Güçlü Burak, Gescheider George A, Bolanowski Stanley J, Istefanopulos Yorgo
Biomedical Engineering Institute, Boğaziçi University, Bebek, Istanbul 34342 Turkey.
Somatosens Mot Res. 2005 Dec;22(4):239-53. doi: 10.1080/08990220500262075.
A computational model based on previous physiological and psychophysical data is presented for the human Pacinian (P) psychophysical channel. The model can predict the probability of detection in simple psychophysical tasks, and hence psychometric functions and thresholds. The model simulates stimulating variable and fixed glabrous skin sites with different-sized contactors and includes spatial variation of monkey P-fiber sensitivities. Therefore, it is especially suitable for studying spatial summation, i.e. the improvement of threshold with increasing contactor area. Selective contributions of neural integration (n.i.) and probability summation (p.s.) are also incorporated into the model. Model predictions are compared to psychophysical results of Gescheider et al. (2005). The performance of the model regarding the effects of contactor size is very good. In addition to predicting approximately 3 dB improvement of thresholds when the contactor area is doubled, the model also reveals nonlinear contributions of p.s. and n.i. Furthermore, the model asserts that thresholds are largely governed by neural integration when small contactors are used. These and other findings discussed in the article show that the presented model is a helpful tool for formulating testable hypotheses. Although the model can also simulate some temporal summation effects, simulation results do not conform well to previous data on temporal response properties. Thus, the model needs to be refined in that respect.
本文提出了一种基于先前生理和心理物理学数据的人类帕西尼(P)心理物理通道计算模型。该模型可以预测简单心理物理任务中的检测概率,从而预测心理测量函数和阈值。该模型模拟了用不同尺寸的接触器刺激可变和固定的无毛皮肤部位,并包括猴子P纤维敏感性的空间变化。因此,它特别适合研究空间总和,即阈值随接触器面积增加而改善的情况。神经整合(n.i.)和概率总和(p.s.)的选择性贡献也被纳入模型。将模型预测结果与格施德等人(2005年)的心理物理结果进行了比较。该模型在接触器尺寸影响方面表现非常出色。除了预测当接触器面积加倍时阈值大约提高3 dB外,该模型还揭示了p.s.和n.i.的非线性贡献。此外,该模型断言,当使用小接触器时,阈值在很大程度上受神经整合支配。本文讨论的这些及其他发现表明,所提出的模型是制定可测试假设的有用工具。虽然该模型也可以模拟一些时间总和效应,但模拟结果与先前关于时间响应特性的数据不太相符。因此,该模型在这方面需要改进。