Researchers use electrodes to measure brain activity while children carry out tasks. Understanding this brain activity can provide clues as to how teachers might optimise the learning environment for children of different ages and abilities. In the final instalment of a three-part series, cognitive neuroscientist Paul Matusz explains how his research group uses advanced EEG analyses to study how children develop attention skills in multisensory contexts.
Advanced EEG methods in action
In a recent study, we were able to show that the attention of children and adults differed when they played a simple computer game. But traditional methods of brain analysis were unable to answer the question of how. What neurological bases of attentional skills were shared across adults and children?
We asked adults and 5-, 7- and 9-year-old children to play a computer game involving a search for diamonds. While carrying out that search, the participants were distracted by sounds and coloured visual distractors. We recorded EEG data while they played, and then analysed the EEG data using traditional methods of recording the EEG response, which is known as N2pc (described in part one). However, this method revealed differences in how the children and adults performed, but told us nothing about what might be causing these differences.
“Electrical neuroimaging can detect patterns of ‘hills and valleys’ in the electrical field.”
We then turned to the advanced ‘electrical neuroimaging’ approach (described in part two). Electrical neuroimaging can detect patterns of ‘hills and valleys’ in the electrical field. Through this, it can identify which EEG patterns across the brain recorded at each millisecond are similar to each other. These patterns reflect the activity of distinct brain networks.
Using this new method, we were able to identify the brain mechanism underlying the skills that control attention to visual information based on a specific task goal. Also, in contrast to the traditional method of N2pc analysis, which could not distinguish between brain activity when participants were presented with purely visual elements and the activity that was triggered by when the visual elements appeared with a sound, our new method was able to make that distinction. For the first time, we succeeded in identifying the brain mechanism of adults who were paying attention to multisensory objects!
“It was only from age 9 that different EEG patterns, one relating to the colour and one to the audiovisual nature of the attended objects, started to fully mature.”
We also wanted to know whether the same brain mechanism was present in children. Intriguingly, the EEG patterns we saw in adults when they paid attention to visual objects with and without the presence of a sound, were also found in all the children we tested. However, it was only from age 9 that different EEG patterns, one relating to the colour and one to the audiovisual nature of the attended objects, started to fully mature. Electrical neuroimaging, so far used mainly in research on adults, revealed similarities in brain mechanisms across development that simply would not have been found if only traditional analyses had been used.
Why is this relevant to children’s learning?
In our study, we also collected data on children’s school achievement. We were particularly excited to discover that children’s EEG patterns were related to their basic educational skills, even though performance on the computer game was not. Certain patterns of EEG activity in space and time, which reflected attention to visual and multisensory objects, were linked to children’s scores on standardised tests of their basic skills in reading and maths. In children aged 5, for example, the length of time a specific EEG pattern (one which reflects skill in paying attention to visual objects) was present was linked to the strength of the children’s numerical skills. Amazingly, this suggests that attentional skills, and certain EEG patterns, might actually predict children’s learning success. We are currently analysing these results more closely, but they suggest that different attention brain mechanisms may underlie educational achievements as children grow older.
“A better understanding of attention and its brain mechanisms may help us to design better classrooms.”
Electrical neuroimaging methods have provided important and exciting new insights into how adults and children differ – and resemble one another – when it comes to paying attention. Brain mechanisms supporting attention in natural, multisensory environments are already present around the age of school entry (around 5 years in Switzerland). However, they continue to mature for at least 4 years, ultimately reaching a state where visual and audiovisual objects are processed as they are in adult brains. It also appears that both general and age-specific brain mechanisms are involved in attention. We are currently investigating this idea in more detail.
These results open up an exciting avenue of new research into the developmental trajectories of attentional skills in natural contexts. Greater insight into how children pay attention in classroom-like settings will teach us more about what makes learning in school successful. Ultimately, a better understanding of attention and its brain mechanisms may help us to design better classrooms and provide support to improve learning for all children.