frequency, natural image Humans can recognize the gist of a novel image in a single glance, independent of its complexity. How is this remarkable feat accomplished? Based on behavioral and computational evidence, this paper describes a formal approach to the representation and the mechanism of scene gist understanding, based on scene-centered, rather than objectcentered primitives. We show that the structure of a scene image can be estimated by the mean of global image features, providing a statistical summary of the spatial layout properties (Spatial Envelope representation) of the scene. Global features are based on configurations of spatial scales and are estimated without invoking segmentation or grouping operations. The scene-centered approach is not an alternative to local image analysis but would serve as a feed-forward and parallel pathway of visual processing, able to quickly constrain local feature analysis and enhance object recognition in cluttered natural scenes. 1

Spatial attention: Visual selection and deployment over space The attentional spotlight and spatial cueing Attentional shifts, splits, and resolution Object-based Selection The visual search paradigm Top-down and bottom-up control of attention Inhibitory mechanisms of attention Invalid cueing Negative priming Inhibition of return Temporal attention: Visual selection and deployment over time Single target search Attentional blink and attentional dwell time Repetition blindness NEURAL MECHANISMS OF SELECTION Single-cell physiological method Event-related potentials Functional imaging: PET and fMRI

Efficient categorizations of complex visual stimuli require effective encodings of their distinctive properties. However, the question remains of how processes of object and scene categorization use the information associated with different perceptual spatial scales. The psychophysics of scale perception suggests that recognition uses coarse blobs before fine scale edges, because the former is perceptually available before the latter. Although possible, this perceptually determined scenario neglects the nature of the task the recognition system must solve. If different spatial scales transmit different information about the input, an identical scene might be flexibly encoded and perceived at the scale that optimizes information for the considered task—i.e., the diagnostic scale. This paper tests the hypothesis that scale diagnosticity can determine scale selection for recognition. Experiment 1 tested whether coarse and fine spatial scales were both available at the onset of scene categorization. The second experiment tested that the selection of one scale could change depending on the diagnostic information present at this scale. The third and fourth experiments investigated whether scalespecific cues were independently processed, or whether they perceptually cooperated in the recognition of the input scene. Results suggest that a mandatory low-level registration of multiple spatial scales promotes flexible scene encodings, perceptions, and categorizations.

This article opens by noting that positive emotions do not fit existing models of emotions. Consequently, a new model is advanced to describe the form and function of a subset of positive emotions, including joy, interest, contentment, and love. This new model posits that these positive emotions serve to broaden an individual's momentary thought-action repertoire, which in turn has the effect of building that individual's physical, intellectual, and social resources. Empirical evidence to support this broaden-and-build model of positive emotions is reviewed, and implications for emotion regulation and health promotion are discussed. Even though research on emotions has this new perspective are featured. My hope is flourished in recent years, investigations that that this article will unlock scientific curiosity expressly target positive emotions remain few about positive emotions, not only to test the and far between. Any review of the psychologi- ideas presented here, but also to build other new cal literature on emotions will show that models that might illuminate the nature and psychologists have typically favored negative value of positive emotions. Psychology sorely emotions in theory building and hypothesis needs more studies on positive emotions, not testing. In so doing, psychologists have inadver- simply to level the uneven knowledge bases tently marginalized the emotions, such as joy, between negative and positive emotions, but interest, contentment, and love, that share a more critically, to guide applications and pleasant subjective feel. To date, then, psycholo- interventions that might improve individual and gy's knowledge base regarding positive emo- collective functioning, psychological welltions is so thin that satisfying answers to the question "What good are positive emotions?" have yet to be articulated. This is unfortunate. being, and physical health. Experiences of positive emotion are central to Why Have Positive Emotions human nature and contribute richly to the quality of people's lives (Diener & Larsen, Been Marginalized? 1993; Myers & Diener, 1995). But how? In At this point, it might be useful to inspect

Elevated power increases the psychological distance one feels from others, and this distance, according to construal level theory (Y. Trope & N. Liberman, 2003), should lead to more abstract information processing. Thus, high power should be associated with more abstract thinking—focusing on primary aspects of stimuli and detecting patterns and structure to extract the gist, as well as categorizing stimuli at a higher level—relative to low power. In 6 experiments involving both conceptual and perceptual tasks, priming high power led to more abstract processing than did priming low power, even when this led to worse performance. Experiment 7 revealed that in line with past neuropsychological research on abstract thinking, priming high power also led to greater relative right-hemispheric activation.

ABSTRACT—The representation of visual information inside the focus of attention is more precise than the representation of information outside the focus of attention. We found that the visual system can compensate for the cost of withdrawing attention by pooling noisy local features and computing summary statistics. The location of an individual object is a local feature, whereas the center of mass of several objects (centroid) is a summary feature representing the mean object location. Three experiments showed that withdrawing attention degraded the representation of individual positions more than the representation of the centroid. It appears that information outside level that lacks local detail, but nevertheless carries a precise statistical summary of the scene. The term ensemble features refers to a broad class of statistical summary features that we propose collectively make up the representation of information outside the focus of attention. As people go about their daily lives, they seem to effortlessly manage the extremely rich and detailed stream of information entering their eyes. For the most part, people successfully navigate through busy intersections; find items of interest, such as food or friends; and understand complex social situations— all just by the simple act of looking. However, despite these many successes, there are also countless demonstrations that people fail to notice potentially important visual events, particularly when their attention is focused elsewhere. For example, traffic accidents often involve drivers ‘‘not seeing’ ’ clearly visible obstacles (e.g., McLay, Anderson, Sidaway, & Wilder, 1997). Such occurrences are typically interpreted as attentional

journal homepage: www.elsevier.com/locate/cogpsych Recognition of natural scenes from global properties:

We propose an object recognition model based on analogical mapping and transfer. The objective of our model is to be able to generate and bind structural representations; and to recognize objects from a small set of primitives. The input is mapped to the associative memory and activation is spread upwards. Anticipations are generated through local mappings and transferred to be tested serially in the order of their relevance. Due to these mechanisms, our model is able to simulate phenomena such as object priming and global precedence effect. Additionally, it provides a framework for integrating visual perception and other higher-order cognitive processes.

Suppose you see a red ball. Unless you happen to be in a psychologist’s lab, you are unlikely to see just the red ball against, say, a white background. Rather, a myriad of objects is simultaneously presented to you. For instance, you see the cricket bat beside the red ball, the table upon which they both lie, as well as what’s in the background of the table: the wall, the lamp, the bookshelf on the right, etc. Needless to say, you also see the shapes of these objects, together with the manifold of spatial relations connecting them. And for some of these objects at least, you see their particular shade$s " of colour; even the texture of their surface$s". Most of our visual experiences seem to be like that: we are typically presented with a wealth of objects, properties, and relations, etc. This owes partly to the fact that the visual scenes we encounter tend to be complex and ‘contain ’ many objects&in contrast to the psychologist’s lab. More importantly, though, each single experience has the propensity to convey a rich amount of information about the objects, properties, and relations, which make up such scenes&together with

People often get unnecessarily mired in trivial decisions. Four studies support a metacognitive account for this painful phenomenon. Our central premise is that people use subjective experiences of difficulty while making a decision as a cue to how much further time and effort to spend. People generally associate important decisions with difficulty. Consequently, if a decision feels unexpectedly difficult, due to even incidental reasons, people may draw the reverse inference that it is also important and consequently increase the amount of time and effort they expend. Ironically, this process is particularly likely for decisions that initially seemed unimportant because people expect them to be easier (whereas important decisions are expected to be difficult to begin with). Our studies demonstrate that unexpected difficulty not only causes people to get caught up in unimportant decisions but also to voluntarily seek more options, which can increase decision difficulty even further. People often find themselves mired in seemingly trivial decisions. We agonize over what toothbrush to buy,