Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience, NYU Child Study Center, New York, NY 10016, USA.
Eur Child Adolesc Psychiatry. 2012 Feb;21(2):101-9. doi: 10.1007/s00787-011-0237-6.
Greater intra-subject variability (ISV) in response time is a heritable endophenotype of attention-deficit/hyperactivity disorder (ADHD). Spontaneous low frequency oscillations (LFO: 0.01-0.1 Hz) observed in brain functional magnetic resonance signals might account for such behavioral variability. Recently, we demonstrated that ISV in response time (RT) explained ratings of ADHD symptoms. Building on this finding, here we hypothesized that LFO in RT time series would explain these ratings, both independently and in addition to RT coefficient of variation (CV). To measure RT LFO, we applied Morlet wavelet transform to the previously collected RT data. Our community sample consisted of 98 children (including 66 boys, mean age 9.9 ± 1.4 years), who completed four computer Tasks of Executive Control. Conners' Parent Rating Scale ratings were obtained. RT LFO of three tasks significantly explained ratings of inattention, hyperactivity and three global Conners' subscales. In addition, RT LFO during two tasks that included an inhibitory component increased the proportions of variance explained in subscales of both inattention and hyperactivity/impulsivity, beyond the effects of RT-CV. Three specific low frequency bands (Slow-5: 0.01-0.027 Hz; Slow-4: 0.027-0.073 Hz; Slow-3: 0.073-0.20 Hz) were strongly related to the ADHD scales. We conclude that RT LFO predict dimensional ratings of ADHD symptoms both independently and in addition to RTCV. Results suggest that frequency analyses are a suitable methodology to link behavioral responses to putative underlying physiological processes.
反应时的个体内变异性（ISV）较大是注意缺陷多动障碍（ADHD）的一种可遗传的内表型。大脑功能磁共振信号中观察到的自发低频振荡（LFO：0.01-0.1 Hz）可能解释了这种行为变异性。最近，我们证明了反应时（RT）的 ISV 可以解释 ADHD 症状的评分。在此发现的基础上，我们假设 RT 时间序列中的 LFO 可以独立于 RT 变异系数（CV），并补充 RT 解释这些评分。为了测量 RT LFO，我们将 Morlet 小波变换应用于之前收集的 RT 数据。我们的社区样本包括 98 名儿童（包括 66 名男孩，平均年龄 9.9 ± 1.4 岁），他们完成了四项执行控制计算机任务。同时获得了 Conners 父母评定量表的评分。三个任务的 RT LFO 显著解释了注意力不集中、多动和三个 Conners 整体子量表的评分。此外，在包括抑制成分的两个任务中，RT LFO 增加了注意力和多动/冲动性两个子量表的方差解释比例，超出了 RT-CV 的影响。三个特定的低频带（Slow-5：0.01-0.027 Hz；Slow-4：0.027-0.073 Hz；Slow-3：0.073-0.20 Hz）与 ADHD 量表密切相关。我们得出结论，RT LFO 可以独立于 RTCV 预测 ADHD 症状的维度评分。结果表明，频率分析是一种将行为反应与潜在生理过程联系起来的合适方法。
