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Related Concept Videos

Attention-Deficit/Hyperactivity Disorder01:30

Attention-Deficit/Hyperactivity Disorder

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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and impulsivity. It affects approximately 5-8% of children globally, with around 60-70% of cases persisting into adulthood. ADHD has significant implications for educational attainment, social interactions, and occupational success.
Diagnostic Criteria and Symptoms
To diagnose ADHD, symptoms must manifest before age 12 and be evident across multiple settings....
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Information-based multivariate decoding reveals imprecise neural encoding in children with attention deficit

Dongwei Li1, Xiangsheng Luo2,3, Jialiang Guo1

  • 1State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.

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Children with Attention Deficit Hyperactivity Disorder (ADHD) show impaired neural responses during attentional tasks. This study reveals inefficient neural encoding may underlie ADHD

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Area of Science:

  • Neuroscience
  • Developmental Psychology
  • Clinical Psychology

Background:

  • Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder in school-aged children.
  • Attentional orientation is a potential diagnostic marker for early ADHD detection, but its neural basis in childhood ADHD is not fully understood.

Purpose of the Study:

  • To investigate the neural underpinnings of impaired attentional orienting in children with ADHD using electroencephalography (EEG).
  • To explore the utility of univariate and multivariate EEG analyses for identifying cognitive deficits in childhood ADHD.

Main Methods:

  • Electroencephalography (EEG) data were collected from 135 school-aged children (70 with ADHD, 65 typically developing).
  • Univariate Event-Related Potential (ERP) analysis (focusing on N2pc) and multivariate pattern machine learning analysis were employed to assess spatial selective attention and target localization.
  • Analyses focused on neural responses during a visual search task.

Main Results:

  • Children with ADHD exhibited a smaller N2pc component compared to typically developing children.
  • Lower parieto-occipital multivariate decoding accuracy was observed in children with ADHD (240-340 ms post-stimulus onset), correlating with slower and more variable reaction times.
  • A significant correlation between N2pc and decoding accuracy was found in typically developing children, but not in those with ADHD.

Conclusions:

  • Impaired attentional orienting in childhood ADHD may stem from inefficient neural encoding processes.
  • The findings suggest that multivariate machine learning approaches can enhance the understanding of cognitive deficits in neurodevelopmental disorders.
  • This research offers potential avenues for the early diagnosis and personalized intervention strategies for children with ADHD.