PT  - JOURNAL ARTICLE
AU  - Cynthia K. Kahl
AU  - Rose Swansburg
AU  - Tasmia Hai
AU  - James G. Wrightson
AU  - Tiffany Bell
AU  - Jean-François Lemay
AU  - Adam Kirton
AU  - Frank P. MacMaster
TI  - Differences in neurometabolites and transcranial magnetic stimulation motor maps in children with attention-deficit/hyperactivity disorder
AID  - 10.1503/jpn.210186
DP  - 2022 Jul 05
TA  - Journal of Psychiatry and Neuroscience
PG  - E239--E249
VI  - 47
IP  - 4
4099  - http://jpn.ca/content/47/4/E239.short
4100  - http://jpn.ca/content/47/4/E239.full
SO  - JPN2022 Jul 05; 47
AB  - Background: Although much is known about cognitive dysfunction in attention-deficit/hyperactivity disorder (ADHD), few studies have examined the pathophysiology of disordered motor circuitry. We explored differences in neurometabolite levels and transcranial magnetic stimulation (TMS)–derived corticomotor representations among children with ADHD and typically developing children.Methods: We used magnetic resonance spectroscopy (MRS) protocols to measure excitatory (glutamate + glutamine [Glx]) and inhibitory (γ-aminobutyric acid [GABA]) neurometabolite levels in the dominant primary motor cortex (M1) and the supplementary motor area (SMA) in children with ADHD and typically developing children. We used robotic neuronavigated TMS to measure corticospinal excitability and create corticomotor maps.Results: We collected data from 26 medication-free children with ADHD (aged 7–16 years) and 25 typically developing children (11–16 years). Children with ADHD had lower M1 Glx (p = 0.044, d = 0.6); their mean resting motor threshold was lower (p = 0.029, d = 0.8); their map area was smaller (p = 0.044, d = 0.7); and their hotspot density was higher (p = 0.008, d = 0.9). M1 GABA levels were associated with motor map area (p = 0.036).Limitations: Some TMS data were lost because the threshold of some children exceeded 100% of the machine output. The relatively large MRS voxel required to obtain sufficient signal-to-noise ratio and reliably measure GABA levels encompassed tissue beyond the M1, making this measure less anatomically specific.Conclusion: The neurochemistry and neurophysiology of key nodes in the motor network may be altered in children with ADHD, and the differences appear to be related to each other. These findings suggest potentially novel neuropharmacological and neuromodulatory targets for ADHD.