Ensemble representations are often described as efficient tools when summarizing features of multiple similar objects as a group. However, it can sometimes be more useful not to compute a single summary description for all of the objects if they are substantially different, for example when they belong to entirely different categories. It was proposed that the visual system can efficiently use the distributional information of ensembles to decide whether simultaneously displayed items belong to single or several different categories. Here we directly tested how the feature distribution of items in a visual array affects an ability to discriminate individual items (Experiment 1) and sets (Experiments 2–3) when participants were instructed explicitly to categorize individual objects based on the median of size distribution. We varied the width (narrow or fat) as well as the shape (smooth or two-peaked) of distributions in order to manipulate the ease of ensemble extraction from the items. We found that observers unintentionally relied on the grand mean as a natural categorical boundary and that their categorization accuracy increased as a function of the size differences among individual items and a function of their separation from the grand mean. For ensembles drawn from two-peaked size distributions, participants showed better categorization performance. They were more accurate at judging within-category ensemble properties in other dimensions (centroid and orientation) and less biased by superset statistics. This finding corroborates the idea that the two-peaked feature distributions support the “segmentability” of spatially intermixed sets of objects. Our results emphasize important roles of ensemble statistics (mean, range, distribution shape) in explicit visual categorization.
Binocular rivalry is a phenomenon of visual competition in which perception alternates between two monocular images. When two eye’s images only differ in luminance, observers may perceive shininess, a form of rivalry called binocular luster. Does dichoptic information guide attention in visual search? Wolfe and Franzel (1988) reported that rivalry could guide attention only weakly but that luster (shininess) “popped out”, producing very shallow reaction time (RT) × set size functions. In the present study, we have revisited the topic with new and improved stimuli. By using a checkerboard pattern in rivalry experiments, we found that search for rivalry can be more efficient (16msec/item) than standard, rivalrous grating (30 msec/item). The checkerboard may reduce distracting orientation signals that masked the salience of rivalry between simple orthogonal gratings. Lustrous stimuli did not pop-out when potential contrast and luminance artifacts were reduced. However, search efficiency was substantially improved when luster was added to the search target. Both rivalry and luster tasks can produce search asymmetries, as is characteristic of guiding features in search. These results suggest that interocular differences that produce rivalry or luster can guide attention but these effects are relatively weak and can be hidden by other features like luminance and orientation in visual search tasks.
Foraging tasks are increasingly used to investigate human visual attention as they may provide a more dynamic and multifaceted picture of attentional orienting than more traditionally used visual search tasks. A common way of assessing foraging performance involves measuring when foragers decide to move to a new “patch” with a higher yield. We assessed this using Anne Treisman’s famous feature versus conjunction manipulation in an iPad foraging task. We measured how well patch leaving accorded with the predictions of the marginal value theorem that describes how foragers may optimize their foraging by leaving a patch once the average yield within a patch drops below the average yield in the whole environment. Human foraging in our paradigm deviated from the predictions of such optimal foraging conceptions, and our participants kept on foraging within the same patch for longer than expected. Patch leaving and intertarget times differed surprisingly little between feature and conjunction foraging, especially in light of the dramatic differences typically seen between performance on feature and conjunction visual search tasks. Other aspects of foraging performance (run number and switch costs) differed strongly between feature and conjunction foraging, however. We conclude that human foraging is probably influenced by too many factors to be captured with a relatively simple mathematical model.
Anne Treisman’s Feature Integration Theory (FIT) is a landmark in cognitive psychology and vision research. While many have discussed how Treisman’s theory has fared since it was first proposed, it is less common to approach FIT from the other side in time: to examine what experimental findings, theoretical concepts, and ideas inspired it. The theory did not enter into a theoretical vacuum. Treisman’s ideas were inspired by a large literature on a number of topics within visual psychophysics, cognitive psychology, and visual neurophysiology. Several key ideas developed contemporaneously within these fields that inspired FIT, and the theory involved an attempt at integrating them. Our aim here was to highlight the conceptual problems, experimental findings, and theoretical positions that Treisman was responding to with her theory and that the theory was intended to explain. We review a large number of findings from the decades preceding the proposal of feature integration theory showing how the theory integrated many ideas that developed in parallel within neurophysiology, visual psychophysics, and cognitive psychology. Our conclusion is that FIT made sense of many preceding findings, integrating them in an elegant way within a single theoretical account.
People often miss them. This phenomenon, reveals the limits of visual awareness. Here, we will investigate the blindness of the patient. Traditional gazecontingent paradigms adapt the display in real time. We’ll compare you with a mouse-contingent paradigm for your mouse. 2) and untethered overt and covert attention (mousecontingent display; Experiment 1). In the case of a person who has been in a state of discomfort, it can lead to change blindness. The results of the show are processed. In addition, there is a need for further changes to the changing target. Finally, it’s possible to establish a direct connection. The results of the show are processed. In addition, there is a need for further changes to the changing target. Finally, it’s possible to establish a direct connection. The results of the show are processed. In addition, there is a need for further changes to the changing target. Finally, it’s possible to establish a direct connection.
People often miss salient events that occur right in front of them. This phenomenon, known as change blindness, reveals the limits of visual awareness. Here, we investigate the role of implicit processing in change blindness using an approach that allows partial dissociation of covert and overt attention. Traditional gaze-contingent paradigms adapt the display in real time according to current gaze position. We compare such a paradigm with a newly designed mouse-contingent paradigm where the visual display changes according to the real-time location of a user-controlled mouse cursor, effectively allowing comparison of change detection with mainly overt attention (gaze-contingent display; Experiment 2) and untethered overt and covert attention (mouse-contingent display; Experiment 1). We investigate implicit indices of target detection during change blindness in eye movement and behavioral data, and test whether affective devaluation of unnoticed targets may contribute to change blindness. The results show that unnoticed targets are processed implicitly, but that the processing is shallower than if the target is consciously detected. Additionally, the partial untethering of covert attention with the mouse-contingent display changes the pattern of search and leads to faster detection of the changing target. Finally, although it remains possible that the deployment of covert attention is linked to implicit processing, the results fall short of establishing a direct connection.
Ensemble statistics are often thought of as a reliable impression of numerous items despite limited capacities to consciously represent each individual. However, whether all items equally contribute to ensemble summaries (e.g., mean) and whether they might be affected by known limited-capacity processes, such as focused attention, is still debated. We addressed these questions via a recently described “amplification effect,” a systematic bias of perceived mean (e.g., average size) towards the more salient “tail” of a feature distribution (e.g., larger items). In our experiments, observers adjusted the mean orientation of sets of items varying in set size. We made some of the items more salient or less salient by changing their size. While the whole orientation distribution was fixed, the more salient subset could be shifted relative to the set mean or differ in range. We measured the bias away from the set mean and the standard deviation (SD) of errors, as it is known to reflect the physical range from which ensemble information is sampled. We found that bias and SD changes followed the shifts and range changes in salient subsets, providing evidence for amplification. However, these changes were weaker than those expected from sampling only salient items, suggesting that less salient items were also sampled. Importantly, the SD decreased as a function of set size, which is only possible if the number of sampled elements increased with set size. Overall, we conclude that orientation summary statistics are sampled from an entire ensemble and modulated by the amplification effect of attention.
It has been noted that it has been the case that it has been recognized as a paradigm. Krüger, MacInnes, and Hunt (2014) propose that it is possible to re-enterrant processing. In the case of experiments, we’ve been working on the asynchrony (CTOA) ranging from -300 to + 1000ms. An analysis of the reaction time has been shown in the analysis of the reaction time. . In the experiment, we’ve eliminated the need for restriction, and (b) the discrete, and (c) blocked discrete CTOAs. Results obtained in the continuous and binned conditions showed no facilitation but robust IOR. We found both early facilitation and IOR in the blocked condition. Overall, he received a suggestion of different underlying mechanisms. Second,
Humans are very good at remembering large numbers of scenes over substantial periods of time. How good are they at remembering changes to scenes? In this study, we tested scene memory and change detection two weeks after initial scene learning. In Experiments 1-3, scenes were learned incidentally during visual search for change. In Experiment 4, observers explicitly memorized scenes. At Test, after two weeks, observers were asked to discriminate old from new scenes, to recall a change that they had detected in the study phase, or to detect a newly introduced change in the memorization experiment. Next, they performed a change detection task, usually looking for the same change from the study period. Scene recognition memory was found to be similar in all experiments, regardless of study task. In Experiment 1, more difficult change detection produced better scene memory. Experiments 2 and 3 supported a ‘depth of processing’ account for the effects of initial search and change detection on incidental memory for scenes. Of most interest, change detection during the Test phase was faster than during the Study phase, even when the observer had no explicit memory of having found that change previously. This result was replicated in two of three change detection experiments. We conclude that scenes can be encoded incidentally as well as explicitly and that changes in those scenes can leave measurable traces even if they are not explicitly recalled.