Study details epic transportation of Stonehenge stone across ancient Britain

Peer-Reviewed Publication

Curtin University

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Dr Anthony Clarke at Stonehenge

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New research by Curtin University has revealed how one of Stonehenge’s most mysterious stones was likely transported hundreds of kilometres across Britain through challenging terrain, highlighting the remarkable capabilities of ancient communities.

 

Stonehenge’s central Altar Stone is a six-tonne sandstone megalith now believed to have originated in northeast Scotland, around 700km from Salisbury Plain, underscoring the extraordinary scale of its journey.

 

The new study builds on earlier findings that ruled out glaciers as the sole mechanism for moving the stones, strengthening the conclusion people were responsible for transporting them across difficult terrain rather than relying on natural Ice Age processes.

 

Researchers have now focused on what that journey may have looked like, combining mineral grain dating with ice-sheet modelling to pinpoint the stone’s origin and test whether glaciers could have carried it south.

 

Co-lead author Dr Anthony Clarke, from the Timescales of Minerals Systems Group within Curtin’s School of Earth and Planetary Sciences, said the findings suggest the journey was far from simple and likely required careful planning across multiple stages.

 

“Rather than being carried naturally by ice, the evidence points to a deliberate, carefully planned movement across a challenging and varied landscape,” Dr Clarke said.

 

“Our modelling shows glaciers may have transported rocks part of the way during the last Ice Age — potentially as far as Dogger Bank in the North Sea — but not into southern England, meaning the stone would still have needed to be moved hundreds of kilometres by people.

 

“The research indicates there were no viable glacial pathways linking the source region directly to Stonehenge, reinforcing the conclusion that human transport was required.

 

“Instead, this suggests the stone was likely moved in stages, potentially combining overland hauling with river or coastal transport where possible.”

 

Dr Clarke said the findings reveal a level of organisation and cooperation among Neolithic communities not previously fully appreciated.

 

“Transporting a stone of this size over such a long distance would have required planning, coordination and a deep understanding of the landscape – not to mention tremendous determination,” Dr Clarke said.

 

“The study demonstrates how combining geological analysis with computer modelling can help resolve long-standing questions about how Stonehenge was built.”

 

Future research will aim to pinpoint the Altar Stone’s exact source in northeast Scotland and further investigate possible transport routes used by prehistoric communities.

 

The research was conducted in collaboration with experts from Sheffield Hallam University, the University of Sheffield, Wessex Archaeology, and the University of Bristol in the United Kingdom.

 

The study, ‘From Highlands to Henge: Refining the Provenance and Transport Pathways of Stonehenge’s Altar Stone’ (DOI:10.1002/jqs.70080), was published in the Journal of Quaternary Science.

Dr Anthony Clarke and Professor and research co-author Chris Kirkland at Stonehenge [VIDEO] | 1

Dr Anthony Clarke and Professor and research co-author Chris Kirkland at Stonehenge [VIDEO] | 2

Dr Anthony Clarke at work in the lab [VIDEO] 

 

Dr Anthony Clarke at Stonehenge

Credit

Curtin University

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Journal

Journal of Quaternary Science

DOI

10.1002/jqs.70080 

Method of Research

Computational simulation/modeling

Subject of Research

Not applicable

Article Title

From Highlands to Henge: Refining the Provenance and Transport Pathways of Stonehenge’s Altar Stone

Article Publication Date

4-Jun-2026

 

Study shows offshore wind could potentially cover 11% of North Sea by 2050

Heriot-Watt University

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Map showing a plausible arrangement of offshore wind farms in the North Sea in 2050.

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Credit: Heriot-Watt University

New research has mapped a plausible scenario for how offshore wind could reshape the North Sea by 2050, showing that if all current political commitments were built, around 11% of the basin would fall within wind farm boundaries. 

Led by Heriot‑Watt University, the study provides one of the most comprehensive assessments to date of European offshore wind ambitions, showing that current political commitments imply a total of around 19,400 offshore wind turbines across the North Sea by 2050, including those already built. 

The analysis examined both operational offshore wind farms and projects already in national development pipelines across all seven countries with North Sea waters: the Netherlands, Belgium, Denmark, Germany, the UK, Norway and France. 

Where necessary, hypothetical wind farms were added to bring each country’s total capacity in line with its stated commitments. The researchers stress that this is a scenario, not a forecast, and does not predict where wind farms will actually be located in 2050.  

Dr Simon Waldman, Assistant Professor of Energy Technologies at Heriot-Watt University’s School of Energy, Geoscience, Infrastructure and Society said: “Our scenario shows the scale that we would be looking at if every country were to build the amount of offshore wind capacity that they have promised.” 

“It’s important to be clear that this isn’t a prediction of what the North Sea will look like in 2050, it’s simply a projection based on the data and national ambitions we have today. 

“We originally began this work because we wanted to understand the environmental effects of a very large rollout of offshore wind. To do that properly, we needed a plausible set of turbine locations and that simply didn’t exist at the time. 

“Since the project began, national ambitions have grown in response to global events, so we updated the dataset to reflect the higher targets governments now have.” 

By 2030, the UK is projected to remain the largest offshore wind nation in the North Sea, with roughly 4,200 turbines in operation. Germany follows with around 2,700 turbines, and the Netherlands with approximately 1,700. 

By 2050, these three countries continue to dominate in scale, with the UK expected to host around 6,300 turbines, Germany in the region of 4,300, and the Netherlands just over 4,200. 

In spatial terms, the Netherlands is projected to be the most intensively used national zone, with offshore wind farms occupying around 19% of its North Sea waters by 2050. 

Belgium follows at around 18%, ahead of Denmark (about 15%) and Germany (around 14%). The UK (around 9%), Norway (around 8%) and France (around 7%) show lower proportions of their national waters within wind farm boundaries. 

Taken together, projected and operational offshore wind developments would cover approximately 58,500 square kilometres of the North Sea, rising from around 1% of the basin today to about 11% by 2050. 

Dr Waldman added: “To build this scenario, we brought together a wide range of international marine and energy datasets, from national targets and spatial plans to seabed depths, wind and wave records, existing infrastructure and projected turbine technologies, to create a realistic picture of what current ambitions might mean in practice.  

“When placing our projected future wind farms, we tried to avoid shipping lanes, environmentally protected areas, existing seabed cables and pipelines, and more. 

“What this shows is the scale of activity we will be dealing with if offshore wind grows as promised, and the practical considerations that come with that.” 

The research was carried out with colleagues at the University of Hull and the University of St Andrews. It began as a master’s dissertation by former student Peter Munro, who created the first version of the wind farm and turbine layouts while studying at Hull. 

A 2024 update was completed by Conor Gilmour, who worked as a research assistant at the University of St Andrews before moving into industry. Further expertise came from Professor Rodney M Forster at Hull and Dr Debbie J F Russell at the University of St Andrews. The work was, in part funded by the NERC INSITE as part of the EcoSTAR project. 

Debbie Russell (EcoSTAR project lead) said: “There is an urgent need to predict the potential impact of development at this scale; this layer represents a feasible layout that can be used for such scenario testing. 

“We certainly believe it is one of the most detailed resources available for looking at how offshore wind could develop across the North Sea.  

“Not only does our research show this plausible scenario, but it also highlights some new and existing challenges that we may face.  

“Below the surface, turbines sit within busy and sensitive marine environments, which affects how other sea users, especially fishers, can operate, because many fishing methods depend on the seabed as well as the surface. 

“Above the surface, large wind farms create long atmospheric wakes. A single turbine slows the air behind it, but very big farms can cast wakes stretching 40 kilometres or more, meaning one project can influence another even across national borders. 

“We’re already seeing early signs of developers reporting energy losses due to neighbouring wakes, and there are ecological considerations too as we look at how these structures alter marine systems. As the sector expands, understanding these interactions clearly becomes essential.” 

Professor Rodney Forster from the Hull Marine Laboratory at the University of Hull said: “The North Sea supports fragile marine ecosystems and coastal communities dependent on logistics, fishing and energy industries.

“It’s clear that coming decades will see a significant increase in offshore wind developments. As these expand we need to understand possible impacts on those diverse ecosystems and the implications for wider marine industries.

“The next steps are to identify other uses of the sea that can be placed alongside or within operational windfarms. In separate research we have identified that the best conditions for growing mussels in aquaculture farms happens to coincide with the best sites for offshore wind.

“Our work with the University of St Andrews and Heriot-Watt University will help us to manage our interactions with the sea to better support those ecosystems and the communities that depend on them.”

 

 

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Journal

Energies

Article Title

Offshore Wind and the Spatial Squeeze: A Plausible Future Layout for the North Sea

Football: How to become technically good

The short answer: practice, practice, practice.

Norwegian University of Science and Technology

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Without good technical skills, neither you nor your team will perform their best in football. But how do you actually become technically good?

Unfortunately, a new study shows that natural talent is not enough. It takes training – and targeted training.

"We investigated the relationship between eight different skills in football. We wanted to see if they were connected in some way, or if you have to develop them separately," says Professor Hermundur Sigmundsson at the Department of Psychology at the Norwegian University of Science and Technology (NTNU).

Icelandic elite team

Twenty-three semi-professional players from Iceland participated in the survey. All the players belonged to the same Icelandic elite club. It provides a comparable basis in terms of training and experience in football matches.

The players had to go through eight technical exercises from the "Test of Technical Skills in Football" (TTSF). These measure skills in:

• Juggling (keeping the ball in the air for one minute)
• Passing accurately at a distance of 25 meters
• Heading
• Kicking
• Dribbling
• Corner precision from 16.5 metres (shooting the ball from the end line into the goal from this distance)
• Shooting precision from 16.5 metres
• Wall-volley (pass the ball against a wall)

You have to practice everything in football

"The correlations between the different skills are low. We find minimal overlap," says Sigmundsson.

This means that you have to practice the different skills separately. If you train yourself to become good at one of the skills, you will not automatically get better at another of them.

"This supports the hypothesis that you need to train motor skills separately. Practicing technical soccer skills requires targeted training. If you get better in one area, it doesn't spill over to another," says Sigmundsson.

Important for the coaches

This information is important for both trainers and researchers.

"The training must be well thought out and differentiated if you are to get the best possible results. You have to adapt the training to the skills you want the players to get better at," he says.

Sigmundsson worked together with colleagues from NTNU and from Queensland University of Technology.

Reference:
Hermundur Sigmundsson, Rúnar Páll Sigmundsson, Monika Haga, Remco Polman, The association between eight different skills in football: an explorative study, Football Studies, Volume 1, 2026, 100033, ISSN 3051-2689, https://doi.org/10.1016/j.footst.2026.100033

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DOI

10.1016/j.footst.2026.100033 

Method of Research

Data/statistical analysis

Subject of Research

People

Article Title

The association between eight different skills in football: an explorative study

 

Georgetown researchers show how brain rewires itself to enable true multitasking

Georgetown University Medical Center

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WASHINGTON – New research by Georgetown scientists shows how the brain rewires itself to automate learned tasks. The findings challenge a long-held understanding of how humans master complex skills, suggesting that true multitasking is really possible.

Beyond offering encouragement to busy people that they really can do two things at once, the study also has important implications for the development of artificial intelligence capable of building on prior learning as the brain does.

“We have another stepping stone in our understanding of how the brain learns,” said senior author Maximilian Riesenhuber, PhD, a professor of neuroscience at Georgetown University School of Medicine, and co-director of the Center for Neuroengineering. “The encouraging part is that you really can learn to multitask. There is actually a way to remodel your brain architecture and use other parts of your brain.”

The new study builds on decades of research on how learning occurs in the brain.

Scientists wanted to understand the mechanisms behind automation, and how the brain shifts from learning a new task into a way of executing that task  more unconsciously after extensive experience.

A good example is driving, Riesenhuber said. When someone first learns to drive, it requires their full concentration. But after driving for many years, most people can talk, listen to music, or consider a problem without having to focus completely on operating the vehicle.

“The question is: how does your brain do that?” Riesenhuber said.

Most previous research on learning has focused on the early stages, but what happens to the brain long-term is harder to study and less understood.

For the new study, researchers trained people to sort morphed images of cars into two categories, learning to spot subtle differences to tell them apart. Participants completed more than 30,000 trials over 5 to 10 weeks, using an app that allowed them to sort the images as a game on their phone. Researchers used fMRI and EEG to conduct brain scans on the participants before and after they completed the trials.

They found that after people had initially learned to sort the images, the task activated their prefrontal cortex. This area of the brain is responsible for executive function and thinking, but can typically only handle one task at a time.

However, when researchers scanned the brains of participants who had been practicing the sorting task for weeks, they found that the categorization was now happening in the temporal cortex, a part of the brain involved in encoding memory and recognizing complex objects.

"Previous studies have shown that parts of the temporal cortex can be activated by particular object categories in experienced observers, birds, cars, even Pokemon, but a limitation of all of those studies is that they only looked after people became experts. The strength of this study is that it is longitudinal, we measure before and after training, so we can see that extensive training essentially put a category selective area in the temporal lobe that was not there before,"  said first author Patrick Cox, PhD, who began the study as  a graduate student in Riesenhuber’s lab and is now an assistant professor of psychology at Lehigh University.

“This has implications for critical real world scenarios, like when a radiologist can accurately classify masses on an x-ray as benign or malignant fairly automatically, often without extensive deliberation, thanks to years of training," Cox said.

Category information from the car-selective area in the temporal cortex bypassed the prefrontal cortex and connected directly to output parts of the brain. “Experience remodels the brain to bypass that frontal bottleneck. The prefrontal cortex then stays free for whatever else you want to do, increasing your capacity,” Riesenhuber explained. Indeed, the researchers found that the more the car task was “offloaded” from the prefrontal cortex, the better people were able to do another task in parallel to the car task.

The finding challenges a longstanding theory that humans are not capable of true multitasking. Instead, it was thought that the brain rapidly switched back and forth between two tasks.

“What we show is that the circuitry actually changes so the brain can do two things at once,” Riesenhuber said. “This really is true multitasking.”

The findings can also have implications for understanding compulsive behaviors, because they demonstrate that learned behaviors move into brain circuits that are less accessible to  conscious thought or executive function.

“The first step to unlearning something is understanding where it is actually happening in the brain,” Riesenhuber said. “This shows why strategies like telling someone to think of something else don’t really help, because they don’t really have the behavior under conscious control.”

It also helps explain why humans are so good at continuous learning, or building skills upon skills — something that AI still struggles with.

Moving a learned skill into the temporal cortex and freeing space in the prefrontal cortex could allow the brain to use the old information as a building block to learn something new, Riesenhuber said. Current AI models don’t have that same capability, he noted.

Next, researchers want to study the mechanisms or signals involved in moving learning from one part of the brain to another and to figure out what the limits of multitasking are.

“Another really interesting question is what kinds of tasks can be learned well enough to do in parallel,” Cox said. “We can walk and chew gum at the same time, but looking at our phones to text while driving will never be safe, because we take our eyes away from the road. It comes down to being able to train fully separate neural circuits for two tasks to become compatible.”

The paper, “Extensive Experience Remodels Neural Task Circuitry to Escape the Frontal Bottleneck and Increase Automaticity of Categorization,” was published June 4 in the Journal of Cognitive Neuroscience.

 

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In addition to Riesenhuber and Cox additional authors include Clara A. Scholl, Marissa L. Laws, Nelson E. Jaimes and Xiong Jiang, all from Georgetown University. Funding for this study was provided by the National Science Foundation (BCS-1232530) and the ARCS Foundation, and the Army Research Laboratory (W911NF-24-1-0097). The authors report having no personal financial interests related to the study.

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Journal

Journal of Cognitive Neuroscience

Method of Research

Observational study

Subject of Research

People

Article Title

Extensive Experience Remodels Neural Task Circuitry to Escape the Frontal Bottleneck and Increase Automaticity of Categorization

Article Publication Date

4-Jun-2026

 

Classroom performance of students with autism in interaction with the NAO robot

Higher Education Press

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An interface screenshot of Choregraphe.

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Credit: HIGHER EDUCATON PRESS

This paper investigates NAO robot’s role in supporting autistic students in real classroom settings. Most prior research focuses on one-on-one intervention, lacking group-based evidence. The study uses a within-subject design with six autism spectrum disorder (ASD) students, comparing robot-assisted and regular classrooms across attention, communication, interaction, and emotion. Statistical analyses reveal significant enhancements in attention duration, communication frequency, interaction scores, and positive emotions, with reduced negative behaviors. NAO’s compact design and predictable interaction reduce intimidation and boost sustained engagement. Findings validate the feasibility of robot-integrated teaching for ASD, providing a basis for long-term curriculum design. Limitations include small sample size; future research will adopt larger samples and longitudinal tracking.

The work entitled “Classroom Performance of Students with Autism in Interaction with the NAO Robot” was published on Frontiers of Digital Education (published on April 25, 2026).

 

NAO robot’s appearance. (a) NAO robot; (b) NAO component.

Credit

HIGHER EDUCATON PRESS

Journal

Frontiers of Digital Education

DOI

10.1007/s44366-026-0083-1 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Classroom Performance of Students with Autism in Interaction with the NAO Robot