Tuesday, June 4, 2019
Attentional Control and Working Memory
Attentional Control and Working MemoryAttentional ascendence and working keeping over top-down, bottom-up factorsComplicated activities entrust on tutelage to selectively focus on task-relevant stimuli patch over porting salient distractive stimuli. For instance, drivers need to able to attend to oncoming traffic while at the analogous time ignoring distracting stimuli such as eating, looking after children, or hearing the bell of a cellphone receive a message. Most models pertaining to the selectivity of direction suggest that our concern is biased to either stimulus-based factors (bottom-up selection) and/or goal-driven factors (top-down selection) (Theeuwes, 2010). Physically salient properties of objects that draw wariness involuntarily be bottom-up factors, in contrast, past knowledge, goals, and rising plans atomic number 18 top-down factors that automatically guide our attention (Katsuki Constantinidis, 2014). Attentional get wind fronters urinate continuousl y argued whether goal-driven factors or stimulus-based factors have a larger influence on attentional control. However, this assumes that attention control involves a dichotomous selection amidst stimulus-based factors and goal-driven factors. This is an assumption that is incorrect and does non consider attentional control research that exists beyond this dichotomic viewpoint (Vecera et al, 2014). ago theories of attention focusing on the biases between goal-driven (top-down) and physically salient stimuli (bottom-up) do not take into consideration findings that persist surfaceside of these factors, such as, the influence of bring with distractors on future search tasks. Attentional control, using working memory of distractor finger and strong biases, is a more effective posit than the dichotomic bias between goal-driven factors and physically salient factors.Although the dichotomy of bottom-up and top-down does not account for selection biases that argon not goal-related nor physically salient, it still provides a luxuriouslyly bankable theory of attentional control. The first optical sweep is completely driven by stimuli (Theeuwes, 2010). Theeuwes (2010) claims that the most physically salient spot drives attention during the first visual s plunder, it is not until later in time that visual selection is biased in a top-down manner. This top-down manner involves feedback influenceing and voluntary control based on willful plans and current goals. Theeuwes (1992) tack that when looking for a circle among diamonds of all the same color, the response time was a lot poky when one of the diamonds was red. Their study demonstrated that salience has an impact on visual attentional control. Goal driven selection matches targets that most fit the observers goal template. For example, when at the supermarket, if the goal is to buy a red apple, the observer will prioritize red items. Overall, the bottom-up and top-down model offers a much more simple appro ach to attention and is one that foundation be easily accepted due to its lack of complexity in reasoning. For instance, it is easy to comprehend that items that pop disclose are more likely to grab attention, as well as, current selection goals of the on looker. However, this theory suggests that irrelevant items are not learned and cannot be used in future search tasks.Both stimulus-based and goal-driven factors influence attentional control, however, researchers have recently started to notice the impact have it away has on the selective spirit of attention (Awh et al., 2012). For example, participants point out noticeable, color targets quickly if the target-color is repeated throughout subsequent trials (Maljkovic Nakayama, 1994). They found that even when observers have a strong stimulus-based bias towards the target, experience strengthens this bias. Accordingly, fix of pop out of targets in repeated trials demonstrates the ability of experience to change the efficiency and overall efficacy of attentional control (Lee, Mozer, Vecera, 2009). These findings further assert the idea that experience can influence attentional control, an idea that is not supported by bottom-up and top-down theories.In contrast to research through in favor of bottom-up, top-down posits, one memory system that falls in favor of experience and attentional control is priming of pop out (PoP). PoP occurs when individuals can point out a target faster if the essential feature of that target is constant in subsequent trials (Maljkovic Nakayama, 1994). In their study, they had their participants look for a colored diamond and had them identify if the diamond had a feature missing from either side. They found that PoP helped individuals and appendd their response times. Their findings suggest that by continually showing a targets defining features, it reinforces the selective bias towards that targets features. In a similar vein, Tulving and Schacter (1990) found that re beq uestation systems based on perception capture for perceptual priming to occur. These representation system process new info in short-term memory. This short-term memory hastens the processing of similar information in future tasks. Thus, when the visual information sweep frequently encounters similar items to process, these items are processed in a faster manner because short-term memory already has a memory trace of that item. Priming of pop out further demonstrates how learned experience with physically salient items realizes subsequent search tasks. It demonstrates that passive priming can provoke strong selection biases that have nothing to do with goal-driven selection. The bottom-up, top-down attentional control model does not consider these findings.Large amounts of research on attentional selection cannot be accounted for by the tendency to group attentional control in either top-down or bottom-up factors (Awh et al., 2012), for example, memory. there are two types of me mory that have different usages and first need to be distinguished. Visual working memory depictions are different from visual semipermanent memories (VLTM). Visual working memory depictions are held for a limited amount of time, while visual long-term depictions continue throughout time ( raft, 2008). The constant sustenance of information limits the length of time for which visual working memory (VWM) depictions are upheld in memory. Lastly, VWM can only hold three to four items at the same time, while VLTM depictions are not bounded to a specific amount of objects (Brady et al., 2008). Although VWM is important in memory, VWM, in regards to attentional control, is specifically important for building experience with distractor rejections, but, is not useful for future use. Visual long term memory (VLTM) uses information (information that is no longer relevant to the task) encoded in the past to guide attention (Fan Turk-Browne, 2016). In their first experiment, Fan and Turk-Br owne (2016) found that VLTM for the associated location of a target guided spatial attention during visual search for the target, even when this location was not relevant to the task. Their second experiment expanded on these findings by discovering that VLTM for the associated color of a target influenced attentional capture in a different task. Memories can guide attention toward associated features, even when these features were encoded incidentally and were never relevant to any task (Fan Turk-Browne, 2016). An items features are automatically retrieved from long-term memory based on environmental cues encoded into working memory. These working memory representations bias selection toward items perceived in the world that match with features in memory through reactivation. An example of this would be shop at a supermarket frequently gone to. When shopping at the local supermarket looking for your favorite cereal, for example, you are less likely to be distracted by other grocer y items because you know where youre going and do not have to scan the visual area as often as opposed to it beingness the first time at that specific store.Observers find targets more easily when knowledge is given beforehand concerning the physical features of the target, like location, identity, and color (Moher Egeth, 2012). This is a process known as visual cueing. Observers find targets more easily, when they are told beforehand, not to look at authorized irrelevant areas of the display areas that will not have any targets pop up. For example, an individual is more often than not to find their friend at a mall if told that their friend will be exhausting a bright yellow shirt. In the same manner, Woodman and Luck (2007) found that targets were located faster if distractor items that were in the color that had to be ignored were present versus the distractors not being there at all. They concluded that participants used a template for rejection wherein items that match any beforehand features that had to be ignored, could be avoided during search, thus, items possessing the feature that had to be ignored were quickly rejected, ultimately, minimizing the size of the search. Knowing what not to look for reduces the number of items needed to be scanned, inadvertently reducing the time it takes to search through items. further extending current research on the theory that individuals can use cues to bias attention away from salient distractors, individuals need experience with distractors before the distractors can in truth be ignored (Cunningham Egeth, 2016). Experience with irrelevant stimuli can improve search in tasks. Learning to ignore features can result in a benefit in search tasks because time spent learning about these features, that need to be ignored, enhances its ability to be used by individuals in future search tasks (Cunningham Egeth, 2016). Results from their experiment found that within the same task, observers only benefited from cu es that were consistent and not by cues that changed trial by trial. This demonstrates that cues can only be beneficial in search tasks if the cues are repeatedly shown developing a more concrete trace in long term memory in which participants can use. The mentioned studies ratify that memory is an important part of the attentional selection process. The concept of memory cannot be put into a category that is either stimulus-driven or goal-driven, but preferably makes its own valid case in the plethora of selection phenomena.Biased competition proposes that attentional control mechanisms occur when several neuronal axons land in the same receptive vicinity (Desimone Duncan, 1995). They found that when several stimuli fall into one receptive field, a neuron has multiple choices as to which of these stimuli it should respond to this is quite an changeful process. However, attentional mechanisms solve this uncertainty through two processes attention is biased towards matching targe t objects with templates held in VWM. And, attention is biased towards items that are physically salient. Objects that are held in VWM are preferred over objects that are not because cells that have the objects features show higher rates of activity (Miller Desimone, 1994). Features of items in the external world are represented by these cells held in VWM, thus, the higher the activation rate, the more probable these neurons are to reach supra-threshold and fire an action potential when an external item matches that of the item in working memory.In support of experience and attentional control, biased competition reveals that past experience directs learning towards novel characteristics in settings and plays an important subprogram forming the long-term memory system (Hutchinson et al., 2016). Frequent studies of attention have looked at task-related goals and its effect on memory encoding, but not much research has investigated the role of memory guiding itself during selection (Awh et al., 2012). According to Hutchinson et al. (2016), memory allows for the brain to differentiate between old information (information in which the individual has already encountered) and new information that will give the best representation of the surroundings. Thus, in circumstances that involve both the presence of old and new information, old information will bushel how new information is processed and interpreted. Biased competition further supports that experience has an effect on what enters the memory system, which then, subsequently affects the attentional systems use of templates in the prioritization of certain items.Cases that cannot be explained by the traditional dichotomy of attentional control can be further expanded by reward control. Although attentional selection can be voluntary, in the case of goal-driven tasks, subsequent selection can be provoked be rewards. Hickey et al. (2010) had participants look for a diamond shape while also ignoring irrelevant c olor stimuli at the same time. Participants were given a low or a high monetary reward depending on whether they answered right. The researchers found that rewards could bias attentional selection to either the target or to the irrelevant stimuli trial after trial. For instance, if the target color stayed the same on subsequent trials, participants had a fast response time after given a high monetary reward. However, when the distractor had the same color as the previous target, reaction times were wordy after given a high monetary reward. This study suggests that monetary reward influenced attention towards the color that was given the high reward, irrespective of whether the color was associated with the distractor or the target. Several studies have shown that attentional selection is biased towards monetary reward. These findings cannot be explained by the voluntary, top-down or the physically salient, bottom-up attentional control dichotomy. fiscal reward further demonstrates that the dichotomic posit of attentional control is one that is incomplete and that monetary reward only expands on the present findings related to selection phenomena. Rewards are one of the strong biases that have a significant influence on selective processes.When encountering physically noticeable distractors, the experiences built on these distractors allows individuals to focus in future search tasks. This finding reveals that experience with physically noticeable distractors, and not only target templates held in working memory, benefits the high functionality of attentional control. Like further posits of attentional controls dependence on experience, learning to reject irrelevant stimuli depends on visual long term memory. This is an acceptable finding to grasp because long term memory possesses the ability to direct attention to target items in the present and later on, and, away from distractors. This finding further validates that attentional control cannot be explained by strictly using the dichotomy of goal-driven and physically-salient-driven efforts. Rather, attentional control is an active process founded on creating experience with specific objects. Consequently, attentional control is a skill that is increasingly alter as we gain experience out in the world. By not having much experience, the skills used in controlling attention is rather basic and depends on the simple use of the physical noticeability of object features. However, as individuals experience increases with certain tasks, the skills involved in attentional control sharpens and focuses on specific features. erst our attention is focused on a specific set of features, top-down control of attention can operate more efficiently. The importance of attentional control can be further seen in everyday life, especially in the realm of mental health. Several findings have found that there is a high correlation between those who prolong with mental illnesses and levels of attentiona l control. individualists who have Alzheimers disease, for example, have trouble maintaining goal-directedness (Coubard, et al., 2011). They found that Alzheimers disease affects the ability of switching attention, suppressing, and preparing attention for random events. Further, individuals who suffer from schizophrenia and attention deficit hyperactivity perturb (ADHD) have a fast response time in tasks when levels of anxiety and depression are lessened (Sarter and Paolone, 2011). randy processing is an important of valet interaction and communication. Low attentional control would hinder the ability to shift attention away from potentially threating information which would increase ones susceptibility of developing harmful psychological effects (Fergus et al., 2012). Post-traumatic stress disorder (posttraumatic stress disorder) is another mental illness that is also affected by attentional control. Individuals with PTSD and low attentional control show attentional avoidance ( Schoorl et al., 2014). Attentional avoidance is the concept of biasing attention away from threatening situations. These threatening situations serve as triggers that remind individuals with PTSD of the traumatic events they have experienced. This cognitive avoidance can be dysfunctional because individuals with PTSD do not face threatening stimuli toss on and avoid it, which, deprive them of the chance to realize that the traumatic event will not occur again (Schoorl et al., 2014). This was only the case when post-traumatic stress disorder symptoms were high and attention control levels were low.Works CitedAwh, E., Belopolsky, A. V., Theeuwes, J. (2012). Top-down versus bottom-up attentionalcontrol A failed theoretical dichotomy. Trends In cognitive Sciences, 16(8), 437-443. doi10.1016/j.tics.2012.06.010Brady, T.F., Konkle, T., Alvarez, G.A., Oliva, A. (2008). Visual long-term memory has amassive storage capacity for object details. Proceedings of the National Academy of Science s, 105(38), 14325-14329. doi 10.1073/pnas.0803390105Cunningham, C. A., Egeth, H. E. (2016). Taming the white bear Initial costs and eventual(prenominal)benefits of distractor prohibition. Psychological Science, 27(4), 476-485. doi10.1177/0956797615626564Coubard, O. A., Ferrufino, L., Boura, M., Gripon, A., Renaud, M., Bherer, L. (2011).Attentional control in normal aging and Alzheimers disease. Neuropsychology, 25(3), 353-367. doi10.1037/a0022058Desimone, R., Duncan, J. (1995). Neural mechanisms of selective visual attention. AnnualReviews of Neuroscience, 18(1), 193-222. doi 10.1146/annurev.ne.18.0030195.001205Fan, J. E., Turk-Browne, N. B. (2016). Incidental biasing of attention from visual long-termmemory. Journal Of Experimental Psychology Learning, Memory, And Cognition, 42(6), 970-977. doi10.1037/xlm0000209Fergus, T. A., Bardeen, J. R., Orcutt, H. K. (2012). Attentional control moderates therelationship between activation of the cognitive attentional syndrome and symptom s of psychopathology. Personality And Individual Differences, 53(3), 213-217. doi10.1016/j.paid.2012.03.017Hickey, C., Chelazzi, L., Theeuwes, J. (2010). Reward Changes Salience in Human Vision viathe Anterior Cingulate. Journal of Neuroscience, 30(33), 11096-11103. doi10.1523/jneurosci.1026-10.2010Hutchinson, J. B., Pak, S. S., Turk-Browne, N. B. (2016). Biased competition during long-term memory formation. Journal Of Cognitive Neuroscience, 28(1), 187-197. doi10.1162/jocn_a_00889Katsuki, F., Constantinidis, C. (2014). Bottom-up and top-down attention Different processesand overlapping neural systems. The Neuroscientist, 20(5), 509-521. doi10.1177/1073858413514136Lee, H., Mozer, M.C., Vecera, S.P. (2009). Mechanisms of priming of pop-out Storedrepresentations or feature-gain modulations? Attention, Perception, Psychophysics, 71(5), 1059-1071. doi 10.3758/APP.71.5.1059Luck, S.J. (2008). Visual short-term memory. In S.J. Luck A. Hollingworth (Eds.), VisualMemory (pp. 43-85). Ne w York Oxford University Press.Maljkovic, V., Nakayama, K. (1994). Priming of pop-out I. Role of features. Memory Cognition, 22(6), 657-72. doi 10.3758/BF03209251Miller, E.K., Desimone, R. (1994). Parallel neuronal mechanisms for short-term memory.Science, 263((5146), 520-522. doi 10.1126/science.8290960Moher, J., Egeth, H.E. (2012). The ignoring paradox Cueing distractor features leads first toselection, then to inhibition of to-be-ignored items. Attention, Perception, Psychophysics, 74(8), 1590-1605. doi 10.3758/s13414-012-0358-0Sarter, M., Paolone, G. (2011). Deficits in attentional control Cholinergic mechanisms andcircuitry-based treatment approaches. Behavioral Neuroscience, 125(6), 825-835. doi10.1037/a0026227Schoorl, M., Putman, P., Van Der Werff, S., Van Der Does, A. W. (2014). Attentional biasand attentional control in posttraumatic stress disorder. Journal Of Anxiety Disorders, 28(2), 203-210. doi10.1016/j.janxdis.2013.10.001Theeuwes, J. (1992). Perceptual selectivi ty for color and form. Perception Psychophysics, 51(6), 599-606. doi10.3758/BF03211656Theeuwes, J. (2010). Top-down and bottom-up control of visual selection. Acta Psychologica, 135(2), 77-99. doi10.1016/j.actpsy.2010.02.006Tulving, E., Schacter, D.L. (1990). Priming and human memory systems. Science, 247(4940),301-306. doi 10.1126/science.2296719Vecera, S. P., Cosman, J. D., Vatterott, D. B., Roper, Z. J. (2014). The control of visualattention Toward a unified account. In B. H. Ross, B. H. Ross (Eds.) , The psychology of learning and motivation, Vol. 60 (pp. 303-347). San Diego, CA, US Elsevier Academic Press.Vogel, E.K., Woodman, G.F., Luck, S.J. (2006). The time tune of consolidation in visualworking memory. Journal of Experimental Psychology Human Perception and Performance,32(6), 1436-1451. doi 10.1037/0096-1523.32.6.1436
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