Detecting unidentified changes

Abstract

Does becoming aware of a change to a purely visual stimulus necessarily cause the observer to be able to identify or localise the change or can change detection occur in the absence of identification or localisation? Several theories of visual awareness stress that we are aware of more than just the few objects to which we attend. In particular, it is clear that to some extent we are also aware of the global properties of the scene, such as the mean luminance or the distribution of spatial frequencies. It follows that we may be able to detect a change to a visual scene by detecting a change to one or more of these global properties. However, detecting a change to global property may not supply us with enough information to accurately identify or localise which object in the scene has been changed. Thus, it may be possible to reliably detect the occurrence of changes without being able to identify or localise what has changed. Previous attempts to show that this can occur with natural images have produced mixed results. Here we use a novel analysis technique to provide additional evidence that changes can be detected in natural images without also being identified or localised. It is likely that this occurs by the observers monitoring the global properties of the scene.

Figure 1. An example trial from the first experiment.

Two portraits of the same individual were shown separated by a blank interval. The observer was first asked if a change occurred and, if they indicated that one had, they were then asked to indicate which change had occurred from a list of nine possible changes. The subject of the photograph has given written informed consent, as outlined in the PLOS consent form, to publication of their photograph.

Figure 2. The number of only-sense trials, out of a total of 100 trials where a change occurred, corrected for possible observer response bias.

Error bars represent the standard error of the mean.

Figure 3. The results for individual observers for Experiment 1.

The x-axis shows the maximum number of only-sense trials that could be attributed to observer bias (i.e. a guessing strategy) and the y-axis shows the number of only-sense trials that were actually measured. Data points above the dotted line constitute evidence that observers could detect changes that they could not identify.

Figure 4. The results for individual observers for Experiment 2 using the same format as Figure 3.

Figure 5. The results for individual observers for Experiment 3 using the same format as Figure 3.

Figure 6. The results for individual observers for Experiment 4 using the same format as Figure 3.