Complex background information slows down parallel search efficiency by reducing the strength of interitem interactions.

In the laboratory, visual search is often studied using uniform backgrounds. This contrasts with search in daily life, where potential search items appear against more complex backgrounds. In the present study, we examined the effects of background complexity on a parallel visual search under conditions where objects are easily segregated from the background. Target-distractor similarity was sufficiently low such that search could unfold in parallel, as indexed by reaction times that increase logarithmically with set size. The results indicate that when backgrounds are relatively simple (sandy beach with water elements), search efficiency is comparable to search using a solid background. When backgrounds are more complex (child bedroom or checkerboard), logarithmic search slopes increase compared to search on solid backgrounds, especially at higher levels of target-distractor similarity. The results are discussed in terms of different theories of visual search. It is proposed that the complex visual information occurring in between distractors slows down individual distractor rejection times by weakening the strength of interitem interactions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Irrelevant features of distractors in intervening visual search tasks cause active visual working memory interference - the more difficult the search task, the more interference it causes.

Visual working memory (VWM) content disrupts visual search performance when there is a singleton in the search array that is similar to the content in VWM, even when this singleton is task irrelevant. Typically, the memory-similar singleton captures attention, which results in slower search performance for memory-similar conditions compared to conditions where memory-similar content is absent. Recently, it has also been shown that VWM content may be affected when memory-similar stimuli are processed. Specifically, it appears that VWM representations bias toward memory-similar information that is processed but not memory-dissimilar information. Here, we test whether the bias caused by processing memory-similar information is an active interference process (growing with engagement with the memory-similar stimuli) or a passive interference process (indifferent to the engagement with memory-similar stimuli). To test this, observers were tasked with memorizing a single color followed by a search task. The search task was either easy or difficult, and the search items could either be memory-similar or memory-dissimilar. Critically, the target in the search task was defined by its shape, so the color of the search items was irrelevant to the search task. At the end of each trial, participants reported the color in memory using a continuous report color wheel. The results showed that VWM representations drifted towards the irrelevant color of the search items in the memory-similar conditions, and this effect was larger in the difficult search condition. The results provide evidence that VWM representations receive active interference from processing memory-similar stimuli.

Correction to: A target contrast signal theory of parallel processing in goal-directed search.

During production of the article, Figure 4 was incorrectly used twice in the initial article, so it appeared both as Figure 4 and Figure 5 in the article.

A target contrast signal theory of parallel processing in goal-directed search.

Feature Integration Theory (FIT) set out the groundwork for much of the work in visual cognition since its publication. One of the most important legacies of this theory has been the emphasis on feature-specific processing. Nowadays, visual features are thought of as a sort of currency of visual attention (e.g., features can be attended, processing of attended features is enhanced), and attended features are thought to guide attention towards likely targets in a scene. Here we propose an alternative theory - the Target Contrast Signal Theory - based on the idea that when we search for a specific target, it is not the target-specific features that guide our attention towards the target; rather, what determines behavior is the result of an active comparison between the target template in mind and every element present in the scene. This comparison occurs in parallel and is aimed at rejecting from consideration items that peripheral vision can confidently reject as being non-targets. The speed at which each item is evaluated is determined by the overall contrast between that item and the target template. We present computational simulations to demonstrate the workings of the theory as well as eye-movement data that support core predictions of the theory. The theory is discussed in the context of FIT and other important theories of visual search.

Fixed-target efficient search has logarithmic efficiency with and without eye movements.

Stage 1 processing in visual search (e.g., efficient search) has long been thought to be unaffected by factors such as set size or lure-distractor similarity (or at least to be only minimally affected). Recent research from Buetti, Cronin, Madison, Wang, and Lleras (Journal of Experimental Psychology: General, 145, 672-707, 2016) showed that in efficient visual search with a fixed target, reaction times increase logarithmically as a function of set size and, further, that the slope of these logarithmic functions is modulated by target-distractor similarity. This has led to the proposal that the cognitive architecture of Stage 1 processing is parallel, of unlimited capacity, and exhaustive in nature. Such an architecture produces reaction time functions that increase logarithmically with set size (as opposed to being unaffected by it). However, in the previous studies, eye movements were not monitored. It is thus possible that the logarithmicity of the reaction time functions emerged simply as an artifact of eye movements rather than as a reflection of the underlying cognitive architecture. Here we ruled out the possibility that eye movements resulted in the observed logarithmic functions, by asking participants to keep their eyes at fixation while completing fixed-target efficient visual search tasks. The logarithmic RT functions still emerged even when participants were not allowed to make eye movements, thus providing further support for our proposal. Additionally, we found that search efficiency is slightly improved when eye movements are restricted and lure-target similarity is relatively high.

Salience network connectivity in the insula is associated with individual differences in interoceptive accuracy.

The insula and the anterior cingulate cortex are core brain regions that anchor the salience network, one of several large-scale intrinsic functional connectivity networks that have been derived consistently using resting-state functional magnetic resonance imaging (fMRI). While several studies have shown that the insula and anterior cingulate cortex play important roles in interoceptive awareness, no study to date has examined the association between intrinsic salience network connectivity and interoceptive awareness. In this study, we sought to test this idea in 26 healthy young participants who underwent a resting-state fMRI scan and a heartbeat counting task outside the scanner in the same session. Greater salience network connectivity in the posterior insula (but not the anterior cingulate cortex) using independent component analysis correlated with higher accuracy in the heartbeat counting task. Furthermore, using seed-based approach, greater interoceptive accuracy was associated with greater intrinsic connectivity of all insular functional subdivisions to salience network regions, including the anterior insula, orbitofrontal cortex, ventral striatum and midbrain. These associations remained after correcting for voxel-wise grey matter volumes. The findings underscore the critical role of insular salience network intrinsic connectivity in interoceptive awareness and pave the way for future investigations into how salience network dysconnectivity affects interoceptive awareness in brain disorders.