Open access opens the skull of Homo naledi

As I mentioned a few weeks ago, some colleagues and I have recently published an article about brain structure and function of the fossil hominin Homo naledi, based on endocranial evidence. Ben Taub wrote up a nice summary of the paper for IFL Science that lays out some of the main points and bigger picture (here). The article is open access for everyone to read (here), as are the new landmark data and R code (here) that we used to reconstruct and analyze the endocast of the most complete H. naledi skull.

Over the past decade it has become standard practice to publish data and code, to both facilitate transparency and allow others to add to existing datasets. It turns out it’s also important when journals don’t include your high-resolution figures in the final publication and are incapable of replacing the low quality images that made it into print (makes you wonder just what the $5000 article processing charge pays for). So, this is a good opportunity to follow up on the earlier blog post and walk you through the R code that produces the graphs (along with a few other images) that help illustrate the story told by H. naledi endocasts.

Homo naledi is one of the wildest discoveries in human evolution, from its unusual geological contexts to the variability exhibited in the large subfossil sample. The endocasts are tantalizing, since they are as small as those of hominins from over one million years ago, yet they date to only around 300,000 years ago. They buck the general trend of brains getting bigger of the course of human evolution.

Brain size in human evolution. Colored shapes indicate fossils included in the geometric morphometric analyses described below. Data adapted from DeSilva et al. (2021).

Unlike the other small-brained, later Pleistocene hominin Homo floresiensis (a.k.a., “the hobbit”), there is a nice and big sample of H. naledi crania. The floresiensis sample is restricted to a relatively complete skeleton from one individual (“LB1”) and a few other bones from several other individuals. The small brain size of LB1 precipitated a series of studies in the early 2000s, arguing for (or against) various pathological explanations, though I think the consensus today is that H. floresiensis was in fact a small-brained hominin. It probably blew the minds of our human ancestors when they encountered hobbits on Flores 10s of 1000s of years ago. In contrast to the case of H. floresiensis, at least five adult H. naledi crania have been recovered from Rising Star Cave in South Africa, all indicating brain sizes between 460–610 ml.

Homo naledi crania viewed from the left side (top row) with their endocast impressions highlighted in pink (bottom row). Specimens from left to right: LES1, DH1, DH2, DH3, DH4.

Despite having small brains, the impressions from the frontal lobe suggest this part of the brain was organized like that of humans today. This is important in part because this specific region including Brodmann Areas 44-45 (highlighted in blue below) is involved in both spoken language as well as stone tool production. In addition, these naledi endocasts support to the idea, proposed over 100 years ago, that early hominin brains may have been structured like those of modern humans but at smaller sizes.

Inferior frontal lobe morphology viewed from the front-left, in chimpanzee (A) and human (B) brains, and H. naledi endocasts DH3 (C and E) and LES1 (D and F). Brains in A and C are from the National Chimpanzee Brain Resource.

To learn more about the brain of H. naledi, we virtually reconstructed the endocast of the sample’s most complete skull, referred to as “LES1” (the first hominin from the Lesedi Chamber of Rising Star Cave). The R code linked above uses geometric morphometrics to estimate the likely positions of endocranial surfaces that are missing from the actual LES1 fossil. When reconstructing a fossil from fragments, we can rarely know what the original bone truly looked like when it was intact. But with geometric morphometrics, we can estimate missing data based on different references (e.g., a specific Homo erectus fossil or a sample average), allowing us to explore many reasonable alternatives. So, the R code generates 15 reconstructions of the LES1 endocast based on over a dozen fossil hominin references (previously published by Simon Neubauer and colleagues).

Workflow for virtually reconstructing the LES1 endocast. A) Isolate the endocranial surface. B) Duplicate and mirror the endocast, then apply the landmark template to the preserved service (block dots). C) Estimate missing landmarks based on different fossil references (indicated by colored lines and nodes). D) Observe how the reconstructed endocast fits the actual fossil.

Although LES1 is missing nearly all of the bottom of the skull and endocast, all of our reconstructions based on various fossils and an average human are quite similar to one another. In geometric morphometrics, a shape is captured by a configuration of landmarks—in our case, 935 coordinates in 3D space. The Procrustes distance provides a quick summary of the overall shape difference between two individuals (for instance, two different reconstructions of LES1). The R code includes a simple function for calculating pairwise Procrustes distances, and then uses randomization and loops to obtain Procrustes distances between all LES1 reconstructions, between all humans, between all Homo erectus included in the study, and between the average LES1 and all other fossils.

Endocast shape affinities in the full sample. Left: Boxplot of Procrustes distances between all humans, all Homo erectus, and LES1 reconstructions and the fossil sample. Right: Cluster analysis of all Procrustes distances shows that Homo erectus endocasts are most similar to one another, that erectus variation accords with geography, and that LES1 is most similar to the Indonesian H. erectus from Ngandong, Ngawi, and Sambungmacan.

In the left graph above, the pink dots show the shape differences between all LES1 reconstructions: these differences are smaller than all the within-erectus differences and nearly all of the within-human differences. This means that most of the reconstructions are more similar to one another than two different individuals of the same species would be to one another. This in turn means that missing data uncertainty is fairly low for LES1; if we were to run various analyses, the results should be pretty much the same regardless of which LES1 reconstruction we use. Great! (As an aside, we had also estimated the endocranial volumes of each LES1 reconstruction and these ranged from 608–622 ml, a precise span very similar to the first estimate of 610 ml when the fossil was first discovered. But we ended up cutting this from the paper.)

Looking at the same graph, Procrustes distances between LES1 and most of the other fossils are comparable to the within-species variation seen in humans and H. erectus. These distances, along with the cluster analysis in the right side of the image above, show that the LES1 endocast shape is most similar to those of H. erectus from Java (Ngandong, Ngawi, Sambungmacan).

This was an unexpected result. The skull and teeth of H. naledi have been shown to be more similar to earlier members of the genus Homo, but the LES1 endocast doesn’t show this affinity. Plus, these later H. erectus endocasts are almost twice the size of LES1, yet LES1 doesn’t appear to be a simply a H. erectus ‘scaled down’ to a smaller size. The Procrustes distances and cluster analysis highlight overall endocast shape variation in the sample, so the R code then goes on to look at the more detailed differences between LES1 and each fossil reference group. In the next image, the top row compares the scaled and aligned endocasts of LES1 and given reference, while the bottom row color-codes the difference between each 3D coordinate on LES1 and the reference endocast.

Shape differences between H. naledi and each other species ‘type.’ LES1 is depicted in gray in the top and bottom rows. Triangle meshes in the top row show the average endocast shapes, while the spheres on the endocasts below depict differences between the landmark coordinates of LES1 and each reference.

Notice that the inferior frontal lobe appears relatively expanded in LES1 compared to all of the other groups. This corroborates previous research indicating a human-like anatomy in this area that is important for language and tool production. We speculate that the almost-human morphology here (recall the third image in this post) may relate to how different parts of the brain are connected, but much more research is needed to develop this idea.

The last aspect of endocast shape that we examined is the proportional size of the areas surrounding the cerebral cortex versus the cerebellum. The bottom of the cerebellum is cupped by the occipital and temporal bones (dark pink in the image below), while the top and sides of the cerebral cortex are capped by the rest of the endocranial surface (lighter pink below). We can quickly measure the overall sizes of these two brainy coverings based on their 3D landmarks, but we should bear in mind these are only approximations of the cerebrum and cerebellum themselves. The graph below shows how these proxies scale within the sample, with a best-fit line showing the relationship in recent humans. All of the fossil hominins including naledi have relatively smaller cerebella than modern humans, which might suggest a disproportionate expansion of the cerebral cortex later in human evolution.

Size scaling of the bony surfaces covering the cerebral cortex (light pink landmarks) and cerebellum (dark pink landmarks).

In our review of the brain of H. naledi we presented some new data and evidence, and also tried to point toward important areas for future research. These include exploring physical influences on brain/endocast shape—both intrinsically due to connections between different regions of the brain, and extrinsically due to how the eyes, nose, throat, and jaws interact with the brain during growth and development. Bigger samples of both fossils and living apes would also help uncover how the cerebellum has changed over time.

This latter project is ripe for the picking. The shape analyses we presented in the paper basically just entailed creating and applying a 3D landmark template to LES1, and inserting LES1 into an existing dataset. Recall from another recent blog post that second research group, led by Marcia Ponce de León and Christoph Zollikofer, has also published their similar endocast landmark data and provides a much larger fossil and ape sample. It wouldn’t take too much work to create and apply a landmark template from this sample to LES1 and do all the same analyses (and more) that we included in our open access article and code. And because the H. naledi fossils themselves are available for study (originals at the University of the Witwatersrand, and so many 3D models on Morphosource), a more comprehensive analysis of all H. naledi endocasts is well within reach.

So many fossils, so little time!

Mind the gaps, mend the gaps

A very long time ago I asked whether Neandertals’ brains grew like ours do today, a question raised by conflicting results coming from two research teams. Both teams reconstructed the brain endocasts of modern humans and fossil Neandertals, and compared how endocast shapes changed during growth and development. As I mused in that post, the different results seem to result largely from differences in how a critical fossil specimen (the Neandertal newborn from Mezmaiskaya, Russia) was reconstructed.

Physical reconstruction of a Homo erectus cranium (A and turquoise in C) compared to its “virtual” reconstruction (B and gray in C), by Karen Baab (2025).

This is a perennial problem for paleoanthropology. Our knowledge of the human past hinges on a few thousands of individuals whose bones and teeth managed to survive and be discovered after several thousands or millions of years. Most of these precious remains are fragmentary and cannot speak for themselves. So, researchers must rely on their own anatomical expertise and a bit of artistic license to reconstruct what many key fossils would have looked like in their original condition.

Over thirty years ago Christophe Zollikofer and colleagues (1995: 283) reported that, “Fossil specimens can be restored, measured and replicated without physical contact using … computer assisted reconstruction.” The development of these “virtual anthropology” methods has made fossil reconstruction much more accessible. Most importantly, virtual methods allow researchers to generate multiple, reasonably realistic reconstructions of the same fossil. As Philipp Gunz and colleagues (2009: 61) noted, “While there typically will be shape differences among equally plausible reconstructions, these different estimates might still support a single conclusion. But they need not do so, and all assumptions must be strenuously challenged if one or more reconstructions, or a statistical analysis based on them, are to be treated as arguments for a scientific claim.”

As these paleo pioneers have also acknowledged, making data publicly available will also help assess the extent to which specific reconstructions might affect subsequent interpretations. Both of these research groups have published 3D landmark datasets with some overlapping specimens, allowing us to address this central question. Simon Neubauer and colleagues (2018) published the landmark data used in their reconstruction and analysis of a juvenile Homo erectus cranium (here). A team led by Marcia Ponce de León (2021) and Christophe Zollikofer (2022) have posted comparable data from their endocast reconstructions of Homo erectus from Dmanisi, Georgia (here) and early Homo sapiens from Herto, Ethiopia (here). These great datasets bear on the evolution of brain size and shape—let’s dig in.

Both groups—Neubauer et al. and Ponce de León et al. + Zollikofer et al. (hereafter “PZ”)—include recent modern humans from different skeletal collections and the same nine fossil Homo specimens: KNM-ER 1813 (H. habilis), KNM-ER 1470 (H. rudolfensis), and seven other fossils from Kenya and Indonesia typically attributed to Homo erectus. Most of the fossils required varying extents of reconstruction, from the alignment of separate cranial fragments to the mathematical estimation of endocranial surfaces that aren’t preserved. The two teams measured endocast shape using comparable but slightly different sets of 3D landmark coordinates, so we can’t combine the datasets but we can run the same set of analyses on each sample separately and then compare the results.

Overall size and shape variation in the two datasets. Left: Centroid size of each specimen with the dashed line indicating parity between samples. Center and right: endocast shape variability within the Neubauer (center) and PZ (right) samples; color-coded 3D models beneath each graphs show how endocast shape varies along PC1.

The graphs above show how the nine fossils vary within and between datasets. The 3D landmarks used to measure endocast size and shape return similar overall sizes for each specimen (left graphs). There are differences in the relative positions of a few specimens (ER 3883 vs. WT 15000 and ER 3733 vs. Sambungmacan 3), but these discrepancies are small probably mostly within the range of uncertainty for individual fossil reconstructions.

The effects of different reconstructions on endocranial shape, on the other hand, are a bit more profound. In each dataset, the main dimension of variation (PC1, the horizontal axis in the center and right graphs) captures similar patterns of shape variability. In both samples, fossils with a longer and lower endocast fall on the left side of the graph, while rounder endocasts fall on the right side of the graph. But where individual specimens plot in the graphs (i.e., their overall endocast shape) differs notably between datasets. For example, the “Mojokerto” infant Homo erectus has the roundest shape while WT 15000 has one of the ‘flatter’ shapes in the Neubauer sample, whereas WT 15000 is the ‘roundest’ in the PZ sample.

So, different decisions in the reconstruction process can lead to different overall patterns of shape variation within a sample. This can have important impacts on subsequent analyses. For instance, we often want to assess how similar or different fossil specimens are to one another, looking for clusters of similar shapes that might tell us something meaningful about the biology we’re hoping to capture. The two datasets, however, produce slightly different clusters:

Cluster dendrograms based on shape variation within the two endocast datasets. Fossil specimens are color-coded to highlight difference between the two trees.

Both datasets produce clusters with early H. erectus specimens ER 3733 and ER 3883, and later Indonesian H. erectus fossils Sambungmacan 3 and Solo XI. But the similarities among other fossils differ between the two samples, in ways that could lead to different biological interpretations. One might interpret the Neubauer clustering to mean that the Mojokerto infant differs from the rest since it hadn’t completed brain growth, while the other clusters could potentially reflect evolutionary changes both from early Homo (ER 1813 and 1470) to H. erectus and over time within H. erectus. In contrast, the PZ tree could be interpreted to mean that the adolescent WT 15000 had an ‘underdeveloped’ brain like Mojokerto, while the different clusters of ER 1813 and ER 1470 could reflect a more convoluted pattern of brain evolution from early Homo to H. erectus.

Of course, principal components and cluster analyses are statistical approaches for exploring variation within a sample, and they don’t necessarily map onto meaningful phenomena. Biological patterns could ‘override’ variation due to differences in reconstruction. For instance, endocast shape variation due to growth and development could produce marked, characteristic differences between infants and adults. Indeed, if we compare endocast shape of the infant Mojokerto to the average adult H. erectus, both datasets yield fairly similar results:

Endocast shape differences between the Mojokerto infant and adult H. erectus. In both rows, the left side shows Mojokerto (blue/red) aligned to the adult (gray); note that they are scaled to the same size. The center shows where Mojokerto (blue/red) or the adult (yellow) projects more than the other. On the right, lines between points show how corresponding landmarks differ between Mojokerto and the average adult in each sample.

In addition, if groups/species have distinct endocast shapes, such differences could still be captured by studies using different fossil reconstructions. For instance, both studies produce similar results when comparing early Homo specimens ER 1813 and ER 1470, and comparing adult H. erectus and modern humans:

So, getting back to our original question: do different virtual reconstructions produce different results? Yes and no. Yes, there will be observable differences between studies, and these could be subtle (e.g., brain sizes estimates) or more severe (e.g., clustering patterns within a fossil sample). But as Melvin Moss reminded us, we must keep in mind the underlying biological questions when interpreting statistical patterns. Ultimately, fossil preservation is probably the greatest source of variability between different studies. Many researchers will bring similar levels of expertise and similar analytical toolkits to study fossils, but more fragmentary specimens will have greater uncertainty in how to to reconstruct them. In contrast to the different growth patterns identified in the Neandertal studies mentioned at the beginning of this post, the consistent ‘growth’ signal in H. erectus fossils may be due to the fact that the Mojokerto infant is better preserved and required less reconstruction than Neandertal neonates.

As Gunz and colleagues (2009) stressed when they laid out “principles for the virtual reconstruction of hominin crania,” these powerful virtual methods can never produce “the” single correct reconstruction of a fossil. Rather, researchers must acknowledge and remain cognizant of all the decisions and assumptions that go into their reconstructions, and attempt to produce multiple reconstructions reflecting these varied uncertainties. Making data openly available further allows other researchers to assess how conclusions were reached, and to add new fossils to existing datasets.

REFERENCES

Baab, K. L. (2025). A fresh look at an iconic human fossil: Virtual reconstruction of the KNM-WT 15000 cranium. Journal of Human Evolution, 202, 103664. https://doi.org/10.1016/j.jhevol.2025.103664

Gunz, P., Mitteroecker, P., Neubauer, S., Weber, G. W., & Bookstein, F. L. (2009). Principles for the virtual reconstruction of hominin crania. Journal of Human Evolution, 57(1), 48–62. https://doi.org/10.1016/j.jhevol.2009.04.004

Neubauer, S., Gunz, P., Leakey, L., Leakey, M., Hublin, J.-J., & Spoor, F. (2018). Reconstruction, endocranial form and taxonomic affinity of the early Homo calvaria KNM-ER 42700. Journal of Human Evolution, 121, 25–39. https://doi.org/10.1016/j.jhevol.2018.04.005

Ponce De León, M. S., Bienvenu, T., Marom, A., Engel, S., Tafforeau, P., Alatorre Warren, J. L., Lordkipanidze, D., Kurniawan, I., Murti, D. B., Suriyanto, R. A., Koesbardiati, T., & Zollikofer, C. P. E. (2021). The primitive brain of early Homo. Science, 372(6538), 165–171. https://doi.org/10.1126/science.aaz0032

Zollikofer, C. P. E., Bienvenu, T., Beyene, Y., Suwa, G., Asfaw, B., White, T. D., & Ponce De León, M. S. (2022). Endocranial ontogeny and evolution in early Homo sapiens: The evidence from Herto, Ethiopia. Proceedings of the National Academy of Sciences, 119(32), e2123553119. https://doi.org/10.1073/pnas.2123553119

Zollikofer, C. P. E., Ponce de León, M. S., Martin, R. D., & Stucki, P. (1995). Neanderthal computer skulls. Nature, 375(6529), 283–285. https://doi.org/10.1038/375283b0

Picking the brain of Homo naledi

A question that has come up a lot on the blog is what endocast fossils can tell us about the brains and behaviors of long-extinct animals. This question is especially salient for Homo naledi, an unexpected human cousin that lived in South Africa at the same time as the earliest modern-like humans around 300,000 years ago. Brain size in H. naledi ranged from 460–610 ml, similar to Australopithecus and the earliest Homo over 1.5 million years ago and less than half the size of other, contemporaneous fossil humans. Despite its small brain size, the frontal lobe of H. naledi seems to have been more similar to humans than australopiths, including in the area associated with speech.

To learn more about the brain of Homo naledi, I teamed up with Shawn Hurst and John Hawks to virtually reconstruct the endocast from the most complete skull and skeleton of the species, nicknamed Neo (which means “gift” in the SeSotho language). We have a paper about it coming out soon in the journal Brain Structure and Function, where we show that Neo’s endocast shape is fairly distinct among Pleistocene hominins. We go on to discuss some implications and limitations of our results for understanding the brain and behavior of H. naledi and other hominins. I’ll write more about it when the paper is actually in press, but in the meantime you can get a sneak preview by checking the data and running the analyses for yourself.

The original Neo cranium (left), its preserved endocranial surface (center), and virtually reconstructed endocast shape (right)

I published the landmark data and R code from our study in the open access repository Zenodo (here). I built off the endocast landmark data that Simon Neubauer and colleagues (2018) made available from their study of the KNM-ER 42700 fossil. I created a landmark template from that dataset and applied it to Neo and Australopithecus africanus cranium Sts 5, and then used geometric morphometric methods to reconstruct the missing regions of Neo and compare it to the other hominins. The accompanying R code walks you through inputting these data, estimating missing landmark positions, and comparing endocast shapes of humans and fossil hominins.

Endocast shapes of Neo and a modern human, as viewed from the left, front, and bottom. Endocasts are scaled by size and aligned by the cranial base.

Hopefully these data and code will let others build off our results, add more fossils to the mix, and generate more insights about how the human brain has changed over the past several millions of years.

A whisper to a scream

Endocasts are the faint whispers of ancient minds. These fossilized phantoms are just about all we have to tell us about the evolutionary history of brains. We are (we are, we are) rather helpless—how can we turn a whisper to a scream?

A human brain (left) and its endocast (center), and a colormap showing distance between endocast and brain (right). Produced using data published by Balzeau and colleagues (2026) and the R package “Morpho” by Stefan Schlager .

Antoine Balzeau and colleagues have recently published an incredible resource for studying brain endocasts, which they aptly call the ‘Rosetta Stone for paleoneurology.’ This is the latest paper from their project PaleoBRAIN, which draws on advanced techniques for studying endocasts and reconstructing the brains of extinct hominins. A few years ago the group published an article led by Nicole Labra asking “What do brain endocasts tell us?”, where they demonstrated the extent to which experts in brain anatomy can nevertheless misidentify actual brain impressions on endocasts. This is a big deal since the identification of brain features, namely sulci separating specific parts of the cortex, is essential for understanding how the human brain has evolved over the past several millions of years. When looking at an endocast, are we really seeing the brain structures that we think we’re seeing?

Balzeau and colleagues make another major contribution to address this problem for paleoneurology. The researchers used advanced MRI brain scanning methods to directly compare the brains and bony endocasts of 75 living humans. They used software that automatically identifies brain sulci from MRI scans and then examined the extent to which each individual’s sulci (left image, above) were expressed on their endocast (center image, above). The study expands greatly on similar work by Jean Dumoncel and colleagues using a slightly different approach. As in the previous research, Balzeau and co found that the endocast can serve as a decent proxy for the underlying brain anatomy, but with some pretty big limitations.

One of the major differences the authors identified between brain and endocast is that whereas brain sulci are often like long valleys (for instance, the long, straight lateral sulcus separating the temporal and frontal/parietal lobes), the corresponding sulci on endocasts are usually much shorter: that is, less of the sulcus makes an impression. Worse, sulci are often broken up into separate segments on the endocast. This is important because if a sulcus isn’t fully preserved we may not know its true course or the spatial relationship between certain brain structures. Plus, if a sulcus is broken up on an endocast, we risk misidentifying the different segments as other, incorrect sulci.

Perhaps the most shocking and sobering observation is that endocasts may bear imprints that are completely unrelated to any actual brain sulci, which they term “MNAS” (marks not associated with sulci). What causes these impish impressions is unclear at this point, but it raises the harrowing possibility that we might identify and interpret fossilized impressions that didn’t actually exist in the brains of ancient animals. Fortunately, Balzeau and team found that MNASes tend to be located closer to the top of an endocast where the brain is not impressing as strongly, whereas true cerebral impressions are strongest in the lower regions of the endocast.

Along these lines, one cool result of the study is that the orbitofrontal sulci, from the part of the brain sitting directly above the eye sockets, were “the most visible impressions” and were observed in all 75 of the endocasts they studied. The orbitofrontal cortex is involved in regulating emotions and impulse control (reviewed in Rudebeck & Rich, 2018), so this part of the brain may have been very important for the evolution of human social behavior. The findings of Balzeau and colleagues suggests we may be able to study this region reliably in the human fossil record. A fossil called MLD 6, for example, is best known for being a beautiful Australopithecus face (well, the right part of it). Yet the fossil is also another overlooked endocast from Makapansgat, South Africa. Specifically, MLD 6 shows pronounced impressions of several of the orbitofrontal sulci, though it is admittedly only well preserved toward the middle.

The partial face and brain endocast of the fossil MLD 6. Views: Front view of the face (top left), face rendered transparent to show the mirror-imaged endocast (top right), right lateral view of the transparent face and endocast (bottom left), and inferior view of the mirror-imaged endocast (bottom right). The “H-shaped” impressions on either side are the medial and lateral orbital sulci connected by the transverse orbital sulcus.

The other major contribution of this paper by Balzeau and colleagues is that all of the data are publicly available (here), meaning that other researchers can validate and expand on this research. This is huge. Historically, most paleoneurologists would have to assess a fossil endocast by consulting an atlas of brain anatomy, which overlooks normal variability. If one were lucky, they could use publications documenting brains of more than one individual, such as the annotated chimpanzee brain images published by Dean Falk and colleagues. The normal variability in both brain morphology and endocranial preservations that Balzeau and co present in this study are great resources on their own. Making all the original data available, though, is a huge step toward putting all paleoneurologists on the same page.

References

Balzeau, A., Bardinet, É., Bardo, A., Bernat, A., Derrey, T., Didier, M., Filippo, A., Hui, J., Kubicka, A. M., Labra, N., Leprince, Y., Mangin, J., Mounier, A., Prima, S., Rivière, D., Santin, M. D., & Giolland, V. (2026). The ‘Rosetta Stone’ of palaeoneurology: A detailed study of the link between the brain and the endocast on 75 volunteers. Journal of Anatomy, joa.70101. https://doi.org/10.1111/joa.70101

Cofran, Z., Hurst, S., Beaudet, A., & Zipfel, B. (2023). An overlooked Australopithecus brain endocast from Makapansgat, South Africa. Journal of Human Evolution, 178, 103346. https://doi.org/10.1016/j.jhevol.2023.103346

Dart, R. A. (1949). The cranio‐facial fragment of Australopithecus prometheus. American Journal of Physical Anthropology, 7(2), 187–214. https://doi.org/10.1002/ajpa.1330070204

Dumoncel, J., Subsol, G., Durrleman, S., Bertrand, A., De Jager, E., Oettlé, A. C., Lockhat, Z., Suleman, F. E., & Beaudet, A. (2021). Are endocasts reliable proxies for brains? A 3D quantitative comparison of the extant human brain and endocast. Journal of Anatomy, 238(2), 480–488. https://doi.org/10.1111/joa.13318

Falk, D., Zollikofer, C. P. E., Ponce de León, M., Semendeferi, K., Alatorre Warren, J. L., & Hopkins, W. D. (2018). Identification of in vivo sulci on the external surface of eight adult chimpanzee brains: Implications for interpreting early hominin endocasts. Brain, Behavior and Evolution, 91(1), 45–58. https://doi.org/10.1159/000487248

Labra, N., Mounier, A., Leprince, Y., Rivière, D., Didier, M., Bardinet, E., Santin, M. D., Mangin, J. F., Filippo, A., Albessard‐Ball, L., Beaudet, A., Broadfield, D., Bruner, E., Carlson, K. J., Cofran, Z., Falk, D., Gilissen, E., Gómez‐Robles, A., Neubauer, S., … Balzeau, A. (2024). What do brain endocasts tell us? A comparative analysis of the accuracy of sulcal identification by experts and perspectives in palaeoanthropology. Journal of Anatomy, 244(2), 274–296. https://doi.org/10.1111/joa.13966

Rudebeck, P. H., & Rich, E. L. (2018). Orbitofrontal cortex. Current Biology, 28(18), R1083–R1088. https://doi.org/10.1016/j.cub.2018.07.018

Shilton, D., Breski, M., Dor, D., & Jablonka, E. (2020). Human social evolution: Self-domestication or self-control? Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.00134

Homo naledi in a lawn chair

It is a great relief that Homo naledi, a most curious critter, was announced to the world on Thursday. I’ve been working on these fossils since May 2014, and it was really hard to keep my trap shut about it for over a year.

Homo naledi on my mind, and phone, all year.

Homo naledi on my mind, and the lock screen on my phone, all year. CT rendering of cranium DH3, top is to the left and front is to the top.

I was in London for the ESHE conference last week when **it hit the fan, and so I got to attend a small press conference from the paper’s publisher, eLife, for the announcement.

eLife press conference last Thursday. From left to right: Will Harcourt-Smith, Matthew Skinner, Noel Cameron, Alia Gurtov and Tracy Kivell.

eLife press conference last Thursday. From left to right: friends and colleagues Will Harcourt-Smith, Matthew Skinner, Noel Cameron, Alia Gurtov and Tracy Kivell.

I had just flown in from Kazakhstan, and was presenting some recent work on the evolution of brain growth (I’ll write a post about it soon, promise), so it was a bit hard to appreciate the gravity of the announcement. Although the awesome spread in National Geographic did help it sink in a bit.

Really blurry photo of Markus Bastir holding up the heaviest copy of National Geographic ever.

I’m wending my way back to Kazakhstan now, but in the coming weeks I will try to post more about these fossils, the project, and specifically what I’m working on.

Until then, I’d like to point out how much information is freely and easily available to the entire world about these fossils. The paper, full-length and filled with excellent images of many of the specimens and reconstructions, is available for free online here. In addition, you can download 3D surface scans of over 80 of the original fossils on MorphoSource, also totally free. Everything about this scientific discovery and its dissemination is unprecedented – the sheer number of fossils and the ease of access with which literally everyone (well, with an internet connection) can access this information has never occurred before. This is the way paleoanthropology should be. Hats off to Lee Berger and the other senior scientists on the project for making such a monumental resource available to all.

ResearchBlogging.orgBerger LR, Hawks J, de Ruiter DJ, Churchill SE, Schmid P, Delezene LK, Kivell TL, Garvin HM, Williams SA, DeSilva JM, Skinner MM, Musiba CM, Cameron N, Holliday TW, Harcourt-Smith W, Ackermann RR, Bastir M, Bogin B, Bolter D, Brophy J, Cofran ZD, Congdon KA, Deane AS, Dembo M, Drapeau M, Elliott MC, Feuerriegel EM, Garcia-Martinez D, Green DJ, Gurtov A, Irish JD, Kruger A, Laird MF, Marchi D, Meyer MR, Nalla S, Negash EW, Orr CM, Radovcic D, Schroeder L, Scott JE, Throckmorton Z, Tocheri MW, VanSickle C, Walker CS, Wei P, & Zipfel B (2015). Homo naledi, a new species of the genus Homo from the Dinaledi Chamber, South Africa. eLife, 4 PMID: 26354291

One more great bioanthro resource

Following up on yesterday’s post containing links to various online data and resources, Dr. Rebecca Jabbour brought the Human Origins Database to my attention today. As stated on the database’s home page:

Currently the Human Origins Database contains the measurements and skeletal element information present in the Koobi Fora Research Project. Volume 4: Hominid Cranial Remains by Bernard Wood (1991). In addition, a complete inventory of skeletal elements present for the chimpanzee and gorilla collections at the Powell-Cotton Museum is included, along with annotated data sheets providing information on epiphyseal fusion, element condition, etc.

Here’s a taste of the Powell-Cotton chimpanzee catalog & maturation info:

You have to register to access the database – which you should do since it’s free and appears immensely useful. Enjoy!

Online skeletal and dental datasets (links links links!)

The TM 1517a fossil, from here

Jean Jacques Hublin has a commentary [1] in the current issue of Nature, about making fossils available for scanning, digital replication, and ultimately hopefully open dissemination. As Hublin points out, it’s a bit ridiculous that a fossil is a rare enough thing as it is, but even after their discovery, fossils “can become unreachable relics once they are in storage.” Fortunately, Hublin goes on to point to online collections that are available to anyone interested. Somewhat ironically, the article about free-ish data is behind a paywall, so here are the resources Hublin describes:

  • The Ditsong CT Archive, created by the collaboration of Hublin’s group at Max Planck and the Ditsong (formerly Transvaal) Museum in South Africa, which contains digitized hominin fossils from the site of Kromdraai (see also [ref 2]). Check out the type specimen of Paranthropus robustus, from this site, above!
  • You can download CT scans of the Skhul V early human fossil, thanks to the Harvard Peabody Museum.
  • Wanna see the the oldest possible animal embryos, early humans, insects, and other crazy fossils? Check out the European Synchrotron Radiation Facility’s microCT database.
  • Get free CT scans of 2 human skulls, thanks to the Virtual Anthropology program at the University of Vienna.
  • Finally, the NESPOS initiative is a large repository of Pleistocene hominin fossil scans, which I somehow don’t know enough about.

In addition to these sources, here are 2 other datasets that are pretty badass:

ResearchBlogging.orgI haven’t had much opportunity to look into these datasets Hublin pointed out, but they look promising. If you know of other good resources, please do share!

References
[1] Hublin, J. (2013). Palaeontology: Free digital scans of human fossils Nature, 497 (7448), 183-183 DOI: 10.1038/497183a

[2] Skinner MM, Kivell TL, Potze S, & Hublin JJ (2013). Microtomographic archive of fossil hominin specimens from Kromdraai B, South Africa. Journal of human evolution, 64 (5), 434-47 PMID: 23541384

Open wide for open access: chimpanzee tooth eruption

Two anthropology papers came out yesterday in advance print at the Proceedings of the National Academy of Sciences. I’d like first to draw your attention to the fact that they’re open access – normally such scientific papers are behind a paywall, but these two can be obtained by anyone (well, anyone with internet). One is about the chronology and nature of Acheulean technology at the 1.7-1.0 mya site of Konso in Ethiopia. The other, and the subject of this post, is about life history in wild chimpanzees from Uganda.

Tanya Smith and colleagues analyzed behavior of chimps and photographs of chimps’ erupting first molars (“M1”) to determine a] the age at which these events happen in the wild (in this population at least), and b] whether M1 eruption is tightly linked with other important life history variables, such as the adoption of adult foods, as had previously been claimed. What an adorable study – check out figure 1 from the paper (right):

Figuring out age at M1 eruption in wild, healthy chimps is important because there has been debate about whether wild chimps actually erupt their teeth at as young of ages as they do in captivity – not natural conditions. This question has recently been investigated in a skeletal sample of wild chimps of known age, from Tai forest in Cote d’Ivoire (Zihlman et al. 2004, T Smith et al. 2010), but somehow these studies raised more questions than they answered (e.g. BH Smith and Boesch 2011). So TM Smith and colleagues decided to further address this question with photographic evidence of living, arguably healthy chimps.

They found that M1 eruption occurred anywhere from 2.8-3.3 years of age in their sample of 5 cuddly infants, consistent with estimates from captivity. I have to say I’m a bit surprised it wasn’t later (but what fun is science if it’s not surprising?). Of course, this is based on 5 infants from one population, so it could stand to be reinvestigated in other chimp populations as the authors note.

Smith et al’s second task was to see how well age at M1 eruption coincided with other life history variables – this is supposed to be an important event, alleged to coincide with cessation of weaning and the adoption of adult foods. Moreover, since a mother is no longer nursing her infant, M1 eruption “should” also be roughly contemporaneous with a mother’s return to estrus cycling and subsequent reproduction. Many infants were observed to begin eating adult-like foods prior to M1 eruption, around 3 years. Unexpectedly however, infants also nursed for a while even after M1 eruption. In fact, time spent nursing actually increased for a brief period around 3 years of age, possibly because their mothers’ milk was not as nutritious as at younger ages.

Now, what interests me most about this are possible implications for the evolution of growth and life history. Many researchers have argued that extinct hominids, like the australopithecines, would have grown up relatively rapidly like apes, rather than slowly like humans. This claim has been based pretty much entirely on dental development, until my dissertation research. There, I’ve shown that one hominid, Australopithecus robustus, probably experienced greater jaw growth than humans prior to eruption of the M2. Now, if this hominid erupted its teeth as fast as apes, and grew more than humans, this implies really really high growth rates for A. robustus (that is, if we can extrapolate from the jaw to the overall body size).

ResearchBlogging.orgI’ll be working a bit more on this latter point in the near future. In the mean time, let’s hear it for open access bioanthro Continue reading

And so the plot thickens



These results suggest admixture between Denisovans or a Denisova-related population and the ancestors of East Asians, and that the history of anatomically modern and archaic humans might be more complex than previously proposed.


I’m sure it will turn out to be more complex still. Onward and upward!


Freely available online through the PNAS open access option.”
http://www.pnas.org/content/early/2011/10/24/1108181108.abstract


Sweet!


Here you go
Skoglund P and Jakobsson M. Archaic human ancestry in East Asia. Proceedings of the National Academy of Sciences in press. doi:10.1073/pnas.1108181108.