Fatigue in children using motor imagery and P300 brain-computer interfaces.

BACKGROUND: Brain-computer interface (BCI) technology offers children with quadriplegic cerebral palsy unique opportunities for communication, environmental exploration, learning, and game play. Research in adults demonstrates a negative impact of fatigue on BCI enjoyment, while effects on BCI performance are variable. To date, there have been no pediatric studies of BCI fatigue. The purpose of this study was to assess the effects of two different BCI paradigms, motor imagery and visual P300, on the development of self-reported fatigue and an electroencephalography (EEG) biomarker of fatigue in typically developing children. METHODS: Thirty-seven typically-developing school-aged children were recruited to a prospective, crossover study. Participants attended three sessions: (A) motor imagery-BCI, (B) visual P300-BCI, and (C) video viewing (control). The motor imagery task involved an imagined left- or right-hand squeeze. The P300 task involved attending to one square on a 3 × 3 grid during a random single flash sequence. Each paradigm had respective calibration periods and a similar visual counting game. Primary outcomes were self-reported fatigue and the power of the EEG alpha band both collected during resting-state periods pre- and post-task. Self-reported fatigue was measured using a 10-point visual analog scale. EEG alpha band power was calculated as the integrated power spectral density from 8 to 12 Hz of the EEG spectrum. RESULTS: Thirty-two children completed the protocol (age range 7-16, 63% female). Self-reported fatigue and EEG alpha band power increased across all sessions (F(1,155) = 33.9, p < 0.001; F = 5.0(1,149), p = 0.027 respectively). No differences in fatigue development were observed between session types. There was no correlation between self-reported fatigue and EEG alpha band power change. BCI performance varied between participants and paradigms as expected but was not associated with self-reported fatigue or EEG alpha band power. CONCLUSION: Short periods (30-mintues) of BCI use can increase self-reported fatigue and EEG alpha band power to a similar degree in children performing motor imagery and P300 BCI paradigms. Performance was not associated with our measures of fatigue; the impact of fatigue on useability and enjoyment is unclear. Our results reflect the variability of fatigue and the BCI experience more broadly in children and warrant further investigation.

Differences in neurometabolites and transcranial magnetic stimulation motor maps in children with attention-deficit/hyperactivity disorder.

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.