Visual search can be seen as a decision-making process that aims to assess whether a target is present or absent from a scene. In this perspective, eye movements collect evidence related to target detection and verification to guide the decision. We investigated whether, in real-world scenes, target detection and verification are differentially recruited in the decision-making process in the presence of prior information (expectations about target location) and perceptual uncertainty (noise). We used a mouse-tracking methodology with which mouse trajectories unveil components of decision-making and eye-tracking measures reflect target detection and verification. Indoor scenes were presented, including a target in usual or unusual locations or no target, and were degraded with additive noise (or no noise). Participants had to respond to the target's presence or absence. Degrading the scene delayed the decision due to increased verification times and reduced mouse velocity. Targets in unusual locations delayed the decision and deviated mouse trajectories toward the target-absent response. Detection times played a major role in these effects. Thus, target detection and verification processes influence decision-making by integrating the available sources of information differently and lead to an accumulation of evidence toward both the presence of a target and its absence.

Detecting a pedestrian while driving in the fog is one situation where the prior expectation about the target presence is integrated with the noisy visual input. We focus on how these sources of information influence the oculomotor behavior and are integrated within an underlying decision-making process. The participants had to judge whether high-/low-density fog scenes displayed on a computer screen contained a pedestrian or a deer by executing a mouse movement toward the response button (mouse-tracking). A variable road sign was added on the scene to manipulate expectations about target identity. We then analyzed the timing and amplitude of the deviation of mouse trajectories toward the incorrect response and, using an eye tracker, the detection time (before fixating the target) and the identification time (fixations on the target). Results revealed that expectation of the correct target results in earlier decisions with less deviation toward the alternative response, this effect being partially explained by the facilitation of target identification.

By forcing selection into response execution processes, the present mouse-tracking study investigated whether the ongoing process of response selection in the colour-word Stroop task is influenced by conflict and facilitation at both the level of response and stimulus. Mouse-tracking measures including partial errors provided credible evidence that both response and semantic conflict (i.e., distinct constituents of interference) contribute to the overall Stroop interference effect even after a response has been initiated. This contribution was also observed for the overall facilitation effect (that was credibly decomposed into response and semantic components in response times but not in mouse deviation measures). These results run counter to the dominant single-stage response competition models that currently fail to explain: 1) the expression of Stroop effects in measures of response execution and; 2) the composite nature of both interference and facilitation. By showing that Stroop effects–originating from multiple levels of processing–can cascade into movement parameters, the present study revealed the potential overlap between selection and execution process. It therefore calls for further theoretical efforts to account for when, where and under what conditions Stroop effects originating from different loci are controlled.