Tailoring a psychophysical discrimination experiment upon assessment of the psychometric function: Predictions and results

Abstract

Decision making is a widespread research topic and plays a crucial role in neuroscience as well as in other research and application fields of, for example, biology, medicine and economics. The most basic implementation of decision making, namely binary discrimination, is successfully interpreted by means of signal detection theory (SDT), a statistical model that is deeply linked to physics. An additional, widespread tool to investigate discrimination ability is the psychometric function, which measures the probability of a given response as a function of the magnitude of a physical quantity underlying the stimulus. However, the link between psychometric functions and binary discrimination experiments is often neglected or misinterpreted. Aim of the present paper is to provide a detailed description of an experimental investigation on a prototypical discrimination task and to discuss the results in terms of SDT. To this purpose, we provide an outline of the theory and describe the implementation of two behavioural experiments in the visual modality: upon the assessment of the so-called psychometric function, we show how to tailor a binary discrimination experiment on performance and decisional bias, and to measure these quantities on a statistical base. Attention is devoted to the evaluation of uncertainties, an aspect which is also often overlooked in the scientific literature.

Statistical analysis of a Bayesian classifier based on the expression of miRNAs

“…In this equation, p T and p V correspond to the prior presentation probabilities of the target class and the versus class, respectively, whereas H and C respectively correspond to the sensitivity and the specificity of the classifier, provided that the condition positive is taken to correspond to the target class [ 19 ]. Under the assumption that the values of y are normally distributed, sensitivity and specificity are given by the following expressions: …”