Bilan Danylyna Shpakivska, Chicchi Giglioli Irene Alice, Cuesta Pablo, Cañadas Elena, de Ramón Ignacio, Maestú Fernando, Alda Jose, Ramos-Quiroga Josep Antoni, Herrera Jorge A, Amado Alfonso, Quintero Javier
Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Complutense University of Madrid, Madrid, Spain.
Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, 28040, Madrid, Spain.
Npj Ment Health Res. 2025 Jan 9;4(1):1. doi: 10.1038/s44184-024-00111-9.
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.
注意力缺陷多动障碍（ADHD）表现为冲动、注意力不集中和多动等症状，常常影响儿童的学业和社交功能。非药物干预措施，如数字认知疗法，正逐渐成为ADHD的辅助治疗方法。这项随机对照试验探讨了一个由人工智能驱动的数字认知项目对41名8至12岁ADHD儿童的冲动性、注意力不集中和神经生理指标的影响。参与者接受了为期12周的人工智能驱动治疗或安慰剂干预。在干预前后进行了评估，并通过脑磁图（MEG）分析了大脑活动。结果显示，治疗组的冲动性和注意力不集中得分显著降低，同时MEG频谱图正常化，表明神经成熟。值得注意的是，抑制控制能力的改善与颞顶叶皮质的频谱图正常化相关。与频谱图正常化相关的抑制控制能力的改善表明，人工智能驱动的数字认知疗法可以通过提高神经生理效率来降低ADHD儿童的冲动性。这强调了使用神经生理指标评估疗效的个性化、技术驱动的ADHD治疗方法。
