The Psychology of Learning and Motivation series publishes empirical and theoretical contributions in cognitive and experimental psychology, ranging from classical and instrumental conditioning to complex learning and problem solving. Volume 57 of the highly regarded Psychology of Learning and Motivation seriesAn essential reference for researchers and academics in cognitive scienceRelevant to both applied concerns and basic research.

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The Psychology of Learning and Motivation

Eye movements are now widely used to investigate cognitive processes during reading, scene perception, and visual search. In this article, research on the following topics is reviewed with respect to reading: (a) the perceptual span (or span of effective vision), (b) preview benefit, (c) eye movement control, and (d) models of eye movements. Related issues with respect to eye movements during scene perception and visual search are also reviewed. It is argued that research on eye movements during reading has been somewhat advanced over research on eye movements in scene perception and visual search and that some of the paradigms developed to study reading should be more widely adopted in the study of scene perception and visual search. Research dealing with "real-world" tasks and research utilizing the visual-world paradigm are also briefly discussed.

https://www.cogsci.ucsd.edu/~bkbergen/cogs200/Rayner-Bartlett.pdf

Eye movements and attention in reading, scene perception, and visual search.

The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this

Analyzing linguistic data: a practical introduction to statistics using R

Top–down and bottom–up control of visual selection

When natural scenes are viewed, a multitude of objects that are stable in their environments are brought in and out of view by eye movements. The posterior parietal cortex is crucial for the analysis of space, visual attention and movement 1 . Neurons in one of its subdivisions, the lateral intraparietal area (LIP), have visual responses to stimuli appearing abruptly at particular retinal locations (their receptive fields)2. We have tested the responses of LIP neurons to stimuli that entered their receptive field by saccades. Neurons had little or no response to stimuli brought into their receptive field by saccades, unless the stimuli were behaviourally significant. We established behavioural significance in two ways: either by making a stable stimulus task-relevant, or by taking advantage of the attentional attraction of an abruptly appearing stimulus. Our results show that under ordinary circumstances the entire visual world is only weakly represented in LIP. The visual representation in LIP is sparse, with only the most salient or behaviourally relevant objects being strongly represented.

The representation of visual salience in monkey parietal cortex

A salient event in the visual field tends to attract attention and the eyes. To account for the effects of salience on visual selection, models generally assume that the human visual system continuously holds information concerning the relative salience of objects in the visual field. Here we show that salience in fact drives vision only during the short time interval immediately following the onset of a visual scene. In a saccadic target-selection task, human performance in making an eye movement to the most salient element in a display was accurate when response latencies were short, but was at chance when response latencies were long. In a manual discrimination task, performance in making a judgment of salience was more accurate with brief than with long display durations. These results suggest that salience is represented in the visual system only briefly after a visual image enters the brain.

/pdf/effects-of-salience-are-short-lived-2jeh9zu9rx.pdf

Effects of salience are short-lived.

In a standard visual marking experiment, observers are presented with a display containing one set of elements (old elements) followed after a certain time interval by a second set of elements (new elements). The task of observers is to search for a target among the new elements. Typically, the time to find the target depends only on the number of new elements in the display and not on the number of old elements, showing that observers search only among the new elements. This effect of prioritizing new elements over old elements is explained in terms of top-down inhibition of old objects—that is, visual marking (Watson & Humphreys, 1997). The present study addressed whether this prioritizing is in fact mediated by top-down inhibition of old objects, as suggested by Watson and Humphreys (1997), or whether it is mediated by the abrupt onsets of the newly presented elements (Yantis & Jonides, 1984). In three experiments, the presentations of the old and new elements were or were not accompanied by a luminance change. The results showed that if new elements were equiluminant with the background, no visual marking occurred, suggesting that new elements must have a luminance onset in order to be prioritized over old elements. Implications for current theories on visual selection are discussed.

/pdf/visual-marking-beside-the-mark-prioritizing-selection-by-55uvsvaq3q.pdf

Visual marking beside the mark: Prioritizing selection by abrupt onsets

Two experiments were conducted to investigate the effects of saliency on saccadic target selection as a function of time. Participants were required to make a speeded saccade towards a target defined by a unique orientation presented concurrently with multiple nontargets and one distractor. Target and distractor were equally salient within the orientation dimension but varied in saliency in the colour dimension. Within the colour dimension, the target presented could be more, equally, or less salient than the distractor. The results showed that saliency played a large role early during processing while no effects of saliency were found in later processing. Results are discussed in terms of models on visual selection.

/pdf/the-effects-of-salience-on-saccadic-target-selection-2yqwjgzjay.pdf

The effects of salience on saccadic target selection.

Previous research suggests that the allocation of attention is largely controlled either in a stimulus-driven or in a goal-driven manner. To date, few studies have systematically manipulated variables affecting stimulus-driven and goal-driven selection independently in order to investigate how both manners of control interrelate and affect performance in visual search. In the present study observers were presented with search displays consisting of an array of line segments rotated at various orientations. The task of observers was to indicate the presence or absence of a vertical line segment (the target) presented amongst a series of nontargets and possibly one distractor. By varying the absolute differences in orientation between the target, nontargets, and distractors, relative target-distractor salience and target-distractor similarity were independently manipulated to investigate the contribution of stimulus-driven and goal-driven control. The major result was that relative target-distractor salience and target-distractor similarity affected search performance independently. Performance was better in cases where the irrelevant distractor was not a salient item in the search display and did not look similar to the target. The results are discussed in terms of models of attentional control.

/pdf/bottom-up-and-top-down-control-in-visual-search-2qhk2wqjgo.pdf

Bottom-up and top-down control in visual search.

Recent evidence indicates that stimulus-driven and goal-directed control of visual selection operate independently and in different time windows (van Zoest et al., 2004). The present study further investigates how eye movements are affected by stimulus-driven and goal-directed control. Observers were presented with search displays consisting of one target, multiple non-targets and one distractor element. The task of observers was to make a fast eye movement to a target immediately following the offset of a central fixation point, an event that either co-occurred with or soon followed the presentation of the search display. Distractor saliency and target-distractor similarity were independently manipulated. The results demonstrated that the effect of distractor saliency was transient and only present for the fastest eye movements, whereas the effect of target-distractor similarity was sustained and present in all but the fastest eye movements. The results support an independent timing account of visual selection.

/pdf/saccadic-target-selection-as-a-function-of-time-gcjeunu1l6.pdf

Saccadic target selection as a function of time.

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