The brain network underlying attentional blink predicts symptoms of attention deficit hyperactivity disorder in
Dai Zhang1, Ruotong Zhang2, Liqin Zhou2
1Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Health Science Center, No. 1066, Xueyuan Street, Nanshan District, Shenzhen 518073, China.
Insights
Brain connectivity in the attentional blink (AB) network can predict attention deficit hyperactivity disorder (ADHD) symptoms. This neural network may serve as a neuroimaging biomarker for ADHD, aiding in diagnosis and understanding neuropathology.
Area of Science:
- Neuroscience
- Psychiatry
- Medical Imaging
Background:
- Attention deficit hyperactivity disorder (ADHD) is a chronic neuropsychiatric condition impacting lifelong functioning.
- Behavioral deficits in ADHD may indicate underlying neurological impairments.
- Children with ADHD show a more pronounced attentional blink (AB) deficit in rapid serial visual presentation (RSVP) tasks.
Purpose of the Study:
- To investigate if brain connectivity within the AB neural network can predict ADHD symptoms.
- To explore the potential of the AB network as a neuroimaging biomarker for ADHD neuropathology.
Main Methods:
- Utilized connectome-based predictive modeling on adult resting-state fMRI data to identify the AB network.
- Assessed functional connectivity (FC) strength within the AB network.
- Validated findings using an independent dataset of pediatric ADHD patients.
Main Results:
- The summed FC strength within the AB network reliably predicted individual differences in AB magnitude.
- The AB network's FC strength also predicted individual differences in ADHD Rating Scale scores in pediatric patients.
Conclusions:
- The individual AB network shows potential as a neuroimaging-based biomarker for both AB deficits and ADHD symptoms.
- This finding offers a novel approach to understanding and potentially diagnosing ADHD through brain connectivity patterns.
Abstract:
Attention deficit hyperactivity disorder (ADHD) is a chronic neuropsychiatric disease that can markedly impair educational, social, and occupational function throughout life. Behavioral deficits may provide clues to the underlying neurological impairments. Children with ADHD exhibit a larger attentional blink (AB) deficit in rapid serial visual presentation (RSVP) tasks than typically developing children, so we examined whether brain connectivity in the neural network associated with AB can predict ADHD symptoms and thus serve as potential biomarkers of the underlying neuropathology. We first employed a connectome-based predictive model analysis of adult resting-state functional magnetic resonance imaging data to identify a distributed brain network for AB. The summed functional connectivity (FC) strength within the AB network reliably predicted individual differences in AB magnitude measured by a classical dual-target RSVP task. Furthermore, the summed FC strength within the AB network predicted individual differences in ADHD Rating Scale scores from an independent dataset of pediatric patients. Our findings suggest that the individual AB network could serve as an applicable neuroimaging-based biomarker of AB deficit and ADHD symptoms.
