The 128-channel EEG net as worn by a child.

Research agrees that there are prominent changes in brain rhythm (repeated patterns of brain wave activity across different areas of the scalp) from early to middle childhood. Currently, researchers are investigating if – and how – these changes are related to key developmental outcomes such as Executive Function (EF). EF is an umbrella term that refers to multiple cognitive processes – including working memory, inhibitory control, and cognitive flexibility. It’s easy to see how EF could be important across development, but it is especially significant and rapidly improving as children begin to enter school. One of our recent studies examined age-related changes in brain rhythm activity from age 3 to 9 years and how they correlate with EF. We used a technique called electroencephalography (EEG) to measure brain activity. Our EEG machine uses a net, similar to a swim cap, with 128 electrodes (or small sponges) that sit on the surface of the scalp (pictured to the right).

These electrodes measure the electrical activity produced by brain rhythm, and how neurons fire together in relatively slow or fast frequencies over different parts of the scalp. We looked at 5 different frequency bands (theta, low alpha, high alpha, beta, and gamma) in two different conditions. The first condition involved the child sitting in silence with eyes closed, and in the second, they looked at planets in space on a screen while still in a relaxed state. With this EEG data, we were able to see how brain rhythms at rest were different across ages and between participants. We also used these developmental and individual differences to see how they are related to EF, measured using the Minnesota Executive Function Scale (MEFS App).

Before turning to the results from this study, some background on the different electric waves (theta to gamma) might be helpful. First, studies have shown that theta activity generally decreases over childhood. Next, high gamma activity at rest was suggested to be positively associated with cognitive developmental outcomes. Other work has shown that alpha is the brain’s dominant rhythm and tends to increase in speed over development. Finally, the ratio between theta and beta frequencies has been studied in the context of cognitive development as well and has been shown to be linked to EF in adults and children with ADHD. Generally, a high theta/beta ratio is thought to be evidence of reward-oriented, lower executive control whereas a low theta/beta ratio indicates goal-driven, higher executive control. With our study, we predicted that the theta/beta ratio in children would decrease as performance on the MEFS App increased.


Brain Rhythm Study Results:

We highlighted several major results from this study. In general, theta activity decreased and alpha activity increased with age, in line with previous research, but our study was the first to show this using the same method across a wider age range, from 3-9. Next, we found that our different conditions of rest (eyes open versus closed) highlighted different frequencies. Across participants, theta and alpha (slower waves) were generally higher with eyes closed than eyes open, whereas beta and gamma (faster waves) were higher with eyes closed than open. In addition to showing the complex work our brain does even at rest, this suggests that each condition made participants use a different form of attention. Furthermore, it suggests that different forms of attention may be related to specific frequency bands. Finally, we saw that as the theta/beta ratio decreased, children’s performance on the MEFS App increased, even after accounting for age and general language skills. These results suggest that the MEFS is a valid behavioral indicator of brain development in this age group. For a more in-depth discussion of the study, you can access our full paper in Developmental Science.

Perone, S., Palanisamy, J., & Carlson, S. M. (2018). Age-related change in brain rhythms from early to middle childhood: Links to executive function. Developmental Science, e12691. doi: 10.1111/desc.12691.

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About the Author:

Jeeva Palanisamy is the current lab manager for the Developmental Social Cognitive Neuroscience Lab at the Institute of Child Development. He worked there as a research assistant from early in his undergraduate career, helping collect and analyze data for the study described above. Currently, he is taking a gap year to apply to medical schools while working in the lab and as a medical scribe. He hopes to use his experience as a child development researcher to support his future patients and wishes to continue linking research from bench to bedside.