Modelling visual detection: Luminance response non-linearity and internal noise

Two experiments that investigate the effect of various display factors on the detectability of a thin line signal in random visual noise are described. Three statistical decision models are described, together with their ability to account for the results. The first is an “ideal detector” model, the second an “energy integrator” model, and the third a model based upon the operation of retinal ganglion cells which incorporates a gain control mechanism. The ideal detector model fails to give a good account of human performance, whereas the other two models provide a good fit to the data. The digital Laplacian with gain control model has the slight advantage over the energy integrating model in being able to account for a small superiority in the detection of dark as opposed to bright signals. Finally, both models require the inclusion of an estimate of the internal noise of the human visual system to account for the pattern of performance observed under changing conditions of display contrast.     

Orienting to guilty knowledge

The Guilty Knowledge Test (GKT; Lykken, 1959) assesses whether suspects conceal information about a crime ( “guilty knowledge”). Previous studies have demonstrated larger physiological reactions to guilty knowledge compared to unknown information. In three experiments, we investigated whether guilty knowledge also demands attention. During an alleged polygraph examination, participants were presented with to‐be‐detected pictures ( “guilty knowledge”), nonsignificant, familiar pictures ( “mere knowledge”), and previously unseen pictures ( “neutral information”) for 250 ms in a modified dot probe task. In all three experiments, probe responses were slower on guilty knowledge trials as compared to the neutral trials. Results are discussed in terms of an information‐processing view on orienting to guilty knowledge.