The Time Constant of Attentional Control: Short, Medium and Long (Infinite?)

Statistical learning of target and distractor spatial probability shape a common attentional priority computation

Converging evidence recently put forward the notion that dedicated neurocognitive mechanisms do exist for the suppression of salient, but irrelevant distractors. Along this line, it is plausible to hypothesize that, in appropriate contexts, experience-dependent forms of attentional learning might selectively induce plastic changes within this dedicated circuitry, thus allowing an independent shaping of priorities at the service of attentional filtering. Conversely, previous work suggested that statistical learning (SL) of both target and distractor spatial probability distributions converge in adjusting only the overall attentional priority of locations: in fact, in the presence of an independent manipulation, either related to the target or to the distractor only, SL induces indirect effects (e.g., changes in filtering efficiency due to an uneven distribution of targets), suggesting that SL-induced plastic changes affect a shared neural substrate. Here we tested whether, when (conflicting) target- and distractor-related manipulations are concurrently applied to the very same locations, dedicated mechanisms might support the selective encoding of spatial priority in relation to the specific attentional operation involved. In three related experiments, human healthy participants discriminated the direction of a target arrow, while ignoring a salient distractor, if present; both target and distractor spatial probability distributions were concurrently manipulated in relation to each single location. Critically, the selection bias produced by the target-related SL was marginally reduced by an adverse distractor contingency, and the suppression bias generated by the distractor-related SL was erased, or even reversed, by an adverse target contingency. Our results suggest that even conflicting target- and distractor-related SL manipulations result in the adjustment of a unique spatial priority computation, likely because the process directly relies on direct plastic alterations of shared spatial priority map(s).

Integrated effects of top-down attention and statistical learning during visual search: An EEG study

The present study aims to investigate how the competition between visual elements is solved by top-down and/or statistical learning (SL) attentional control (AC) mechanisms when active together. We hypothesized that the "winner" element that will undergo further processing is selected either by one AC mechanism that prevails over the other, or by the joint activity of both mechanisms. To test these hypotheses, we conducted a visual search experiment that combined an endogenous cueing protocol (valid vs. neutral cue) and an imbalance of target frequency distribution across locations (high- vs. low-frequency location). The unique and combined effects of top-down control and SL mechanisms were measured on behaviour and amplitudes of three evoked-response potential (ERP) components (i.e., N2pc, P1, CNV) related to attentional processing. Our behavioural results showed better performance for validly cued targets and for targets in the high-frequency location. The two factors were found to interact, so that SL effects emerged only in the absence of top-down guidance. Whereas the CNV and P1 only displayed a main effect of cueing, for the N2pc we observed an interaction between cueing and SL, revealing a cueing effect for targets in the low-frequency condition, but not in the high-frequency condition. Thus, our data support the view that top-down control and SL work in a conjoint, integrated manner during target selection. In particular, SL mechanisms are reduced or even absent when a fully reliable top-down guidance of attention is at play.

Attention and platypuses

This perspective piece discusses a set of attentional phenomena that are not easily accommodated within current theories of attentional selection. We call these phenomena attentional platypuses, as they allude to an observation that within biological taxonomies the platypus does not fit into either mammal or bird categories. Similarly, attentional phenomena that do not fit neatly within current attentional models suggest that current models are in need of a revision. We list a few instances of the "attentional platypuses" and then offer a new approach, that we term dynamically weighted prioritization, stipulating that multiple factors impinge onto the attentional priority map, each with a corresponding weight. The interaction between factors and their corresponding weights determines the current state of the priority map which subsequently constrains/guides attentional allocation. We propose that this new approach should be considered as a supplement to existing models of attention, especially those that emphasize categorical organizations. This article is categorized under: Psychology > Attention Psychology > Perception and Psychophysics Neuroscience > Cognition.

An egocentric straight-ahead bias in primate's vision

As we plan to reach or manipulate objects, we generally orient our body so as to face them. Other objects occupying the same portion of space will likely represent potential obstacles for the intended action. Thus, either as targets or as obstacles, the objects located straight in front of us are often endowed with a special behavioral status. Here, we review a set of recent electrophysiological, imaging and behavioral studies bringing converging evidence that the objects which lie straight-ahead are subject to privileged visual processing. More precisely, these works collectively demonstrate that when gaze steers central vision away from the straight-ahead direction, the latter is still prioritized in peripheral vision. Straight-ahead objects evoke (1) stronger neuronal responses in macaque peripheral V1 neurons, (2) stronger EEG and fMRI activations across the human visual cortex and (3) faster reactive hand and eye movements. Here, we discuss the functional implications and underlying mechanisms behind this phenomenon. Notably, we propose that it can be considered as a new type of visuospatial attentional mechanism, distinct from the previously documented classes of endogenous and exogenous attention.

Goal-driven, stimulus-driven, and history-driven selection

In this paper, I present a framework which considers three independent factors that drive attentional selection. In addition to goal-driven and stimulus-driven selection, I discuss how lingering biases of selection history play a major role in attentional selection. Visual statistical learning of the regularities in the environment forms the basis for this history-based selection which provides an elaborate and flexible attentional biasing mechanism above and beyond goal-driven and stimulus-driven factors. A selection based on experience and history is fast, automatic and occurs without much, if any, effort. I conclude that learning and extracting the distributional properties of the environment have a major impact on attentional selection.

Visual Selection: Usually Fast and Automatic; Seldom Slow and Volitional; A Reply to Commentaries

In this reply I react to the commentaries of my colleagues to my review article "Visual Selection: Usually Fast and Automatic; Seldom Slow and Volitional" (Theeuwes, 2018). I have organized the reply into separate sections and discuss issues that were commonly raised.