Brain wiring could be behind learning difficulties, say experts

Scientists say current system for labelling children with difficulties is ‘too simple’

The Guardian

Nicola Davis

Fri 28 Feb 2020 

Learning difficulties are not linked to differences in particular brain regions, but in how the brain is wired, research suggests. In the study, the children with learning difficulties showed different levels of connection in certain brain ‘hubs’ than those without. According to figures from the Department for Education, 14.9% of all pupils in England about 1.3 million children – had special educational needs in January 2019, with 271,200 having difficulties that required support beyond typical special needs provision.

Dyslexia, attention deficit hyperactivity disorder (ADHD), autism and dyspraxia are among conditions linked to learning difficulties.

Now experts say different learning difficulties are not specific to particular diagnoses, nor are they linked to particular regions of the brain – as has previously been thought. Instead the team, from the University of Cambridge, say learning difficulties appear to be associated with differences in the way connections in the brain are organised.

Dr Roma Siugzdaite, a co-author of the study, said it was time to rethink how children with learning difficulties were labelled.

“We know that children with the same diagnoses can have very different profiles of problems, and our data suggest that this is because the labels we use do not map on to the reasons why children are struggling – in other words, diagnoses do not map on to underlying neural differences,” she said. “Labelling difficulties is useful for practical reasons, and can be helpful for parents, but the current system is too simple.”

Writing in the journal Current Biology, the team report how they made their discovery using a type of artificial intelligence called machine learning, which picks up on patterns within data.

The team drew on data from 479 children, 337 of whom had learning difficulties regarding performance in areas such as vocabulary, listening skills and problem-solving.

These data were presented to a machine learning system, which produced six chief categories reflecting the children’s cognitive abilities. The team found only 31% of children in the category reflecting the best performance were those with learning difficulties, while 97% of children in the category reflecting the poorest performance had learning difficulties.

Further work showed the system accurately assigned children into a wide range of categories relating to their cognitive abilities. However, the team found no link between these categories and particular diagnoses such as dyslexia, autism or ADHD.

“Having particular diagnoses doesn’t tell you about the kind of cognitive profile the children have,” said Dr Duncan Astle, another author of the study.

“Whilst diagnoses might be important, interventions should look beyond the label,” he added, noting children with different diagnoses may benefit from similar interventions while those with the same diagnosis may need different forms of support.

The researchers then extracted information from brain scans of the children and fed it into a machine learning system.

This generated 15 chief categories based on the structure of brain regions.

However, the team found that predictions of the cognitive abilities of a child were only about 4% better when based on their brain scans than by relying on guesswork alone.

“There is a whole literature … of people saying: ‘This brain structure is related to this cognitive difficulty in kids who struggle, and this brain structure related to that cognitive difficulty,’” said Astle. However, he added, the new study suggested that was not the case.

The team then turned to another feature of the brain: its wiring. Using data from 20 5children, the team found all showed similar efficiency of communication across the brain, with certain areas, known as hubs, showing many connections.

However, the children with learning difficulties showed different levels of connections in these hubs than those without. To explore whether this was important, the team turned to computer modelling, revealing the better the children’s cognitive abilities, the greater the drop in brain efficiency if the hubs were lost.

“The ‘hubbiness’ of a child’s brain was a strong predictor of their cognitive profiles,” said Siugzdaite . 

“Children’s whose brains ‘used’ hubs had higher cognitive abilities. We observed that in the case of the children who are struggling at school, they don’t rely too much on these hubs.”

Siugzdaite said the study raised further questions, including what biological or environmental factors could affect the development of such hubs, and whether some hubs were more important for particular cognitive skills. However, the study has limitations, including that the team did not look at other issues,such as social behaviour, which may be linked to different diagnoses and brain structure.

Dr Tomoki Arichi from the Centre for the Developing Brain at King’s College London, who was not involved in the research, said the study added to a growing body of evidence that learning difficulties are better understood by looking at the skills people struggle with,rather than focusing on particular diagnoses.  Arichi said the research offered good evidence that how connections in the brain are organised is important in learning difficulties, but added: “Understanding how this actually develops and then causes difficulties is still extremely complex, however, it is still possible that what they are seeing is a consequence rather than a cause, or is just a snapshot of an effect that is changing through childhood.”

© 2020 BiC Brain Injury Centre

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