Kontsevich L L, Tyler C W
Smith-Kettlewell Eye Research Institute, San Francisco CA 94115, USA.
Vision Res. 1999 Aug;39(16):2729-37. doi: 10.1016/s0042-6989(98)00285-5.
We introduce a new Bayesian adaptive method for acquisition of both threshold and slope of the psychometric function. The method updates posterior probabilities in the two-dimensional parameter space of psychometric functions and makes predictions based on the expected mean threshold and slope values. On each trial it sets the stimulus intensity that maximizes the expected information to be gained by completion of that trial. The method was evaluated in computer simulations and in a psychophysical experiment using the two-alternative forced-choice (2AFC) paradigm. Threshold estimation within 2 dB (23%) precision requires less than 30 trials for a typical 2AFC detection task. To get the slope estimate with the same precision takes about 300 trials.
我们介绍了一种用于获取心理测量函数阈值和斜率的新型贝叶斯自适应方法。该方法在心理测量函数的二维参数空间中更新后验概率，并基于预期的平均阈值和斜率值进行预测。在每次试验中，它设定的刺激强度能使完成该试验所获得的预期信息最大化。该方法在计算机模拟以及使用二选一强制选择（2AFC）范式的心理物理学实验中进行了评估。对于典型的2AFC检测任务，在2 dB（23%）精度内进行阈值估计所需的试验次数少于30次。要以相同精度获得斜率估计则需要大约300次试验。
