背景:在寻找量化Rett综合征(RTT)神经功能的客观工具时,这对临床试验的疗效评估至关重要,使用事件相关电位(ERP)方法记录感官知觉功能已成为潜在的强大工具。大量工作指向RTT中高度异常的听觉诱发电位(AEP)。然而,用于得出这些度量的典型信号平均法的假设是潜在反应的“平稳性”-即对每个输入的神经反应是高度定型的。另一种可能性是对重复刺激的反应在RTT中是高度可变的。如果是,这将显著影响潜在神经功能障碍假设的有效性,并可能导致对潜在神经病理学的高估。为了评估这种可能性,在单次试验水平上进行分析,评估信噪比(SNR),试验间变异性(ITV)和试验间相位相干性(ITPC)是必要的。
方法:从18个RTT和27个年龄匹配的对照(年龄:6-22岁)将AEP记录到简单的100Hz音调。我们采用标准AEP平均,以及单次试验水平的神经元可靠性度量(即SNR,ITV,ITPC)。为了将携带信号的分量与非神经噪声源分开,我们还应用了去噪源分离(DSS)算法,然后重复了可靠性措施。
结果:ITV大幅增加,较低的SNR,在RTT参与者的听觉反应中观察到ITPC降低,支持“神经不可靠”账户。DSS技术的应用清楚地表明,非神经噪声源有助于高估RTT中处理缺陷的程度。后DSS,ITV措施大幅减少,如此之多,以至于不再检测到RTT和TD人群之间的DSS前ITV差异。在SNR和ITPC的情况下,DSS大大改善了RTT群体中的这些估计,但RTT和TD之间的强劲差异仍然非常明显。
结论:为了使用ERP技术准确表示RTT中的神经功能障碍程度,强烈建议在单次试验水平上考虑响应可靠性。非神经性噪声源导致对RTT中病理处理程度的高估,信号处理过程中的去噪源分离技术大大改善了这个问题。
BACKGROUND: In the search for objective tools to quantify neural function in Rett Syndrome (RTT), which are crucial in the evaluation of therapeutic efficacy in clinical trials, recordings of sensory-perceptual functioning using event-related potential (ERP) approaches have emerged as potentially powerful tools. Considerable work points to highly anomalous auditory evoked potentials (AEPs) in RTT. However, an assumption of the typical signal-averaging method used to derive these measures is \"stationarity\" of the underlying responses - i.e. neural responses to each input are highly stereotyped. An alternate possibility is that responses to repeated stimuli are highly variable in RTT. If so, this will significantly impact the validity of assumptions about underlying neural dysfunction, and likely lead to overestimation of underlying neuropathology. To assess this possibility, analyses at the single-trial level assessing signal-to-noise ratios (SNR), inter-trial variability (ITV) and inter-trial phase coherence (ITPC) are necessary.
METHODS: AEPs were recorded to simple 100 Hz tones from 18 RTT and 27 age-matched controls (Ages: 6-22 years). We applied standard AEP averaging, as well as measures of neuronal reliability at the single-trial level (i.e. SNR, ITV, ITPC). To separate signal-carrying components from non-neural noise sources, we also applied a denoising source separation (DSS) algorithm and then repeated the reliability measures.
RESULTS: Substantially increased ITV, lower SNRs, and reduced ITPC were observed in auditory responses of RTT participants, supporting a \"neural unreliability\" account. Application of the DSS technique made it clear that non-neural noise sources contribute to overestimation of the extent of processing deficits in RTT. Post-DSS, ITV measures were substantially reduced, so much so that pre-DSS ITV differences between RTT and TD populations were no longer detected. In the case of SNR and ITPC, DSS substantially improved these estimates in the RTT population, but robust differences between RTT and TD were still fully evident.
CONCLUSIONS: To accurately represent the degree of neural dysfunction in RTT using the ERP technique, a consideration of response reliability at the single-trial level is highly advised. Non-neural sources of noise lead to overestimation of the degree of pathological processing in RTT, and denoising source separation techniques during signal processing substantially ameliorate this issue.