Objective Estimation of Sensory Thresholds Based on Neurophysiological Parameters
Objective Estimation of Sensory Thresholds Based on Neurophysiological Parameters
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DOI：
10.3389/fnins.2019.00481
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发表时间：
2019-05-16
影响因子：
4.3
通讯作者：
Schulze, Holger
中科院分区：
文献类型：
--
作者：
Schilling, Achim;Gerum, Richard;Schulze, Holger
可靠地确定感觉阈值是信号检测理论的圣杯。然而，尽管可靠的估计方法对于科学研究和临床诊断都至关重要，但基于神经生理学参数的阈值估计不存在独立于假设的金标准。当无法与受试者进行交流时，例如在动物或新生儿的研究中，阈值必须从神经记录或间接行为测试中得出。每当基于此类测量来估计阈值时，迄今为止的标准方法是通过肉眼或通过统计手段将阈值主观设置为至少可检测到“清晰”信号的值。这些测量是高度主观的，强烈依赖于噪声，并且由于阈值附近的低信噪比而波动。在这里，我们展示了一种基于神经生理学参数可靠估计生理阈值的新方法。使用替代数据，我们证明，使用硬 sigmoid 函数拟合对不同刺激强度的响应，并结合二次采样，可以提供稳健的阈值以及准确的不确定性估计。该方法对噪声没有系统依赖性，甚至不需要传感系统的整个动态范围内的样本。我们证明这种方法普遍适用于所有类型的感觉系统，从皮层的体感刺激处理到脑干的听觉处理。
Reliable determination of sensory thresholds is the holy grail of signal detection theory. However, there exists no assumption-independent gold standard for the estimation of thresholds based on neurophysiological parameters, although a reliable estimation method is crucial for both scientific investigations and clinical diagnosis. Whenever it is impossible to communicate with the subjects, as in studies with animals or neonates, thresholds have to be derived from neural recordings or by indirect behavioral tests. Whenever the threshold is estimated based on such measures, the standard approach until now is the subjective setting-either by eye or by statistical means- of the threshold to the value where at least a "clear" signal is detectable. These measures are highly subjective, strongly depend on the noise, and fluctuate due to the low signal-to-noise ratio near the threshold. Here we show a novel method to reliably estimate physiological thresholds based on neurophysiological parameters. Using surrogate data we demonstrate that fitting the responses to different stimulus intensities with a hard sigmoid function, in combination with subsampling, provides a robust threshold value as well as an accurate uncertainty estimate. This method has no systematic dependence on the noise and does not even require samples in the full dynamic range of the sensory system. We prove that this method is universally applicable to all types of sensory systems, ranging from somatosensory stimulus processing in the cortex to auditory processing in the brain stem.