Suppr超能文献

探究雷特综合征听觉感觉处理异常的神经不可靠性解释。

Probing a neural unreliability account of auditory sensory processing atypicalities in Rett Syndrome.

作者信息

Brima Tufikameni, Beker Shlomit, Prinsloo Kevin D, Butler John S, Djukic Aleksandra, Freedman Edward G, Molholm Sophie, Foxe John J

机构信息

The Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory Ernest J. Del Monte Institute for Neuroscience &Department of Neuroscience University of Rochester School of Medicine and Dentistry Rochester, New York 14642, USA.

The Cognitive Neurophysiology Laboratory Departments of Pediatrics and Neuroscience Albert Einstein College of Medicine & Montefiore Medical Center Bronx, New York 10461, USA.

出版信息

medRxiv. 2024 Jan 26:2024.01.25.24301723. doi: 10.1101/2024.01.25.24301723.

Abstract

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 100Hz 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.

摘要

背景

在寻找用于量化雷特综合征(RTT)神经功能的客观工具时,这对于评估临床试验中的治疗效果至关重要,使用事件相关电位(ERP)方法记录感觉 - 知觉功能已成为潜在的有力工具。大量研究表明RTT患者的听觉诱发电位(AEP)存在高度异常。然而,用于得出这些测量值的典型信号平均方法的一个假设是潜在反应的“平稳性”,即对每个输入的神经反应具有高度刻板性。另一种可能性是RTT患者对重复刺激的反应高度可变。如果是这样,这将显著影响关于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,有必要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)。

方法

记录了18名RTT患者和27名年龄匹配的对照者(年龄:6 - 22岁)对100Hz简单音调的AEP。我们应用了标准的AEP平均法,以及单次试验水平上的神经元可靠性测量方法(即SNR、ITV、ITPC)。为了将携带信号的成分与非神经噪声源分离,我们还应用了去噪源分离(DSS)算法,然后重复进行可靠性测量。

结果

在RTT参与者的听觉反应中观察到ITV显著增加、SNR降低以及ITPC降低,支持了“神经不可靠性”的观点。DSS技术的应用表明,非神经噪声源导致对RTT患者加工缺陷程度的高估。应用DSS后,ITV测量值大幅降低,以至于在RTT组和正常对照组之间不再检测到DSS应用前的ITV差异。就SNR和ITPC而言,DSS显著改善了RTT组的这些估计值,但RTT组和正常对照组之间的显著差异仍然完全明显。

结论

为了使用ERP技术准确表征RTT患者的神经功能障碍程度,强烈建议考虑单次试验水平上的反应可靠性。非神经噪声源导致对RTT患者病理加工程度的高估,并且在信号处理过程中使用去噪源分离技术可显著改善这一问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adb9/10854351/2dd5d4c70a3c/nihpp-2024.01.25.24301723v1-f0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验