Effects of spatial separation between stimuli in whole report from brief visual displays

Crowding and attention in a framework of neural network model

In this article, I present a framework that would accommodate the classic ideas of visual information processing together with more recent computational approaches. I used the current knowledge about visual crowding, capacity limitations, attention, and saliency to place these phenomena within a standard neural network model. I suggest some revisions to traditional mechanisms of attention and feature integration that are required to fit better into this framework. The results allow us to explain some apparent theoretical controversies in vision research, suggesting a rationale for the limited spatial extent of crowding, a role of saliency in crowding experiments, and several amendments to the feature integration theory. The scheme can be elaborated or modified by future research.

Critical resolution: A superior measure of crowding

Visual object recognition is essential for adaptive interactions with the environment. It is fundamentally limited by crowding, a breakdown of object recognition in clutter. The spatial extent over which crowding occurs is proportional to the eccentricity of the target object, but nevertheless varies substantially depending on various stimulus factors (e.g. viewing time, contrast). However, a lack of studies jointly manipulating such factors precludes predictions of crowding in more heterogeneous scenes, such as the majority of real life situations.

To establish how such co-occurring variations affect crowding, we manipulated combinations of 1) flanker contrast and backward masking, 2) flanker contrast and presentation duration, and 3) flanker preview and pop-out while measuring participants’ ability to correctly report the orientation of a target stimulus. In all three experiments, combining two manipulations consistently modulated the spatial extent of crowding in a way that could not be predicted from an additive combination. However, a simple transformation of the measurement scale completely abolished these interactions and all effects became additive. Precise quantitative predictions of the magnitude of crowding when combining multiple manipulations are thus possible when it is expressed in terms of what we label the ‘critical resolution’. Critical resolution is proportional to the inverse of the smallest flanker free area surrounding the target object necessary for its unimpaired identification. It offers a more parsimonious description of crowding than the traditionally used critical spacing and may thus constitute a measure of fundamental importance for understanding object recognition.

A new perspective on the perceptual selectivity of attention under load

The human attention system helps us cope with a complex environment by supporting the selective processing of information relevant to our current goals. Understanding the perceptual, cognitive, and neural mechanisms that mediate selective attention is a core issue in cognitive neuroscience. One prominent model of selective attention, known as load theory, offers an account of how task demands determine when information is selected and an account of the efficiency of the selection process. However, load theory has several critical weaknesses that suggest that it is time for a new perspective. Here we review the strengths and weaknesses of load theory and offer an alternative biologically plausible computational account that is based on the neural theory of visual attention. We argue that this new perspective provides a detailed computational account of how bottom-up and top-down information is integrated to provide efficient attentional selection and allocation of perceptual processing resources.

Don't words come easy? A psychophysical exploration of word superiority

Words are made of letters, and yet sometimes it is easier to identify a word than a single letter. This word superiority effect (WSE) has been observed when written stimuli are presented very briefly or degraded by visual noise. We compare performance with letters and words in three experiments, to explore the extents and limits of the WSE. Using a carefully controlled list of three letter words, we show that a WSE can be revealed in vocal reaction times even to undegraded stimuli. With a novel combination of psychophysics and mathematical modeling, we further show that the typical WSE is specifically reflected in perceptual processing speed: single words are simply processed faster than single letters. Intriguingly, when multiple stimuli are presented simultaneously, letters are perceived more easily than words, and this is reflected both in perceptual processing speed and visual short term memory (VSTM) capacity. So, even if single words come easy, there is a limit to the WSE.

Visual attention capacity parameters covary with hemifield alignment

The theory of visual attention (TVA; Bundesen, 1990. Psychological Review, 97(4), 523-547), allows one to measure distinct visual attention parameters, such as the temporal threshold for visual perception, visual processing capacity, and visual short-term memory (VSTM) capacity. It has long been assumed that visual processing capacity and VSTM capacity parameters are nearly constant from trial to trial. However, Dyrholm, Kyllingsbæk, Espeseth, and Bundesen (2011). Journal of Mathematical Psychology, 55(6), 416-429, found evidence of considerable trial-by-trial variability of VSTM capacity. Here we show that one cause of trial-by-trial variation is that some parameters depend on whether processing of relevant information occurs in only one hemifield or in both hemifields. Our results show that VSTM and visual processing capacities are higher when stimuli are distributed across the hemifields rather than located in the same hemifield. This corresponds to previous suggestions that parallel processing is more efficient across hemifields than within a single hemifield because both hemispheres are involved (e.g., Alvarez & Cavanagh, 2005. Psychological Science, 16(8), 637-643; Kraft et al., 2005. Cognitive Brain Research, 24(1), 453-463). We argue that the established view of a fixed visual attentional capacity must be relativized by taking hemifield distribution into account.