Identifying ADHD children using hemodynamic responses during a working memory task measured by functional...

Area of Science:

• Neuroscience
• Medical Imaging
• Developmental Psychology

Background:

• Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder impacting cognitive functions.
• Previous research indicates functional near-infrared spectroscopy (fNIRS) can detect brain differences in ADHD during working memory tasks.

Purpose of the Study:

• To investigate the efficacy of fNIRS brain activation patterns in distinguishing children with ADHD from healthy controls.
• To explore the potential of fNIRS as a diagnostic tool for ADHD.

Main Methods:

• fNIRS data were collected from 25 children diagnosed with ADHD and 25 typically developing controls during an n-back task.
• Multivariate pattern analysis (MVPA) was employed to classify participants based on their fNIRS signals.
• Permutation testing was used to assess the statistical significance of classification accuracy.

Main Results:

• An 86.0% classification accuracy was achieved in identifying ADHD participants using a leave-one-out cross-validation approach.
• Key brain regions contributing to the classification included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex.

Conclusions:

• Multivariate pattern analysis of fNIRS signals can effectively differentiate children with ADHD from healthy controls.
• These findings highlight the potential of fNIRS as a valuable tool for ADHD assessment, even with a small sample size.