Understanding visual attention with RAGNAROC: A Reflexive Attention Gradient through Neural AttRactOr Competition

Abstract

A quintessential challenge for any perceptual system is the need to focus on task-relevant information without being blindsided by unexpected, yet important information. The human visual system incorporates several solutions to this challenge, one of which is a reflexive covert attention system that is rapidly responsive to both the physical salience and the task-relevance of new information. This paper presents a model that simulates behavioral and neural correlates of reflexive attention as the product of brief neural attractor states that are formed across the visual hierarchy when attention is engaged. Such attractors emerge from an attentional gradient distributed over a population of topographically organized neurons and serve to focus processing at one or more locations in the visual field, while inhibiting the processing of lower priority information. The model moves towards a resolution of key debates about the nature of reflexive attention, such as whether it is parallel or serial, and whether suppression effects are distributed in a spatial surround, or selectively at the location of distractors. Most importantly, the model develops a framework for understanding the neural mechanisms of visual attention as a spatiotopic decision process within a hierarchy and links them to observable correlates such as accuracy, reaction time, and the N2pc and PD components of the EEG. This last contribution is the most crucial for repairing the disconnect that exists between our understanding of behavioral and neural correlates of attention.

Spatially Guided Distractor Suppression during Visual Search

“…The color contrast was strong for the distractor singletons, such that they were likely more salient than the shape-defined target singletons. Thus, stronger initial capture by the distractor falls in line with the notion that salient stimuli capture attention automatically and may receive priority over less salient, yet task-relevant items (Theeuwes, 2010; see also Wyble et al, 2020). The spatial selectivity for distractor positions was transient, however, and later exceeded by the spatial selectivity of targets (from ;280 ms on, only targets were attended), in line with the idea that attentional capture is followed by rapid disengagement (Belopolsky et al, 2010) as well as with the idea that topdown attention deployment eventually overrides attentional capture and thus supports encoding of task-relevant information (Leber and Egeth, 2006).…”

“…Relevant features can be enhanced to facilitate target processing (Desimone and Duncan, 1995;Wolfe, 2007), while irrelevant features can be suppressed below baseline to reduce distraction (Gaspelin et al, 2015;Chang and Egeth, 2019;. Thus, recent models of visual attention implement enhancement and suppression as independent processes that resolve the competition of simultaneously presented stimuli for attentional resources (Liesefeld and Müller, 2019;Wyble et al, 2020).…”

A theoretical attempt to revive the serial/parallel-search dichotomy

“…The weighting is likely never "absolute" for one dimension, in order to ensure that unexpected but highly relevant signals generated in other dimensions can pass through and summon attention (see , and/or because stronger weighting might require more cognitive resources than the observer may be able or willing to expend (e.g., due to other cognitive demands of the task; see, e.g., Irons & Leber, 2018;Lavie, Hirst, de Fockert, & Viding, 2004). Once the weights are set, priority guidance is performed by a relatively autonomous (i.e., reflexive) system, which is why it subjectively feels rather passive and effortless (see Wyble et al, 2018).…”

Spatial and feature-based suppression in working memory

“…The present study adds the notion of a negative priority in WM to the notion of varying priority in WM. This is similar to the notion that stimuli can be represented with a negative weight on a priority map based on which attentional selection takes place (Failing et al, 2019;Ferrante et al, 2018;Gaspelin et al, 2015;Wyble et al, 2018).…”