Day: April 22, 2026

Every parent that’s watched their children play with dinosaurs have all had the same thought at one time or another: thank God dinosaurs are extinct. While the idea of dinosaurs seems mythical to some, paleontologists have determined their existence through fossils since the 1820’s. As technology advances, and paleontologists uncover more dinosaur fossils, the science world is realizing how crucial dinosaurs were to their ecological environment. To better understand what dinosaurs ate, paleontologists are transitioning from observing tooth structures to something most individuals may find repulsive or uncanny: fossilized feces, otherwise known as coprolites.

More specifically, paleontologists are currently studying a 26.5 inch coprolite- the largest recorded fossilized dung- of a Tyrannosaurus rex (T.Rex) to uncover what kind of organisms they preyed upon. The reason paleontologists are so keen on examining coprolites compared to other fossils is because dung structures provide an in-depth look into their diet. Karen Chin, a paleo-ecologist and professor at the University of Colorado describes the coprolite search to be fascinating, “…they’re basically like receipts of transactions of carbon resources that are traveling through an ecosystem” (Scott et.al, 2023). Dr. Chin’s analogy breaks down the concept of coprolites and gently nudges at the importance of the molecular structure within coprolites, which allows researchers like Dr. Chin to identify likely organisms part of the food web. 

Firstly, what does a coprolite consist of? In terms of their chemical composition, coprolites are mainly composed of calcium phosphate, a compound that allows the structure to be preserved (as they have been for millions of years). Externally, coprolites do not have a universal look- some are coiled or cylindrical while others have defined features that create an unwieldy look. Color wise, coprolites look…well one doesn’t need a description for that. As paleontologists continue studying the internal components of coprolites, a major breakthrough emerges. While analyzing coprolites of carnivorous dinosaurs, like the T.Rex and Spinosaurous, they discover intact bone fragments. This suggests that carnivorous dinosaurs ingested bones and that their digestive systems adapted to this lifestyle, as seen in the coprolites. Furthermore, coprolites are aiding scientific advancements in understanding the types of living organisms that lived during the Triassic to Cretaceous periods. Bone remnants have the potential to revolutionize how we comprehend dinosaur digestion in relation to their ecosystem.

The future implications of dinosaur coprolites are unimaginable; paired with the technology scientists develop for paleontologists to utilize, novel discoveries are on the up and coming. One of the many technological devices paleontologists are focusing on is the synchrotron microtomography, an X-ray machine that analyzes biological specimens (Sena et.al, 2022). These images provide paleontologists with a micro-analysis of the coprolites and make the process of tracking dietary habits easier. Not only can paleontologists identify the type of prey (animal or plant) but are able to answer the biggest question regarding dinosaurs: how did these creatures become the top predator of their food chain? 

The search for possible solutions led paleontologists to discover herbivores and their reign among the food chain. They’ve discovered that dinosaurs who acquired plant-based diets were surviving, reproducing, and growing in size. Essentially, as carnivorous dinosaurs converted to herbivores and made their palate diverse, by the Triassic period, they could adapt to any type of environment. Coprolites played a major role in revealing this fact by displaying trace fossils of the animals herbivores hunted. (Pattison 2024). Herbivore coprolites are proving to be indispensable in the paleontologist world- who knows what other mysteries could be solved as more coprolites emerge. For years paleontologists have observed fossilized dinosaur teeth and even vomit as the primary methods of identifying dietary patterns. Now, they utilize dinosaur coprolites, or dung, with the help of innovative technology that is paving the way for thorough research like never before.

References

Scott, A., McCoy, B., & Ramirez, R. (2023, November 24). What fossilized poop can teach us about dinosaurs. NPR. https://www.npr.org/2023/11/24/1198908684/dinosaurs-fossilized-poop-utah-dung-beetles-jurassic-park 

Brumfiel, G. (2024, November 27). Over 500 fossilized poops show how dinosaurs came to rule the Earth. NPR. https://www.npr.org/2024/11/26/nx-s1-5206634/fossilized-poops-show-how-dinosaurs-came-rule-earth#:~:text=A%20few%20years%20ago%2C%20he,were%20eating%20lots%20of%20stuff 

Sena G, Fidalgo G, Paiva K, Barcelos R, Nogueira LP, Colaço MV, Gonzalez MS, Azambuja P, Colaço G, da Silva HR, de Moura Meneses AA, Barroso RC. Synchrotron X-ray biosample imaging: opportunities and challenges. Biophys Rev. 2022 Jun 2;14(3):625-633. doi: 10.1007/s12551-022-00964-4. PMID: 35791381; PMCID: PMC9250583.

Pattison, K. (2024, November). Dino droppings reveal how the Giant Beasts came to dominate Earth | science | AAAS. Science. https://www.science.org/content/article/dino-droppings-reveal-how-giant-beasts-came-dominate-earth 

Science communication is an often-overlooked but very important part of furthering the scientific process, and both researchers and publishers often use graphical means to display experimental results and data through figures, as presenting data this way is considered standard within reporting results and finding as it is easily interpretable for a vast array of audiences. However, as a neuroscience student, both involved with research in a computational cognition and neuroAI lab and involved with STEM communication as a communications assistant for an institutional research institute, an interesting nuance to researchers’ use of graphs and figures to portray their results, both statistically, as the results of an experimental analysis, and methodologically, which shows their experimental process, is that while we think that we know what cognitive mechanisms people are using while interpreting these figures, in reality, the neural mechanisms are, for the most part, completely unexplored.

Inherently, almost anyone that you ask would believe that graph and figure comprehension is a visual task; however, research as recent as 2023 published by the National Eye Institute has shown that this might not be as true a heuristic – a mental shortcut or “cheat” that makes solving a problem easier – as initially thought. The National Eye Institute’s research showed that connections to the first region of the brain where visual information is processed, the primary visual cortex (V1), are rather small, accounting for between only 2 and 10 percent of neural connections that would be thought to inform us as to what we are perceiving. This is really interesting from a systems perspective in neuroscience, as this implies that what we are seeing only accounts for a relatively small portion of what we perceive. Therefore, in terms of graph and figure comprehension, the vast majority of neural connections are from other, non-visual,  regions of the brain, leading us to believe that our cognitive processing of graphs is largely a top-down process; a process where our understanding is heavily biased by prior experience and not what we are seeing in the moment.

From our understanding of the cognitive processes of how we interpret graphs and figures, many different brain regions could theoretically be responsible for this task; until neuroimaging research is done, we will never know for certain. However, one region of the brain that is non-visual and could be responsible for and contribute to our ability to understand information embedded within graphs is the language network and its associated regions. The language network is a portion of the brain made up of many distinct regions, such as Broca’s and Wernicke’s areas, which are commonly known to be involved with speech generation and understanding, respectively, that neuroscientists know contribute to our linguistic abilities. This region of the brain, along with other associated regions such as the cerebral cortex, suggested by some recent research in the context of semantics (Ivanova et. al., 2025), might play a large role in our ability to understand and interpret graphs and figures.

Additionally, research that has looked at large language models (LLMs), a form of artificial neural networks loosely modeled after how researchers understand the nervous system to process language, has interestingly shown that while really bad at processing graphs and figures, LLMs do technically use language to interpret and draw conclusions as to what they are looking at and pull from prior experience and reinforcement learning (Wang 2025).

Overall, because of this, I believe that our ability to process and understand graphs and figures would rely on another cognitive mechanism, such as language or semantics, for example, where we can “think through” and connect what we are observing in a figure to information that we already know – so this inherent visual task, may not be as much about seeing, as it is about knowing. In general, rephrasing this question to What is the neural basis of data visualization comprehension? to explore The Semantics of Data Visualization is a really interesting idea that sits at the intersection of computational cognition, neuroAI, and STEM communication.  

References

Ivanova, A. A., Kauf, C., Gao, R., She, J. S., Kean, H. H., Goldhaber, T., Nieto-Castañón, A., Varley, R., Kanwisher, N., & Fedorenko, E. (2025). Semantic reasoning takes place largely outside the language network (Version 1) [Preprint]. bioRxiv. https://doi.org/10.64898/2025.12.07.692873

National Eye Institute. (2023). Sparse, small, but diverse neural connections help make perception reliable, efficient. U.S. Department of Health and Human Services, National Institutes of Health. 

Wang, H. W., Wang, Z., Xu, Y., Chen, Z., Wu, Y., Qu, H., & Hullman, J. (2025). How aligned are human chart takeaways and LLM-generated insights? IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2024.10681139