BACKGROUND: Increased intra-subject response time standard deviations (RT-SD) discriminate children with attention-deficit/hyperactivity disorder (ADHD) from healthy control subjects. The RT-SD is averaged over time; thus it does not provide information about the temporal structure of RT variability. We previously hypothesized that such increased variability might be related to slow spontaneous fluctuations in brain activity occurring with periods between 15 sec and 40 sec. Here, we investigated whether these slow RT fluctuations add unique differentiating information beyond the global increase in RT-SD. METHODS: We recorded RT at 3-sec intervals for 15 min during an Eriksen flanker task for 29 children with ADHD and 26 age-matched typically developing control subjects (TDC) (mean ages 12.5 +/- 2.4 and 11.6 +/- 2.5; 26 and 12 boys, respectively). The primary outcome was the magnitude of the spectral component in the frequency range between .027 and .073 Hz measured with continuous Morlet wavelet transform. RESULTS: The magnitude of the low-frequency fluctuation was greater for children with ADHD compared with TDC (p = .02, d = .69). After modeling ADHD diagnosis as a function of RT-SD, adding this specific frequency range significantly improved the model fit (p = .03; odds ratio = 2.58). CONCLUSIONS: Fluctuations in low-frequency RT variability predict the diagnosis of ADHD beyond the effect associated with global differences in variability. Future studies will examine whether such spectrally specific fluctuations in behavioral responses are linked to intrinsic regional cerebral hemodynamic oscillations that occur at similar frequencies.
BACKGROUND: Increased intra-subject response time standard deviations (RT-SD) discriminate children with attention-deficit/hyperactivity disorder (ADHD) from healthy control subjects. The RT-SD is averaged over time; thus it does not provide information about the temporal structure of RT variability. We previously hypothesized that such increased variability might be related to slow spontaneous fluctuations in brain activity occurring with periods between 15 sec and 40 sec. Here, we investigated whether these slow RT fluctuations add unique differentiating information beyond the global increase in RT-SD. METHODS: We recorded RT at 3-sec intervals for 15 min during an Eriksen flanker task for 29 children with ADHD and 26 age-matched typically developing control subjects (TDC) (mean ages 12.5 +/- 2.4 and 11.6 +/- 2.5; 26 and 12 boys, respectively). The primary outcome was the magnitude of the spectral component in the frequency range between .027 and .073 Hz measured with continuous Morlet wavelet transform. RESULTS: The magnitude of the low-frequency fluctuation was greater for children with ADHD compared with TDC (p = .02, d = .69). After modeling ADHD diagnosis as a function of RT-SD, adding this specific frequency range significantly improved the model fit (p = .03; odds ratio = 2.58). CONCLUSIONS: Fluctuations in low-frequency RT variability predict the diagnosis of ADHD beyond the effect associated with global differences in variability. Future studies will examine whether such spectrally specific fluctuations in behavioral responses are linked to intrinsic regional cerebral hemodynamic oscillations that occur at similar frequencies.
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