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Grabbing Your Attention: The Impact of Finding a First Target in Multiple-Target SearchAdamo, Stephen Hunter January 2016 (has links)
<p>For over 50 years, the Satisfaction of Search effect, and more recently known as the Subsequent Search Miss (SSM) effect, has plagued the field of radiology. Defined as a decrease in additional target accuracy after detecting a prior target in a visual search, SSM errors are known to underlie both real-world search errors (e.g., a radiologist is more likely to miss a tumor if a different tumor was previously detected) and more simplified, lab-based search errors (e.g., an observer is more likely to miss a target ‘T’ if a different target ‘T’ was previously detected). Unfortunately, little was known about this phenomenon’s cognitive underpinnings and SSM errors have proven difficult to eliminate. However, more recently, experimental research has provided evidence for three different theories of SSM errors: the Satisfaction account, the Perceptual Set account, and the Resource Depletion account. A series of studies examined performance in a multiple-target visual search and aimed to provide support for the Resource Depletion account—a first target consumes cognitive resources leaving less available to process additional targets. </p><p>To assess a potential mechanism underlying SSM errors, eye movements were recorded in a multiple-target visual search and were used to explore whether a first target may result in an immediate decrease in second-target accuracy, which is known as an attentional blink. To determine whether other known attentional distractions amplified the effects of finding a first target has on second-target detection, distractors within the immediate vicinity of the targets (i.e., clutter) were measured and compared to accuracy for a second target. To better understand which characteristics of attention were impacted by detecting a first target, individual differences within four characteristics of attention were compared to second-target misses in a multiple-target visual search. </p><p>The results demonstrated that an attentional blink underlies SSM errors with a decrease in second-target accuracy from 135ms-405ms after detection or re-fixating a first target. The effects of clutter were exacerbated after finding a first target causing a greater decrease in second-target accuracy as clutter increased around a second-target. The attentional characteristics of modulation and vigilance were correlated with second- target misses and suggest that worse attentional modulation and vigilance are predictive of more second-target misses. Taken together, these result are used as the foundation to support a new theory of SSM errors, the Flux Capacitor theory. The Flux Capacitor theory predicts that once a target is found, it is maintained as an attentional template in working memory, which consumes attentional resources that could otherwise be used to detect additional targets. This theory not only proposes why attentional resources are consumed by a first target, but encompasses the research in support of all three SSM theories in an effort to establish a grand, unified theory of SSM errors.</p> / Dissertation
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Attentional Sub-Processes Involved with Emotional EatingDenke, Gregory 18 May 2018 (has links)
Emotional eating behavior is characterized by eating a large amount of calorie dense sweet and/or high fat foods in an attempt to control, cope with, or avoid negative emotions. Numerous factors are likely to contribute to emotional eating behavior, including attentional factors, such as rumination and avoidance coping. Rumination based emotional eating (attention focused on negative stimuli while mindlessly eating) is often utilized to improve mood while dwelling on problems. However, for those inclined to escape/avoid troublesome thoughts, another type of emotional-eating pattern may be used. By focusing attention on food, emotional eating is believed to distract individuals from negative emotions. However, along with avoiding distressing thoughts, a strong attentional focus on food may also lead to diminished attention resources and subsequently the missing of self-preserving thoughts (e.g. dietary restraint or satiety). While Denke & Lamm (2015) explored neural mechanisms underlying rumination based emotional eating, to the best of our knowledge, no one has investigated the neural correlates underlying avoidance based emotional eating. This study examined how attentional sub-processes contribute to emotional eating behavior among female participants in a task designed to explore escape type emotional-eating behavior. Dense-array EEG and a version of the canonical attentional blink task were used to ascertain the neural correlates underlying the attentional sub-processes and how attentional activation differs for emotional eaters vs. non-emotional eaters. Findings do not support the food fixation escape type emotional-eater hypothesis, but do indicate task validity.
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The Effect of Emotional Faces on the Attentional Blink in Younger and Older AdultsSklenar, Allison M. 01 July 2016 (has links)
The attentional blink occurs when detection of a second target (T2) is impaired when it occurs between 180 to 450 ms after the first target (T1) in a rapid serial visual presentation (RSVP). The attentional blink can be affected by relevant emotional stimuli, like emotional faces, such that an emotional T1 enhances the attentional blink, and an emotional T2 attenuates it. However, not all studies use the same type of face stimuli, and there is debate over whether schematic and photo-realistic faces are processed in the same way. Furthermore, the effect of emotion on the attentional blink should differ with age, given the tendency for younger adults to display a negativity bias and for older adults to display a positivity effect. Very little research has been conducted on the attentional blink with emotional stimuli in older adults. In fact, the effect of emotional faces, which are arguably more salient stimuli than other stimuli such as emotional words, on the attentional blink has not been investigated in older adults. Therefore, this study sought to examine the impact of emotional faces on the attentional blink in younger and older adults using photo-realistic faces with angry, happy, and neutral expressions as targets in a RSVP. Although older adults did perform worse overall, there were no age differences in the effect of emotion on the attentional blink. Angry faces, as well as happy faces to a limited extent, increased the attentional blink when they served as T1. Neither the angry or happy faces as T2 were able to attenuate the blink. Given that emotional faces affected the attentional blink at T1 but not at T2, it may be the case that the emotional expressions served to maintain attention, rather than to capture it. Future studies are necessary to test this idea, as well as to more directly test the differential effect of emotional photorealistic and schematic faces on the attentional blink.
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Attentional Blink: An Antecedent to Binge Eating BehaviorDenke, Gregory 18 December 2014 (has links)
This study examined how attentional sub-processes contribute to binge-eating. Dense-array EEG and a version of the canonical attentional blink task were used to ascertain the neural correlates underlying the attentional sub-processes that comprise the Posner model of attention (alerting, orienting, and executive control) and how attentional activation differs for binge-eaters vs. non-binge eaters. Furthermore, we examined a number of the event-related potentials (ERP), including P2 activation, which has been linked with orientating of attention, and N2 activation which has been linked with attentional conflict. We found decreased P2 activation for binge-eaters, in the negative condition, for incorrect target 2 (T2) detection trials. We also found more N2 activation for binge-eaters than non-binge eaters, in negative trials when T2 was not detected. This pattern of results suggest that binge-eaters showed deficiencies in allocating attention to stimuli that followed negative images; this attention deficiency may be a key factor for binge-eating behavior.
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Dėmesio mirksėjimo efektas: individualūs skirtumai / Attentional blink: individual differencesGulbinaitė, Rasa 23 June 2014 (has links)
Dėmesio mirksėjimo efektas – tai plačiai žinomas reiškinys dėmesio tyrimuose. Jis atspindi dėmesingo informacijos apdorojimo ribas, kadangi greitai (10 stimulų per sekundę dažniu) toje pačioje regos lauko vietoje pateikus stimulų seką dažniausiai žmonės nepastebi ir/ arba neatsimena antrojo reikšminio stimulo. Tai įvyksta tuo atveju, kai šis pasirodo 200-500 ms intervale nuo pirmojo reikšminio stimulo pateikimo. Neseniai Martens ir kolegos (2006) nustatė, jog kai kuriems žmonėms dėmesio mirksėjimo efektas nepasireiškia, jie buvo pavadinti „nemirksinčiais“. Manoma, kad individualius skirtumus lemia nevienodai efektyvus gebėjimas iš nereikšmingos informacijos srauto išsirinkti reikšmingą. Šiame darbe siekta patikrinti, ar individuali darbinės atminties talpa, tiriamojo emocinė būsena ir tiriamojo asmenybės bruožai turi įtakos dėmesio efekto išreikštumui. Naudojant parametrizuotą dėmesio mirksėjimo efekto analizės būdą, nustatyta, kad didesnė darbinės atminties talpa sąlygoja mažesnį dėmesio mirksėjimo efektą. Šie rezultatai patvirtina nuomonę, kad dėmesio mirksėjimo efektas yra darbinės atminties talpos ribotumo pasekmė. Taip pat nustatyta, kad tiriamojo emocinio sužadinamumo būsena yra susijusi su dėmesio mirksėjimo efekto stiprumu, o asmenybės bruožai – su trukme. / The attentional blink is a well-known phenomenon in the study of attention. It reflects the impaired ability to identify the second of two targets presented in a rapid serial visual presentation (RSVP) of events if it appears between 200 and 500 ms after the first target. Recently Martens et al. (2006) reported that about 5% of the population (referred to as “non-blinkers”) shows little or no attentional blink under conditions in which most people (“blinkers”) do show. It is proposed that aforementioned differences are determined by individual differences in efficiency of ignoring irrelevant information. Thus, the aims of this master’s thesis were to investigate the impact of working memory capacity, emotional state and personality traits on attentional blink effect. Using parameterized attentional blink analysis method, based on curve fitting, the negative correlation between the size of attentional blink and working memory capacity was revealed. These findings support the idea that individual processing limitations and working memory play a key role in attentional blink. Also it was demonstrated that emotional arousal has impact on the strength of attentional blink and personality traits have effect on the span of attentional blink.
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Supporting the link between the locus coeruleus – norepinephrine system, the P300, and the attentional blinkWarren, Christopher M. 27 August 2008 (has links)
This paper provides evidence to support the hypothesis that the locus coeruleus – norephinephrine (LC-NE) system is the neurophysiological basis of both the attentional blink (AB) and the event related potential (ERP) component known as the P300. The LC-NE system is thought to provide a brief burst of processing facilitation in response to motivationally salient events. The AB refers to decreased accuracy for reporting the second of two targets (T1 and T2) inserted into a rapid serial visual presentation (RSVP). The LC-NE account of the AB holds that the AB is the result of a refractory-like period in LC-NE activity. The LC-NE account of the P300 suggests the P300 is the electrophysiological manifestation of the activity of the LC-NE system. I support the three-way link between these different aspects of brain activity by predicting differences in the AB dependent on characteristics of the P300 in response to T1 (T1-P300).
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Supporting the link between the locus coeruleus – norepinephrine system, the P300, and the attentional blinkWarren, Christopher M. 27 August 2008 (has links)
This paper provides evidence to support the hypothesis that the locus coeruleus – norephinephrine (LC-NE) system is the neurophysiological basis of both the attentional blink (AB) and the event related potential (ERP) component known as the P300. The LC-NE system is thought to provide a brief burst of processing facilitation in response to motivationally salient events. The AB refers to decreased accuracy for reporting the second of two targets (T1 and T2) inserted into a rapid serial visual presentation (RSVP). The LC-NE account of the AB holds that the AB is the result of a refractory-like period in LC-NE activity. The LC-NE account of the P300 suggests the P300 is the electrophysiological manifestation of the activity of the LC-NE system. I support the three-way link between these different aspects of brain activity by predicting differences in the AB dependent on characteristics of the P300 in response to T1 (T1-P300).
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An Empirical Assessment of the Magician's "Off-beat"January 2013 (has links)
abstract: Magicians are informal cognitive scientists who regularly test their hypotheses in the real world. As such, they can provide scientists with novel hypotheses for formal psychological research as well as a real-world context in which to study them. One domain where magic can directly inform science is the deployment of attention in time and across modalities. Both magicians and scientists have an incomplete understanding of how attention operates in time, rather than in space. However, magicians have highlighted a set of variables that can create moments of visual attentional suppression, which they call "off-beats," and these variables can speak to modern models of temporal attention. The current research examines two of these variables under conditions ranging from artificial laboratory tasks to the (almost) natural viewing of magic tricks. Across three experiments, I show that the detection of subtle dot probes in a noisy visual display and pieces of sleight of hand in magic tricks can be influenced by the seemingly irrelevant rhythmic qualities of auditory stimuli (cross-modal attentional entrainment) and processes of working memory updating (akin to the attentional blink). / Dissertation/Thesis / Ph.D. Psychology 2013
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A Case for Missing Salience in the Attentional BlinkJanuary 2019 (has links)
abstract: A literature search revealed that previous research on the Attentional Blink (AB) has not examined the role of salience in AB results. I examined how salience affects the AB through multiple forms and degrees of salience in target 1 (T1) and target 2 (T2) stimuli. When examining increased size as a form of salience, results showed a more salient T2 increased recall, attenuating the AB. A more salient T1 did not differ from the control, suggesting the salience (increased size) of T2 is an important factor in the AB, while salience (increased size) of T1 does not affect the AB. Additionally, the differences in target size (50% or 100% larger) were not significantly different, showing size differences at these intervals do not affect AB results. To further explore the lack of difference in results when T1 is larger in size, I examined dynamic stimuli used as T1. T1 stimuli were presented as looming or receding. When T1 was presented as looming or receding, the AB was attenuated (T2 recall at lag 2 was significantly greater). Additionally, T2 recall was significantly worse at lags three and four (showing a larger decrease directly following the attenuated AB). When comparing looming and receding against each other, at lag 2 (when recall accuracy at its lowest) looming increased recall significantly more than receding stimuli. This is expected to be due to the immediate attentional needs related to looming stimuli. Overall, the results showed T2 salience in the form of size significantly increases recall accuracy while T1 size salience does not affect the AB results. With that, dynamic T1 stimuli increase recall accuracy at early lags (lag 2) while it decreases recall accuracy at later lags (lags 3 and 4). This result is found when the stimuli are presented at a larger size (stimuli appearing closer), suggesting the more eminent need for attention results in greater effects on the AB. / Dissertation/Thesis / Doctoral Dissertation Human Systems Engineering 2019
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Spatial and temporal processing biases in visual working memory in specific anxietyReinecke, Andrea 12 April 2007 (has links) (PDF)
BACKGROUND.One group of theories aiming at providing a framework explaining the etiology, maintenance and phenomenology of anxiety disorders is classified as cognitive models of anxiety. These approaches assume that distortions in specific levels of information processing are relevant for the onset and maintenance of the disorder. A detailed knowledge about the nature of these distortions would have important implications for the therapy of anxiety, as the implementation of confrontative or cognitive elements precisely fitting the distortions might enhance efficacy. Still, these models and related empirical evidence provide conflicting assumptions about the nature of disorder-linked processing distortions. Many cognitive models of anxiety (e.g., Fox, Russo, &amp; Dutton, 2002; Mathews &amp; Mackintosh, 1998; Williams, Watts, MacLeod, &amp; Mathews, 1997) postulate that anxiety-linked biases of attention imply hypervigilance to threat and distractibility from other stimuli in the presence of feared materials. This is convincingly confirmed by various experimentalclinical studies assessing attention for threat in anxious participants compared to non-anxious controls (for a review, seeMathews &amp;MacLeod, 2005). In contrast, assumptions concerning anxiety-linked biased memory for threat are less convincing; based on the shared tendency for avoidance of deeper elaboration in anxiety disorders, some models predict memory biases only for implicit memory tasks (Williams et al., 1997) or even disclaim the relevance of memory in anxiety at all (e.g., Mogg, Bradley, Miles, &amp; Dixon, 2004). Other theories restrict the possibility of measuring disorder-specific memory biases to tasks that require merely perceptual encoding of the materials instead of verbal-conceptual memory (e.g., Fox et al., 2002; Mathews &amp;Mackintosh, 1998). On the one hand, none of these models has integrated all the inconsistencies in empirical data on the topic. On the other hand, the numerous empirical studies on memory in anxiety that have been conducted with varying materials, anxiety disorders, encoding and retrieval conditions do not allow final conclusions about the prerequisites for finding memory biases (for a review, see MacLeod &amp; Mathews, 2004). A more detailed investigation of the complete spectrum of memory for threat utilizing carefully controlled variations of depth of encoding and materials is needed. In view of these inconsistencies, it is all the more surprising that one important part of this spectrum has so far remained completely uninvestigated: visual working memory (VWM). No study has ever differentially addressed VWM for threat in anxious vs. nonanxious participants and none of the cognitive models of anxiety provides any predictions concerning this stage of information processing. Research on cognitive biases in anxiety has thus far only addressed the two extremes of the processing continuum: attention and longer-term memory. In between, a gap remains, the bridging of which might bring us closer to defining the prerequisites of memory biases in anxiety. As empirical research has provided substantial and coherent knowledge concerning attention in anxiety, and as attention and VWM are so closely linked (see, for instance, Cowan, 1995), the thorough investigation of VWM may provide important clues for models of anxiety. Is anxiety related to VWM biases favoring the processing of threatening information, or does the avoidance presumed by cognitive models of anxiety already begin at this stage? RESEARCH AIMS. To investigate the relevance of biased VWM in anxiety, the present research focused in eight experiments on the following main research questions: (1) Is threat preferably stored in VWM in anxious individuals? (2) Does threat preference occur at the cost of the storage of other items, or is extra storage capacity provided? (3) Would the appearance of threat interrupt ongoing encoding of non-threatening items? (4) Does prioritized encoding of threat in anxiety occur strategically or automatically? (5) Are disorder-specific VWM biases also materials-specific? (6) Are VWM biases in anxiety modifiable through cognitive-behavioral therapy? METHODS. In Experiments 1-4, a spatial-sequential cueing paradigm was used. A subset of real-object display items was successively cued on each trial by a sudden change of the picture background for 150 ms each. After the cueing, one of the display pictures was hidden and probed for a memory test. On most trials, a cued item was tested, and memory accuracy was determined depending on the item’s position within the cue string and depending on its valence. In some cases, memory for an uncued item was tested. Experiment 1 and 2 were directed at discovering whether spider fearfuls and non-anxious controls would differ with respect to the accuracy in memorizing cued spiders and uncued spiders and, thus, reveal disorder-specific biases of VWM. In addition, the question whether the presence of a spider image is related to costs for the memorization of other images was tested. Experiment 3 addressed whether any disorder-specific VWM biases found earlier were specific to the feared spiders. Therefore, the critical stimuli here were a snake and a spider. Participants were spider fearfuls and non-anxious controls, both without snake anxiety. In Experiment 4, it was tested whether disorder-specific biases found in Experiment 1 and 2 were modifiable through cognitive-behavioral treatment. The critical stimulus was a spider image. Spider fearfuls were tested three times. Half of them received a cognitive-behavioral intervention after the first test, the other half only after the second test. In two additional experiments, VWM was assessed with a change-detection paradigm. The main aim was to clarify whether disorder-specific effects found in the previous experiments were associated with automatic or with strategic selective encoding of threatening materials, and whether any group differences in spider change detection were materials-specific to spiders, but not to snakes. In Experiment 5, several images were presented simultaneously in a study display for either 100 or 500 milliseconds. After a short interruption, a test display was presented including either the same items as the first one or one changed item. Participants’ accuracy in determining whether displays were the same or different was measured depending on the valence of the changed item, set size, and presentation time of the display. There were trials with and without spiders. If a change was made, it could involve either a non-spider or a spider item. Of specific interest was the condition in which a spider image was presented initially, but not in the test phase, as noticing this specific change would require storage of that image in VWM. Would group differences be particularly pronounced in the shorter encoding condition suggesting automatic encoding of threat, or would they occur in the longer encoding condition, suggesting strategic encoding of spiders? In Experiment 6, change detection accuracy for spiders vs. snakes was tested. The participants in both experiments were spider fearfuls vs. controls, but those of Experiment 6 were additionally required to lack snake anxiety. Moreover, a temporal VWM paradigm - an attentional blink task - was applied to assess whether a biased encoding of spider images in spider fearfuls would occur at the expense of non-threatening items undergoing concurrent processing, and whether this effect was specific to spiders, but not to snakes. Series of real-object pictures were presented at rates of 80 ms at the display center. The observer’s task was to identify and report the two target pictures indicated by a brighter background. In Experiment 7, the first target always depicted a neutral item. The valence of the second target was varied - either negative depicting a spider, positive, or neutral. Participants varied with respect to their spider anxiety. In Experiment 8, spider fearfuls and non-anxious controls, both without snake anxiety, were tested. The experiment was nearly the same as the previous one, but two negative target types were tested: disorder-relevant spiders and negative but not feared snakes. Of specific interest was whether the appearance of a threatening target would reduce the report probability of the earlier attended target, indicating the interruption of its VWM encoding in favor of the threat item. RESULTS. (1) Both anxious and non-anxious controls, showed VWM advantages for negative materials such as spider or snake images. (2) In addition, there were disorderspecific VWM biases: some effects were larger in spider fearfuls than in non-anxious controls and some effects occurred exclusively in spider fearfuls. (3) Group differences and, thus, disorder-specificity were particularly pronounced under competitive circumstances, that is, under the condition of numerous stimuli competing for processing resources: when only little orientation time was allowed, when only little time was provided for selecting and encoding items from a crowd, and when VWMfor the critical item required reflexive instead of voluntary attention. (4) Pronounced memory for task-relevant, voluntarily attended spiders was related to difficulties in disengaging attention from these items in the fearful group, reflected in reduced memory accuracy for the item following it. (5) Disorder-specific VWM biases seem to be based on attentional biases to threatening materials resulting in a very quick, automatic memory consolidation. However, this preferential encoding was not at the cost of neutral materials currently undergoing encoding processes. (6) All disorder-specific VWM biases occured only with fear-related materials, not with other negative materials. (7) Automatic and highly disorder-specific fear-related VWM biases – but not strategic VWM biases occuring in both groups - were modifiable through cognitive-behavioral intervention. CONCLUSIONS. This work provides additional information about informationprocessing distortions related to specific anxiety. With the experimental investigation of biased VWM, this work has been performed to fill a gap within research on cognitive biases in anxiety. Moreover, this dissertation contributes to cognitive theories of anxiety by proposing several recommendations for refinements of current theoretical approaches. Most important, it was suggested to extend existing models by a more detailed consideration of attention and memory. In view of numerous previous empirical studies on the topic and the conclusions of this dissertation, a differentiation of the attentional engagement and disengagement component appears inevitable. Even more important, in view of the data presented here predictions concerning VWM for threatening materials need to be taken into account. In addition, suggestions are provided for the differential consideration of biases occuring from prepotent threat value of negative stimuli vs. individual threat value. A proposal for a cognitive model of anxiety extended by all these aspects is provided to serve as an invitation of further research in the investigation of the nature of memory biases in anxiety disorders. REFERENCES: Cowan, N. (1995). Attention and Memory. An integrated framework.New York: Oxford University Press. Fox, E., Russo, R., &amp; Dutton, K. (2002). Attentional bias for threat: Evidence for delayed disengagement from emotional faces. Cognition and Emotion, 16, 355-379. MacLeod, C., &amp; Mathews, A. (2004). Selective memory effects in anxiety disorders: An overview of research findings and their implications. In D. Reisberg &amp; P. Hertel (eds.), Memory and Emotion. Oxford: Oxford University Press. Mathews, A., &amp; Mackintosh, B. (1998). A cognitive model of selective processing in anxiety. Cognitive Therapy and Research, 22 (6), 539-560. Mathews, A., &amp; MacLeod, C. (2005). Cognitive vulnerability to emotional disorders. Annual Review of Clinical Psychology, 1, 167-195.Mathews, Mogg, May, &amp; Eysenck (1989). Mogg, K., Bradley, B.P., Miles, F., &amp; Dixon, R. (2004). Time course of attentional bias for threat scenes: Testing the vigilance avoidance hypothesis. Cognition and Emotion, 18(5), 689-700. Williams, J.M.G., Watts, F.N., MacLeod, C., &amp; Mathews, A. (1997). Cognitive psychology and emotional disorders. Chichester: John Wiley.
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