Four experiments were conducted to investigate the role of stimulus-driven and goal-driven control in saccadic eye movements. Participants were required to make a speeded saccade toward a predefined target presented concurrently with multiple nontargets and possibly 1 distractor. Target and distractor were either equally salient (Experiments 1 and 2) or not (Experiments 3 and 4). The results uniformly demonstrated that fast eye movements were completely stimulus driven, whereas slower eye movements were goal driven. These results are in line with neither a bottom-up account nor a top-down notion of visual selection. Instead, they indicate that visual selection is the outcome of 2 independent processes, one stimulus driven and the other goal driven, operating in different time windows.

ABSTRACT-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.A salient object tends to attract attention and often initiates a subsequent eye movement. This finding has been replicated often and is well established (Itti & Koch, 2001;Theeuwes, Kramer, Hahn, & Irwin, 1998). It demonstrates that visual selection is very much influenced by the stimulus properties in the visual field. Current computational, functional, and neurophysiological models of visual selection account for stimulusdriven effects by assuming that the brain possesses a salience map, a topographical representation of the relative distinctiveness of all objects in the visual field

Magazine R219of the population (which is now an evolutionary response). Wouldn't that be a good way of studying evolution in action over a few generations?One would think so. In particular, it is possible to measure all three components of the breeder's equation, and see directly whether R = h 2 S. But, quite often, it appears that R does not equal h 2 S. For example, a study on antler size in red deer showed that red deer with larger antlers had more offspring than red deer with smaller antlers, and antler size has a high heritability. Yet no response to selection, R, could be detected. How is this possible? The problem is not in the measurement of h 2 or R, but in the measurement of S. In artificial selection, where individuals are selected by the experimenter on the basis of their value of the trait, it is the trait itself that determines reproduction, and any source of variation in the trait will affect which individuals are chosen. But, in studies of natural selection, all that is seen is a correlation between measured fitness and the trait. In this case, therefore, the trait itself does not necessarily cause the fitness differences. An environmental insult, such as disease, could simultaneously lower the trait value and also survivorship and/or reproduction, in other words, fitness. The consequence is that it is possible to have a trait-fitness correlation, arising from a purely environmental covariance, which creates the false impression of selection, without there being any correlation between fitness and the breeding value of the trait. What matters is the genetic correlation between fitness and the trait.Where can I find out more?

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Self-relevant information is prioritized in processing. Some have suggested the mechanism driving this advantage is akin to the automatic prioritization of physically salient stimuli in information processing (Humphreys & Sui, 2015). Here we investigate whether self-relevant information is prioritized for awareness under continuous flash suppression (CFS), as has been found for physical salience. Gabor patches with different orientations were first associated with the labels You or Other. Participants were more accurate in matching the self-relevant association, replicating previous findings of self-prioritization. However, breakthrough into awareness from CFS did not differ between self- and other-associated Gabors. These findings demonstrate that self-relevant information has no privileged access to awareness. Rather than modulating the initial visual processes that precede and lead to awareness, the advantage of self-relevant information may better be characterized as prioritization at later processing stages.

During early visual processing the eyes can be captured by salient visual information in the environment. Whether a salient stimulus captures the eyes in a purely automatic, bottom-up fashion or whether capture is contingent on task demands is still under debate. In the Wrst experiment, we manipulated the relevance of a salient onset distractor. The onset distractor could either be similar or dissimilar to the target. Error saccade latency distributions showed that early in time, oculomotor capture was driven purely bottom-up irrespective of distractor similarity. Later in time, top-down information became available resulting in contingent capture. In the second experiment, we manipulated the saliency information at the target location. A salient onset stimulus could be presented either at the target or at a non-target location. The latency distributions of error and correct saccades had a similar time-course as those observed in the Wrst experiment. Initially, the distributions overlapped but later in time task-relevant information decelerated the oculomotor system. The present Wndings reveal the interaction between bottom-up and topdown processes in oculomotor behavior. We conclude that the task relevance of a salient event is not crucial for capture of the eyes to occur. Moreover, task-relevant information may integrate with saliency information to initiate saccades, but only later in time.

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.Imagine yourself in the library looking for a specific book. You know the name of the author and the title, but you have no idea what the book looks like. Assume that on an average day, it takes you about 5 minutes, measured from the point in time you walk into the library, to find an average shaped and coloured book by title and author. It might take you only 1 minute when the book you are looking for happens to be bright red and very large. Many people believe that if a stimulus is sufficiently salient, it will pop out of a visual scene. In turn, they assume that search performance is better when the salient stimulus is the target of search, as compared to when a nonsalient item is the target of search.Most researchers in the area of visual selective attention assume that covert (attentional) selection and overt (oculomotor) selection are at least partly determined by stimulus salience, or more generally speaking by the stimulus properties in the visual field (Cave & Wolfe, 1990;Itti & Koch, 2000;Koch & Ullman, 1985; Theeuwes, 1991Theeuwes, , 1992Theeuwes, , 1994Wolfe, 1994;Wolfe, Cave, & Franzel, 1989). To incorporate this idea, recent models of visual selection have proposed that visual selection is determined by the output provided by some common salience map. Within a salience map, the location with the highest activation level corresponds to the most salient location at that point in time and

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