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    Home » News » Optimize a powerful tool for measuring brain activity
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    Optimize a powerful tool for measuring brain activity

    healthadminBy healthadminApril 28, 2026No Comments2 Mins Read
    Optimize a powerful tool for measuring brain activity
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    Clinicians use electroencephalography (EEG) to assess brain activity in epilepsy and sleep pathologies, but this powerful tool has shown promise in other conditions as well. Emerging evidence suggests that brain development, age, and time of day influence EEG signals measured during sleep. new e-neuro In this paper, researchers from the University Children’s Hospital Zurich investigated how differences in brain development, age, and sleep affect measurements of EEG signals recorded from awake people.

    Lead author Sophia Snipes explains in detail. ”Although EEG studies have typically relied on summary measurements when comparing patients and experimental conditions, we have separated EEG signals in more detail to better understand the meaning behind the differences we are observing.”

    First, supporting previous findings, the researchers found that four measures of brain wave signals in 163 awake people aged 3 to 25 were affected differently by sleep history and age. Researchers say some measurements show an interaction between sleep history and age, which may reflect that children experience more brain changes during learning and memory than adults. This is a new discovery. Other measurements showed surprising developmental changes, with opposite results in children and adults after a single night’s sleep. These findings ultimately show that brain signals during wakefulness are dependent on previous sleep and that this influence differs in children and adults.

    Because ADHD patients have developmental differences from neurotypical people, and because previous studies had identified differences in brain activity in EEG recordings taken from sleeping ADHD patients, the researchers further evaluated specific interventions using data from 58 awake children with ADHD. No differences in measurements were observed based solely on ADHD diagnosis, suggesting to the researchers that sleep quality, rather than symptoms of ADHD itself, may explain previously observed variation in EEG data, although further research is needed.

    Snipes discusses how this initiative will improve brainwave research and clinical use. ”Although (researchers and clinicians) have been using this tool for some time, more sophisticated forms of data analysis could improve the interpretation of EEG recordings. Even if we know that certain variables change the EEG signal, we cannot infer what these changes mean unless we know which part of the signal is changing.”

    sauce:

    Reference magazines:

    Snipes, S. Others. (2026). Interaction between sleep and the development of waking EEG oscillations. e-neuro. DOI: 10.1523/ENEURO.0384-25.2026. https://www.eneuro.org/content/early/2026/04/03/ENEURO.0384-25.2026



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