A new research facility that combines wearable brain imaging, motion capture and artificial intelligence has opened in London, promising to transform the understanding of how children engage with digital media and how that content shapes their developing minds.
The Nerve Lab, described as the first facility of its kind in the UK, is based at University of the Arts London’s Creative Computing Institute and was made possible by Research England’s Regional Innovation Funding. By integrating neurotechnology with AI-powered analytics, the lab aims to quantify human responses to media and artistic experiences in real time, opening the door to more precise guidance for parents, educators and regulators.
At the heart of the lab’s work is the Animating Minds project, a two-year study running from February 2025 to February 2027, funded by a £1.16 million UKRI Cross Research Council grant. The multidisciplinary team — drawing expertise from UAL, Queen Mary University of London, Birkbeck, University of London, Arts University Bournemouth, and the University of Brescia — spans animation theory, developmental psychology, neuroscience and AI. Their focus: understanding what makes children’s animated content age-appropriate in an era when screen time begins as young as two.
“Today’s young viewers are increasingly engaging with short-form, fast-paced, highly captivating content, often created by splicing and rearranging existing episodic content into quickly digestible snippets or compilations,” said Professor Tim Smith, director of the Nerve Lab and professor in cognitive data science at UAL. “This evolution is not only changing how content is produced and distributed, but may also affect children’s attention, comprehension and emotional response.”
To investigate this, researchers have compiled a database of around 1,000 episodes of popular animated television shows. Using AI-driven tools, they are analysing features such as pacing, colourfulness, loudness, shot frequency and narrative structure. At the same time, the team is interviewing animators, producers and commissioners about the creative decisions that shape children’s content. The goal is to build a computational system capable of predicting the direct effect that a piece of animation is likely to have on a young child.
“The question is, can we build a computational system where we can understand and predict the direct effect that children’s animated content is going to have on young children?” Smith said.
The research goes beyond traditional observation. The lab uses functional near-infrared spectroscopy (fNIRS) — a non-invasive form of brain scanning that monitors blood flow in the brain — along with eye-tracking and motion capture. Children aged three to six are fitted with a neoprene cap studded with sensors that use near-infrared light to track activity in different brain regions as they watch media. This data, combined with behavioural measures, allows researchers to see not just what children look at but how their brains respond moment by moment.
“We have kids as young as two spending three or four hours a day on screens. It is really important to have a wider understanding of what it means for them to watch something that’s appropriate for their age,” said Alisa Musatova, a research assistant on the Animating Minds project.
The team is currently recruiting UK families with children aged three to six to take part in an online study examining how animated programmes influence short-term attention. The longer-term ambition is to develop tools that could help animators, commissioners and regulators determine whether programmes are having their intended effect, while building the foundations for more nuanced classification systems. As Smith put it, the aim is to move the discussion from “moral panic to measurement.”
Professor Heather Kirkorian, a developmental psychologist at the University of Wisconsin-Madison who studies children’s media use, said the work addresses a significant gap. “The digital media landscape has changed a lot in recent years,” she said. “While there is a lot of speculation about potential impacts on development, there is very little research that uses the types of precise measurement proposed in this work.” She noted that AI-based tools could analyse children’s programming at a scale that would previously have been impractical. “In the past, this kind of work required very time-intensive – and sometimes subjective or imprecise – manual coding. Now that streaming platforms have democratised content creation, young children are watching an ever-growing array of videos on different platforms. Time-intensive manual coding just can’t keep up.”
Polly Conway, senior editor at Common Sense Media, a non-profit organisation that provides age-based reviews and guidance, said additional evidence about the impact of programming on young brains could be valuable, particularly if researchers can quantify features that have previously been difficult to define. “Just because a programme or YouTube channel is teaching the ABCs, numbers or shapes, they may not be doing it at the correct level for the intended audience,” she said.
Understanding why children make the same mistake differently
Another project under the Nerve Lab umbrella, Mathstronauts, is using brain imaging to tackle a different educational challenge: why two children can solve the same maths problem incorrectly but for fundamentally different reasons. Take fractions: one child may not understand the concept at all, while another may know the rules but cannot suppress an intuitive impulse — for instance, assuming that 1/4 is bigger than 1/2 because four is bigger than two.
“With conventional testing, I can see whether an answer is correct and how many seconds a child took to solve it, but it doesn’t tell me why two children have made the same mistake,” said Dr Rakhi Leela Nair, who leads the Mathstronauts project. “One child may need help learning the concept of fractions. The other may know the rules, but need help to stop, think and inhibit the wrong answer.”
Mathstronauts uses fNIRS to monitor brain activity in children as they play a maths game on a computer. The sensors in the neoprene cap track activity in different regions of the brain in real time. That information, combined with the child’s game scores, is then used to adapt the game instantly. Children who appear to understand the concept but respond impulsively are directed toward tasks that encourage them to slow down and think more carefully. Those who have not yet mastered the concept are given additional teaching and practice exercises designed to strengthen their understanding.
The system is now being tested with seven- and eight-year-olds at a north London primary school.
Professor Roi Cohen Kadosh, a cognitive neuroscientist at the University of Surrey, described the approach as “a plausible and potentially useful direction for educational neuroscience” but cautioned that its value would depend on whether brain-imaging data could provide insights beyond those already available from teachers and conventional assessments. “The important test is whether the system performs better than existing approaches,” he said. “A teacher may already be able to distinguish between a child who lacks conceptual understanding and a child who is answering impulsively.” He added that technologies such as fNIRS should be seen as tools to support, rather than replace, teachers. “The opportunity is to use neuroscience, psychology and AI to understand the learner more precisely and give teachers better tools.”
Cohen Kadosh, who also founded Cognite Neurotechnology, has pioneered research into AI-personalised brain stimulation. His comments underscore the broader ambition of the Nerve Lab: not simply to measure what children see or do, but to understand the neural processes behind their learning and media consumption, and to turn that understanding into practical support for families, educators and content creators.
