Decreased impulsiveness and MEG normalization after AI-digital therapy in ADHD children: a RCT

Abstract Attention-deficit/hyperactivity disorder (ADHD) presents with symptoms like impulsiveness, inattention, and hyperactivity, often affecting children’s academic and social functioning. Non-pharmacological interventions, such as digital cognitive therapy, are emerging as complementary treatmen...

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Main Authors: Danylyna Shpakivska Bilan, Irene Alice Chicchi Giglioli, Pablo Cuesta, Elena Cañadas, Ignacio de Ramón, Fernando Maestú, Jose Alda, Josep Antoni Ramos-Quiroga, Jorge A. Herrera, Alfonso Amado, Javier Quintero
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:npj Mental Health Research
Online Access:https://doi.org/10.1038/s44184-024-00111-9
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Summary:Abstract Attention-deficit/hyperactivity disorder (ADHD) presents with symptoms like impulsiveness, inattention, and hyperactivity, often affecting children’s academic and social functioning. Non-pharmacological interventions, such as digital cognitive therapy, are emerging as complementary treatments for ADHD. The randomized controlled trial explored the impact of an AI-driven digital cognitive program on impulsiveness, inattentiveness, and neurophysiological markers in 41 children aged 8–12 with ADHD. Participants received either 12 weeks of AI-driven therapy or a placebo intervention. Assessments were conducted pre- and post-intervention and magnetoencephalography (MEG) analyzed brain activity. Results showed significant reductions in impulsiveness and inattentiveness scores in the treatment group, associated with normalized MEG spectral profiles, indicating neuromaturation. Notably, improvements in inhibitory control correlated with spectral profile normalization in the parieto-temporal cortex. Improvements in inhibitory control, linked to normalized spectral profiles, suggest AI-driven digital cognitive therapy can reduce impulsiveness in ADHD children by enhancing neurophysiological efficiency. This emphasizes personalized, technology-driven ADHD treatment, using neurophysiological markers for assessing efficacy.
ISSN:2731-4251