- The evidence used by the observer to make the decision can be represented by a single continous number \(x\) (Gold & Shadlen, 2007; Green & Swets, 1966; J. A. Swets, 1961).
- Examples:
- Ouput of a neuron

- Examples:
\(x\) is a sample from a random variable \(X \in \mathcal{X}\) (Gold & Shadlen, 2007; Green & Swets, 1966).

The decision rule \(d \in \mathcal{D}\) to choose and action \(a \in \mathcal{A}\) is established by using a simple criterium on a decision variable \(W(x)\) (Gold & Shadlen, 2007; Green & Swets, 1966; Wickens, 2001).

\(W(x)=\Lambda(x)\) for simple hypothesis tests (Gold & Shadlen, 2007; Green & Swets, 1966; Kay, 1998; Wickens, 2001).

- No probalistic computation: the observer does not have access to the representation of uncertainty on a trial-by-trial basis (Ma, 2012).

Given an particular SDT model, the estimated parameters across tasks should be consistent (Green & Swets, 1966; Wickens, 2001).

- For example under the equal variance normal model, \(\widehat{d'}\) should be the same independently on whether the task is Yes-No, Rating or 2AFC.

Given an particular SDT model, the estimated parameters should be consistent across criteria (Green & Swets, 1966; Wickens, 2001).

- For example under the equal variance normal model, \(\widehat{d'}\) should be the same independently on \(p_{FA}\) (Green & Swets, 1966; Wickens, 2001) .

Gold, J. I., & Shadlen, M. N. (2007). The neural basis of decision making. *Annu. Rev. Neurosci.*, *30*, 535–574.

Green, D., & Swets, J. (1966). Signal detection theory and psychophysics. 1966. *New York*, *888*, 889.

Kay, S. M. (1998). Fundamentals of statistical signal processing, vol. ii: Detection theory. *Signal Processing. Upper Saddle River, NJ: Prentice Hall*.

Ma, W. J. (2012). Organizing probabilistic models of perception. *Trends in Cognitive Sciences*, *16*(10), 511–518.

Swets, J. A. (1961). Is there a sensory threshold. *Science*, *134*(3473), 168–177.

Wickens, T. D. (2001). *Elementary signal detection theory*. Oxford University Press.