In our basic task, one or two streams of stimuli are rapidly presented. The target(s) to be reported are highlighted with cues that encircle them. On half of trials, participants are first queried about the left target, and in half they are first queried about the right target. This has no significant effect on the main result- a substantial disadvantage in reporting the right target, if the left target must also be reported.
My collaborators and I have started using a new behavioural technique to better understand attentional selection from a rapid stream of stimuli. We have applied this to gain insights into the effect of naps on learning (Cellini et al., in press), the nature of the attentional blink (Goodbourn et al., in preparation), and function in parietal patients.
Here I explain the technique in the context of our study of a particular attentional phenomenon called pseudoextinction (Goodbourn & Holcombe, 2015).
The technique dissociates time of sampling visual information from the nature of subsequent processing. Stimuli are presented rapidly in series (a “stream”), shown here with one stream of letters on the left and a second stream on the right.
On an unpredictable frame in the sequence, the stimuli on that frame are cued by two circles, which enclose the stimuli. The participants’ task is to report the cued stimuli, letters in this case.
Accuracy is much poorer for the cued stimulus on the right than for the cued stimulus on the left. But if only one of the streams is cued, accuracy is equally high whether the cue is on the left or the right. This deficit specific to two-target conditions is pseudoextinction. The deficit is unaffected by which stream the participant is asked to report first. It likely reflects a severe capacity limit.
a. Each response of the participant corresponds to a particular item in the stream (because all items are presented on each trial). The distribution of the positions of these items is usually centred around the time of the cue, denoted as zero. b. Mixture modelling fits the data with a combination of two distributions, the guessing distribution shown in light grey and a Gaussian, shown in dark grey. This fit yields the latency (mean) and temporal precision (standard deviation) of the Gaussian as well as the proportion of guessing trials.
Participants’ responses were coded in terms of the serial position of the corresponding item in the stream. For example, if a participant reports the letter ‘A’ for the left stream and it was presented not at the time of the cue but two frames later, that response is coded as +2. If their report corresponds to the item immediately preceding the cued stimulus, it is coded as -1, and a report of the cued item is coded as 0. Random guesses thus will contribute an approximately uniform distribution to the histogram of serial position errors . This is quantified by mixture modelling, which determines the relative proportion of guesses and cue-related reports that best fit the data. We model the cue-related responses as a Gaussian distribution. The mixture modeling procedure yields its latency (position of the peak of the distribution relative to the time of the cue) and precision (standard deviation). It also estimates the proportion of trials that participants guessed or misperceived the letter versus the complementary proportion, which we call efficacy, of trials that participants reported a letter from around the time of the cue.
In cuing experiments, researchers typically conceive of the appearance of the cue as triggering attention to begin sampling from the scene. However, we have consistently observed that the distribution is symmetric and centred near the time of the cue. This indicates that rather than the cue triggering the intake of information from the letter stream, the letters are taken into a buffer before the cue is even presented. If letters were not already in a buffer at the time of the cue, responses from the left (earlier) side of the distribution would be relatively uncommon, skewing the distribution towards later responses.
When two streams are presented, participants perform much better for the stream on the left (if the streams are in a horizontal configuration) or much better for the stream on the top (if the streams are vertically arrayed). If only one stream is presented, participants perform approximately equally in all four positions (data not shown).
The pseudoextinction phenomenon, a right-side deficit when both streams are cued, manifests both in raw accuracy and also in the accuracy-related parameter of the mixture modelling. This is the efficacy parameter – the proportion of trials captured by the cue-related Gaussian distribution. Whereas efficacy when only one stream is presented or cued is similar on both the left and the right of fixation, and above and below fixation (not shown), when two streams are presented one stream suffers. The right stream suffers in a horizontal arrangement and in a vertical arrangement the inferior stream suffers, consistent with preferred reading order.
The decrease in efficacy for the extinguished stream is not accompanied by a change in latency or standard deviation of the Gaussian distribution of cue-related responses. Moreover, the correlogram of the serial position error for the two streams reveals that the two streams are sampled independently, indicating that the items are buffered independently, without regard to reading order or which hemisphere they are processed by. Together these results suggest that items are always sampled from the stream in the same way, but a subsequent processing limitation results in pseudoextinction if two targets must be processed.
Related patterns of performance have arisen in previous literature, and typically have been attributed to a difference between the left and right hemisphere (e.g. Scalf, Banich, Kramer, Narechania, & Simon, 2007). That however cannot explain the superior/inferior difference, so researchers sometimes then appeal to a difference in dorsal vs. ventral cerebral functioning. We suspect it instead reflects attentional prioritisation of the left item for serial high-level processing, for tokenisation or memory consolidation.
Cellini, N., Goodbourn, P.T., McDevitt, E.A., Martini, P., Holcombe, A.O., & Mednick, S.C. (in press). A daytime nap reduces the attentional blink. Attention, Perception, & Psychophysics.
Goodbourn, P.T. & Holcombe, A.O. (2015). ‘Pseudoextinction’: Asymmetries in simultaneous attentional selection. Journal of Experimental Psychology: Human Perception and Performance, 41(2), 364–84.
Martini, P. (2013) “Sources of bias and uncertainty in a visual temporal individuation task.” Attention, Perception, & Psychophysics 75: 168-181.
Scalf, P. E., Banich, M. T., Kramer, A. F., Narechania, K., & Simon, C. D. (2007). Double take: parallel processing by the cerebral hemispheres reduces attentional blink. Journal of Experimental Psychology. Human Perception and Performance, 33(2), 298–329. doi:10.1037/0096-15188.8.131.528