Statistical learning in visual search reflects distractor rarity, not only attentional suppression

Post-loss speeding or post-win slowing? An empirical note on the interpretation of decision-making time as a function of previous outcome

Differences in response time following previous losses relative to previous wins are robust observations in behavioural science, often attributed to an increased (or decreased) degree of cognitive control exerted after negative feedback, hence, post-loss slowing (or post-loss speeding). This presumes that the locus of this effect resides in the specific modulation of decision time following negative outcomes. Across two experiments, I demonstrate how the use of absolute rather than relative processing speeds, and the sensitivity of processing speeds in response to specific experimental manipulations (Experiment 1: win rate, Experiment 2: feedback), provide clarity as to the relative weighting of post-win and post-loss states in determining these behavioural effects. Both experiments show that the speeding or slowing of decision-time is largely due to the flexibility generated by post-win cognitive states. Given that post-loss speeding may actually represent post-win slowing, conclusions regarding the modulation of decision-making time as a function of previous outcomes need to be more carefully considered.

Habituation to visual onsets is affected by local and global distractors rate

Recent findings demonstrate that habituation of capture is stronger where onset distractors are frequent and weaker where they are rare, thus showing that habituation to onsets has a spatial selective nature. However, a debated question is whether habituation at a specific location is exclusively determined by the distractors' local rate, or whether instead local habituation is also affected by the global rate of the distractors, which may occur also at other locations. Here, we report the results from a between-participants experiment involving three groups of participants exposed to visual onsets during a visual search task. In two groups, onsets appeared at a single location with a high 60% rate or a low 15% rate, respectively, whereas in a third group, distractors could appear in four distinct locations with the same 15% local rate, leading to a 60% global rate. Our results confirmed that locally, habituation of capture was stronger the higher the distractors rate. However, the key finding was that we found a clear and robust modulation of the global distractors rate on the local habituation level. Taken together, our results unambiguously show that habituation has both a spatially selective and a spatially nonselective nature.

Statistical learning of target location and distractor location rely on different mechanisms during visual search

More studies have demonstrated that people have the capacity to learn and make use of environmental regularities. This capacity is known as statistical learning (SL). Despite rich empirical findings, it is not clear how the two forms of SL (SL of target location and SL of distractor location) influence visual search and whether they rely on the shared cognitive mechanism. In Experiment 1 and Experiment 2, we manipulated the probability of target location and the probability of distractor location, respectively. The results suggest that attentional guidance (they referred to overt attention) may mainly contribute to the SL effect of the target location and the distractor location, which is in line with the notion of priority mapping. To a small extent, facilitation of response selection may also contribute to the SL effect of the target location but does not contribute to the SL effect of the distractor location. However, the main difference between the two kinds of SL occurred in the early stage (it involved covert attention). Together, our findings indicate that the two forms of SL reflect partly shared and partly independent cognitive mechanisms.

Target templates and the time course of distractor location learning

When searching for a shape target, colour distractors typically capture our attention. Capture is smaller when observers search for a fixed target that allows for a feature-specific target template compared to a varying shape singleton target. Capture is also reduced when observers learn to predict the likely distractor location. We investigated how the precision of the target template modulates distractor location learning in an additional singleton search task. As observers are less prone to capture with a feature-specific target, we assumed that distractor location learning is less beneficial and therefore less pronounced than with a mixed-feature target. Hierarchical Bayesian parameter estimation was used to fit fine-grained distractor location learning curves. A model-based analysis of the time course of distractor location learning revealed an effect on the asymptotic performance level: when searching for a fixed-feature target, the asymptotic distractor cost indicated smaller distractor interference than with a mixed-feature target. Although interference was reduced for distractors at the high-probability location in both tasks, asymptotic distractor suppression was less pronounced with fixed-feature compared to mixed-feature targets. We conclude that with a more precise target template less distractor location learning is required, likely because the distractor dimension is down-weighted and its salience signal reduced.

Biased Competition between Targets and Distractors Reduces Attentional Suppression: Evidence from the Positivity Posterior Contralateral and Distractor Positivity

The biased competition account claims that competition between two stimuli increases when they are close together compared with when they are far apart. The reason is that nearby stimuli are more likely to be represented in the same receptive fields, requiring top-down or bottom-up biases to resolve the ambiguity. Consistent with biased competition, previous research showed that an index of attentional enhancement, the N2pc component, was attenuated when two targets were close together. In contrast, it is unclear whether distractor processing would also be attenuated when the distractor is close to the target. To answer this question, we used the additional singleton paradigm where a target is sometimes accompanied by a more salient, but entirely irrelevant, distractor. In the conditions of interest, the distance between the target and the distractor was systematically manipulated whereas the eccentricity to central fixation was always the same. The results showed that two indices of attentional suppression, the positivity posterior contralateral and distractor positivity components, were attenuated when the distractor was close to the target. Consistent with biased competition, attentional suppression of distractors was inhibited when the distance between target and distractor was short. The reduced attentional suppression of distractors with nearby targets may contribute to the increased behavioral interference with close distractors.