Stand in front of Turner’s Sun Rising Over Water (1825-30) and something odd tends to happen. The painting holds you, even though observers might struggle to say why. Maybe it is the colour, the balance, the composition, or the strange stillness the artwork seems to carry.

Whatever it is, you feel it long before you can explain why. And the stranger next to you, looking at the same canvas with the same awe in their eyes, very likely feels it too.

We often say that beauty is in the eye of the beholder. Yet show almost anyone a misty Chinese Song-dynasty mountain landscape, or the softly brushed figure of the Mona Lisa, and nearly everyone agrees that something striking is unfolding before them.

Beauty feels intensely private, and, at the same time, we keep discovering that we collectively share it. That contradiction is one of the longstanding puzzles in “neuroaesthetics” – the science of how the brain responds to art and beauty. How does our sense of beauty actually take shape in the brain?

In our latest study, published in Nature Communications, we tried to map that shared experience. We found that instead of representing it as a single entity, the brain instead splits aesthetic experience into two major strands. One strand handles what an image shows, whether a landscape, an object or a figure.

The other tracks how much pleasure it gives us, drawing on the same circuits that respond to food or money. These two separate neural systems combine to shape every judgment of beauty we make when viewing visual artworks.

Neuroscientists have long argued about this question, from positions that compete as often as they overlap. One camp focuses largely on perception, on how the brain takes in composition, contrast and form.

Another emphasises evaluation and reward, placing beauty in the brain’s value circuitry. A third looks to the brain systems behind imagination and self-reflection. Each account captures something real, but they had rarely been tested together in a single study.

Algorithms for art

We asked 34 volunteers to look at 96 traditional Chinese watercolour paintings inside a 7T MRI scanner, powerful enough to pick up the small shifts in blood flow that track the brain’s activity. Once they were out of the scanner, each participant rated how the paintings made them feel.

Instead of working straight from those raw ratings, however, we borrowed a tool from somewhere less obvious: the recommendation engines that power services such as Netflix and Spotify.

Known as collaborative filtering algorithms, these tools excel at detecting patterns of agreement buried in people’s preferences. When applied to our aesthetic ratings, they pulled out two dimensions running underneath everyone’s responses.

The first sorted the paintings from most figure-like to most landscape-like, a measure of what each picture conceptually depicts. The second sorted them from most disliked to most liked across all participants, a measure of emotional value, or hedonic value (the sensory enjoyment someone gets from an experience).

Despite their complementary contribution to the overall aesthetic experience, the brain kept these two dimensions remarkably separate. Visual content was read out along the visual pathways, the familiar circuits that let us tell a face from a scene.

Hedonic value, on the other hand, was decoded somewhere else, within deeper regions that handle reward and pleasure. Put simply, the brain seems to judge a visual painting with much the same machinery it uses to judge the rest of the world around us.

Changing the brain

We also found that how strongly the brain encoded this two-dimensional aesthetic landscape depended on a person’s expertise in visual arts. In particular, the difference showed up in the default mode network, a system of connections in the brain tied to imagination, consciousness, self-reflection and meaning-making that several leading theories place at the heart of aesthetic experience.

These results suggest that, beyond mere exposure, training in visual arts appears to change how the brain represents beauty in the first place.

This last point carries significant weight. If aesthetic experience has a measurable structure in the brain, and if making and viewing art can reshape it, then arts education starts to look less like enrichment and more like a kind of training that alters how perception, emotion and meaning are wired together. The clinical implications run along the same line.

Art-based therapies for depression, trauma and dementia have long been valued on instinct and anecdote. A clearer neural account gives us a way to test and sharpen them. Finally, as more of the images around us, in advertising, in design and on our screens, are generated by machines, knowing what beauty looks like inside the human brain matters more than ever.

Most often, we tend to treat beauty as something purely personal and assume that asking scientific questions about it misses the point. Building on pioneering work in the field of neuroaesthetics, our results suggest otherwise.

Beauty has a structure, and that structure says something about the kind of creature we have become over countless years of evolution. We do not simply look at the world, instead we cannot seem to stop judging it for its beauty.

Deniz Vatansever receives funding from the Ministry of Science and Technology of the People's Republic of China.

Xinyu Liang receives funding from the China Postdoctoral Science Foundation and is a Visiting Scholar at Clare Hall and Division of Anaesthesia, University of Cambridge.

Emmanuel A Stamatakis does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

Amy, a 27-year-old software developer, has struggled with disordered eating since she was a teenager. “But after learning to code, I got much better,” she said in a research interview. “I often code for ten or more hours without stopping.” Her psychiatrist, however, worried that Amy has replaced one compulsive behaviour with another.

“Digital addiction” is often used to describe our relationship with smartphones, social media and other digital technologies. This way of thinking suggests that people get “hooked” on digital activity because their body becomes “addicted” to dopamine. It borrows from models of substance addiction: the focus is on the physical need to keep using a substance because the body has adapted to it, despite harmful consequences. The implied solution is straightforward: abstinence, which translates into practices like digital detox.

But Amy’s story, which forms part of our ongoing research, points to a more complicated reality of our relationship with digital technology. Coding consumed much of her time and attention, yet it also helped her earn an income and build a professional identity. Like many forms of digital engagement, it was not just a distraction but a way of navigating life.

As research shows, for many people digital technologies are not only a source of entertainment but key components of their education, work and social mobility. Unlike in the case of addictive substances, opting out of digital life is easier said than done when schools, banks and public services increasingly require it.

How people relate to digital technology isn’t just about them as individuals. It’s shaped by their personal vulnerabilities, but also by digital environments intentionally built to hook us, and by the wider social conditions people live in.

So comparing smartphones to substances like alcohol, tobacco or drugs can be misleading. It overlooks the fact that digital devices have become a kind of essential infrastructure for daily life. Given how we have built our lives around them, these technologies are now very difficult to live without.

How, then, do we develop a sustainable relationship with technologies such as smartphones that are both indispensable and potentially harmful?

The sugar model

Amy’s story with disordered eating may be useful here. Recovery from an eating disorder isn’t about eliminating food altogether, but about learning to live with it.

In the same way that we cannot remove food from our lives, it is also difficult to remove digital technologies from our everyday. So the challenge becomes developing ways of living with them.

Take, for example, sugar. In many countries, foods high in sugar are subject to a wide range of public health measures. Think national food safety standards, public health interventions, school nutrition policies, limits on advertising. So it’s not about focusing on one thing only. Rather, it’s the interaction between all of these interventions that shapes patterns of consumption and impacts wellbeing.

A similar approach is needed for digital technologies. At the level of state and industry governance, this includes regulation of platform and design – particularly when it is aimed at capturing and holding users’ attention.

Just as food labels describe ingredients, nutrition and additives, digital products could disclose what data they collect, what algorithms they run on and what psychological techniques keep their users engaged.

The UK’s decision to ban social media for under 16s while continuing to expand digital literacy and coding education reflects an important point: not all digital technologies are the same.

“Digital use” cannot be treated as a single category to be either embraced or banned. Like sugar, the question is not whether children should have it at all, but what kinds, in what quantities, and in what conditions.

Beyond counting calories and screen hours

Just as sharing a meal with family affects people differently from eating alone, playing games with friends is not the same as scrolling endlessly through social media. Both count as screen time, but they create very different social and emotional experiences.

Reflecting on our own digital habits remains important. But tracking screen time is like counting calories: it tells us how much, but not necessarily why. We have to ask ourselves what role digital technologies play in our lives.

Are they helping us work, connect, rest, escape, cope, feel less or more alone? Without this kind of reflection, self-tracking risks turning a complex social issue into a matter of individual self-control.

Understanding digital technologies through the lens of food rather than addiction shifts the emphasis in important ways. Both are domains where necessity, pleasure, risk and social obligation are intertwined, which is why abstinence may not be an adequate, long-term response.

Instead of treating excessive technology use as a matter of personal discipline, approaching them like some foods locates it within broader systems of design, industry governance, state policy and social practices. The challenge then is to integrate these different levels to make life with digital technologies sustainable.

Tanja Ahlin receives funding from the Dutch Research Council (NWO), Grant number VI.Veni.241S.150, https://doi.org/10.61686/EWUXQ23921

Xin Zhan receives funding from the University of Cambridge.