Brain size & scaling – virtual lab activity

Each year in my intro bio-anthro class, we start the course by asking how our brains contribute to making us humans such quirky animals. Our first lab assignment in the class uses 3D models of brain endocasts, to ask whether modern human and fossil hominin brains are merely primate brains scaled up to a larger size. In the Before Times, students downloaded 3D meshes that I had made, and study and measure them with the open-source software Meshlab. But since the pandemic has forced everyone onto their own personal computers, I made the activity all online, to minimize issues arising from unequal access to computing resources. And since it’s all online, I may as well make it available to everyone in case it’s useful for other people’s teaching.

The lab involves taking measurements on 3D models on Sketchfab using their handy measurement tool, and entering the data into a Google Sheets table, which then automatically creates graphs, examines the scaling relationship between brain size (endocranial volume, ECV) and endocast measurements, and makes predictions about humans and fossil hominins based off the primate scaling relationship. Here’s the quick walk-through:

Go to the “Data sources” tab in the Google Sheet, follow the link to the Sketchfab Measurement Tool, and copy the link to the endocast you want to study (3D models can only be accessed with the specific links).

Following the endocast Sketchfab link (column D) will bring you to a page with the 3D endocast, as well as some information about how the endocast was created and includes its overall brain size (ECV in cubic cm). Pasting the link when prompted in the Measurement Tool page will allow you to load, view, and take linear measurements on the endocast.

Hylobates lar endocast, measuring cerebral hemisphere length between the green and red dots.

Sketchfab makes it quite easy to take simple linear measurements, by simply clicking where you want to place the start and end points. The 3D models of the endocasts are all properly scaled, and so all measurements that appear in the window are in millimeters.

The assignment specifies three simple measurements for students to take on each endocast (length, width, and height). In addition, students get to propose a measurement for the size of the prefrontal cortex, since our accompanying reading (Schoenemann, 2006) explains that it is debated whether the human prefrontal is disproportionately enlarged. All measurements are then entered into the Google Sheet — I wanted students to manually enter the ECV for each endocast, to help them appreciate the overall brain size differences in this virtual dataset (size and scale are often lost when you have to look at everything on the same-sized 2D screen).

Feel free to use or adapt this assignment for your own classes. The assignment instructions can be found here, and the data recording sheet (with links to endocast 3D models) can be found here — these are Google documents that are visible, but you can save and edit them by either downloading them or making a copy to open in Docs or Sheets.

Ah, teaching in the pandemic 🙃

Latest from the lab: Brain size at Krapina

In the latest paper out of the lab (here), my students and I reconstructed the brain endocasts of the Krapina Neandertals. The Krapina rock shelter in Croatia is a remarkable site. Dating to around 130,000 years ago (if not older), the Krapina fossils are early members of the Neandertal lineage. In addition, the fossils represent dozens of Neandertals, from infants to adults. Part of what drew me to the site were the juvenile skulls, since they can tell us about growth and development in these early humans. But, the fossils are quite fragmentary, and needed to be reconstructed to estimate important characteristics like brain size.

Figure 1 from our paper, showing the five Krapina crania (A & B are the same individual) with the endocranial surface highlighted.

Vassar College has a great program called URSI, where students team up with faculty to get hand on experience conducting research over the summer. So, two summers ago my students and I worked on virtually putting these Humpties Dumpty back together again. Using 3D surface scans of the original fossils and CT scans of modern humans, we used virtual methods to digitally reconstruct the endocasts, which are a good proxy for brain size and shape. Here’s the basic workflow:

Figure 2 from the paper, depicting the workflow for virtually reconstructing fossil endocasts, represented by the famous Krapina 3 or “C” cranium.

The human endocasts were produced from recent humans from the Terry Anatomical Collection, generously made available here by Dr. Lynn Copes. We have posted the 3D landmark data for the humans, the preserved landmarks from the Neandertals, and a big list of estimated brain sizes for Neandertals, in the open access repository Zenodo (here). So, hopefully anyone can repeat our results, or use these data in their own research.

With virtual methods, we could generate multiple reconstructions of each Neandertal fairly easily, giving an idea of how certain or uncertain our brain size estimates were. In the end, we showed that i) the Krapina juveniles, who were probably around 6-7 years old, had brain sizes within the adult range (it’s same with modern humans); ii) average brain size at Krapina was a little lower than previously estimated; and iii) although later Neandertals from other sites had larger brains on average, the difference is not necessarily greater than could be expected by chance.

I’ve participated in Vassar’s URSI program for the past few years and it has been a lot of fun. Last (virtual) summer, my students and I compared hip growth in humans and Australopithecus africanus, and this coming summer we will examine the brains of the greatest animals of all time — gibbons!

Scientific Racism

The site’s been quiet in 2017, with little time to blog on top of my regular professional responsibilities, and of course watching the fascist smoke rising from the garbage fire of our 45th presidential administration with horrified disbelief. At work, my two new classes are keeping me plenty busy, and their content is quite distinct – one is on the archaeological record of Central Asia, the other centers around Homo naledi to teach about fossils. But by complete accident, examples of scientific racism came up in the readings for each course last week.

scientific-racism

Scientific racism refers to using data or evidence from the biological and social sciences to support racist arguments, that one racial group is better or worse than another group; the groups of course, are culturally determined rather than empirically discrete biological entities. This evidence is often cherry-picked, misinterpreted, and/or outright weak. Nicolas’ Wade’s 2014 A Troublesome Inheritance is a recent example of such a work. The book’s racial claims amount to nothing more than handwaving, and so egregious is the misrepresentation of genetic evidence that nearly 150 of the world’s top geneticists signed a letter to the editor rebuking Wade for “misappropriation of research from our field to support arguments about differences among human societies.” Wade’s book has no place in scientific discourse, but then almost anyone can write a book as long as a publisher thinks it will sell.

In addition to the outright misrepresentation of scientific evidence to support racist arguments, another manifestation of scientific racism is the influence of cultural biases in the interpretation of empirical observations. This may be less malicious than the first example, but is equally dangerous as it more tacitly supports systemic and pervasive racism. And this brings us to my classes’ recent readings.

First was a reference to the “Movius Line” in a review of the Paleolithic record of Central Asia (Vishnyatsky 1999) for my prehistory class. Back in the 1940s Hallum Movius, archaeologist and amazing-name-haver, noticed a distinct geographic pattern in the distribution of early stone tool technology across the Old World: “hand-axes” could be found at sites across Africa and western Eurasia, while they were largely absent from East Asian sites, which were dominated by more basic stone tools.

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Movius’ illustration of the distribution of Early Paleolithic technologies. From Fig. 1 in Dennell (2015).

Robin Dennell (2016) provides a nice review of how Movius’ personal, culturally influenced perception of China colored his interpretation of this pattern. Movius read this archaeological evidence to mean that early East Asian humans were unable to create the more advanced technology of the west, a biological and cognitive deficiency resulting from cultural separation: “East Asia gives the impression of having acted (just as historical China and in sharp contrast with the Mediterranean world) as an isolated and self-sufficient area, closed to any major human migratory wave” (Movius 1941: 86, cited in Dennell 2015). Racial and cultural stereotypes about East Asia directly translated to his interpretation of an archaeological pattern.

This type of old school scientific racism also arose in a review of endocasts (Falk, 2014) for my Homo naledi class. Endocasts are negative impressions or casts of a space or cavity, and comprise the only direct evidence of what extinct animals’ brains looked like. So to see how the structure of the brain has changed over the course of human evolution, scientists can search for the impressions of important brain structures in fossil human endocasts. Falk (2014) reviews one of the most famous of these structures – the “lunate sulcus” – which was used as evidence for reorganization of the hominin brain for nearly 100 years. In the early 20th century, anatomist and anthropologist GE Smith (not GE Smith from the Saturday Night Live Band)  thought he’d identified the human homologue of a groove that in apes separates the parietal lobe from the visual cortex. In humans, however, this groove was positioned more toward the back of the brain, which Smith interpreted as an expansion of an area relating to advanced cognition.

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The back of the brain, viewed from the left, of a chimpanzee (left) and two humans, the red line illustrating the Affenspalte or lunate sulcus (Fig. 1 from Falk 2014, which was modified from Smith 1903). The middle one also might be a grumpy fish.

It turns out that the lunate sulcus does not actually exist in humans, as the grooves identified as such are not structurally or functionally the same as the lunate sulcus in apes (Allen et al., 2006). Nevertheless, given what Smith thought the lunate sulcus was, it’s tragic to read his interpretations of human variation: “resemblance to the Simian [ape] pattern… is not quite so obvious…. in European types of brain….” (Smith 1904: 437, quoted in Falk 2014). The human condition for this trait was for it to be located in the back, reflecting an expansion of the cognitive area in front of it, and this pattern was less pronounced, according to Smith, in non-European people’s brains. This interpretation reflects two traditions at the time: 1) to refer to racial ‘types,’ ignoring variation within and overlap between groups, as well as 2) the prevailing wisdom that Europeans were more intelligent or advanced than other geographical groups.

ResearchBlogging.orgAnecdotes such as these may seem like mere scientific and historical curios, but they should serve as important reminders both that science can be accidentally guided by cultural values, or intentionally used for malevolent ends. Misconceptions and errors of the past shouldn’t be erased, but rather touted so that we don’t repeat mistakes that can have major consequences in our not-so-post-racial society.

References

Allen JS, Bruss J, & Damasio H (2006). Looking for the lunate sulcus: a magnetic resonance imaging study in modern humans. The anatomical record. Part A, Discoveries in molecular, cellular, and evolutionary biology, 288 (8), 867-76 PMID: 16835937

Dennell, R. (2016). Life without the Movius Line: The structure of the East and Southeast Asian Early Palaeolithic Quaternary International, 400, 14-22 DOI: 10.1016/j.quaint.2015.09.001

Falk D (2014). Interpreting sulci on hominin endocasts: old hypotheses and new findings. Frontiers in human neuroscience, 8 PMID: 24822043

Vishnyatsky L (1999). The Paleolithic of Central Asia. Journal of World Prehistory, 13, 69-122.

Worst year in review

As we’re wrapping up what may be the worst year in recent global memory, especially geopolitically, let’s take a moment to review some more positive things that came up at Lawnchair in 2016.

Headed home

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Alternate subtitle: Go West
This was a quiet year on the blog, with only 18 posts compared with the roughly thirty per year in 2014-2015. The major reason for the silence was that I moved from Kazakhstan back to the US to join the Anthropology Department at Vassar College in New York. With all the movement there was  less time to blog. Much of the second half of 2016 was spent setting up the Biological Anthropology Lab at Vassar, which will focus on “virtual” anthropology, including 3D surface scanning…

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Cast of early Homo cranium KNM-ER 1470 and 3D surface scan made in the lab using an Artec Spider.

… and 3D printing.

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gibbon endocast, created from a CT scan using Avizo software and printed on a Zortrax M200.

This first semester stateside I reworked my ‘Intro to Bio Anthro’ and ‘Race’ courses, which I think went pretty well being presented to an American audience for the first time. The latter class examines human biological variation, situating empirical observations in modern and historical social contexts. This is an especially important class today as 2016 saw a rise in nationalist and racist movements across the globe. Just yesterday Sarah Zhang published an essay in The Atlantic titled, “Will the Alt-right peddle a new kind of racist genetics?” It’s a great read, and I’m pleased to say that in the Race class this semester, we addressed all of the various social and scientific issues that came up in that piece. Admittedly though, I’m dismayed that this scary question has to be raised at this point in time, but it’s important for scholars to address and publicize given our society’s tragically short and selective memory.

So the first semester went well, and next semester I’ll be teaching a seminar focused on Homo naledi and a mid-level course on the prehistory of Central Asia. The Homo naledi class will be lots of fun, as we’ll used 3D printouts of H. naledi and other hominin species to address questions in human evolution. The Central Asia class will be good prep for when I return to Kazakhstan next summer to continue the hunt for human fossils in the country.

Osteology is still everywhere

A recurring segment over the years has been “Osteology Everywhere,” in which I recount how something I’ve seen out and about reminds me of a certain bone or fossil. Five of the blog 18 posts this year were OAs, and four of these were fossiliferous: I saw …

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Anatomy terminology hidden in 3D block letters,

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Hominin canines in Kazakhstani baursaki cakes,

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The Ardipithecus ramidus ilium in Almaty,

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Homo naledi juvenile femur head in nutmeg,

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And a Homo erectus cranium on a Bangkok sidewalk. As I’m teaching a fossil-focused seminar next semester, OA will probably become increasingly about fossils, and I’ll probably get my students involved in the fun as well.

New discoveries and enduring questions

The most-read post on the blog this year was about the recovery of the oldest human Nuclear DNA, from the 450,000 year old Sima de los Huesos fossils. My 2013 prediction that nuclear DNA would conflict with mtDNA by showing these hominins to be closer to Neandertals than Denisovans was shown to be correct.

giphy

These results are significant in part because they demonstrate one way that new insights can be gained from fossils that have been known for years. But more intriguingly, the ability of researchers to extract DNA from exceedingly old fossils suggests that this is only the tip of the iceberg.

The other major discoveries I covered this year were the capuchin monkeys who made stone tools and the possibility that living humans and extinct Neandertals share a common pattern of brain development.

Pride & Predator

An unrelated image from 2016 that makes me laugh.

The comparison between monkey-made and anthropogenic stone tools drives home the now dated fact that humans aren’t the only rock-modifiers. But the significance for the evolution of human tool use is less clear cut – what are the parallels (if any) in the motivation and modification of rocks between hominins and capuchins, who haven’t shared a common ancestor for tens of millions of years? I’m sure we’ll hear more on that in the coming years.

In the case of whether Neandertal brain development is like that of humans, I pointed out that new study’s results differ from previous research probably because of differences samples and methods. The only way to reconcile this issue is for the two teams of researchers, one based in Zurich and the other in Leipzig, to come together or for a third party to try their hand at the analysis. Maybe we’ll see this in 2017, maybe not.

There were other cool things in 2016 that I just didn’t get around to writing about, such as the publication of new Laetoli footprints with accompanying free 3D scans, new papers on Homo naledi that are in press in the Journal of Human Evolution, and new analysis of old Lucy (Australopithecus afarensis) fossils suggesting that she spent a lifetime climbing trees but may have sucked at it. But here’s hoping that 2017 tops 2016, on the blog, in the fossil record, and basically on Earth in general.

Osteology Everywhere: Skull in the Stone #FossilFriday edition

It’s that time of year again.

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It’s the end of the year and I’ve got Homo erectus on the brain somethin fierce. Our precedent-erect first popped up in Africa around 1.9 million years ago, quickly spread throughout much of the Old World, and persisted until perhaps as late as ~ 100,000 years ago in Java, Indonesia. This was a very successful species by all accounts, and as a result of its great range and duration, you can imagine it was also pretty variable.

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Hominin brain sizes. Boxes and whiskers represent sample tendencies and points are individual specimens. 1 = Australopithecus, 2 = Early Homo (cf. habilisrudolfensis), 3 = Dmanisi H. erectus, 4 = Early African H. erectus, 5 = Early Indonesian H. erectus, 6 = Chinese H. erectus, 7 = Later Indonesian H. erectus, 8 = modern humans.

Despite this great variation, H. erectus skulls generally share a common visage: long and low cranial vault, low forehead, protruding brow ridges, fun tuberosities and tori in the back. You’d recognize them anywhere. Including the sidewalk!

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Homo erectus in front of Ploenchit Tower, Bangkok (lateral view, front is to the right).

The relief in this sidewalk slat superficially looks like a trace fossil of partial H. erectus cranium, the face either missing (from the lower right) or taphonomically displaced toward the left side of the tile (see here for actual H. erectus trace fossils). This looks really similar to H. erectus from Indonesia, not surprising given its discovery in Thailand. Why, it could have come straight out of Figure 6 from a 2006 paper by Yousuke Kaifu and colleagues:

Bangkok erectus.png

Left lateral views of Javanese H. erectus crania, modestly modified from Kaifu et al. (2006: Fig. 6). Front is to the left this time.

Using my insane photo editing skills, I’ve inserted the Ploenchit Tower trace fossil (reversed) within the horde of heads presented by Kaifu et al., above. Like many of the real fossils, the Ploenchit specimen is missing the face (due to taphonomy), the supraorbital torus or brow ridge juts out from a low-rising forehead, and the occipital bone also projects out about from the otherwise rounded contour of the cranium. Note that there is a good deal of variation in each of these features among the real fossils.

What a happy holiday accident to find a Homo erectus cranium on the street!

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ResearchBlogging.org Reference
Kaifu Y, Aziz F, Indriati E, Jacob T, Kurniawan I, & Baba H (2008). Cranial morphology of Javanese Homo erectus: new evidence for continuous evolution, specialization, and terminal extinction. Journal of human evolution, 55 (4), 551-80 PMID: 18635247

Bioanthro lab activity: Hominin brain size

Last week in my Human Evolution class we looked at whether we could estimate hominin brain sizes, or endocranial volumes (ECV), based on just the length and width of the bony brain case. Students took these measurements on 3D surface scans…

Maximum cranial length in Australopithecus boisei specimen KNM-ER 406.

Maximum cranial length in Australopithecus boisei specimen KNM-ER 406.

… and then plugged their data into equations relating these measurements to brain size in chimpanzees (Neubauer et al., 2012) and humans (Coqueugniot and Hublin, 2012).

The relationship between cranial length (x axis) and ECV (y axis).

The relationship between cranial length (x axis) and ECV (y axis). Left shows the chimpanzee regression (modified from Fig. 2 in Neubauer et al., 2012), while the right plot is humans (from the Supplementary Materials of Coqueugniot and Hublin, 2012).

So in addition to spending time with fossils, students also learned about osteometric landmarks with fun names like “glabella” and “opisthocranion.” More importantly, students compared their estimates with published endocranial volumes for these specimens, based on endocast measurements:

Human and chimpanzee regression equations don't do great at estimating hominin brain sizes.

Human and chimpanzee regression equations don’t do great at predicting hominin brain sizes. Each point is a hominin fossil, the x value depicting its directly-measured endocranial volume and the y value its estimated volume based on different regression equations. Black and red points are estimates based on chimpanzee cranial width and length, respectively, while green and blue points are based on human width and length, respectively. The dashed line shows y=x, or a correct estimate.

This comparison highlights the point that regression equations might not be appropriate outside of the samples on which they are developed. Here, estimates based on the relationship between cranial dimensions and brain size in chimpanzees tend to underestimate fossils’ actual values (black and red in the plot above), while the human regressions tend to overestimate hominins’ brain sizes. Students must think about why these equations perform poorly on fossil hominins.

Most of the fossil scans come from AfricanFossils.org, but a few are from Artec’s sample gallery. One of the cool, fairly recent humans at African Fossils (KNM ER 5306) will give students something else to think about:

"Why doesn't this look like the rest of the human crania we've seen this semester?"

“Why doesn’t this look like the rest of the human crania we’ve seen this semester?”

Here are the lab materials so you can use and adapt this for your own class:

Lab 4-Brain size (Instructions & questions)

Lab 4 data table (with equations)

ResearchBlogging.orgReferences
Coqueugniot, H., & Hublin, J. (2012). Age-related changes of digital endocranial volume during human ontogeny: Results from an osteological reference collection American Journal of Physical Anthropology, 147 (2), 312-318 DOI: 10.1002/ajpa.21655

Neubauer, S., Gunz, P., Schwarz, U., Hublin, J., & Boesch, C. (2012). Brief communication: Endocranial volumes in an ontogenetic sample of chimpanzees from the taï forest national park, ivory coast American Journal of Physical Anthropology, 147 (2), 319-325 DOI: 10.1002/ajpa.21641

A new year of bioanthro lab activities

One of my goals in teaching is to introduce students to how we come to know things in biological anthropology, and lab activities give students hands-on experience in using scientific approaches to address research questions. Biological anthropology (really, all biology) is about understanding variation, and I’ve created some labs for students to scrutinize biological variation within the classroom.

In my Introduction class, the first aspect of human uniqueness we will focus on is the brain. To complement readings and lectures, we’ll also investigate variation in brain size among students in class. Of course, measuring their actual brain sizes is impossible without either murdering them (unethical and messy) or subjecting them to CT or MRI scanning (costly and time-consuming). Instead, it’s fast and easy to measure head circumference, so we’ll estimate just how brainy they are in a way that will also introduce them to data collection, measurement error, and the regression analysis.

The lab activity is based on a paper by Bartholomeusz and colleagues (2002), who used CT scanning to measure the external head circumferences and brain volumes of males ranging from 1-40 years. Focusing on the adults of this sample, there are several possible regression equations that students could use to estimate their brain size from their head circumference:

The relationship between head circumference and brain volume in adult humans. Note each regression line is based on different age groups.

The relationship between head circumference and brain volume in adult humans. Note each regression line is based on different age groups. Data from Bartholomeusz et al. (2002).

Bartholomeusz et al. divided their sample into age groups, and students will learn that the relationship between the two variables differs subtly depending on the age group. Students will therefore have to decide (and justify) which equation they will use – should they pick the one based on their own age group, or the one with the lowest prediction error?

Once students have estimated their brain sizes, I’ll enter the data into R and we’ll look at how (estimated) brain size varies within the classroom, looking also at possible covariates including sex and region of birth. After discussing our data in class, students have to write up a brief report describing our research question and proposing additional hypotheses about brain size variation.

So that’s this week’s lab in Introduction to Biological Anthropology. There will be four more this semester, in three of which students will collect data on themselves, as well as four other labs for my Human Evolution course. In case you’re interested in using this activity for your class, I’m including the lab handout here. I’ll also try to post lab assignments to the blog (as I’ve done here) as the semester progresses.

Activity handout: Lab 1 Instructions and report

ResearchBlogging.orgReference

Bartholomeusz, H., Courchesne, E., & Karns, C. (2002). Relationship Between Head Circumference and Brain Volume in Healthy Normal Toddlers, Children, and Adults Neuropediatrics, 33 (5), 239-241 DOI: 10.1055/s-2002-36735