Monday, January 12, 2026


How brain waves shape our sense of self



Karolinska Institutet




A new study from Karolinska Institutet, published in Nature Communications, reveals how rhythmic brain waves known as alpha oscillations help us distinguish between our own body and the external world. The findings offer new insights into how the brain integrates sensory signals to create a coherent sense of bodily self.

What makes you feel that your hand is yours? It might seem obvious, but the brain’s ability to tell self from non-self is a complex process.

Using a combination of behavioural experiments, brain recordings (EEG), brain stimulation, and computational modelling with a total of 106 participants, researchers from Karolinska Institutet investigated how the brain combines visual and tactile signals to create the feeling that a body part belongs to oneself – a phenomenon known as the sense of body ownership. Their experiments showed that the frequency of alpha waves in the parietal cortex, the brain region that processes sensory information from the body, determines how precisely we perceive our body as our own.

“We have identified a fundamental brain process that shapes our continuous experience of being embodied,” explains lead author Mariano D’Angelo, researcher at the Department of Neuroscience, Karolinska Institutet. “The findings may provide new insights into psychiatric conditions such as schizophrenia, where the sense of self is disturbed.”

The rubber hand illusion

Participants took part in the rubber hand illusion, a classic method for studying the sense of body ownership. When touches on a visible rubber hand and the participant’s hidden real hand were synchronised, many reported feeling that the rubber hand was part of their body. But when the timing was off, that feeling faded.

The study found that individuals with faster alpha frequencies were more sensitive to timing differences between the seen and felt touches. They noted smaller timing differences, as if their brains operated at higher temporal resolution, resulting in a more precise sense of body ownership.

In contrast, slower alpha frequencies were linked to a broader ‘temporal binding window,’ causing the brain to treat more asynchronous visual and tactile signals as if they occurred together. This reduced temporal precision made it harder to separate self-related sensations from external ones, weakening the distinction between body and world.

Better prostheses and VR experiences

To test whether alpha frequency directly causes these perceptual effects, the researchers used non-invasive electrical brain stimulation to slightly speed up or slow down participants’ alpha waves. The results showed that adjusting the alpha frequency in this way also changed how precisely people experienced body ownership and how precisely they perceived visual and tactile stimuli as simultaneous. Computational models showed that alpha frequency influences how precisely the brain judges the timing of sensory signals, meaning that these brain waves regulate the temporal precision of perception and thereby help shape our sense of bodily self.

“Our findings help explain how the brain solves the challenge of integrating signals from the body to create a coherent sense of self,” says Henrik Ehrsson, professor at the Department of Neuroscience, Karolinska Institutet, and last author of the study. “This can contribute to the development of better prosthetic limbs and more realistic virtual reality experiences.”

The study was a collaboration between Karolinska Institutet in Sweden and Aix-Marseille Université in France. It was funded by the European Research Council (ERC), the Swedish Research Council, VINNOVA, StratNeuro and A*Midex. The researchers declare that there are no conflicts of interest.

Publication: “Parietal alpha frequency shapes own-body perception by modulating the temporal integration of bodily signals”, Mariano D’Angelo, Renzo C. Lanfranco, Marie Chancel, H. Henrik Ehrsson, Nature Communications, online 12 January 2026, doi: 10.1038/s41467-025-67657-w.

 

Parkrun participation surging thanks to parkwalkers, new Stirling research shows



Every week 400,000 people take part in parkruns across the world, with the launch of parkwalkers - to support those walking the 5k routes - shown to have increased the proportion of new female participants and reversed a decline in the average age of new



University of Stirling

University of Stirling parkrun 

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The University of Stirling parkrun is one of the most scenic in the UK.

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Credit: University of Stirling





New research from the University of Stirling has revealed that introducing parkwalkers to parkrun events has led to a surge in those walking the routes.

Every week 400,000 people take part in parkruns across the world, with the launch of parkwalkers - to support those walking the 5k routes - shown to have increased the proportion of new female participants and reversed a decline in the average age of new attendees.

The parkwalker role was introduced in October 2022 with volunteers donning a distinctive vest and asked to offer encouragement and conversation to make walkers feel more welcome at events.

Now a new study by Dr Andre Gilburn, a Senior Lecturer at the University of Stirling’s Faculty of Natural Sciences, has shown that their introduction has been successful in encouraging more people from underrepresented groups to take part, by removing the fear of being too slow that is known to deter people from taking part in physical activity.

The research, which analysed more than 31,000 participants from 68 parkrun venues across Scotland, shows that the number of walkers increased by 54.6 percent at events that partially engaged with parkwalkers and 55.3 percent at those fully engaged with the initiative - compared with 22 percent at those that didn’t.

The study also showed that finishing times became significantly slower at events after a parkwalker was introduced - pointing to an increased number of participants with a reduced pace, most notably women and older attendees.

Dr Gilburn explained: “These findings show that an active leisure event organiser can easily make changes to the social environment at their events that result in increased engagement.

“Introducing parkwalkers has been effective at encouraging older participants and women, therefore it is increasing inclusivity by encouraging those in under-represented groups to engage in parkrun.

“We know that the fear of being too slow is a barrier to engagement with physical activity, and this shows how that barrier can be successfully overcome.”

Dr Gilburn now hopes that practitioners who engage in social prescriptions of parkrun will now prioritise sending patients to events that feature a parkwalker.

He added: “Widely the findings of this study suggest that physical activity in a group context with encouragement from within the group is more effective than lone activity, therefore future initiatives aimed at encouraging walking might be more effective if they promote group walking.”

Dr Hussain Al-Zubaidi, GP and Health Partnerships Lead, parkrun UK said: “This research powerfully shows that small, thoughtful changes to the social environment can remove real barriers to physical activity. The parkwalker role has helped make parkrun feel more welcoming, particularly for people who may have previously felt it wasn’t ‘for them’."

The University of Stirling’s campus hosts a weekly parkrun around Airthrey Loch and Dr Gilburn is a regular participant.

Colin Sinclair, event director at the University of Stirling parkrun, said: "parkrun is all about participation and we're delighted that this research has shown the positive impact that the parkwalker initiative has had on numbers - especially in under-represented groups.

"At the University of Stirling parkrun we're always warmly welcoming new participants, whether they want to push for personal bests running the route or simply want to enjoy a social walk around one of the most scenic parkrun locations in the country. These findings proudly showcase parkrun's commitment to inclusivity and physical activity that is welcoming and open to all."

The study, Testing the effectiveness of a health intervention that manipulates the social environment at active leisure events in Scotland, was published in the Journal of Public Health Research.


parkwalkers have resulted in a spike in those taking part in events

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parkrun

Chonnam National University researchers develop novel virtual sensor grid method for low-cost, yet robust, infrastructure monitoring


Researchers utilize superpixels, instead of pixel-level information, to enhance the robustness and accuracy of vision-based structural health monitoring



Chonnam National University, The Research Information Management Team, Office of Research Promotion

Proposed superpixel-based virtual sensor framework. 

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The proposed approach superpixels, instead of pixel-level information, are used as virtual sensors for vibration measurements, enhancing robustness and accuracy.

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Credit: Gyuhae Park from Chonnam National University, Korea





Structural health monitoring (SHM) and condition monitoring are crucial processes that ensure reliability and safety of engineering systems in a variety of fields, including aerospace, civil engineering, and industry. These systems are often assessed using vibration-based methods, where damage is detected by analyzing changes in a structure’s vibration characteristics. Traditional methods typically employ contact-type sensors for this purpose. While effective, these methods face several limitations, including low spatial resolution, high costs, difficulties in sensor placement, and measurements that are restricted to small regions around each sensor.

Vision-based methods, where non-contact, full-field vibration measurement is conducted directly from video sequences, have emerged as promising alternatives. In addition to being simple and low cost, these methods offer high spatial resolutions and are suitable for structures with complex geometries or limited accessibility. Full-field motion estimation also enables assessment of the entire structure. However, many existing vision-based approaches struggle with large structural motions, low-texture surfaces, or changes in lighting. Although recently developed phase-based optical flow methods improve robustness by estimating motion from phase information, they still rely on pixel-level data, which, in addition to being computationally intensive and difficult to interpret, is inherently vulnerable to noise, lighting fluctuations, and distortion.

To address these challenges, a research team led by Professor Gyuhae Park from the Department of Mechanical Engineering at Chonnam National University in South Korea, has developed a novel superpixel-based virtual sensor framework. “Our approach utilizes superpixels, clusters of neighboring pixels with similar vibrational and structural behavior, as virtual sensors for motion estimation,” explains Prof. Park. “This creates a virtual sensor grid that can adapt to any structure and offers robust and accurate full-field vibration measurement without the need for physical markers or contact sensors. ” The study was made available online on September 30, 2025, and published in Volume 240 of Mechanical Systems and Signal Processing on November 01, 2025.

The proposed approach operates in three stages. In the first stage, pixel-level motion is estimated from video sequences using the phase nonlinearity-weighted optical flow (PNOF) algorithm, developed by the authors in a previous study. For each pixel, the algorithm extracts local motion from phase information and evaluates the reliability of the estimated displacements in different directions. Unreliable displacement components with high phase nonlinearity are then discarded, and the remaining reliable components are integrated to produce a marker-free full-field displacement map.

In the second stage, the overall confidence of the full displacement at each pixel is calculated, providing a built-in reliability assessment, a first among vision-based vibration measurement methods.

In the third stage, this overall confidence and the full field displacement map are used together to group pixels into superpixels, creating a virtual sensor grid. Depth information is also incorporated to improve alignment between the sensor grid and structure. Finally, full-field displacement is calculated at the sensor level for damage detection.

Experimental validation performed on an air compressor system showed that the proposed method achieves accuracy comparable to that of a laser Doppler vibrometer (LDV) while enabling effective structural damage detection without physical markers or contact sensors. While individual pixels showed some variability, the superpixel-based virtual sensors effectively mitigated these effects.

“Vibration-guided superpixel segmentation enhances both robustness and interpretability of structural diagnostics even in complex environments,” explains Prof. Park. “Our approach makes full-field structural monitoring accessible, low-cost, and deployable using ordinary cameras supporting applications in infrastructure monitoring, aerospace and mechanical equipment diagnostics, smart cities, robotics, and digital twins.”

Overall, this innovative method represents a major advancement for vision-based SHM and may help pave the way for its broader adoption.

 

About the institute

Chonnam National University (CNU), established in 1952 as Korea’s first national university, is a leading institution of higher learning located in Gwangju and South Jeolla Province. Building on its founding commitment to cultivating leaders of integrity and professional excellence, CNU contributes to national development and global progress through the pursuit of knowledge, ethical responsibility, and inclusive excellence. Guided by the core motto “Truth, Creativity, and Service,” the university advances research, education, and public engagement that strengthen resilient societies, foster sustainable development, and promote the well-being of future generations. As a trusted partner in the global community, CNU remains dedicated to addressing complex challenges in an increasingly interconnected world.

Website: https://global.jnu.ac.kr/jnumain_en.aspx

About the author

Prof. Gyuhae Park is a Professor of Mechanical Engineering at Chonnam National University, contributing to advanced sensing and structural diagnostics research. His research group focuses on smart systems, noise and vibration, AI-driven structural health monitoring, and non-contact, vision-based sensing technologies. He has published more than 500 technical works, including over 130 journal articles, more than 400 conference papers, and 10+ book chapters (Google Scholar citations: 20,550; h-index: 59 as of Nov. 2025). He has served as an Associate Editor for nine top-tier SCI(E) journals and has actively contributed to international conferences as an organizing and scientific committee member. His work has been widely recognized, including being listed in the Stanford–Elsevier Top 2% Scientists list (lifetime and single-year categories) since its inception and his election as a Fellow of the American Society of Mechanical Engineers (ASME) in 2017. He received his Ph.D. in Mechanical Engineering from Virginia Tech in 2000 and his B.S. from Chonnam National University in 1992.