N), or
Both (B) of a visible bridging gyrus. * Indicates the subsample of individuals with known siding.
Symmetry 2021, 13, 1862
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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].
3. 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.
Table 2. Summary statistics detailing mean, variance, standard deviations for the subsample (n = 15)
with known hemisphere siding.
Summary Statistics (Known Sample)
L Height
R Height
L Width
R Width
N
15
15
15
15
Min
26
27
31
32
Max
45
44
39
39
Sum
522
526
522
525
Mean
34.8
35.06667
34.8
35
Std. error
1.40814
1.31
0.57
0.53
Variance
29.74286
25.78095
4.885714
4.285714
Stand. dev
5.453701
5.077495
2.210365
2.070197
Median
33
33
35
35
25 percentile
31
32
33
33
75 percentile
39
39
37
36
Skewness
0.4577742
0.476494
0.108067
0.613097
Kurtosis
−0.4279719
−0.52249
−0.60243
−0.46667
Geom. mean
34.40985
34.73166
34.73453
34.94389
Coeff. var
15.67156
14.47955
6.351624
5.914848
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
−
−
−
−
Symmetry 2021, 13, 1862
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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).
Table 3. Canonical Correspondence Analysis values of occipital lobe bridge patterns, with permutation (999 iterations). Statistically significant values are reported in italics.
Axis
Eigenvalue
Percentage
p-Value
1
2
0.2851
0.0347
89.14
10.86
0.001
0.002
Abbreviations: p-value is the permutated p-value from 1000 iterations.
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).
Figure 2. Canonical Correspondence analysis showing the four distinct groups of bridge patterns
and a biplot indicating the direction of correlations between variables where longer lines indicate a stronger correlation. Abbreviations: Green square = Right Bridge; Purple square = Left
bridge; Blue Sphere = No bridge; Red Triangle = Both bridges; L Height = Left occipital lobe height;
R Height = Right occipital lobe height; L Width = Left occipital lobe width; R Width = Right occipital
lobe width.
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.
Symmetry 2021, 13, 1862
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Table 4. Correlation Analysis between occipital lobe metrics and bridging patterns, with Monte Carlo
permutation (9999 iterations) and two-tailed significance. Statistically significant values are reported
in italics (p < 0.01). Correlation values reported in the lower triangle with two-tailed significance that
variables are uncorrelated are reported in the upper triangle.
Correlation Table
L Height
R Height
0.0001
L Height
L Width
R Width
L Bridge 1
R Bridge 1
N Bridge 1
0.0001
0.0001
0.0022
0.0161
0.0026
0.0001
0.0001
0.0101
0.0008
0.0002
0.0001
0.6361
0.3920
0.4240
R Height
0.0001
L Width
0.0001
0.0001
R Width
0.0001
0.0001
0.0001
L Bridge
0.0022
0.0101
0.6361
0.8226
0.8226
R Bridge
0.0161
0.0008
0.3920
0.7199
0.0001
N Bridge
0.0026
0.0002
0.4240
0.9431
0.0001
0.7199
0.9431
0.0001
0.0001
0.0001
0.0001
Abbreviations: Correlation in lower triangle of matrix; probability of uncorrelated variables with two-tailed
significance (p < 0.05) in upper triangle of matrix. L Height = Left occipital lobe height; R Height = Right occipital
lobe height; L Width = Left occipital lobe width; R Width = Right occipital lobe width; R Bridge = Right Bridge; L
Bridge = Left bridge; No Bridge = Nbridge; 1 = Included as binary values (present/absent scores).
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.
Right Lobe Regression Statistics
Metrics
a
b
s.e
r
p
R Height
0.82901
0.61434
0.11182
0.90
0.0001
R Width
0.79421
0.73609
0.12819
0.86
0.0001
Left Lobe Regression Statistics
Metrics
a
b
s.e
r
p
L Height
0.97553
0.07749
0.13158
0.90
0.0001
L Width
0.94058
0.20515
0.15181
0.86
0.0001
Abbreviations: a = slope; b = intercept; s.e = standard error of the regression estimate; r = Correlation coefficient; p = p-value for significance; L Height = Left occipital lobe height; R Height = Right occipital lobe height;
L Width = Left occipital lobe width; R Width = Right occipital lobe width.
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
Symmetry 2021, 13, 1862
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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).
Figure 3. Log-log Ordinary Least Squares (OLS) regression of Occipital lobe fitted with a 95% confidence interval for lobe
(A) height and (B) width where black triangles are specimens with a bridging gyrus and black dashed line to emphasize
symmetry and asymmetry (the departure from symmetry).
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
Subject
L
R
L
R
Alex
Artifee
Bashful
Betty
Billy
Bo
Carl
Cheeta
Chip
David
Edwina
Elwood
Emily
Jarred
Jolson
1%
−2%
1%
0%
4%
−2%
−4%
−1%
1%
0%
1%
0%
2%
1%
0%
1%
1%
0%
−1%
−4%
2%
4%
0%
0%
−
1%
0%−
−1%
−1%
0%
0%
0%
−1%
0%
1%
2%
0%
1%−
1%
0%
−2%
0%
0%
0%
0%
−1%
0%
1%
0%
−2%
−1%
0%
0%
−2%
0%
−
1%
−
1%
0%
0%
0%
−
0%
−
−
−
−
−
−
Symmetry 2021, 13, 1862
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Table 6. Cont.
Relability of Prediction Errors
Subject
Height
Width
Alex
Artifee
Bashful
Betty
Billy
Bo
Carl
Cheeta
Chip
David
Edwina
Elwood
Emily
Jarred
Jolson
0%
3%
−1%
0%
−9%
4%
8%
1%
−1%
1%
−1%
−1%
−3%
−1%
0%
0%
2%
0%
−3%
−3%
1%
−1%
−3%
0%
3%
1%
0%
0%
1%
1%
Table 7. Prediction of occipital lobe width and height (in mm) listed with the corresponding variable
calculated from the bivariate ordinary least-squares equations. Observed values reported beside
predicted in parentheses.
Prediction of Height and Width
Subject
Alex 2
Artifee 2
Bashful 2
Betty 2
Billy 2
Bo 2
Carl 2
Cheeta 2
Chip 2
David 2
Edwina 2
Elwood 2
Emily 2
Jarred 2
Jolson 2
Abby
Agatha
Ahni
Akimel
Alpha
Amanda
Angie
Artemus
Arthur
Augusta
Azalea
Bahn
Barbara
Bart
Becca
Height 1
Width 1
R
L
R
L
28 (27)
37 (37)
33 (32)
43 (44)
39 (39)
34 (33)
33 (32)
43 (44)
34 (34)
30 (29)
33 (32)
39 (40)
33 (32)
34 (33)
38 (38)
38 (38)
43 (44)
32 (31)
40 (41)
35 (35)
40 (41)
31 (30)
34 (33)
37 (38)
35 (35)
38 (38)
36 (36)
42 (43)
30 (29)
38 (38)
26 (26)
39 (39)
31 (31)
43 (44)
33 (34)
35 (35)
37 (37)
44 (45)
33 (33)
29 (29)
31 (31)
39 (39)
30 (30)
32 (32)
38 (38)
36 (36)
41 (42)
28 (28)
41 (42)
33 (33)
40 (41)
27 (27)
32 (32)
38 (37)
38 (38)
36 (36)
35 (35)
41 (42)
31 (31)
36 (36)
34 (34)
36 (36)
34 (34)
38 (38)
34 (33)
34 (33)
34 (34)
38 (39)
36 (36)
35 (35)
33 (32)
35 (35)
35 (35)
34 (33)
38 (39)
37 (37)
44 (46)
36 (36)
40 (41)
38 (39)
37 (37)
35 (35)
35 (35)
35 (35)
34 (34)
37 (37)
34 (33)
37 (37)
37 (37)
31 (30)
34 (34)
37 (37)
34 (34)
36 (36)
31 (31)
33 (33)
33 (33)
37 (37)
36 (36)
37 (37)
32 (32)
35 (35)
35 (35)
33 (33)
39 (38)
38 (39)
46 (47)
35 (35)
39 (39)
36 (36)
37 (37)
35 (35)
35 (35)
33 (33)
32 (32)
33 (33)
33 (33)
37 (37)
37 (37)
28 (28)
Symmetry 2021, 13, 1862
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Table 7. Cont.
Prediction of Height and Width
Subject
Beleka
Bernadette
Bernie
Beta
Boka
Brandy
Bria
Brodie
Callie
Chechkel
Cheopi
Chester
Chinook
Christa
Chuhia
Cissie
Coco
Cybil
Dara
Drew
Duff
Eesha
Ehsto
Elvira
Eniga
Evelyne
Faye
Fiona
Foxy
Frannie
Fritz
Gaygos
Gelb
Gigi
Gimp
Gisoki
Haakid
Hannah
Helga
Heppie
Hobbes
Hodari
Huey
Hug
Huhkalig
Iyk
Jacqueline
Jadyh
Jake
Jamie
Jane
Jcarter
Jewelle
Height 1
Width 1
R
L
R
L
32 (31)
39 (39)
28 (26)
30 (29)
41 (42)
34 (34)
38 (38)
34 (33)
39 (40)
41 (42)
34 (34)
36 (36)
38 (38)
42 (43)
39 (40)
40 (41)
33 (32)
29 (28)
39 (39)
36 (36)
39 (39)
33 (32)
43 (44)
39 (39)
39 (40)
30 (29)
38 (38)
40 (41)
36 (36)
35 (35)
39 (40)
35 (35)
38 (38)
34 (33)
34 (33)
39 (40)
37 (37)
35 (35)
28 (27)
41 (42)
36 (36)
36 (36)
30 (29)
36 (36)
38 (38)
35 (35)
32 (31)
34 (33)
39 (40)
37 (37)
33 (32)
32 (31)
28 (27)
32 (31)
35 (35)
24 (24)
29 (29)
41 (42)
35 (35)
34 (34)
33 (33)
39 (40)
42 (43)
34 (34)
28 (28)
35 (25)
42 (43)
37 (37)
38 (38)
31 (31)
27 (27)
36 (36)
37 (37)
39 (39)
30 (30)
41 (42)
39 (39)
39 (39)
32 (32)
37 (37)
38 (38)
37 (37)
34 (34)
38 (38)
36 (36)
37 (37)
34 (34)
32 (32)
38 (39)
36 (36)
35 (35)
30 (30)
41 (42)
30 (30)
36 (36)
37 (37)
31 (31)
38 (38)
31 (31)
33 (33)
31 (31)
38 (38)
38 (38)
33 (33)
35 (35)
28 (28)
31 (30)
36 (36)
28 (27)
30 (29)
37 (37)
30 (29)
39 (40)
32 (31)
33 (32)
40 (41)
33 (32)
37 (37)
36 (37)
37 (37)
34 (34)
37 (37)
38 (38)
34 (34)
34 (34)
39 (40)
37 (37)
34 (33)
43 (45)
37 (37)
35 (35)
30 (29)
38 (38)
37 (37)
35 (35)
34 (34)
36 (36)
38 (39)
34 (33)
35 (35)
35 (35)
35 (35)
40 (41)
34 (33)
35 (35)
37 (37)
33 (32)
37 (37)
38 (38)
36 (36)
36 (36)
35 (35)
34 (34)
34 (34)
37 (36)
38 (38)
37 (38)
34 (34)
30 (29)
28 (28)
32 (32)
27 (26)
29 (29)
38 (38)
26 (26)
38 (39)
31 (31)
32 (32)
38 (38)
31 (31)
37 (37)
36 (37)
34 (34)
34 (34)
35 (35)
37 (37)
33 (33)
36 (36)
37 (37)
35 (35)
33 (33)
44 (45)
38 (38)
35 (35)
29 (29)
35 (35)
38 (38)
35 (35)
34 (34)
34 (34)
39 (39)
31 (31)
35 (35)
36 (36)
30 (30)
38 (38)
32 (32)
33 (33)
36 (36)
33 (33)
37 (37)
37 (37)
36 (36)
35 (35)
33 (33)
34 (34)
33 (34)
36 (37)
37 (37)
38 (37)
32 (32)
30 (30)
Abbreviations: 1 Measurements of left (L) and right (R) height and width (in mm), 2 The subsample with known
hemisphere siding.
Symmetry 2021, 13, 1862
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Figure 4. The predicted height and width (in mm) for the R occipital lobe in the known subsample
with a confidence interval applied, calculated from the standard error of the regression.
4. 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.
Author Contributions: Conceptualization and methodology, R.H. and S.H.; measurements, G.B.;
Statistical analyzes, review and editing, A.P.; original draft preparation, S.H.; review and editing, S.H.
All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Symmetry 2021, 13, 1862
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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)).
Acknowledgments: The authors would like to thank Chet Sherwood & Aida Gomez-Robles for
providing access to the data for these chimpanzees and Antoine Balzeau for inviting us to participate
in this Special Issue.
Conflicts of Interest: The authors declare no conflict of interest.
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