geometric morphometrics

Open access opens the skull of Homo naledi

/ zcofran

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

/ zcofran

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

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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.

Hip new Australopithecus deyiremeda juveniles

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Header: "Australopithecus deyiremeda" but in a gold Harry Potter font, beneath which in the "Chalkduster" font is written, "And the Explosion of non-adult fossils"

Dr. Yohannes Haile-Selassie & colleagues just published some amazing fossils from around 3.4 million years ago, that convincingly link an unusual hominin foot fossil to an ancient human called Australopithecus deyiremeda.

In 2012, Haile-Selassie and team reported a foot fossil from Burtele, Ethiopia, revealing a bipedal creature (like a human) but with some grasping ability in the big toe (like all other primates). Then in 2015, the team presented some jaws and teeth from a nearby geological locality in the Burtele region, around which they designated a new hominin species, Australopithecus deyiremeda. The researchers hesitated to allocate the Burtele foot to this new species since they didn’t have similar fossils for comparison between the different fossil localities. But as the scientists have recently reported, jaws and teeth discovered from the foot site, including an incredible juvenile mandible, match those of Au. deyiremeda from the nearby Burtele sites. Now we can put a foot to the name.

The Burtele fossils help reveal the diversity of early hominins like Australopithecus and the contexts out of which our own genus Homo evolved. What caught my attention hiding among this amazing assemblage was a fossil that only gets a quick mention in the paper—the ischium bone from the hip of a juvenile deyiremeda:

Extended Data Figure 7 from Haile-Selassie et al. (2025). The BRT-VP-2/87 juvenile ischium (from the right side of the body), depicted in side (a), middle (b), and back (c) views.

The fossil, given the catalog number BRT-VP-2/87, represents a different individual from the juvenile jaw mentioned above. It nevertheless provides a great deal of information despite being a small fragment (less than 2 inches long). The authors observe that the body of the ischium that extends beneath the hip joint is quite long, similar to modern apes, fossil Ardipithecus ramidus, and australopiths. This contrasts with the ischium of modern and fossil Homo in which the bone projects less beyond the hip socket:

Right juvenile ischium bones, scaled to similar size and oriented in similar positions. The black line on each depicts the distance from the hip socket margin to the top of the ischial tuberosity (left modified from Scheuer & Black, 2000 Fig. 10.15)

The bottom of the ischium is called the “ischial tuberosity,” and is the attachment surface for the hamstrings muscles. Having a long ischium provides the hamstrings of apes and other arboreal primates with more powerful hip extension—very useful when climbing trees but it also limits how far back the thigh can extend away from the body (Kozma et al., 2018). The shorter ischium of humans, Homo naledi, and other members of our genus may make our hamstrings a little less powerful, but it also helps us fully extend our legs which is crucial to our efficient bipedal walking and running.

Pelvis growth and development in chimpanzees (top row) and humans (bottom row), all scaled to a similar vertical height. Notice the differences in both the relative length of the ischium (blue bracket) and orientation of the ischial tuberosities between chimps and humans, consistent across the growth period. Images modified from Huseynov et al. (2016 and 2017).

Based on studies of modern humans and other primates, we know that this configuration of bones and muscles is established before birth, so we can be confident that adult Au. deyiremeda would have had a similar anatomy to BRT-VP-2/73, albeit at an unknown, larger size. A hip well adapted for climbing is consistent with the Burtele foot with a grasping big toe.

As Haile-Selassie and colleagues note in the online supplementary information accompanying the paper, only immature fossils allow us to reconstruct the evolution of growth and development. But one of the major challenges of studying immature remains is determining their age or state of maturation, which is critical for understanding how much change occurs between, say, infancy and adulthood. The authors of this study note that the qualitative appearance of the BRT-VP-2/73 hip socket surface is like that of modern humans around 6 years of age, yet the fossil is much smaller and more similar in size to 3 year-old humans. My colleagues and I (2022) faced a similar challenge when analyzing a juvenile Homo naledi hip, and we also relied on qualitative comparisons of how the joint “looks” at different stages of development.

But I think we’re at a point now where we can try to quantify some of these tricky developing surfaces to help place immature fossils more precisely along a timeline of development. For example, Peter Stamos & Tim Weaver (2020) adapted a method for quantifying the topography of teeth, to measure the complex curvature of the developing surface of the knee. If these quantitative methods can distinguish different phases of development in large samples of humans and other primates (e.g., Stamos et al., 2025), they could then be extended to the immature hominin fossil record.

Some cool insights could also be gained by applying older and established methods like landmark-based geometric morphometrics, even on quite fragmentary fossils. This approach could capture the development and orientation of the ischial tuberosity relative to the hip socket surface in fragments like BRT-VP-2/73, MLD 8, and Homo naledi fossils (depicted above) and compared with fossil adults. Researchers have also devised robust ways of quantifying size and shape changes during growth based on modern animals, and using these patterns to then ‘grow’ immature fossils to more developed states, for comparison with actual adult fossils (McNulty et al., 2006). Applying this approach to even just the small fossil sample of ischia described here could tell us a lot about how ancient animals moved at different periods in their lives. Someone just needs to park their ischial tuberosities in a chair and do it!

A growing fossil record of immature hominins, alongside technical advances in quantifying and comparing anatomy, mean that we are ready to learn much more about how our extinct ancestors and cousins grew into competent adults.

Krapina endocast update (open data & code)

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In the Summer of 2019 I worked with some great Vassar undergrads to make virtual endocasts and generate new brain size estimates for the Neandertals from the site of Krapina, which we then published in 2021 (discussed in this blog post). The virtual approach to endocast reconstruction uses 3D landmark-based geometric morphometrics methods, and so in the spirit of open science we also published all the landmark data used for the study (as well as a bunch of other fossil human brain size estimates) in the Zenodo repository (here).

Neandertal fossil specimens Krapina 3 (purple/green) and Krapina 6 (yellow/red) with preserved landmarks and virtually reconstructed endocasts.

Something major and global happened around that time — who can even remember what? — and so I never got around to posting R code to accompany the study. So, I’ve finally gotten around to adding some very basic code to the Zenodo entry (better late than never). The code simply reads in the landmarks, estimates missing data for fossils, and does some very basic shape analysis and visualization. It’s doesn’t get into all the nuts and bolts of our study, but it should be enough to help folks check our data or get started with shape analysis in R.

R code includes ways to visualize the landmark data. Left: Principal components analysis graph of endocast shape for humans (red) and Neandertals (blue). Right: Triangle meshes of the average human and Neandertal endocast shapes, viewed from the right, bottom, and back.

Original article
Cofran Z, Boone M, Petticord M. 2021. Virtually estimated endocranial volumes of the Krapina Neandertals. American Journal of Physical Anthropology 174: 117–128. (link)

New decade, new syllabi

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We just kicked off the Spring semester here at Vassar College, and so I’ve got some freshly-updated bio-anthro syllabi hot off the press. This semester, I’m doing my annual introductory class (Anth 120, “Human Origins”), a resurrected seminar (Anth 305: “Human Evo-Devo”), and a second stab at a new methods module (Anth 211: “Virtual Anthropology”).

Anth 120 is similar to previous versions, although this year I’ve taken out a reading/lecture on Paleolithic technology, replaced with articles scrutinizing evolutionary psychology. We’ll see how it goes.

The other two classes are greatly overhauled from previous versions. Anth 211, “Virtual Anthropology,” is my first contribution to a new curricular initiative here at Vassar, which are called “intensives.” Anth 211 is kind of a hybrid between a regular class and an independent study, giving students experience with computer-based, “virtual” methods used in biological anthropology and related fields.  In the first half of the semester, students will get to try out some of these methods and see what kinds of research questions they’re used for. In the 2nd half of the term, students do their own Virtual Anthropology study drawing on the materials in my HEAD Lab, and then present a research poster at the end of the year. I debuted this intensive last Fall, and based on that experience I’m providing a bit more training and have more activities for students this Spring. If last semester’s projects are at all predictive, we should have some fun projects in store this year.

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Anth 305 is a fossil-focused examination of the roles of growth and development in human evolution, and this year’s version is also highly modified from the last time I taught it over two years ago. In that first version, course content was patterned along the skeleton, e.g., one week looked at evolution and development of teeth, next week the spine, etc. Such a bauplan might work for building bodies, but it wasn’t the best for teaching. So this year, we’re spending the first few weeks on the fossil record of human evolution, getting acquainted with the curious characters of our deep past. From there, we go over skeletal / developmental biology, before delving into special evo-devo topics like “morphological integration” and “heterochrony” for the rest of the semester. We’ll also read lots of old, “classic” papers along the way.

Syllabi for these, and other classes, can be found on the teaching page of the site, if you want to learn more.