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Interpretacion bases neuroanatomicas y funcionalesTRANSCRIPT
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Brain Behav Evol 2014;84:117–134 DOI: 10.1159/000365276
Endocasts: Possibilities and Limitations for the Interpretation of Human Brain Evolution
Simon Neubauer
Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig , Germany
Introduction
Our specialized cognitive and behavioral abilities largely determine what makes us human. The brain as the organ responsible for our mind is therefore of special in-terest to scientists of various fields who study the evolu-tion of our own species. Neuroscientists study brain mor-phology from micro- to macroscopic levels using diverse techniques, including brain imaging and histological ex-amination [Passingham et al., 2002; Semendeferi et al., 2002; Sherwood et al., 2006; Charvet et al., 2011; Bianchi et al., 2013a, b; Charvet et al., 2013; Teffer et al., 2013]. Geneticists attempt to disentangle the genetic differences between humans and our closest relatives and, given the similarities of genetic sequences, how gene expression and regulation contribute to our human uniqueness [Somel et al., 2009; Konopka et al., 2012; Somel et al., 2013; Wang and Konopka, 2013]. Primatologists and psy-chologists investigate and compare behavior, cognition and their development in humans, great apes, monkeys and other animals, both in natural habitats and in exper-imental settings [Whiten et al., 1999; Chandrasekaran et al., 2011; Hamann et al., 2011; Schmelz et al., 2011; Luncz
Key Words
Hominin brain evolution · Endocast · Paleoneurology · Computed tomography scans · Geometric morphometrics · Evo devo
Abstract
Brains are not preserved in the fossil record but endocranial casts are. These are casts of the internal bony braincase, re-vealing approximate brain size and shape, and they are also informative about brain surface morphology. Endocasts are the only direct evidence of human brain evolution, but they provide only limited data (‘paleoneurology’). This review dis-cusses some new fossil endocasts and recent methodologi-cal advances that have allowed novel analyses of old endo-casts, leading to intriguing findings and hypotheses. Theinterpretation of paleoneurological data always relies on comparative information from living species whose brains and behavior can be directly investigated. It is therefore im-portant that future studies attempt to better integrate differ-ent approaches. Only then will we be able to gain a better understanding about hominin brain evolution.
© 2014 S. Karger AG, Basel
Published online: September 20, 2014
Simon Neubauer Department of Human Evolution, Max Planck Institute for Evolutionary Anthropology Deutscher Platz 6 DE–04103 Leipzig (Germany) E-Mail simon.neubauer @ eva.mpg.de
© 2014 S. Karger AG, Basel0006–8977/14/0842–0117$39.50/0
www.karger.com/bbe
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et al., 2012; Wobber et al., 2014; Ghazanfar, 2013]. These approaches study intra- and interspecific variation of contemporary living individuals.
Paleoanthropologists, in contrast, use fossil remains of past human species to interpret our evolutionary history. Unfortunately, brains are not preserved in the fossil re-cord. However, endocasts, i.e. casts of the internal table of the bony braincase, reveal approximate brain size and shape, sometimes reproducing convolutional details of the brain [Holloway, 1978; Falk, 1980a, 1987; Holloway et al., 2004a; Falk, 2012]. Other anatomical modifications provide further evidence about the evolution of the brain and our cognition, for example changes of the vocal tract that are related to speech production and thereby lan-guage [Lieberman et al., 1992; Barney et al., 2012], or morphological changes of the hands that are indicative of tool making and use [Tocheri et al., 2007, 2008; Kivell et al., 2011; Tsegai et al., 2013]. Similarly, archaeologists study material remains of past societies and thereby the evolution of cognitive and behavioral capabilities that were rendered possible by the evolving brain [Chase and Dibble, 1987; Klein, 2000; McBrearty and Brooks, 2000; d’Errico, 2003; McPherron et al., 2010].
It is a paradox that hominin fossils provide the only direct evidence of human brain evolution, while the kinds of data available from endocasts are relatively limited. On the other hand, the comparative analyses among living species as mentioned above provide high-quality data about the brain on different levels. However, while ana-lytical methods of ancestral state reconstruction can help infer evolutionary processes, the actual data do not di-rectly capture information about the events in our evolu-tionary lineage itself.
To gain a better understanding about human brain evolution it is therefore key to integrate different ap-
proaches and various sources of data. Doing so is a huge challenge because the data based on brains and endocasts, respectively, are very different in nature. This review at-tempts to summarize methodological advances and pa-leoneurological findings of recent years and bring them to the attention of researchers from other fields to boost future integrative research.
Paleoneurology: Brains and Endocasts
Endocasts ( fig. 1 ) can be used to analyze differences and changes in brain size, brain shape and surface mor-phology, including imprints of sulci and gyri (‘paleoneu-rology’) [Holloway, 1978; Falk, 1980a, 1987; Holloway et al., 2004a]. When the bony braincase is filled with sedi-ment during fossilization, morphological information about the brain may be conserved as a natural endocast while the neurocranial bone itself disappears. The Taung child (an Australopithecus africanus individual datedto have lived about 2.6–2.8 million years ago [McKee, 1993]), for example, includes a natural endocast that was very important for Raymond Dart’s [1925] initially con-troversial interpretation that this South African fossil was an early ape-like human relative. For fossils that do not preserve a natural endocast, one can apply molding mate-rial to the air-filled endocranium to generate an artificial one [Holloway et al., 2004a]. In recent years, virtual en-docasts ( fig. 1 , 2 ) have been generated based on computed tomography (CT) data, reducing the risk of harming the fossils during molding and opening up new possibilities for digital reconstruction and analyses [Falk, 2004; Zol-likofer and Ponce de Leó n, 2005; Weber and Bookstein, 2011]. It is important to point out that an endocast, no matter if formed naturally or produced synthetically, is
a b
Fig. 1. Based on CT scans, virtual endocasts can be generated within the computer en-vironment. Here, the endocasts and trans-parent cranial bones of a chimpanzee ( a ) and Sts 5, an early hominin (A. africanus) from Sterkfontein, South Africa ( b ), are shown as examples. The relationship to the endocranial bones is never lost when using digital data and the original individuals are not harmed during endocast generation. These advantages are especially important when reconstructing fragmentary fossil en-docasts.
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not a fossilized brain, but rather a cast of the endocranial cavity. The brain is surrounded by meninges and theneurocranial cavity also contains cerebrospinal fluid, blood vessels and nerves. For example, cerebrospinal flu-id takes up approximately 10% of the endocranial volume [Rengachary and Ellenbogen, 2005], but this proportion changes with age [Wanifuchi et al., 2002] and there are differences between species in the degree of brain shrink-age with aging [Sherwood et al., 2011]. Intracranial com-ponents contribute to the ultimate form of an endocast and some of them may be reproduced on the endocranial surface, such as intracranial venous sinus, for example.
This fact appears disadvantageous on the one hand for obtaining a direct view of the brain’s surface, but menin-ges play an important role for the meaning of endocasts
on the other hand. Developmentally, the brain is enclosed by endo- and ectomeninx [Sperber, 1989]. While the en-domeninx forms the pia and arachnoid mater, the ecto-meninx forms the dura mater and also contributes to en-docranial bone formation [Moss and Young, 1960; Sper-ber, 1989]. According to the functional matrix hypothesis [Moss and Young, 1960; Moss, 1962], the development of the neurocranial bones is caused by the demands of the growing brain. More specifically, the brain generates ten-sion within the neurocranial bones, especially via two folds of the dura mater, the falx cerebri and the tentorium cerebelli, and the neurocranial bones respond to this ten-sion by osteoblast deposition, drift and endochondral growth [Moss and Young, 1960; Moss, 1962; Duterloo and Enlow, 1970; Schoenemann et al., 2000]. Since growth
a b c
d e f
Fig. 2. The virtual endocast of MLD 37/38 (A. africanus) as an ex-ample of the possibilities of digital data. a–c The top row illustrates the digital copy of the matrix-filled cranium that is missing its face and frontal neurocranium before digital processing ( a ), after elec-tronic preparation ( b ; endocast in blue; colors refer to the online version only), and after mirror imaging to estimate the missing regions preserved on one but not the other side ( c ). d–f The bot-
tom row illustrates two different reconstructions of the endocast, based on a human ( d ) and a chimpanzee endocast ( e ); the two al-ternative reconstructions are superimposed ( f ) to highlight the dif-ferences caused by the shape differences of the reference individu-als (preserved endocast parts of MLD 37/38 are shown in gray; green depicts the chimpanzee-based and blue the human-based reconstruction). See Neubauer et al. [2004; 2012b] for more details.
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and development of the brain and the bony braincase are so tightly related, the size and shape of an endocast di-rectly reflects the form of the brain, although it is not a precise copy. This is the essence of ‘paleoneurology’ that highlights both its promising possibilities and its limita-tions.
What Fossil Endocasts Can (and Cannot) Tell Us
The discovery of each new fossil endocast provides an-other glimpse into human brain evolution and sometimes a new astonishing perspective. The following section is devoted to some important fossils that have been uncov-ered and published in roughly the last 10 years, and dis-cusses what kinds of information endocasts can and can-not supply.
Probably the most unexpected discovery was that of a small-bodied hominin that lived quite recently, until at least 18,000 years ago, on the island of Flores in Indonesia [Brown et al., 2004; Morwood et al., 2004]. Not only was body size small in this past population, but so was brain size, as documented by the individual labeled as LB 1. Its relatively well-preserved cranium has an endocranial vol-ume estimated at 417 ml [Falk et al., 2005], which is in the range of modern great apes. Its encecphalization quotient (i.e. relative brain size measured as the ratio between ac-tual brain mass and predicted brain mass for a given body size) was estimated to range between 2.5 and 4.6, which is lower than for modern humans, but overlaps with oth-er early Homo species and the australopithecine range of variation [Brown et al., 2004]. Brown et al. [2004] sug-gested that the small brain and other primitive features in combination with derived features merit the description of a new species, H. floresiensis . Until the publication of the Flores fossils, it was generally thought that 18,000 years ago H. sapiens was the only existing hominin spe-cies, and that these human individuals had brain sizes comparable to modern individuals.
Homo floresiensis challenges the interpretation that brain size is related to cognitive and behavioral capabili-ties. In general, empirical data support the claim that there is some relationship between brain size and brain function. The human brain is over three times larger than would be expected for an anthropoid primate of our body size [Falk, 1980a; Rilling and Insel, 1999] and at the same time humans have a very large and excessively variable suite of complex behaviors. Furthermore, there is an overall trend of increasing brain size during hominin evo-lution, no matter if absolute brain size or brain size in re-
lation to body size (that increased as well during evolu-tion) is investigated [Ruff et al., 1997; Holloway et al., 2004a]. This trend seems to include periods of rapid size increase and periods of stasis, but this could be due to the patchy nature of the fossil record. However, overall the evolutionary brain size increase coincides with an in-crease of technological sophistication, as seen from the archeological record. It is therefore usually interpreted to depict behavioral changes and probably increases in cog-nitive capabilities [Holloway et al., 2004a; Klein, 2009]. That is not to say that sporadic evidence conflicts with this trend, such as cut marks that suggest butchery by A. afarensis in Ethiopia as early as 3.4 million years ago, for example [McPherron et al., 2010]. Stone tool artifacts that can be associated with H. floresiensis have been inter-preted as too advanced to be produced by hominins with such a small brain [Jacob et al. 2006; Martin et al. 2006], but others have claimed that these artifacts were similar to Oldowan tools manufactured by African small-brained hominins about 1.2–1.9 million years ago [Morwood et al., 2004; Brumm et al., 2006; Moore and Brumm, 2009]. Interestingly, the reduction sequence deployed by H. flo-resiensis seems to have also been used by later H. sapiens in the region, who then integrated technological add-ons [Moore et al., 2009].
Similarly, the small brain has been interpreted contro-versially. Several authors [Jacob et al., 2006; Martin et al., 2006; Hershkovitz et al., 2007; Vannucci et al., 2011, 2013] have argued that the individuals from Flores are not members of a previously unknown hominin species, but in fact modern humans suffering from various patholo-gies, including microcephaly. However, accepting this in-terpretation still does not explain that this population seems to have produced and used more or less sophisti-cated stone tools. Moreover, detailed analyses of endocra-nial morphology [Falk et al., 2005, 2007, 2009] and (ex-ternal) neurocranial shape [Baab and McNulty, 2009; Baab et al., 2013] provide growing evidence that, its small size aside, LB 1 is different from humans with microceph-aly and several other pathologies but, in brain shape, rath-er resembles H. erectus , the first member of our genus that moved out of Africa before 1.9 million years ago, and also manifests numerous derived features across the entire surface of the cerebral cortex. Along these lines, H. flore-siensis is interpreted as either a descendant of H. erectus that underwent endemic dwarfing, or as having shared an earlier common ancestor with H. erectus that survived far longer than any other hominin species besides H. sapiens .
The H. floresiensis fossils are fascinating and were an unexpected discovery that changed some views on hom-
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inin brain evolution. However, we are left with more questions than new knowledge about the evolution of our brain. Among the data that can be gleaned from endo-casts, brain size is the variable that can be estimated the easiest and, therefore, endocranial volumes are heavily relied upon when interpreting the fossil record. It is im-portant to note that (single) endocranial volumes from the fossil record should not be overinterpreted, despite the general trend of increasing brain size that is associ-ated with increases in sophistication of cognition and be-havior. In this context, other research fields might bring new insights about the relationship of brain size and ‘in-telligence’, for example, what brain size tells us about the quantity and quality of neurons and neural connections that seem to be more important for brain function than brain size alone [Hofman, 2012]. The scaling relationship between brain size and the number of neurons in pri-mates and rodents of similar brain size, for example, is different [Herculano-Houzel et al., 2007], and Hercula-no-Houzel [2009, 2011, 2012] argues that the absolute number of neurons is far more meaningful to interpret cognitive abilities than brain size and encephalization in-dices that relate brain size to body size.
A. sediba is another recent discovery of a new hominin species [Berger et al., 2010]. This South African australo-pithecine lived about 2 million years ago and has several derived features that link it to early Homo . The holotype, MH 1, includes a partial cranium that is partly filled with sediment. Its endocranial volume (420 ml) is comparable to another, nearly contemporaneous species from South Africa (A. africanus) and in the range of recent great apes [Berger et al., 2010; Carlson et al., 2011]. However, Carl-son et al. [2011] suggested that imprints of the frontal sulcal pattern foreshadow modern human features. Spe-cifically, these authors interpreted a distinct ventrolat-eral bulge in the region of the left inferior frontal gyrus anterior to the fronto-orbital sulcus as an intermediate stage in the emergence of a modern human frontal oper-culum.
This interpretation is reminiscent of previous discus-sions about the timing and order of evolutionary brain size increase and brain reorganization in hominins [Falk et al., 2000; Holloway et al., 2004a]. The discussions most-ly used the position of the lunate sulcus to argue for or against brain reorganization before a major increase in brain size [Falk, 1980b; Holloway, 1984; Falk, 1985; Hol-loway, 1985; Falk, 1989]. This sulcus, situated in the oc-cipital lobe, is clearly visible in apes and lies in an ante-rior location, while in humans it is located more posteri-orly, if observable. The position of the lunate was discussed
controversially for A. africanus , and more specifically for the Taung child. Holloway [1984, 1985] argued that the lunate sulcus was located posteriorly in Taung, implying a relative reduction of primary visual cortex and a relative increase of adjacent posterior parietal association corti-ces. Most interestingly, this implies evolutionary brain re-organization before a major increase in brain size. Falk [1980b, 1985, 1989], on the other hand, interpreted the endocranial surface features to display an ape-like ante-rior position of the lunate sulcus. Similarly, Falk [2014] and Holloway [2004b] do not agree on the position or even the identification of the lunate sulcus on the endo-cast of StW 505, another A. africanus specimen. However, Falk et al. [2000] and Falk [2012, 2014] agree that austra-lopithecines had reorganized brains before a major in-crease in brain size, but that this might be apparent more globally and not as localized as seen from the position of one sulcus.
In addition to the controversy about the location of the imprints of the lunate sulcus, another issue needs to be solved prior to being able to adequately interpret this po-tential evidence for brain reorganization in the hominin fossil record. Cytoarchitectural studies suggest that the lunate sulci of apes and humans are not homologous structures and that brain reorganization during human evolution encompassed more complex processes [Allen et al., 2006; Malikovic et al., 2012; but see de Sousa et al., 2010]. Therefore, further studies are needed to confirm or refute the cytoarchitectural homology of the lunate sulcus between apes and humans. It is worth noting here that while homology among living primates does not prove homology between humans and fossil hominins, homology among the extant relatives of the extinct spe-cies makes the latter more likely.
For the interpretation of brain morphology in A. sedi-ba , two lines of future research will be important. First, further A. sediba endocasts need to be found (or synthet-ically generated from newly discovered skulls) to confirm the observations of Carlson et al. [2011] that the mor-phology of the frontal endocranial surface is typical for this species and not just an individual variant. Second, comparative studies of extant primates that examine gross anatomy as well as cytoarchitecture have to demon-strate that the scenario of transitional brain morphology in MH 1 [Carlson et al., 2011] is a plausible one. In gen-eral, future research should attempt to better integrate evolutionary endocranial surface changes as seen from fossil endocasts and the underlying variation of brain morphology on different anatomical levels that exists in living species. Only a better understanding of these rela-
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tionships will allow us to confirm the ideas based on en-docranial imprints of brain convolutions.
Brain reorganization before an increase in brain size has been claimed also for another newly discovered spe-cies, the 6–7 million-year-old Sahelanthropus tchadensis [Brunet et al., 2002; Zollikofer et al., 2005]. At an estimat-ed endocranial volume of 378 ml, comparable to modern chimpanzees, the cranium TM 266-01-60-1 has been re-ported to show hominin brain shape characteristics, in-cluding strongly posteriorly projecting occipital lobes, a tilted brainstem and a laterally expanded prefrontal cor-tex [Bienvenu et al., 2013a, b]. The hominin status of this fossil is sometimes controversially discussed [Wolpoff et al., 2006], but detailed analyses of its endocast can poten-tially contribute to improve our understanding of pri-mate brain evolution.
The new fossil cranium D4500 from the Georgian site of Dmanisi [Lordkipanidze et al., 2013] is another recent discovery that is interesting for the interpretation of hu-man brain evolution. This early Homo fossil (H. erectus) is the fifth cranium from the site and, unexpectedly, it fits the previously found mandible D2600 [Gabounia et al., 2002], indicating that they came from the same individu-al. Its endocranial volume is only 546 ml [Lordkipanidze et al., 2013]. This is the smallest endocranial volume among the Dmanisi crania, and larger than most A. afri-canus endocasts [Neubauer et al., 2012b], at the lower end of the range of variation for H. habilis , smaller than the known H. rudolfensis endocasts and smaller than those of H. erectus [Holloway et al., 2004a], including the smallest-brained African erectus cranium KNM-ER 42700 from Kenya [Spoor et al., 2007]. Endocranial volumes of the Dmanisi crania now range from 546 to 730 ml (illustrat-ing the variation of what was probably one population given that the sample is rather time-constrained at around 1.8 million years ago [Gabunia et al., 2000; Vekua et al., 2002]). Together with a large overall morphological vari-ation of this cranial sample [Lordkipanidze et al., 2013; but see also Spoor, 2013; Hublin, 2014], this range of brain sizes revives discussions about a single versus mul-tiple species at the origin of our genus and questions how brain size can contribute to this discussion.
Of Digital Data and Three-Dimensional Coordinates
New kinds of data and methodology have proved to be at least as important as new fossil discoveries to fuel prog-ress in the understanding of human brain evolution. CT has been used to study fossil remains and their endocasts,
starting in the 1980s and early 1990s [Conroy and Van-nier, 1984; Conroy et al., 1990]. ‘Digital fossils’ based on CT scans have several advantages [Weber and Bookstein, 2011]. Original fossils are not harmed during endocast generation and their digital copies provide easy access to the endocranial cavity for investigation. Encrustations can be electronically removed (‘digital preparation’), and in the case that the entire endocranial cavity is filled with sediments, these sediments can be digitally separated from the bony remains and then represent a natural en-docast ( fig. 2 ). Today, it is therefore standard practice to generate and investigate so-called virtual endocasts based on CT scans, and this approach is commonly used when describing new fossils (e.g. A. sediba discussed above [Berger et al., 2010]). Nowadays, these virtual endocasts are often based on micro-CT scans or synchrotron X-ray images with a resolution of 100 μm or even less. While higher-resolution data is advantageous for digital prepa-ration of a fossil as well as interpretation of surface details, medical CT scans that have lower resolution are appro-priate for size and shape analyses in the majority of cases.
Virtual endocasts ( fig. 1 , 2 ) provide quantitative data similar to those from physical plaster endocasts, includ-ing endocranial volume and major endocranial dimen-sions. In addition, digital data make the analysis of overall endocranial shape possible. For that purpose, the meth-odological toolkit of geometric morphometrics is used. Geometric morphometrics is based on Cartesian coordi-nates of homologous measurement points (landmarks) instead of distance measurements between these land-marks and, therefore, the geometric relationships in the data are kept throughout the analyses [Bookstein, 1991; Slice, 2007; Mitteroecker and Gunz, 2009]. To obtain shape variables, information on the location and orienta-tion in which the specimens were measured are removed from the raw coordinates and the landmark configura-tions are scaled to a common size (‘Procrustes superim-position’) [Gower, 1975; Rohlf and Slice, 1990]. Size in-formation is removed during this process, but restored in a variable called centroid size (the square root of the sum of squared distances of all the landmarks from their cen-troid). Therefore, size and shape can be analyzed sepa-rately and the shapes of differently sized specimens can be compared. The high-dimensional shape-space built by the shape variables is commonly analyzed using multi-variate statistical tools, such as principal component anal-ysis [Bookstein, 1991; Rohlf, 1993].
For endocranial shape, this kind of analysis had been neglected for a long time because it is difficult to quantify the smooth endocranial surface that lacks a sufficient
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number of homologous landmarks to capture the rele-vant variation within and between groups ( fig. 3 ). Based on endocranial landmarks, Bruner et al. [2003] and Brun-er [2004] found interesting shape differences between modern humans and archaic Homo fossils as old as a few hundred thousand years, including Neanderthals (who lived in Eurasia and survived even until about 28,000 years ago in some refuges [Finlayson et al., 2006]), and suggested that modern humans surpassed the constraints on encephalization imposed by the developmental pat-tern of the genus Homo . Bienvenu et al. [2011] described major patterns of endocranial shape variation in great apes and humans that are important for interpreting en-docranial shape in fossil hominins. While these studies provided interesting insights, they also highlighted that a few landmarks cannot capture all of the relevant endocra-nial shape variation. Furthermore, the quality and ob-servability of landmarks defined on brain sulci is quite variable in fossils and even in individuals of extant spe-cies. The controversial debate about the position of the
lunate sulcus discussed above should advise caution. An-other approach to quantify endocranial shape uses only information of the endocranial surface without the need to measure homologous landmarks [Durrleman et al., 2011]. However, it might be disadvantageous to exclude the few homologous landmarks that are observable and can be measured because they capture biologically rele-vant information.
Methodological advances of recent years [Gunz et al., 2005] have provided another possibility. They enable the inclusion of shape information on curves and surfaces as three-dimensional coordinates in between the homolo-gous landmarks [Neubauer et al., 2009]. In contrast to anatomical landmarks, which are biologically homolo-gous structures, so-called semilandmarks can be used to describe the shape of a homologous curve or a homolo-gous surface. Where along the curve and where on the surface these semilandmarks are measured is more or less arbitrary. In a second step, they are allowed to slide along the curve and on the surface according to the thin-plate-
Fig. 3. Quantification of endocranial shape. Traditionally, distance measurements between a few endocranial landmarks have been measured and analyzed. As illustrated on the left, the geometric relationships between the measurements are lost and the scarcity of measurement points cannot capture all the relevant shape infor-mation. Geometric morphometrics allow retaining geometric re-lationships and the usage of semilandmarks provide the possibil-
ity to capture shape information in between the anatomical land-marks. The landmark configuration on the right [Neubauer et al., 2009] quantifies overall endocranial shape and the curves (thick black lines) compartmentalize the endocast in a cerebral, cerebel-lar, temporal pole and orbital surface, but do not allow further partitions because it abstains from using landmarks based on (sometimes problematic) imprints of brain convolutions.
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spline algorithm, so that they are geometrically homolo-gous within a given sample [Bookstein, 1997; Gunz et al., 2005]. The slid semilandmarks can then be treated like the biologically homologous landmarks in the analyses ( fig. 3 ). Although the curves compartmentalize the endo-cranial cavity [Neubauer et al., 2009], this approach does not use landmarks defined on specific brain convolutions and, therefore, captures less information about the brain itself and its subdivisions. At the same time, it obviates inaccurate (or imprecise) information that results from the difficulties in locating and interpreting imprints of brain convolutions. Both approaches, either including or not using landmarks defined on imprints of brain sulci, have advantages and disadvantages, and the results should be interpreted accordingly.
Only recently, geometric morphometric techniques have been used to quantify and analyze global brain shape itself [Bruner et al., 2010, 2011; Gomez-Robles et al., 2013], but also Euclidean distance matrix analysis, which analyzes interlandmark distances, has been used [Richts-meier et al., 2006; Aldridge, 2011]. MRI scans are used to obtain coordinate data of landmarks defined on specific brain sulci and structures, and thereby the dimensions and shape of different brain regions can be delineated and quantified. Future studies should incorporate results of shape analyses of endocasts and the brain itself in order to better interpret endocranial shape in fossils.
Analyzing fossils usually goes along with another methodological problem: in most cases, fossils are frag-mentary and sometimes parts are deformed. If only en-docranial size is of interest, then a simple regression that allows predicting endocranial volume from a few mea-surements of the preserved areas can be used. However, if endocranial shape is to be investigated, only the pre-served areas can be used or a complete endocast has to be reconstructed. Using digital data, the reconstruction pro-cess is facilitated [Zollikofer et al., 1998; Zollikofer, 2002; Weber and Bookstein, 2011]. First, it is easier to realign bony fragments and, second, bony fragments that are pre-served on only one side can be easily mirror imaged to estimate the other missing side (see fig. 2 ). It is worth mentioning that mirror imaging and digital correction of distortions (see below) are based on the bilateral symme-try of an endocast and therefore cannot ‘recreate’ infor-mation not preserved concerning brain shape asymme-tries, but neither can traditional methods. Based on digi-tal data, the available bony parts are put together, and only then is a virtual endocast generated. Depending on the preservation of the fossil, some areas of the endocast might still be missing or some regions might be deformed.
Landmark-based geometric morphometric tools can be used to estimate these missing regions and to correct dis-torted fragments based on an appropriate reference indi-vidual. The endocast of this reference individual is de-formed based on the landmarks on the preserved areas of the incomplete fossil and the missing parts are deformed accordingly, serving as reconstruction. For both estima-tion of missing parts and ‘retro-deformation’, it is key that semilandmarks are used because the endocranial vault surface does not comprise a sufficient number of anatom-ical landmarks to obtain meaningful results [Gunz et al., 2009]. The choice of the reference individual undoubt-edly influences the resulting reconstruction (see fig. 2 in which two very differently shaped endocasts – from a hu-man and a chimpanzee – are used to estimate the missing parts of an A. africanus endocast). However, instead of using only one reference individual, it is possible to use a reference sample of diverse individuals to create multiple reconstructions, each based on one of the reference indi-viduals [Gunz et al., 2009, 2010; Neubauer et al., 2012b]. The variation among multiple reconstructions can then be used to interpret the influence of the choice of the ref-erence individual. For example, if different reconstruc-tions are very similar, although based on diverse refer-ence individuals, then the reconstruction uncertainty does not influence the results and the conclusions drawn from the analyses are stable.
The Evo-Devo Approach of Paleoneurology
Paleoanthropologists have studied and compared brain growth in humans, extant primates and fossil hom-inins to better understand the interwoven topics of the evolution of cognition, behavior, life history, energy al-location and childbirth [Martin, 1983; Harvey et al., 1987; Trevathan, 1987; Aiello and Wheeler, 1995; Smith and Tompkins, 1995; Martin, 1996; Rosenberg and Treva-than, 1996; Trevathan, 1996; Leonard and Robertson, 1997; Fairbanks, 2000; Langer, 2000; Rosenberg and Trevathan, 2001; Rosenberg and Trevathan, 2002; Leon-ard et al., 2003; Coqueugniot et al., 2004; Leigh, 2004; Leigh and Blomquist, 2007; Ponce de León et al., 2008; Weaver and Hublin, 2009; Zollikofer and Ponce de León, 2010; Leigh, 2012; Neubauer and Hublin, 2012]. Humans, having the largest brains among primates, show a special pattern of brain growth: although gestation differs only by a few weeks [Kappeler and Pereira, 2003], human new-borns have brains that are about two times larger than those of great apes, yet they have achieved a smaller per-
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centage of their total brain growth prenatally compared to great apes, they maintain their high fetal growth rates for about 2 years, and then keep growing their brain at lower rates for a longer duration than chimpanzees and other apes [Schultz, 1940, 1941; Count, 1947; Holt et al., 1975; Jordaan, 1976; Gould, 1977; Passingham, 1982; Martin, 1983; Dienske, 1986; Smith and Tompkins, 1995; Coqueugniot et al., 2004; Leigh, 2004; DeSilva and Lesnik, 2006; Hublin and Coqueugniot, 2006; DeSilva and Les-nik, 2008; Coqueugniot and Hublin, 2012; Neubauer et al., 2012a; McFarlin et al., 2013; but see Jolicoeur et al., 1988; Fragaszy and Bard, 1997; Vrba, 1998; Rice, 2002; Fragaszy et al., 2004; Leigh, 2004; Kennedy, 2005; Vini-cius, 2005]. In this respect, it has been claimed that brain growth has been shifted postnatally in humans and that human neonates are thereby developmentally delayed as compared to the newborns of other related species. This special pattern has been termed secondary altriciality [Portmann, 1941] and has implications for cognition. A delayed and prolonged brain growth while interacting with the extrauterine environment has been interpreted to be advantageous for cognitive and behavioral develop-ment (see references above). It is therefore interesting to study the evolution of brain growth in more detail.
However, this is a difficult endeavor, given the limited fossil samples. The Neanderthal ontogenetic sample is probably the best for any given fossil hominin group but includes only two (nearly) newborns [Coqueugniot and Hublin, 2007; Ponce de León et al., 2008; Gunz et al., 2010, 2011, 2012]. Based on estimates of endocranial volumes for differently aged fossil individuals, the pattern of brain growth seems to be quite similar between modern hu-mans and Neanderthals. But Neanderthal adults hadlarger brains on average (with widely overlapping varia-tion [Ruff et al., 1997; Holloway et al., 2004a]). This might be explained by slightly higher growth rates in early post-natal ontogeny [Ponce de León et al., 2008]. The pattern of brain growth in H. erectus is more uncertain, espe-cially because there is only one nonadult fossil available for investigation, the bony braincase from Mojokerto [Coqueugniot et al., 2004; DeSilva and Lesnik, 2006; Hub-lin and Coqueugniot, 2006; Leigh, 2006; DeSilva andLesnik, 2008; O’Connell and DeSilva, 2013]. Analyses are further complicated because it is difficult to estimate Mo-jokerto’s age at death, and because the geologic dating is insecure [Swisher et al., 1994; Huffman, 2001; Morwood et al., 2003; Huffman et al., 2006]. The latter is important because this long-prevailing hominin species shows a trend of increasing adult brain size during evolution from less than 600 to over 1,000 ml [Holloway et al., 2004a;
Lordkipanidze, 2013]. Therefore, to interpret brain growth in H. erectus , the adult sample should include only indi-viduals comparable in geologic age to Mojokerto. Given these problems, the brain growth pattern of H. erectus or some aspects of it have been interpreted to be chimpanzee-like, intermediate, or human-like by different researchers [Coqueugniot et al., 2004; DeSilva and Lesnik, 2006; Hub-lin and Coqueugniot, 2006; Leigh, 2006; DeSilva and Les-nik, 2008; O’Connell and DeSilva, 2013]. To make progress in resolving this question, new juvenile fossils must be dis-covered and included in the analyses.
In the last few years, the usage of geometric morpho-metrics and digital data has allowed investigations of not only endocranial growth (size increase with age), but also endocranial development (shape change with age). In humans, the ontogenetic pattern of endocranial shape change is nonlinear and shows distinct phases [Neubau-er et al., 2009]. The first phase from birth to about the eruption of the first deciduous dentition includes relative expansion and bulging of parietal and cerebellar areas, as well as cranial base flexion. Since these shape changes make the endocast (or the brain) more globular, it is called the globularization phase [Neubauer et al., 2009, 2010]. It is reasonable to suggest that mostly the growing brain itself drives these shape changes, because brain growth rates are very high and the cranial sutures are not fused yet (consider the ‘functional matrix hypothesis’ [Moss and Young, 1960; Moss, 1962]). In other words, spatial packing of the growing brain [e.g. Biegert, 1957; Gould, 1977; Enlow, 1990; Ross and Ravosa, 1993] con-tributes to endocranial shape changes in early ontogeny, but endocranial shape continues to change after adult brain size has been attained. Shape changes during later ontogeny include relative expansion of cerebellar, sagit-tal and parasagittal frontal, orbital and anterolateral tem-poral areas, and a relative reduction of lateral frontal, pa-rietal and occipital areas. Late shape changes that are not associated with any size increase are probably related to size and shape changes of the later maturing face [Book-stein et al., 2003; Bastir and Rosas, 2006; Bastir et al., 2006; Bastir, 2008; Bastir and Rosas, 2009; Bastir et al., 2010].
To set the human ontogenetic pattern in context, it makes sense to compare it to the pattern of other extant primates. Chimpanzees are our closest living relatives but have very differently sized and shaped brains compared to humans. These differences arise during development via species-specific ontogenetic patterns. To compare postnatal development between humans and chimpan-zees, Neubauer et al. [2010] used developmental simula-
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tions in which neonates of one species developed accord-ing to the ontogenetic pattern of the other species to sim-ulate new adults. The simulated and the measured adults were then compared. While differences exist during pre-natal ontogeny as seen from different endocranial size and shape in neonates, these simulations suggest that our postnatal ontogenetic pattern of shape changes is quite similar to the one in chimpanzees with one large differ-ence: only human newborns undergo the globularization phase in which their brain becomes typically globular ear-ly in development, while this phase is not evident in chim-panzees ( fig. 4 ).
Considering that humans are developmentally delayed due to a postnatal shift of brain growth as compared to apes (see above), the globularization phase could occur prenatally in chimpanzees and is consequently not found in a postnatal sample. However, this hypothesis is unlike-ly given the facts that one measured chimpanzee fetus had an endocranial shape similar to those of chimpanzee new-borns [Neubauer et al., 2010], that chimpanzee neonates have elongated and not globular brains, and that previous studies on cranial base development indicated that the cranial base extends prenatally in all studied primates [Jeffery and Spoor, 2002; Jeffery, 2003, 2005] in contrast
Fig. 4. Postnatal endocranial shape changes from neonates (left) to adults (right). In humans (top row, blue endocasts; colors refer to the online version only), endocranial shape changes in the first year of life include a globularization (blue arrow) that largely con-tributes to the typically globular brain shape of humans. Subse-quently, humans undergo a pattern of endocranial shape changes (gray arrow) that is shared with chimpanzees (middle row, green
endocasts) and Neanderthals (bottom row, red endocasts; left the Mezmaiskaya baby, right an adult individual from La Ferrassie). Note that the shape itself is different between humans, chimpan-zees and Neanderthals, but the pattern of ontogenetic changes (gray arrow) is very similar. See Neubauer et al. [2009, 2010] and Gunz et al. [2010, 2011, 2012] for more details.
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to basicranial flexion during the globularization phase. This implies that the globularization phase evolved in the hominin lineage after the last common ancestor with chimpanzees [Neubauer et al., 2010].
While the absence or presence of the globularization phase distinguishes the early postnatal developmental patterns of humans and chimpanzees, the subsequent shape changes that occur later in ontogeny are remark-ably similar [Neubauer et al., 2010]. This phase of shared shape changes seems to be conserved and is probably an ancestral developmental pattern that was already established in the last common ancestor of hu-mans and chimpanzees. Scott et al. [2014] recently con-firmed a shared pattern of postnatal endocranial devel-opment in extant hominoids [see also Ponce de Léon et al., 2013]. Moreover, the developmental simulations suggest that, while the pattern itself is very similar dur-ing this period, the amount of shape change along this pattern is different. This is reminiscent of the classic concept of heterochrony, which models evolutionary changes of developmental timing as compared to an an-cestral species, leading to changes in size and shape [Gould, 1977]. While the language of heterochrony cannot be used in a straightforward way with multivar-iate data [Mitteroecker et al., 2005], it seems that evo-lutionary changes in the timing or amount of shape change along a shared developmental pattern contrib-ute to species differences. Apes that have larger and more prognathic faces show a higher degree of shape change than humans [Neubauer et al., 2010; Scott et al., 2014]. This reinforces the claim that endocranial shape changes during later ontogeny, especially after brain size has been attained, are related to facial modifica-tions and are probably less informative about intrinsic brain shape changes.
The comparison of ontogenetic patterns between hu-mans and hominoids leads to an appealing, testable hy-pothesis about brain development in our closest extinct relatives. Neanderthals did not have globular brains and flexed cranial bases like modern humans, but rather elongated endocasts [Lieberman et al., 2002; Bruner et al., 2003; Bruner, 2004], suggesting that the globulariza-tion phase has evolved only in modern humans [Neu-bauer et al., 2010]. To test this hypothesis, Gunz et al. [2010, 2011, 2012] reconstructed a sample of variously aged Neanderthal individuals. This sample also included the two known Neanderthal neonates from Le Moustier [Maureille, 2002] and Memaiskaya [Golovanova et al., 1999]. The Neanderthal sample was then analyzed using developmental simulations. The results show: (1) that
Neanderthal juveniles follow the shared phase of shape changes during later ontogeny and (2) that Neanderthals did not have a globularization phase in early postnatal ontogeny ( fig. 4 ). These conclusions are stable taking the uncertainty of the required reconstructions of fragmen-tary fossils into account [Gunz et al., 2010, 2012]. The globularization phase therefore seems uniquely human and supports the hypothesis of Bruner et al. [2003] that modern humans have surpassed the constraints of the ontogenetic pattern on encephalization in the genus Homo .
Given this human uniqueness, it is reasonable to spec-ulate that the globular brain and the developmental pat-tern through which this morphology arises are related to our intellectual performance. While it has been proposed that our species’ globular brain shape is related to in-creased wiring efficiency [Hofman, 1989; Chklovskii and Stevens, 2000; Chklovskii et al., 2002], Bruner et al. [2011] found only subtle correlations between midsagittal brain shape and performance in a series of different cognitive tests among human young adults. Brain shape per se is probably even less correlated to any measure of intelli-gence than brain size [Gunz et al., 2012; Neubauer and Hublin, 2012] but internal brain organization, such as neural pathways and cytoarchitecture, is interpreted to be very important [Schoenemann et al., 2000; Schmithorst et al., 2005; Shaw et al., 2006; Luders et al., 2009; vanLeeuwen et al., 2009].
At the time of birth, neural connections in the brain are sparse [Huttenlocher, 2002]. While the neural net-work of the brain results from scheduled sequences of proliferation and overproduction of axons, dendrites and synapses, followed by selection and retraction of synapses and connections [Rakic, 1972, 1974; Mrzljak et al., 1990; Purves, 1994; Hockfield and Lombroso, 1998], it is not intrinsically predetermined [Changeux and Danchin, 1976]. Synaptic pruning is known to be depen-dent on the communication among neurons so that more active synapses tend to be strengthened and less active ones tend to be eliminated [Chechik et al., 1999]. There is a shift from diffuse to more focal recruitment of corti-cal regions with learning, presumably an experience-driven maturational process [Durston et al., 2004; Brown et al., 2005; Casey et al., 2005], and the sequence in which the cortex matures parallels cognitive milestones [Sowell et al., 2003; Giedd, 2004; Gogtay et al., 2004; Sowell et al., 2004a, b]. Brain reorganization and maturation continue into young adulthood, especially in the myelination of axons [Giedd et al., 1999; Durston et al., 2001; Sowell et al., 2004b; Paus, 2005; Toga et al., 2006]. Clearly, the de-
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velopment of the neural network of the brain is affected by our experience and by external stimuli from the envi-ronment.
Along these lines, the tempo and mode of brain de-velopment is of particular importance for brain organi-zation, and thereby our intellectual abilities ( fig. 5 ). Clinical studies show, for example, that autistic children undergo a period of early brain overgrowth in which both white and gray matter seem to be involved [Courchesne et al., 2001; Carper et al., 2002; Sparks et al., 2002; Courchesne et al., 2003; Dementieva et al., 2005; Hazlett et al., 2005; Dawson et al., 2007; Mraz et al., 2007; Webb et al., 2007; Schumann et al., 2010]. It has been hypothesized that these accelerated growth rates during the first years of life in autistic children re-sult in local over-connectivity and fewer long-range connections between brain regions that are far apart [Courchesne et al., 2003, 2005, 2007] and that this neural network does not fulfill the architectural requirements for the initiation, perception and interpretation of so-cio-emotional and communicative functions, as well as higher-order cognitive, memory and attention func-tions [Herschkowitz, 2000; Gale et al., 2004; Courchesne et al., 2007]. This example shows that relatively modest alterations in early development can have large effects on cognitive and behavioral development.
The tempo and mode of brain development also affect the size and shape of the brain (or the endocast). The studies on ontogenetic brain size increase discussed above highlight that humans have a special growth pattern. The
Cognition and behaviorTempo and modeof development
Brain size and shape
Brain organization
Endocranial size and shape
uniquely human globularization phase is further evi-dence that the tempo and mode of brain development is different in humans as compared to our closest living and extinct relatives. It is worth emphasizing that the globu-larization phase as the process to develop the uniquely human adult globular brain is related to, but probably not the reason for, our wide repertoire of cognitive and be-havioral abilities. The ability to further investigate the pa-leoneurological data awaits integrative research efforts that attempt to link cognitive development, morphologi-cal brain development and the morphological data that can be gleaned from endocasts.
Conclusions
This review has summarized some aspects of recent paleoneurological research. While endocasts are the only direct evidence concerning hominin brain evolution, the information available is limited and the interpretation of paleoneurological data always relies on knowledge about the brains of living species. Future work should therefore integrate different approaches, including genetics and gene expression, micro- and macroanatomy of the brain, cognitive and behavioral data, and size and shape analy-ses of endocasts. In recent years, methodological advanc-es in paleogenetics has allowed the generation of higher quality and higher coverage genomes of fossil hominins [Green et al., 2006; Burbano et al., 2010; Green et al., 2010; Reich et al., 2010, 2011; Meyer et al., 2012, 2014;
Fig. 5. The tempo and mode of brain development affect the inter-nal organization of the brain (neurogenesis, growth of dendrites and axons, synaptogenesis, pruning, myelination) as well as the size and shape of the brain. The quantity of neurons and neural connections and far more so the quality of the neural network and the way it is built are related to our cognitive and behavioral abili-ties. In paleoneurological studies, we can neither analyze the brain
and its development itself, nor observe cognitive performance and behavioral capabilities. However, the patterns of ontogenetic en-docranial size and shape changes provide information about the tempo and mode of brain development and, therefore, allow spec-ulations about cognition and behavior. Integrating different ap-proaches in an evolutionary developmental framework will thus improve our understanding about hominin brain evolution.
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Prüfer et al., 2014]. The genetic data of extinct popula-tions provide one encouraging means of bridging the gap between paleoneurological data of fossil hominins and the comparative morphological and functional data on brains in living species. Another promising approach is an evolutionary developmental framework because, while the size and shape of an endocast per se are not particularly informative about brain function, the tempo and mode of brain development are tightly interrelated with cognitive development, and also affect endocast form.
Acknowledgements
I would like to thank Chet Sherwood, Alice Powers and the J.B. Johnston Club for Evolutionary Neuroscience organizing team of the 2013 Karger Workshop, ‘The Problem of Human Brain Evolu-tion: Integrating Diverse Approaches’, held in San Diego; further-more, the other speakers of the workshop, Christine Charvet, Asif Ghazanfar, Katerina Semendeferi, Genevieve Konopka, Chet Sher-wood and Richard Passingham, for their exciting talks, as well as Georg Striedter, the Editorial Board of Brain Behavior and Evolu-tion and Karger Medical and Scientific Publishers for the invitation to contribute this paper. I am grateful for the constructive com-ments by Chet Sherwood, Dean Falk and an anonymous referee that substantially improved the manuscript. The Max Planck Soci-ety supported this work.
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