Structural correlates of attentional performance in children with ADHD and their transcriptomic and neurotransmitter architectures

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Attention deficits are a core feature of attention deficit hyperactivity disorder (ADHD), yet the biological architecture underlying attentional variation remains incompletely understood. We integrated structural MRI, transcriptomics, and neurotransmitter mapping to investigate attentional performance in 94 children with ADHD. Regional gray matter volume (GMV) was quantified, and data-driven cross-validated predictive models were used to predict individual attention scores (where higher scores indicate better attentional performance). Imaging-transcriptomic and neurotransmitter mapping analyses were performed to characterize the molecular and neurochemical architecture of the predictive regions. The GMV-based predictive model can significantly identify individual differences in attention performance. The involved regions were distributed across cortical and subcortical areas, with ventral attention/salience and limbic networks contributing most. Transcriptomic analysis showed enrichment for genes involved in cell motility, neuron differentiation, and chromatin binding. Spatial similarity analysis revealed significant alignment with serotonin (5-HT1a, 5-HT2a), GABAa, and κ-opioid receptor distributions. Individual differences in attentional performance in children with ADHD are supported by large-scale structural brain organization. These findings link macroscale morphological patterns to underlying molecular and neurochemical systems, providing a multi-level framework for understanding attentional deficits in ADHD.