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Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging
Published on: September 12, 2011
Differences in neurometabolites and transcranial magnetic stimulation motor maps in children with
Cynthia K Kahl1, Rose Swansburg1, Tasmia Hai1
1From the Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, Alta. (Kahl, Swansburg, MacMaster); the Department of Pediatrics, Cumming School of Medicine, University of Calgary, Calgary, Alta. (Kahl, Swansburg, Lemay, Kirton, MacMaster); the Hotchkiss Brain Institute, University of Calgary, Calgary, Alta. (Kahl, Wrightson, Bell, Kirton, MacMaster); the Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alta. (Kahl, Bell, Kirton, MacMaster); the Department of Educational Psychology, University of Alberta, Edmonton, Alta. (Hai); the Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alta. (Bell); the Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alta. (Kirton); and the Strategic Clinical Network for Addictions and Mental Health, Calgary, Alta. (MacMaster).
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.
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