PLoS ONEplosplosonePLOS ONE1932-6203Public Library of ScienceSan Francisco, CA USA10.1371/journal.pone.0129939PONE-D-15-00790Research ArticleOntogenetic Shape Change in the Chicken Brain: Implications for PaleontologyOntogenetic Shape Change in the Chicken BrainKawabeSoichiro12*MatsudaSeiji3TsunekawaNaoki4EndoHideki2Gifu Prefectural Museum, Gifu, JapanThe University Museum, The University of Tokyo, Tokyo, JapanDepartment of Anatomy and Embryology, School of Medicine, Ehime University, Ehime, JapanDepartment of Veterinary Anatomy, The University of Tokyo, Tokyo, JapanDodsonPeterAcademic EditorUniversity of Pennsylvania, UNITED STATES
The authors have declared that no competing interests exist.
Conceived and designed the experiments: SK SM. Performed the experiments: SK SM. Analyzed the data: SK HE. Contributed reagents/materials/analysis tools: SK SM NT HE. Wrote the paper: SK SM NT HE.
* E-mail: kawabe_soichiro@yahoo.co.jp8620152015106e0129939131201514520152015Kawabe et alThis is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Paleontologists have investigated brain morphology of extinct birds with little information on post-hatching changes in avian brain morphology. Without the knowledge of ontogenesis, assessing brain morphology in fossil taxa could lead to misinterpretation of the phylogeny or neurosensory development of extinct species. Hence, it is imperative to determine how avian brain morphology changes during post-hatching growth. In this study, chicken brain shape was compared at various developmental stages using three-dimensional (3D) geometric morphometric analysis and the growth rate of brain regions was evaluated to explore post-hatching morphological changes. Microscopic MRI (μMRI) was used to acquire in vivo data from living and post-mortem chicken brains. The telencephalon rotates caudoventrally during growth. This change in shape leads to a relative caudodorsal rotation of the cerebellum and myelencephalon. In addition, all brain regions elongate rostrocaudally and this leads to a more slender brain shape. The growth rates of each brain region were constant and the slopes from the growth formula were parallel. The dominant pattern of ontogenetic shape change corresponded with interspecific shape changes due to increasing brain size. That is, the interspecific and ontogenetic changes in brain shape due to increased size have similar patterns. Although the shape of the brain and each brain region changed considerably, the volume ratio of each brain region did not change. This suggests that the brain can change its shape after completing functional differentiation of the brain regions. Moreover, these results show that consideration of ontogenetic changes in brain shape is necessary for an accurate assessment of brain morphology in paleontological studies.
This work was supported by the Japan Society for the Promotion of Science 11J08692 & 26916003 (http://www.jsps.go.jp/english/e-grants/index.html). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Data AvailabilityAll relevant data are within the paper.Introduction
The organ shape of extant and extinct vertebrate animals changes during maturation or with increases in size, and the cranial part is of particular interest to many researchers [1–8]. The embryonic growth patterns of the brain and other organs in Aves are well described [9–11]. Early development of the chicken brain was first described by Kamon [12] and gross development of the chicken embryonic brain was described by Rogers [9]. Although many studies focused on the changes in brain volume and/or brain regions during maturation, including both embryonic and post-hatching growth [13–18], post-hatching changes in the shape of the avian brain due to growth are still poorly understood.
Recent paleoneurological studies have made positive progress and brains (cranial endocasts) of many species from various taxa have been analyzed from various angles using CT [19–28]. Nevertheless, interspecific or ontogenetic variations in the brains of fossil taxa have been rarely examined, since multiple specimens of one species or a close taxon are rarely obtained. Hence, paleontologists are usually forced to discuss the phylogeny or neurosensory development based on the brain morphology of an extinct species without consideration of the size or developmental stage of the specimen [24, 29–38]. Can we develop arguments on the brain morphology of extinct species without knowledge of the variation in the shape of the brain during growth? It is noted that brain shape changes considerably based on brain size in birds [39]. This indicates that brain size is important in assessing brain morphology in birds. That is, taking the developmental stage into account is essential when we evaluate the brain morphology of an extinct species. Smaller birds tend to have round, modern, avian-type brains, while larger birds show anteroposteriorly elongated, reptilian-type brains [39]. Given the pattern of shape change based on size, the brain of some species should change shape from the round to the anteroposteriorly elongated type during ontogeny. If that shape change is observed in a single species, then the brain changes its shape considerably during growth. We could incorrectly interpret two size differentiated brains from the same species as distinct species, leading to a misinterpretation of the morphology of the avian brain. Additionally, since the morphological characters that show ontogenetic change contain phylogenetic signals and can affect the results of phylogenetic analyses [40–43], it is imperative we know how avian brain shape changes during growth.
Since, in general, though not always the mass of the neural tissue of a particular region of the brain is correlated with the ability and/or sensory development of animals [44–48], comparisons of brain sizes of extant animals are used to estimate the degree of evolution of different sensory systems [44, 46]. Based on this principle, the relationships between the brain regional volume and sensory abilities of extinct birds and other animals were discussed in many studies [36, 49, 50]. As noted above, some previous studies measured the volumetric changes in brain regions based on growth in birds [13–18]. However, none investigated the covariation between the volume and shape of avian brains. In paleontological studies, the sensory and locomotor capability of extinct species are often assessed from the volume or area of brain regions [35, 37, 51]. However, all the primary data about brain that we can obtain from fossil specimens is external appearance of entire brain, and we had to judge the degree of development in brain regions from external information of brain.
The aims of this study were to quantitatively describe developmental shape changes in the chicken brain and to compare the growth pattern of each brain region with changes in brain shape during development. We also investigated the relationship between the volume and shape of brain regions. Since the relationship between the volume and shape of avian brains has not yet been investigated, it is unclear whether we can assess the cognitive abilities of extinct birds from the appearance of the brain. To achieve these aims, brain shape was compared among various developmental stages in the chicken using 3D geometric morphometric analysis and the growth rates of brain regions (telencephalon, diencephalon and mesencephalon, cerebellum, and myelencephalon) were evaluated using simple regression analysis to explore post-hatching morphological changes in the chicken brain.
Materials and MethodsChicken eggs
This study was carried out in strict accordance with the recommendations of the Guidelines of the Animal Care Committee of Ehime University. The protocol was approved by the Animal Care Committee of Ehime University (Permit Number: 05A-27-10). The broiler eggs were incubated at 38°C in a rocking, humidified incubator for 24 days. They were then manually turned several times per day. Forty-four eggs hatched in August 2011 and the chicks were raised for a maximum of 118 days (Table 1).
10.1371/journal.pone.0129939.t001
Volume of the brain, including eyes, brain, brain and eyes, telencephalon, dien- and mesencephalon, and cerebellum of sampled specimens.
Specimen ID
Day
Body weight (g)
Eyes (mm3)
Telencephalon (mm3)
Dien- Mesencephalon (mm3)
Cerebellum (mm3)
Myerencephalon (mm3)
Whole brain (mm3)
Eyes + Brain (mm3)
#1
119
5300
-
2216.875
994.5811
588.4555
201.2268
4001.139
-
20
282
-
685.255
343.3328
175.4841
55.11907
1259.191
-
#2
26
752
1533.867
1286.919
477.0751
273.0119
81.52103
2118.527
3652.394
15
286
1095.275
737.231
362.7126
265.9438
115.0294
1480.917
2576.192
#3
34
1140
1606.663
1229.209
617.3489
331.4657
137.6827
2315.706
3922.369
16
264
1234.698
799.3646
391.8207
242.8153
107.762
1541.763
2776.461
#4
22
436
1334.28
1176.198
429.1162
275.672
79.7655
1960.752
3295.032
17
286
-
906.6819
431.7303
237.4183
82.42563
1658.256
-
7
88
-
559.0485
262.747
146.744
62.24085
1030.78
-
#5
91
5500
-
2240.134
1042.686
711.5726
204.6842
4199.077
-
15
328
-
794.4812
441.9108
303.8449
92.30719
1632.544
-
11
202
987.7967
739.7763
334.4708
228.5717
108.13
1410.949
2398.745
2
48.2
-
517.3658
257.5618
145.2118
49.6468
969.7863
-
#6
34
1010
-
1352.357
491.6407
405.451
85.3164
2334.765
-
16
312
1092.37
722.5275
334.2332
227.7131
111.8327
1396.306
2488.676
#7
116
7400
5142.16
2312.18
1126.583
744.4218
340.458
4523.643
9665.802
13
268
1335.116
628.5874
355.1002
201.8324
115.7501
1301.27
2636.386
11
208
964.1316
598.1609
335.3371
218.9968
109.4562
1261.951
2226.083
1
51
-
489.6003
265.8774
148.6873
54.2146
958.3795
-
#8
20
470
1286.858
993.4312
427.0233
273.4105
96.30122
1790.166
3077.024
7
132
795.7233
582.1387
289.1413
200.3375
109.3489
1180.966
1976.69
2
56.6
595.4765
510.5206
243.49
143.5814
80.04221
977.6342
1573.111
1
55.2
711.1449
541.3035
249.6146
145.7596
73.52684
1010.204
1721.349
#9
35
1380
1971.116
1628.029
569.2136
358.8872
153.7968
2709.926
4681.043
#10
38
1910
1891.167
1449.371
657.1665
407.3291
143.8615
2657.728
4548.895
#11
40
1450
1898.25
1455.067
571.1915
420.9978
155.9203
2603.176
4501.427
#12
86
4960
5542.183
2395.319
967.382
629.653
308.4215
4300.775
9842.958
#13
94
6000
5486.382
2397.726
1008.74
593.4998
251.9072
4251.873
9738.255
#14
15
258
1259.551
811.0093
411.7908
238.2079
133.4894
1594.497
2854.049
#15
46
2160
2897.04
1696.694
698.5325
483.3612
206.9533
3085.541
5982.58
#16
20
450
1274.362
898.3335
392.0201
244.0494
137.3454
1671.748
2946.111
#17
42
1580
1931.73
1756.03
724.75
611.26
223.66
3315.7
5247.43
#18
26
698
1563.181
1176.528
474.415
292.4377
143.0413
2086.422
3649.603
#19
119
5200
2386.089
1864.205
854.2535
628.6717
124.7347
3471.865
5857.954
#20
32
1060
1603.704
1326.507
450.4125
348.0704
146.6827
2271.672
3875.377
#21
84
4700
-
1991.776
1060.793
710.4534
115.7807
3878.803
-
#22
13
124
793.0706
553.0153
224.7003
153.9424
78.00996
1009.668
1802.739
#23
30
780
1765.857
1249.248
526.8356
304.4888
124.0984
2204.671
3970.528
#24
33
990
1960.522
1389.039
576.2204
381.7245
135.6895
2482.673
4443.195
#25
24
562
-
946.8904
365.1811
206.7157
66.54919
1585.336
-
#26
8
150
834.3523
655.7941
327.9623
192.7327
92.4835
1268.973
2103.325
#27
14
292
1228.236
646.4417
378.0371
176.2891
84.07384
1284.842
2513.077
#28
12
250
-
755.5146
396.7193
235.7088
87.64622
1475.589
-
#29
5
66.2
723.5254
553.1523
260.8034
162.1793
48.1637
1024.299
-
#30
20
460
-
950.5855
406.9995
249.0784
77.49634
1684.16
-
#31
16
300
-
674.9442
298.2716
135.4672
45.2145
1153.897
-
#32
10
148
-
538.2504
264.4796
168.3853
71.91544
1043.031
-
#33
18
342
-
705.9381
301.3073
172.8546
49.79115
1229.891
-
#34
30
950
1726.883
1230.681
518.3032
293.258
143.6545
2185.896
3912.779
#35
32
970
-
1205.705
528.6908
421.8794
205.3434
2361.618
-
#36
22
560
1587.874
1168.908
478.7617
251.2326
89.5934
1988.495
3576.369
#37
28
686
-
1145.948
472.1611
340.159
85.89069
2044.159
-
#38
36
1160
2038.11
1372.135
509.3799
337.3302
114.0405
2332.886
4370.996
#39
35
1390
2272.37
1710.025
570.8695
434.0684
216.6279
2931.591
5203.96
#40
75
3000
3159.385
2212.237
938.9714
739.5308
177.9679
4068.707
7228.092
#41
30
940
-
1353.783
502.8561
349.8643
117.8582
2324.361
-
#42
4
68
589.8324
510.5782
276.2558
145.01
62.36681
994.2108
1584.043
#43
24
606
-
1052.859
418.9663
240.1014
90.32935
1802.256
-
#44
28
714
-
1183.389
516.2258
318.3184
97.02183
2114.955
-
μMRI and image acquisition
μMRI is a non-invasive method that allows for the differentiation of major brain regions from each other. Furthermore, it permits repeated viewing of the same living specimen. Hence, μMRI was used to acquire in vivo volumetric data and data from post-mortem chicken brain and eyes. μMRI was performed using a 1.5-T, MRmini SA (MRTechnology, Inc) at Ehime University (Toon, Japan). Both 30 and 38.5 mm diameter RF coils were used based on the size of the chicken. During scanning, the birds were anesthetized with isoflurane using a gas anesthesia system. When they reached the opening of the MRI apparatus, they were beheaded, and only the heads were scanned by MRI. That is, the decapitation had been at the final growth stage in each development. Images used to create the 3D chicken brain model were recorded using 3D spin-echo sequence mode acquisition, with a data matrix of 512 × 256 × 128 points (Fig 1).
10.1371/journal.pone.0129939.g001
MRI images acquired by μMRI, MRmini SA (MRTechnology, Inc).
Identified brain regions (telencephalon, diencephalon and mesencephalon, cerebellum, and myelencephalon) and eyes were manually labeled using the segmentation tools available in the Amira visualization software (v 5.3.2, Mercury Computer Systems, San Diego, CA, USA). The 3D models were created and brain volumes were calculated by using Amira visualization software. Details of the methods used to prepare and examine the 3D models were previously described by Corfield et al. [52].
3D geometric morphometrics
The 3D coordinates from 20 homologous landmarks of the brain were digitized (Table 2, Fig 2) from 43 specimens using Amira. Five of them (#1 to #8; Fig 3) were scanned several times at different developmental stages. The resulting 3D coordinate data set was subjected to generalized Procrustes analysis (GPA; [53]) using the MorphoJ software package [54]. In GPA, distances between homologous landmarks are minimized by translating, rotating, and scaling all objects to a common reference. That is, the effects of size, position, and orientation are eliminated so that remaining data reflect shape variation (Procrustes shape coordinates). Information on the absolute size of the specimen is preserved as centroid size (CS), which is calculated as the square root of the sum of squared distances of landmarks from their centroids [55].
10.1371/journal.pone.0129939.g002
The three-dimensional brain landmarks used for shape analysis shown in dorsal (upper) and right lateral (lower) views.
10.1371/journal.pone.0129939.g003
Ontogenetic shape variations (#1 to #8) (not to scale).
10.1371/journal.pone.0129939.t002
Landmarks used (Fig 2) and anatomical descriptions (refer to Fig 2) for profiled anatomical structures.
Number
Anatomical description
1
Median anterior tip of the telencephalon
2
Median junction between the telencephalon and cerebellum
3
Median dorsal point of the foramen magnum
4
Median ventral point of the foramen magnum
5
Median junction between the mesencephalon and myelencephalon
6
Median junction between the hypophysis and mesencephalon
7
Median ventral tip of the hypophysis
8
Median point where the two optic nerves intersect
9
Median junction between the telencephalon and mesencephalon
10
Perpendicular at midpoint between landmarks 2 and 3 to dorsal margin of cerebellum in lateral view
11, 12
Perpendicular at midpoint between landmarks 1 and 2 to dorsal margin of telencephalon in lateral view, right and left
13, 14
Most lateral point of the widest part of the telencephalon, right and left
15, 16
Most lateral point of the widest part of the floccular lobe, right and left
17, 18
Intersection of the telencephalon, cerebellum, and optic lobe, right and left
19, 20
Intersection of the cerebellum, myelencephalon, and optic lobe, right and left
Principal component analysis (PCA)
Procrustes shape coordinates were subjected to PCA to explore the patterns of major variation among chicken brains at various developmental stages (sizes) (Fig 4). The proportion of total variance contributed by each PC and the cumulative total for the first 10 PCs from the PCA are provided in Table 3. PCA was performed using MorphoJ, and Morphologika was used to illustrate the 3D profiles [55]. The scores of specimens along the PC axes and log CS were subjected to correlation and regression analyses to examine the effect of aging, namely, the effect of increasing size on brain shape (Table 4, Fig 5). Regression analysis was performed to determine whether size alone was responsible for the differences in shape observed along the PC axes. Regression coefficients are vectors representing the correlations between changes in shape and size. To explore how shape varies with growth, multivariate regressions of brain shape onto brain volume were performed (Fig 6). Statistical significance was tested using a permutation test against the null hypothesis of size independence.
10.1371/journal.pone.0129939.g004
PCA and variation in brain shape for each principal component (PC) score.
10.1371/journal.pone.0129939.g005
Regression analysis of PC1 on log centroid size.
10.1371/journal.pone.0129939.g006
Multivariate regression of brain shape coordinates on log centroid size.
10.1371/journal.pone.0129939.t003
Eigenvalues and explanatory proportion for the first 10 principal components (PCs) from the principal component analysis.
PC
Eigenvalue
Proportion (%)
Cumulative (%)
1
0.00280665
23.383
23.383
2
0.00186082
15.503
38.885
3
0.00103005
8.581
47.467
4
0.00094377
7.863
55.33
5
0.0008114
6.76
62.089
6
0.0006503
5.418
67.507
7
0.00052655
4.387
71.894
8
0.00045568
3.796
75.69
9
0.0004347
3.622
79.312
10
0.00033285
2.773
82.085
10.1371/journal.pone.0129939.t004
Results of the correlation (r) and regression (R2, P) analysis between the PC scores and log centroid size (CS).
PC1
PC2
PC3
PC4
CS
r
0.5259
0.2128
0.2296
-0.0224
R2
0.2766
0.0453
0.0527
0.0005
P
<0.0001
0.1709
0.0313
0.9847
Growth rate
To explore the relationship between the growth of the brain and shape, the logarithmic volume of each brain region (telencephalon, diencephalon and mesencephalon, cerebellum, and myelencephalon) and both eyes were regressed on the log of body weight (Fig 7). Chickens were weighed on a scale before MRI scanning.
10.1371/journal.pone.0129939.g007
Relationship between body weight and eyes + brain (dark green circles), whole brain volume (brown triangles), eyes (light green circles), and brain regions (telencephalon, red triangles; cerebellum, yellow squares; diencephalon and mesencephalon, blue diamonds).
Results
The first three PCs from the PCA analysis accounted for 47.47% of the total shape variation and provided a reasonable approximation of the total variation in shape (Table 3; Fig 4). Since PC1 and PC2 were the only PC axes that accounted for more than 10% of the variance (Table 3; Fig 4), the following descriptions and discussions will be based on these two PCs.
The telencephalon rotates caudoventrally with increasing PC1 score (Fig 4). This change in shape leads to a relative caudodorsal rotation of the cerebellum and myelencephalon. With increasing PC1, all brain regions elongate rostrocaudally, which results in a more slender brain shape. In particular, the optic nerves elongate rostrodorsally. This extension of the optic nerve indicates that the orbit has a tendency to be located more caudally.
The PC2 axis mainly corresponds to lowering of the cerebellum (Fig 4). The telencephalon and myelencephalon change their posterior orientation under the influence of the rotation of the cerebellum.
Since PC1 explained a considerable degree of the shape variation, the shape change accompanying brain growth can be summarized as shape change with increasing PC1 score (Fig 4). The correlation between the PC1 score and log centroid size (CS) was significant (r = 0.5289, P < 0.001; Table 4, Fig 5). Thus, brain shape along the first dimension was affected by increases in size (Fig 5). The multivariate regression analysis of shape against size explained 20.20% of the shape variation and it revealed that the correlation between shape and size is significant (p < 0.001; Fig 6). Comparing larger brains to smaller brains (lower right to upper left in Fig 6), the length of the telencephalon and myelencephalon varies quite substantially. In addition, the optic nerve tends to elongate and rotate rostrodorsally with increasing brain size. These shape changes correspond to positive changes along the PC1 axis (Figs 3 and 5). That is, the ontogenetic changes of the brain are accurately reflected in these two patterns of shape change.
The growth rates for each brain region were constant and the slopes of the growth formula were parallel (Fig 7). However, eye size was relatively large, indicating that the eye exhibits tachyauxesis against the entire brain (Fig 7).
DiscussionShape change
Changes in brain shape during post-hatching development in chickens can be described by positive shape changes in the PC1 axis and multivariate regression. The dominant pattern of shape change was as follows: (1) caudoventral rotation of the telencephalon, (2) caudodorsal rotation of the cerebellum and myelencephalon, (3) rostrocaudal elongation of the entire brain, and (4) extension of the optic nerve in the rostrodorsal direction (Figs 3 and 5). We explored the relationship between brain shape and brain size in Aves using various taxa (60 species from 22 orders) and discovered the dominant allometric shape change [39]. Brain posture and relative brain length dramatically change based on brain size in Aves [39]. The ontogenetic pattern of shape change described above (1)–(3) corresponds to interspecific shape changes with increasing brain size [39]. That is, the intraspecific and interspecific ontogenetic changes in brain shape with increasing size display similar patterns.
The anteriorly elongated optic nerve orients the eyeball and orbit more rostrally. The covariation pattern between brain shape and orbital shape was also discussed in Kawabe et al. [39]; the rostrally elongated orbit has a rostrocaudally elongated brain. In light of the covariation between brain shape and orbital shape described in Kawabe et al. [39], the orbital shape changes from a round type to an elongated type during growth.
Although PC1 explained most of the variation in shape change, the contribution from PC2 was relatively high (Fig 4) and was concentrated mainly in the cerebellum. The shape of the cerebellum is relatively variable due to factors other than size. Plots of each male and female were not deflected to one side of the PC2 axis (Fig 4). Hence, sexually dimorphic variation among brain shape in chickens is vanishingly small. Since the PC2 score did not significantly correlate with size (Table 4) and did not reflect sexual dimorphism (Fig 4), the shape change based on the PC2 axis reflects individual variability other than ontogeny and sexual dimorphism.
Size change
The chicken is precocial bird [56–58] and negative allometry was found in the brains of the broiler chickens used in this study (Fig 7). Previous studies also found negative allometry in many precocial bird species, including some domestic chickens [17, 18, 59–63]. This negative allometry is due to slow post-hatching brain growth [63]. Although the brains of the broiler chickens had a slope (exponent of 0.335) similar to many precocial birds, the slope of the birds in this study is relatively low compared to mallards, ducks [61, 63], and other precocial birds [59, 60, 61]. It is thought that the rapid growth and heavy body of the broiler [64, 65, 66] lowers the allometric slope of the brain and each brain region. However, compared to white leghorns [17], and other domestic chickens [18], the allometric slope of the broiler is relatively high for the brain and each brain region, even considering the slight differences in the brain regional borders between previous works and this study. The slopes of the brain and each brain region are ~0.25 or lower in every domestic chicken [17, 18], except the broiler. This indicates that the brain and each brain region in the boiler grows relatively rapidly compared to other chickens, but slowly compared to many other precocial birds. Further studies are needed to determine the effect of such differences in growth rate on brain morphology in various domestic chickens and other avian taxa.
The similar brain growth rate in the brain regions of chickens is due to differences in growth pattern, i.e. the differences between the precocial and altricial patterns. One of the most striking observations is the substantial difference in chick and adult brain sizes of altricial and precocial birds [62]. The difference in brain volume between precocial and altricial species is well known [13, 62, 67, 68]. All precocial species and some altricial species almost complete brain growth during embryogenesis, hatch with relatively large brains, and undergo little brain growth development from chick to adult [62]. On the other hand, hence the brains of many altricial birds considerably increase in size after hatching compared with those of precocial birds [63], the brain regions of altricial birds are supposed to develop at a different rate after hatching. It is thought that functional differentiation of each brain region in chickens is nearly complete by hatching and this leads to similar growth rates among each brain region.
There was a significant positive relationship between eye size and body size (Fig 7). Additionally, it was found that eyes grow at a faster rate than the brain. Garamszegi et al. [69] calculated the allometric relationship of eye size and brain size to body size from 141 and 159 bird species, respectively. Interspecific allometric equations for eye size and brain size on body mass showed that the avian eye exhibits tachyauxesis against the brain [69] and are consistent with our results from the ontogenetic analysis. This indicates that the rapid growth of the chicken eye is a simple matter of allometric relationships, not functional development through growth.
Relationships between shape and size
The shape of the brain and each brain region changed considerably; however, the volume ratio of each brain region did not change (Fig 7). That is, the brain can change its shape without variation in the proportional and relative sizes of brain regions in post-hatching growth. Distinct functions are localized within the brain [70] and the relative size of each brain region is indicative of their importance in the life of the animal [44]. Therefore, it would appear that functional changes of the brain already modestly advanced at hatching, since the relative sizes of the brain regions do not change throughout its life. In other words, the brains of chickens change shape after measurable functional differentiation of the brain regions, although we could not identify changes in the morphological characters that relate to function based on the ontogenetic shape differences.
Implications for paleontology
As discussed above, we assumed that functional differentiation of the brain in precocial birds, including chickens, is nearly complete by hatching, since the ratios of the brain regions were constant throughout growth. Many non-avian dinosaurs, which are avian ancestors and relatives, are thought to have been precocial [71, 72] and differentiation of their brains is probably complete at hatching, judging from the developing pattern. Thus, the brains of dinosaurs should show roughly similar ontogenetic changes to extant precocial birds, including chickens. The growth process of non-avian theropods leads to a more rostrocaudally elongated brain; indeed, this has been observed in some fossil specimens [73]. Hence, when we compare brain endocasts of the same extinct species, we have to pay due consideration to allometric relationships. Otherwise, we could develop fallacious arguments about fossil animals.
We also concluded that it is difficult to recognize functional development from brain and eye shape in the development of chickens. Brain regions showed no relative volumetric change, though their shape changed considerably. Many studies have discussed the sensory and locomotor abilities of extinct animals by assessing the relative size of individual brain regions based on their appearance in endocasts of fossil specimens [24, 29–38]. However, according to our results, it is not necessarily appropriate to suggest that the relative sizes of brain regions can be determined from external morphology. Since the interior boundaries of the brain regions are indefinable from extinct brain endocasts, we cannot determine the exact value of the regional volume in the brain of an extinct species. Despite these limitations, paleontologists have attempted to calculate the volume or area of the brain regions of extinct avian species [51, 74, 75]. Although we need to establish whether the volume of brain regions significantly correlates with area, assessing the brain morphology of extinct species in these quantitative ways has enormous implications for paleoneurological studies.
Conclusions
We assessed the ontogenetic changes in the brain shape of chickens using μ MRI. The dominant pattern of shape change was as follows: (1) rostrodorsal rotation of the telencephalon, (2) caudoventral rotation of the cerebellum and myelencephalon, (3) rostrocaudal elongation of the entire brain, and (4) extension of the optic nerve in a rostroventral direction. The pattern of these shape changes corresponds to interspecific shape changes due to increases in size. The interspecific and ontogenetic shape changes with increasing size exhibit similar patterns. Not all of the shape variation can be explained by size. The variations that cannot be explained by size are concentrated in the cerebellum. Changes in brain shape were also observed with no change in the ratio of individual brain regions. Growth of brain regions at the same rate as other regions is due to the nearly complete functional differentiation of the brain at hatching. Therefore, we concluded that it is difficult to recognize functional development from brain and eye shape in the development of chickens. A detailed analyses of the brain morphology in other taxon including palaeognathous birds is needed to address the universal rule of the ontogenetic shape change in avian brain, and this study is the starting point for understanding changes in brain shape during post-hatching development in birds. This work, however, provides an important particular case of the ontogenetic shape change, and is critical for future work on the avian brain morphology.
We thank Dr. Eiichi Izawa (Keio University) for his helpful advice, Koji Nomaru (Nagoya University) and the staff of the Integrated Center for Sciences Shigenobu Station, Ehime University for access to the MRI scanner, and Kumiko Matsui (The University of Tokyo) for providing useful information. We wish to thank Stig A. Walsh (National Museum Scotland) and an anonymous reviewer, and the editor Peter Dodson (University of Pensylvania), for greatly improving this manuscript.
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