Could we be looking at an all-female burial chamber?

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An unusual survival advantage.

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Don't blink.

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It really works!

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Hiding in plain sight.

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"The highlight of my career.”

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Archaeologists say the motivation is "very difficult to interpret".

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Long before buboes.

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What went on here?

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The heads are nowhere to be found.

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Archaeologists working with the Israeli Antiquities Authority have announced the discovery and excavation of a cave located just outside the town of Fureidis, which has revealed signs of early human presence dating back to between 250,000 and 400,000 years ago.

The team of researchers behind the ongoing excavation said the fortuitous discovery could represent a “time capsule” that has remained sealed for hundreds of thousands of years, offering researchers an unprecedented glimpse into a critical period in human evolution.

Ancient Cave Contains Evidence of Critical Period in Human Evolution

According to a statement emailed to The Debrief, the ancient cave, which lies south of Haifa, near the Zikhron Ya’akov interchange, likely dates back to sometime between 400,000 and 250,000 years before present. The team notes that the range would mean it was sealed since the time of the Acheulo-Yabrudian culture, a period when ancient human ancestors began to display several complex tool-making skills, including various stone blade designs which were in use by hominins until around 300,000 years ago, marking the end of the Lower Paleolithic period.

“The culture we are investigating here was characterized by a variety of advanced methods for producing flint tools, including small sharp handaxes, scrapers, and blades,” explained Dr. Kobi Vardi, head of the Prehistory Branch at the Israel Antiquities Authority and the study’s co-director.

Most archaeologists put the African departure date of the last common ancestor of humans and Neanderthals between 700,000 and 500,000 years ago, and the first genetic interbreeding between the two species around 130,000-1,000,000 years ago. Therefore, finding a sealed cave containing relics from the period between these two critical evolutionary junctures offers the research team an unprecedented opportunity.

“We have been fortunate to excavate a unique site of global importance that has been protected from the ravages of time thanks to the exceptional conditions that existed here,” said team member Professor Ron Shimelmitz of the Zinman Institute of Archaeology and the School of Archaeology and Maritime Cultures at the University of Haifa.

Dr. Vardi agreed, noting that “It is very rare to find a site in such a state of preservation.”

“Every prehistorian who visits the site is absolutely thrilled,” he added.

“The Seeds That Led to the Development of Our Complex Culture”

In that same statement, Prof. Shimelmitz noted that the end of the Lower Paleolithic was a “unique time period” before Neanderthals and modern humans became the dominant hominids of the era and spread across “many regions.”

“Only a handful of sites from this important phase have been uncovered in Israel, and the wider Levant, and most of them are inaccessible for research,” the professor explained, adding that marked changes in human physiology, technology, and social organization “foreshadowed the traits and complex behavioral patterns that developed later and characterize both Neanderthals and modern humans.”

One component that helped facilitate the development of complex culture, highlighted by Prof. Shimelmitz, is the transition from ancient humans living in larger groups. He also emphasized the advent of human ancestors “spending longer periods at the same sites.”

Early excavations have already uncovered evidence of what the researcher termed “intensive use of fire.” These early forays have also found signs of prolonged human activity. Prof Shimelmitz said these signs suggest a “complex and rich camp life.”

Dr Vardi said that the ongoing excavation is uncovering animal bones, including ancient specimens of fallow deer, gazelle, and an ancient variety of horse.

Dr. Vardi also noted that these finds were discovered “alongside evidence of the presence of water,” which he suggests may have made the ancient cave an attractive location for hunter-gatherer groups inhabiting the region at the time.

High Resolution Studies of How Ancient Humans Lived

When discussing the implications of their findings, Prof. Shimelmitz first expressed the team’s appreciation for the financial support and enthusiasm shown by the project’s sponsor, the Ayalon Highways Company, “in enabling us to undertake the excavation.”

As for the scientific value of their initial discoveries and the potential for further insights into this period in human history, the professor noted that findings to date are typically associated with “the development of social cooperation and the transmission of knowledge, as part of the processes of human evolution.”

Dr. Vardi echoed those sentiments, while also noting that the ancient cave’s archaeological value “is no less important” than that of the well-known Nahal Me’arot site from the same evolutionarily critical period.

“(This site) will allow us to study in high resolution how humans lived at that time,” the researcher added.

Given the importance the research team put on the site, which included co-leader Amit Gabbay, the Israel Antiquities Authority and the University of Haifa are already putting forth what they describe as a “large-scale research program that seeks to reconstruct how humans lived, adapted to their environment, and developed new lifestyles and technologies over the course of human evolution.”

Along with heralding the site’s scientific value, the researchers highlighted its cultural importance by declaring their goal to make the site “open and accessible to all: to the residents of Fureidis, students at the nearby school, and anyone interested in the prehistory of the region,” once the formal excavations are completed.

Christopher Plain is a Science Fiction and Fantasy novelist and Head Science Writer at The Debrief. Follow and connect with him on X, learn about his books at plainfiction.com, or email him directly at christopher@thedebrief.org.

We're not as random as we think.

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"Tremendous determination."

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An analysis of dental tartar containing traces of human diets dating back over 33,000 years has revealed that ancient Europeans and many early Asian populations likely only ate insects by accident, perhaps as larvae in the carcasses of dead animals.

Conversely, the new study found that intentional insect consumption, called entomophagy, was more common in tropical regions and among Neanderthal populations.

Although the difference has some cultural and religious roots, the team found evidence that the abundance of insects in the tropics and the decreasing ability of humans migrating away from the tropics to digest insects likely led to the modern-day separation over thousands of years.

The Institute of Evolutionary Biology (IBE), a joint center of the Spanish National Research Council (CSIC) and Pompeu Fabra University (UPF), research team behind the new findings suggests their research could help explain why some modern populations still consume insects as food while other parts of the world consider it gross or taboo, especially given the increasing food demands of a rising world population.

Insect Consumption in Ancient Northern Europeans Likely Accidental

According to a statement announcing the new research, hundreds of millions of people currently include insects in their diet. However, they also note that most of the Western world continues to “show an aversion” to including any of the more than 1,611 insect species designated as edible by the Food and Agriculture Organization of the United Nations (FAO) in theirs. Although some theories suggest the difference is almost purely cultural, the team concedes that “its origin remains unknown.”

To explore the origins of human entomophagy, the IBE analyzed 745 samples of ancient human dental tartar dating back to 33,000 before present. According to the team’s results published in the journal Science Advances, dental tartar (sometimes called dental ‘calculus’) is a critical archaeological tool because it preserves the DNA of the species these human ancestors consumed during their lifetimes.

Although the analysis found evidence for entomophagy amongst virtually all ancient populations sampled in the study, the levels varied dramatically. Notably, the evidence suggested that ancient humans in northern Eurasia did not routinely eat insects in measurable quantities. Instead, any consumption was likely incidental, including consumption of insect larvae in rotting food.

Curious whether the lack of entomophagy in ancient European and Central and Northern Asian populations was purely cultural or whether genetic and geographic factors were involved, the team studied human genes involved in chitin digestion. Chitin, which can be found in some marine animal shells, is also part of an insect’s hard exoskeleton.

According to the study authors, the analysis revealed that the ‘chitinase’ genes in North Eurasian human populations “carry mutations that confer a reduced capacity to digest insect exoskeletons.” Their analysis revealed that this reduced capacity to digest insect exoskeletons has persisted in the genomes of modern Eurasian populations “for the last 9,000 years,” which would coincide with the widely accepted date for the origin of agriculture.

Pablo Librado, study leader and a principal investigator at the IBE, said the “scarce presence of insects in the diet of northern Eurasians” suggests that the cause may not lie solely in more recent cultural factors but also in ecological and evolutionary components dating back several millennia. 

Neanderthals and Denisovans Probably Ate Insect Larvae in Rotting Meat

When the team compared data from ancient human tartar with that of ancient Neanderthals, they found that Neanderthals engaged in much higher levels of entomophagy than humans living in the same regions. According to the study authors, Neanderthal insect consumption levels were similar to those found in western chimpanzee populations, which the researchers note “rely on entomophagy to supplement their diet on the savanna, especially during periods of drought.”

Further analysis of the extracted insect DNA showed that the group most commonly consumed by the Neanderthal specimens included flies and mosquitoes. Although the team only analyzed the DNA, they noted that a recent hypothesis suggests Neanderthals ate carcasses laden with mosquito larvae.

“The abundance of mosquito remains reinforces the possibility that the carcasses of their prey were kept in ponds and marshy areas, where mosquitoes lay their eggs,” the team’s statement explained.

An analysis of the Neanderthal DNA and the DNA from the lone Denisovan study subject revealed that both ancient hominid populations could digest chitin. This result reinforced the genetic basis for increased or reduced entomophagy beyond cultural factors. 

Humans Ate Fewer Bugs When They Moved Away from Tropical Regions

One geographic component identified by the chitinase DNA analysis showed higher levels of digestive enzyme expression among humans living in or near the tropics. However, the expression of these enzymes gradually decreased as populations moved away from tropical regions. The team said this variation, which has been maintained for at least the last 9,000 years, “reflects the abandonment of entomophagy in European populations.”

Manuel Piñero, a predoctoral researcher at the IBE and first author of the study, noted that large numbers of insects must be consumed to offset the “high caloric cost” of collecting them, which might explain the higher levels of entomophagy in this region.

“In the tropics, there is a greater availability of social insects, such as termites and locusts,”  Piñero  explained, adding that the biomass and diversity of tropical edible insects enable “sustainable exploitation throughout the year.” The researcher also noted that insect consumption “adds to pest control.”

When discussing the implications of their findings, Librado highlighted the DNA and geographic factors the IBE team uncovered.

“Beyond cultural or religious factors, our results suggest that the reduced availability of insects in non-tropical areas may have been a key factor in the abandonment of entomophagy, leading to a reduced capacity to digest insect exoskeletons,” the researcher explained.

Christopher Plain is a Science Fiction and Fantasy novelist and Head Science Writer at The Debrief. Follow and connect with him on X, learn about his books at plainfiction.com, or email him directly at christopher@thedebrief.org.

A century after they were discovered, they're finally getting some appreciation.

Quietly teeming.

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Many blind people navigate the world using a cane, guide dog or wearable GPS. But some have something more in their toolkit: echolocation. That’s the ability to sense nearby objects using sound. A new study shows just how master echolocators use this technique to get around.

These people make a sharp clicking sound with their tongue. (Watch the process in action.) Then they listen for its echo to sense where objects are around them. New brain-activity data show that with each click, expert echolocators improve these mental maps of their environment.  

Researchers shared these findings April 6 in eNeuro.

Clicking and listening for echoes can provide information about the location of nearby objects. Or their size. Maybe even their texture. (Bats use this same process to find their way as they flap through the night sky.)

Many studies have shown that in people, echolocation turns on parts of the brain that have to do with sight. They’ve also shown that echolocation improves a lot with practice.

But scientists still don’t know “how this happens,” says Santani Teng. “How the information builds in real time” beyond what can be learned from each individual echo. He and co-author Haydée García-Lázaro work at the Smith-Kettlewell Eye Research Institute. It’s in San Francisco, Calif. As cognitive neuroscientists, the two study how our brains think, learn and process information.

Mental mapping

To better understand human echolocation, they recorded clicks and echoes. They designed these echoes to act as if they were bouncing off a nearby object. Then, the scientists compared how two groups of volunteers responded to these recordings.

The four blind people in one group were all experts in echolocation. The other group of 21 people could see well. They also had no experience with echolocation.

Each volunteer listened to the recorded clicks followed by their echoes. The sounds were played in sets of two, five, eight or 11. After each set, these people were asked to decide whether an object had been to their right or left. As they listened, electrode caps on their heads recorded their brain activity.

The blind echolocators excelled at figuring out an object’s direction. They scored far better than those who could see. In fact, one echolocator figured out an object’s direction after hearing only two sets of clicks and echoes.

The brain data showed that each click-echo pair gives new details about the surroundings. Echolocators combine these additional details over time, “rather than through a single optimal snapshot,” says Monica Gori. She’s a neuroscientist who did not take part in this study. She works at the Italian Institute of Technology in Genoa. She also works with the Institute for Human & Machine Cognition in Pensacola, Fla.  

García-Lázaro says she and Teng want to learn more about “what exactly makes better echolocators.” She’s especially curious about how experts learn to ignore the click and focus only on its echo.

This “is not magic,” says Teng. “Echolocators have a truly remarkable skill, with real-life benefits.”

Computer-generated images have been around for decades. People use computers to make digital art and animations for movies, TV shows and video games. However, just like making a physical painting with a paintbrush, these images take a lot of time and human effort to produce.

The rise of artificial intelligence has drastically reduced the amount of time and effort it takes to create computer-generated images. New programs and websites can generate images using a text prompt from the user, such as “a picture of a tiger walking through a grassy field.” These programs can automatically generate artwork and photo-realistic images that can be difficult to tell apart from “real” photos and artwork. Can you tell which picture at the top of this story is real and which is AI-generated?

While AI-generated images might seem fun or harmless, they can also cause problems. People can use them to create deepfakes, or fake images of things that did not really happen. Some people might see the picture and believe that it is real. While fake news and fake images have been around for a long time, AI tools can make it easier and faster to produce this misleading content.

Can people tell the difference between real pictures and AI-generated pictures? How hard is it to spot “fake” pictures? In this science project you will find out!

Terms and concepts

• Computer-generated image
• Artificial intelligence
• Deepfake

Questions

• What are some uses for AI-generated images?
• What are some potential problems caused by AI-generated images?

Resources

• Axios (2023, July 31). How to spot deepfakes created by AI image generators. Retrieved September 14, 2023.
• Bond, S. (2023, June 13). AI-generated images are everywhere. Here’s how to spot them. NPR. Retrieved September 14, 2023.

Materials and equipment

• Internet access
• Digital camera or smartphone
• Optional: printer
• Volunteers
• Lab notebook

Experimental procedure

1. Decide on a topic or theme for your pictures. For example, you could use pictures of animals, flowers, scenery, vehicles or people.
2. Take at least 10 real pictures of the object/topic you decided on or find pictures online.
   1. Make sure you label or organize the images so you do not lose track of them later. (As an example, you could put all the real pictures in a folder on your computer.)
   2. If you are finding the pictures online, make sure they are from a legitimate source and you know they are real pictures. (See references in the Bibliography for tips.)
3. Find or make at least 10 AI-generated images of the same object/topic.
   1. You can search online for an “AI image generator” and you will find many options available. Some services might be built into major search engines. Others might have their own websites. Also note that some services might be free, or allow you to generate a limited number of images for free. But others might require a paid subscription.
   2. Follow the instructions for the website or program you decide to use to enter a prompt and generate an image. Since you will be comparing them to real images, make sure you generate “realistic” photos and not images that look like paintings or drawings.
   3. Save the images. Again, make sure you keep track of which images are real and which are AI-generated.
4. Prepare all the images for viewing by your volunteers. For example, you can label them 1 through 20 and put them in a random order in a different folder on your computer. Or you could print them. Make sure you keep track of which images are real and which are AI-generated. But this information should not be visible to your volunteers.
5. Prepare a data table like Table 1. In the second column, write whether each image is real or AI-generated.

Image number	Real or AI generated	Volunteer  1	Volunteer 2	Volunteer 3	Volunteer “real” responses	Volunteer “AI” responses	% of volunteers correct

6. One at a time, show each picture to a volunteer. Ask them whether they think the picture is real or AI-generated. Record their response in your data table.
7. Repeat the process for each volunteer.
8. For each image, add up the number of volunteers who said the image was real. Enter this value in your data table.
9. For each image, add up the number of volunteers who said the image was AI-generated. Enter this response in your data table.
10. Calculate the percentage of volunteers who correctly identified whether each individual image was real or AI-generated. Enter the percentage in your data table.
11. Create another data table like Table 2.

		Volunteer responses
		Real	AI-generated
Actual image	Real
	AI-generated

12. Analyze your data.
    • Overall, how good were your volunteers at correctly identifying real images as real?
    • Overall, how good were your volunteers at correctly identifying AI-generated images as AI-generated?
    • Are there large differences in your results between individual pictures? Were some pictures harder for your volunteers to correctly identify than others? Looking at the pictures, why do you think this occurred?

Variations

• Repeat the experiment with artwork instead of pictures. Can your volunteers tell the difference between real artwork and AI-generated art?
• Do the experiment with two groups of volunteers: a control group and a group that you have trained to spot AI-generated images. (See some of the references in the Bibliography.) Can people with training do a better job correctly identifying the images?
• Try the experiment with different categories of images/objects. Are some things easier for people to recognize than others? For example, what about pictures of inanimate objects vs. pictures of living things? What about pictures of “regular” people vs. famous people like politicians or actors?
• Compare different AI image generation websites or services. Are some better than others at producing convincing images?
• Do an experiment to find out if people can recognize AI-generated text instead of images.
• Can you produce fake news articles that include both images and text about real people or events? Run the experiment with both real and fake news articles. Can people tell which is which?

This activity is brought to you in partnership with Science Buddies. Find the original activity on the Science Buddies website.