Working memory is a cognitive system that retains and manipulates information, such as numbers and names, to facilitate planning, thinking, and comprehension (e.g., Baddeley, 2000). In this sense, working memory is both a store as well as a process to transform information.
Interestingly, with practice, working memory can be enhanced (e.g., Olesen, Westerberg, & Klingberg, 2004). This possibility is very encouraging, because working memory capacity predicts intelligence and may also curb impulsive behavior.
Working memory is a cognitive system that stores and manipulates information over limited periods of time, a concept originally formulated by Baddeley and Hitch (1974). According to recent updates, Baddeley (2002, 2007) proposes that working memory comprises four main systems:
Recent conceptualizations of the central executive have assumed this system comprises distinct processes, such as switching, inhibition, and updating (Baddeley, 2002). Switching involves shifting attention between tasks. Inhibition diverts attention from irrelevant information or stimuli. Updating supersedes information that is relevant to a task with more recent insights.
Each of these components of working memory is assumed to be limited in capacity (Baddeley, 2002). If individuals undertake a task that utilizes one component, other activities that demand the same component will, if performed simultaneously, be impaired.
Oberauer, Sub, Wilhelm, and Wittmann (2008) distinguished three cognitive functions that underpin working memory. The first function is called concurrent storage and processing-?a function that overlaps with the traditional definitions of working memory. In essence, this function enables individuals to maintain a series of items and then initiate some process on these items. To assess this function, a series of items is usually presented, such as words, numbers, or patterns. Then, participants must perform some function, such as report these items in the reverse order or report every second item. Often, while performing this task, they are distracted by a concurrent activity.
The second function is called relational integration. This function enables individuals to establish associations between items that, until then, were unrelated to each other, partly underpinned by the hippocampus. This function is vital to many tasks. To assess this function, participants may be exposed to a sequence of words, and they must press a button if these words rhyme. In one condition, only one word appears at a time. In another condition, all words appear concurrently, diminishing demands on storage capacity. Analogous tasks can be constructed with numbers or patterns.
The third function is called supervision and primarily relates to the capacity of individuals to decide which goals to pursue. Supervision, for example, prevents distraction from irrelevant stimuli and enables individuals to switch between tasks. Such regulation of goals is often subsumed under the concept of executive function rather than working memory.
Specific tasks are commonly assumed to utilize particular components of working memory. To illustrate:
Working memory capacity is positively associated with various indices of intellectual behavior, such as scholastic aptitude and fluid intelligence (for evidence, see Cowan, Fristoe, Elliott, Brunner, & Saults, 2006& Engle, 2002& Engle, Tuholski, Laughlin, & Conway, 1999). In particular, as Fukuda, Vogel, Mayr, and Awh (2010) showed, the number of representations or concepts that individuals can retain and transform in memory working simultaneously?-and not necessarily the resolution of these representations?-is highly associated with fluid intelligence.
Oberauer, Sub, Wilhelm, and Wittmann (2008) showed that relational integration relates to intelligence and reasoning ability, even after controlling storage capacity. Relational integration refers to the capacity of individuals to establish associations between items that, until then, were unrelated to each other. Some variants of this test do not demand the storage of items. For example, in one task, participants may be exposed to a sequence of words concurrently, and they must press a button if these words rhyme. Performance on this task does not relate to storage capacity, such as memory span tasks, but strongly relates to intelligence, especially reasoning ability. Furthermore, performance on this task is associated with intelligence after controlling storage capacity.
Whether training in working memory will enhance intelligence has been a contentious issue over many years. A review, conducted by Chooi and Thompson (2012), showed that training in working memory does not seem to enhance intelligence convincingly. Many studies have shown that training in working memory may improve performance on tasks that utilize similar processes, but even these improvements have been confined to adolescents or older people.
One exception was reported by Jaeggi, Buschkuehl, Jonides, and Perrig (2008). In their study, participants completed the N-back task. Practice on this task for 12 to 19 days enhanced intelligence, as gauged by a matrices task. Yet, Chooi and Thompson (2012) emphasized this study was not optimal. Which of the intelligence tests participants completed varied across conditions, for example. Once these limitations were eliminated, training on the N-back task did not subsequently improve intelligence. Neither 8 nor 20 days of training on this task enhanced performance on any intelligence tests or mental span tests.
Elevated levels of temporal discounting, in which individuals prefer immediate rewards over future rewards, might sometimes represent impairments in working memory. Specifically, when working memory is impaired, individuals may not be able to maintain their attention on hypothetical, but plausible, future consequences. Consistent with this proposition, if working memory is distracted by other considerations, temporal discounting is amplified (e.g., Hinson, Jameson, & Whitney, 2003& Hinson, Jameson, & Whitney, 2003& for some controversies about these principles, see Franco-Watkins, Rickard, & Pashler, 2010). Because only immediate needs are valued, impulsive behavior is likely to ensue.
Indeed, working memory has been shown to increase the capacity of people to inhibit their automatic impulses. In one pair of studies, conducted by Hoffman, Gschwendner, Friese, Wiers, and Schmitt (2008), participants completed a test of working memory capacity. Specifically, they needed to remember a set of answers to various mathematics equations. In addition, they completed an implicit association test to gauge the extent to which they experience a strong, automatic impulse to observe sexual images or eat unhealthy food. Finally, participants were later granted opportunities to observe sexual images or eat unhealthy food, unaware their behavior was being monitored.
Unsurprisingly, individuals who exhibited strong, automatic impulse to observe sexual images or eat unhealthy food were indeed more likely to engage in these acts later. Yet, if the capacity of working memory was extensive, this relationship between impulses and behaviour diminished. Arguably, as the capacity of working memory increases, people can more readily shield their conscious goals from these automatic tendencies.
Some impairments in working memory may amplify rumination and depression. That is, many people, especially if depressed, ruminate excessively over unpleasant events. They deliberate over the same negative experience, such as an error, repeatedly or excessively and cannot switch their attention to more pleasant events or concepts. This rumination is likely to amplify depression (e.g., Nolen-Hoeksema, Wisco, & Lyubomirsky, 2008).
As Joormann, Levens, and Gotlib (2011) argued, individuals who cannot readily transform information in working memory may be more inclined to ruminate excessively. That is, to inhibit rumination, individuals need to transform the contents of working memory. For example, if they remember an error, they need to shift their focus to the antecedents of this mistake and, potentially, how they could act differently in the future. They can, therefore, conceptualize this error as an opportunity to grow.
Joormann, Levens, and Gotlib (2011) undertook a study that confirms this possibility. In one study, participants completed a measure of depression and rumination. In addition, they completed a task that assesses their capacity to transform material in working memory. On each trial, three words appeared on a screen, like coffin funeral sad, in sequence. Next, the word forward or backward was presented. Finally, one of the three words appeared again, such as sad. Participants needed to press 1, 2, or 3 depending on whether this single word was the first, second, or third word of the previous sequence. However, if the word backwards had appeared, participants had to count backwards. In this example, for example, sad would correspond to 1 and coffin would correspond to 3.
In general, this task is more difficult on trials in which the participants needed to count backwards, because they needed to transform the order of these items in working memory. If the words revolved around negative concepts, but not neutral or positive concepts, individuals who reported elevated levels of depression experienced even more pronounced problems when counting backwards. This difficulty also correlated with levels of rumination in the depressed participants. Therefore, rumination and depression seems to be associated with difficulties in transforming negative concepts in working memory.
Emotions affect working memory, and working memory affects emotions. For example, positive emotions enhance verbal working memory, whereas negative emotions enhance spatial working memory (Gray, 2001, 2004). In addition, verbal working memory tends to elicit positive evaluations, and spatial working memory tends to elicit negative evaluations (Storbeck & Watson, 2015).
To illustrate, in a set of studies that were reported by Storbeck and Watson (2015), participants first completed a verbal memory task or a spatial memory task. Specifically, on each trial, a sequence of letters appeared, such as t, r, g, and r. The letters appeared at one of various locations. On some trials, participants needed to indicate whenever one letter was the same as another letter two items ago, and this task utilizes verbal working memory. On other trials, participants needed to indicate whenever one letter appeared in the same location as another letter two items ago, and this task utilizes spatial working memory.
Next, participants completed a task that was intended to assess whether they were biased towards positive or negative evaluations. For example, in one study, they were asked to indicate, as rapidly as possible, whether various pictures were positive or negative--30 of which were positive, 30 were negative, and 15 were neutral. If participants had completed a verbal rather than spatial memory task, they were more inclined to rate the pictures as positive. In a subsequent study, participants rated whether various words were positive or negative. Again, if participants had completed a verbal rather than spatial memory task, they were more inclined to rate the words as positive--and also reported more negative affect.
Presumably, over time, individuals discover that social interactions tend to coincide with both positive emotions and verbal operations. Consequently, positive emotions often coincide with verbal operations. So, while people feel positive, the cognitive apparatus that underpins verbal operations is primed. Likewise, when people engage in verbal operations, the positive emotions that are associated with these cognitions are primed as well.
In contrast, over time, individuals learn to associate the prospect of threats or problems with both negative emotions and the need to scan the environment--a spatial task. Accordingly, negative emotions often coincide with spatial processes. So, while people feel negative, the cognitive apparatus that underpins spatial processes is primed. Similarly, when people engage in spatial tasks, the negative emotions that are associated with these cognitions are primed as well.
If some of the processes that underpin working memory are impaired, the emotional regulation strategies that individuals utilize to improve their mood are not as effective. Strategies that are typically ineffective, such as rumination, become especially detrimental. Strategies that are typically effective, such as reappraisal, are not particularly helpful (Pe, Raes, Koval, Brans, Verduyn, & Kuppens, 2013).
This possibility was demonstrated by Pe, Raes, Koval, Brans, Verduyn, and Kuppens (2013). In this study, participants first undertook an activity called the affective interference resolution task. This task assesses the capacity of people to eradicate negative information from working memory. On each trial, a set of four words appeared& the words were positive, negative, or neutral in valence. Next, another word, called the probe, appeared. Participants needed to decide whether the probe had appeared in the previous set of four words. They pressed one button to indicate "Yes" and another button to indicate "No". On some trials, however, the probe word had appeared in a prior set of four words. The tendency of some participants to indicate "Yes" on these trials would imply they had not eradicated previous words effectively from working memory.
During the following week, 10 times a day, participants received a beep on a palmtop. In response, they needed to complete questions that gauge whether, during the previous period, they had engaged in rumination (ie "Have you ruminated since the last beep?") or reappraisal (e.g., "Have you viewed the cause of your feelings from a different perspective since the last beep") as well as the emotions they experienced.
Some of the participants demonstrated elevated levels of negative interference& that is, they could not easily eradicate negative words from working memory. Relative to the other participants, these individuals were especially likely to experience negative affect, such as anxiety, after ruminating. In addition, they were not as likely as other participants to experienced reduced levels of negative affect, or elevated levels of positive affect, after reappraisal. Accordingly, to reappraise events effectively, individuals need to be able to eradicate negative information from working memory efficiently. This account might explain why reappraisal may not be as effective in depressed patients.
As Houben, Wiers, and Jansen (2011) showed, deficiencies in working memory may amplify alcohol consumption. Specifically, some individuals experience a powerful urge to consume alcohol. That is, they strongly associate alcohol with pleasure. If working memory is intact, individuals can often maintain goals and plans that override these urges. In contrast, if working memory is impaired, individuals cannot maintain these goals and plans, and hence they yield to their temptations and consume excessive alcohol.
Houben, Wiers, and Jansen (2011) reported a study that substantiates this possibility. In brief, this study showed that protocols that are designed to enhance working memory tend to curb alcohol use, especially in participants who strongly associate alcohol with pleasure.
Specifically, in this study, the participants, all of whom drank heavily, completed three working memory tasks, over 28 distinct sessions. One of the tasks, for example, was a backward span task. Another task was a visuo-spatial activity. In particular, 16 squares, arranged in a grid that comprises 4 columns and 4 rows, were presented. A sequence of these squares would then change colors. The task of participants was to reproduce this sequence by clicking the mouse on the corresponding squares.
In the control group, these tasks were relatively simple. In the experimental group, these tasks became increasingly difficult whenever participants completed a sequence of two trials correctly. This protocol was designed to improve the working memory of participants.
In addition, participants completed an implicit association task, designed to assess the extent to which individuals associate alcohol with pleasant concepts. Finally, participants answered questions that assess the extent to which they consumed alcohol over the last week.
If participants were exposed to the protocol that was designed to improve working memory, their performance on these tasks gradually improved over time. Furthermore, after these 28 sessions, their consumption of alcohol diminished significantly. These improvements persisted even a month later. Furthermore, if participants strongly associated alcohol with pleasure, improvements in working memory were especially likely to reduce alcohol intake.
Some research indicates that working memory enables individuals to reappraise events more effectively, ultimately to contain negative emotions and foster positive emotions. That is, if working memory capacity is extensive, people can more readily change their perspective or perception of some event, such as a criticism from a manager, to curb anxiety, dejection, or similar feelings.
In particular, to reappraise events, individuals need to coordinate a set of processes. They may need to inhibit the dominant thoughts, such as "I am a failure". Concurrently, they need to construct other stories about the event, such as imagining themselves develop great skills. Indeed, they need to uncover thoughts that conflict with their negative emotions. Presumably, if working memory is deficient, people may not be able to perform this complex array of cognitive processes.
McRae, Jacobs, Ray, John, and Gross (2012) indeed confirmed that reappraisal ability is related to working memory. To gauge reappraisal ability, participants were exposed to a series of upsetting photographs. On some trials, these individuals were merely asked to look at these photos. On other trials, individuals were encouraged to engage in thoughts, and tell themselves something, that curbs negative emotions. After each trial, participants indicated the extent to which they feel positive and negative emotions. Reappraisal ability was measured by the degree to which participants experienced more pleasant emotions after reappraising the event relative to merely looking at the photo.
In addition, to gauge working memory, participants completed a series of simple mathematics equations. After each equation, either a neutral or negative word appeared. Participants were then asked to recall these words later.
As predicted, reappraisal ability was positively associated with working memory capacity--as gauged by the ability to recall both the neutral and negative words later. Reappraisal ability was also related to the tendency of individuals to reappraise in daily life as well as wellbeing. Finally, reappraisal ability was also related to difficulties in shifting from a focus on details to a focus on broad patterns, as gauged by another task& this finding might indicate that people who are more cautious, or become more engrossed in a particular sequence of thoughts, also reappraise events more effectively.
Moderate, rather than low, levels of dopamine seem to enhance performance on tasks that purportedly utilize working memory (Floresco & Phillips, 2001& Kimberg, D'Esposito, & Farah, 1997). Dopamine corresponds to the expectation of reward (see dopamine).
Consistent with the purported role of dopamine, energized and active emotions have been shown to enhance working memory (Ashby, Valentin, & Turken, 2002). That is, when individuals experience emotions like excitement or anger rather than dejection or contentment, performance on working memory tasks tends to improve.
When people walk, rather than sit, their performance on memory tasks actually improves. This possibility was demonstrated by Schaefer, Lovden, Wieckhorst, and Lindenberger (2010). In their study, participants were either nine years old or adults. Individuals completed the N-back working memory task in which a sequence of numbers was presented. Their task was to indicate when one item was the same as another item N numbers earlier, where N is a number that can range from 1 to 8. If participant were permitted to walk at a preferred speed, rather than sit or walk at a fixed speed on a treadmill, their performance on this task improved. Arguably, walking arouses or activates working memory.
Positive emotions, relative to neutral emotions, tend to enhance some functions of working memory. In particular, positive emotions, according to Yang, Yang, and Isen (2013), seem to enhance the executive or controlled processes of working memory but do not affect the capacity of individuals to store information passively.
Specifically, in one study, conducted by Yang, Yang, and Isen (2013), participants completed two key tasks. First, to measure storage or short term memory, they completed a word span task. Participants received lists of words and were then instructed to report these words in the same order as presented. Second, to measure controlled processing or working memory, participants completed an operational span task. On each trial, they received an equation, such as Does (6/3) + 2 = 4, coupled with a word, such as PLANT. They needed to answer Yes or No to each equation as well as memorize the words. The operational span task, therefore, was the same as the word span task, except participants also needed to perform arithmetic operations. Before completing these tasks, to evoke positive affect, half the participants also completed an unexpected gift. This gift enhanced performance on operational span but not word span.
Several mechanisms could underpin the effect of positive emotions on controlled processing. First, these positive emotions might increase dopamine release, and dopamine may be vital to controlled processing, such as inhibition and other executive functions. Second, positive emotion may diminish the need of individuals to be vigilant to potential threats in the environment. These tendencies may be observed, however, only when the positive emotions are high in approach rather than avoidance.
Logel and Cohen (2011) showed that self-affirmation increases working memory. In this study, half the participants were asked to select which of several values is most important to them. They next wrote an essay about why this value is important to them. In the control conditions, participants wrote about why their ninth most important value is important to other people. About two and a half months later, participants completed a measure of working memory: the N back task. A sequence of numbers was presented. Participants needed to indicate whenever one number was the same as another number that had appeared two items earlier.
Self-affirmation enhanced working memory two months later. After individuals become aware of their broader values, they may not be as distracted by trivial but daily concerns, preserving their working memory.
Recent studies indicate that working memory can indeed be enhanced (e.g., Olesen, Westerberg, & Klingberg, 2004). Olesen, Westerberg, and Klingberg (2004), for example, showed that training that is intended to enhance working memory does indeed increase neural activity in the middle frontal gyrus as well as the superior and inferior parietal cortices--regions that underpin some facets of working memory (see also Klingberg, Forssberg, & Westerberg, 2002a).
Specifically, in the first experiment, every day, across three to four weeks, some participants completed 90 trials that demand working memory (Olesen, Westerberg, & Klingberg, 2004). Three distinct working memory tasks was administered. Other participants did not complete this training. Furthermore, fMRI was undertaken before and after training. Training on these activities was shown to improve performance on tasks that were not included in the training program, such as the Ravens Advanced Progressive Matrices. Furthermore, after training, when participants completed tasks that demanded working memory, activity in the middle frontal gyrus as well as in the parietal cortices increased (Olesen, Westerberg, & Klingberg, 2004).
The second study was similar. In this study, eight healthy adults undertook 25 days of training, across five weeks. On each day, they completed 90 trials, demanding visuospatial memory, such as recalling the position of items that appeared briefly on a screen. After training, digit span performance improved. Furthermore, when participants undertook tasks that demand working memory, activity in the middle frontal gyrus as well as in the parietal cortices was augmented (Olesen, Westerberg, & Klingberg, 2004).
In short, practice on tasks that demand working memory can enhance this ability. These benefits have been observed in clinical populations as well, such as in ADHD (Klingberg, Forssberg, & Westerberg, 2002b). Typically, training might involve tasks like reverse digit span, in which a series of numbers is presented, and individuals must transcribe these numbers in reverse order (Klingberg, Forssberg, & Westerberg, 2002b).
Some research indicates that stimulation of the dorsolateral prefrontal cortex can subsequently enhance working memory, especially if combined with cognitive activity. In one study, for example, conducted by Andrews, Hoy, Enticott, Daskalakis, and Fitzgerald (in press), participants undertook a study that comprised three phases. First, they completed an initial measure of digit forward and backward span. In particular, a series of digits was presented. Participants were instructed to recount these digits in the same order, or in the reverse order, in which the numbers were heard, a test of verbal working memory.
Next, an intervention was implemented to enhance working memory. Specifically, some participants received anodal transcranial direct current stimulation over 10 minutes, to increase excitability of the left dorsolateral prefrontal cortex. Some participants were exposed to the same stimulation, but also completed another cognitive activity that demands working memory, the n-back task. In addition, some participants received a sham condition, in which the stimulation fades rapidly, but also completed the n-back task. Finally, all participants completed the digit forward and digt backward task again.
Relative to the other conditions, performance on the digit forward task was more likely to improve if participants received anodal transcranial direct current stimulation over 10 minutes and completed the n-back task concurrently. Thus, for some reason, stimulation of the left dorsolateral prefrontal cortex was effective, provided that participants also invoked this region concurrently.
Andrews, Hoy, Enticott, Daskalakis, and Fitzgerald (in press) ascribed these findings to long term potentiation, a key mechanism that underpins neural plasticity. Specifically, brief but intense activation of a synapse facilitates transmission across this synapse in the future. Conceivably, direct stimulation, combined with cognitive activity, could represent this brief but intense activation.
Many neural regions underpin working memory. To a significant extent, the prefrontal cortex mediates many facets of the central executive& other regions mediate many of the facets of the other systems.
Several strands of research indicate the left ventrolateral prefrontal cortex facilitates the capacity of individuals to control attention and to resist temptations, a key function of the central executive. In particular, when individuals deliberate over problems, they need to divide the issue into its constituent facets, consider these facets in sequence, maintaining any insights in an active state--all demanding working memory (Baddeley, 2007). Unfortunately, distractions that are extraneous to an ongoing problem, such as irrelevant noises, can supersede some of the information and insights that need to be retained in an active state. That is, only a limited array of insights can be maintained in this state. To sustain thoughts about the ongoing problem, individuals must be able to deflect these distractions. This deflection of distractions is called attentional or inhibitory control, a vital facet of the central executive (Baddeley, 2002).
This need to control attention increases as the load on working memory escalates. When the burden on working memory increases, the left ventrolateral prefrontal cortex is more likely to be activated--as several neuroimaging studies have shown (e.g., Love, Haist, Nicol, & Swinney, 2006& Wolf, Vasic, & Walter, 2006). These findings, according to several researchers, indicate that activation of the left ventrolateral prefrontal cortex might underpin the control of attention (D'Esposito, Postle, & Rypma, 2000).
Indeed, the left ventrolateral prefrontal cortex is especially active when distracters are prevalent. For example, in some studies, a series of stimuli, such as letters are presented. Occasionally, one of the stimuli is presented in a different color. Participants must press a specific button if this stimulus is identical to the letter that was presented three items earlier, called the three back task. In the sequence, Z Y X A Y, for example, participants would need to press this button if the final stimulus appeared in a different color. In the sequence, Z X Y A Y, however, they would not press this stimulus, Nevertheless, in this example, the final stimulus is identical to the letter that appeared two items earlier. Participants might experience a momentary inclination to press the button--an inclination they must suppress, demanding control of attention. The left ventrolateral prefrontal cortex seems to be especially active on these trials (Kane, 2005& Kane & Engle, 2002).
Xu and Chun (2006) showed the various measures of working memory can be divided into two main factors or functions. The first factor primarily reflects the number of representations or concepts that individuals can retain and transform in memory working simultaneously. The second factor primarily reflects the precision or complexity of items that are stored.
Consistent with this distinction, Xu and Chun (2006) demonstrated the number of items that individuals need to store in visual working memory correlate with activation of particular neural regions. In contrast, the complexity of items that individuals need to store correlate with activation of different regions.
To clarify, in this study, activation of the inferior intra-parietal sulcus was positively associated with the number of shapes that individuals needed to retain, regardless of spatial location. Once the number of items reached four, activation of this region began to plateau. This region, thus, seems to represent a maximum of four items.
In contrast, activation of the superior intra-parietal sulcus and occipital regions were associated with the complexity of items. That is, if the items were more complex, activation of these regions increased, even if the number of items remained steady or even diminished.
In addition to neural studies, measures of performance confirm this distinction. To illustrate, as Awh, Barton, and Vogel (2007) demonstrated, individuals who can retain many items do not necessarily store precise representations: the number and precision of these representations are uncorrelated with each other.
Fukuda, Vogel, Mayr, and Awh (2010) developed a measure to differentiate these two factors. In this protocol, four possible geometric figures could be presented. Two of these figures were ovals, and two of these figures were rectangles. The two ovals, as well as the two rectangles, differed from each other. For example, in one oval and in one rectangle, a cross appeared inside the shape. In the other oval and rectangle, a single line appeared towards one end. Hence, the two ovals were similar to each other& the two rectangular figures were similar to each other& but the ovals diverged considerably from the rectangles.
On each trial, a series of four or eight items appeared. For example, the array might include two of the ovals with a cross and one of each rectangle. One second later, one of these items appeared again. Participants had to press a button to indicate whether or not this item had shifted its location. On trials in which one of the items had shifted, the shape may or may not have changed. For example, a rectangle might have been supplanted with an oval, representing an obvious change. Alternatively, one of the rectangles might have been supplanted with the other rectangle, representing a subtle change.
If individuals could readily identify the obvious changes, they can presumably retain many representations at the same time. If individuals could readily identify the subtle changes, they presumably retain precise representations. Fukuda, Vogel, Mayr, and Awh (2010) showed that number, and not precision, of representations was correlated with a measure of fluid intelligence.
Oztekin, Davachi, and McElree (2010) showed that working memory might not be distinct from long term memory. That is, the functions that are ascribed to working memory might be underpinned by the same circuits and mechanisms as the functions that are ascribed to long term memory.
To illustrate, in a study conducted by Oztekin, Davachi, and McElree (2010), on each trial, a series of 12 unrelated words was presented. Then, another pair of words appeared, only one of which was derived from the previous series. Participants had to decide which of these words was presented earlier. This procedure was repeated many times. Furthermore, fMRI was measured to identify the brain regions that were activated during this task.
In general, recognition time was fastest for the last item. This last item is often assumed to be the focus of attention and does not need to be retrieved from a memory story. Recognition time was moderate for the next three or so items before this last word. These three items are potentially words that are represented in a more active state, perhaps in long term memory or working memory. Recognition time was slowest for the first eight or so items. These items are words that are represented in a passive state in long term memory.
Interestingly, during the recognition phase, activation of both the left and right hippocampus was pronounced regardless of whether items corresponded to the passive set or active set. As these findings imply, retrieval from long term memory and retrieval from working memory seem to demand the same processes. These systems, therefore, might be tantamount to each other. That is, working memory might represent activated representations in long term memory and not a distinct system.
The hippocampus was negligibly activated when individuals needed to recognize the last item, presumably because no retrieval processes were needed. Furthermore, the hippocampus was slightly more activated when items were derived from the active set compared to the passive set. Hence, the probability of successful retrieval might correlate with activation of the hippocampus (Oztekin, Davachi, & McElree, 2010) .
Contradictory findings can be reconciled. For example, in some studies, the last three items are recognized more rapidly. Nevertheless, in these studies, participants might have been able to cluster these three items together to form one chunk (Oztekin, Davachi, & McElree, 2010).
Despite these findings, some important differences between working memory and long term memory have been uncovered. To illustrate, when individuals engage in tasks that demand long term memory, their eyes sometimes shift, even if the activity does not demand vision. When individuals engage in tasks that demand working memory, these eye movements are not as prevalent (e.g., Micic, Ehrlichman, & Chen, 2010).
Physical exercise has been shown to improve the capacity of individuals to inhibit responses in a variety of populations, from children to the elderly, and from healthy populations to clinical populations (for a review, see Padilla, Perez, Andres, & Parmentier, 2013). To illustrate, in one study, conducted by Padilla, Perez, Andres, and Parmentier (2013), participants completed a stop signal task. On most trials, either a square or circle appeared on a screen. Participants needed to press a z or - to indicate which shape appeared. However, on 25% of trials, soon after this shape appeared, a tone was emitted. On these trials, participants needed to refrain from pressing a button. The experimenter gradually increased the time between the shape and tone until participants could no longer readily inhibit their responses. Half the participants were also informed the tone could appear immediately after the shape or after some delay-information that simplified the task.
Furthermore, an interview was conducted to ascertain the degree to which participants engaged in physical activity or exercise. In addition, VO2 max was assessed to measure fitness. If participants engaged in significant exercise over time, they were especially proficient on the stop signal task. That is, they could more readily inhibit their response even after a delay between the shape and tone. This finding, however, was observed only if participants were not informed the tone could appear immediately after the shape or after some delay--increasing the difficulty and working memory demands of this task, demanding more strategic choice.
These findings indicate that lasting exercise may improve one feature of executive control or working memory: the capacity of individuals to inhibit responses. This discovery is consistent with the notion that chronic exercise increases the volume of prefrontal and anterior gray and white matter, vital to inhibition.
Andrews, S. C., Hoy, K. E., Enticott, P. G., Daskalakis, Z. J., & Fitzgerald, P. B. (in press). Improving working memory: The effect of combining cognitive activity and anodal transcranial direct current stimulation to the left dorsolateral prefrontal cortex. Brain Stimulation.
Ashby, F. G., Valentin, V. V., & Turken, A. U. (2002). The effects of positive affect and arousal on working memory and executive attention: Neurobiology and computational models. In S. Moore & M. Oaksford (Eds.), Emotional contagion: From brain to behavior (pp. 245-287). Amsterdam, the Netherlands: Benjamins.
Awh, E., Barton, B., & Vogel, E. K. (2007). Visual working memory represents a fixed number of items, regardless of complexity. Psychological Science, 18, 622-628.
Baddeley, A. D. (2000). The episodic buffer: A new component of working memory. Trends in Cognitive Science, 4, 417-423.
Baddeley, A. D. (2003). Working memory: Looking back and looking forward. Nature Reviews, Neuroscience, 4, 829-839.
Baddeley, A. D. (2007). Working memory, thought, and action. Oxford, UK: Oxford University Press.
Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. A. Bower (Ed.), Recent advances in learning and motivation (Vol. 8, pp. 47-89). New York: Academic Press.
Baddeley, A. D., & Larsen, J. D. (2007). The phonological loop unmasked? A comment on the evidence for a "perceptual-gestural" alternative. Quarterly Journal of Experimental Psychology, 60, 497-504.
Baddeley, A. D., Baddeley, H. A., Bucks, R. S., & Wilcock, G. C. (2001). Attentional control in Alzheimer's disease. Brain, 124, 1492-1508.
Baddeley, A. D., Chincotta, D., & Adlam, A. (2001). Working memory and the control of action: evidence from task switching. Journal of Experimental Psychology. General, 130, 641-57.
Baddeley, A. D., Grant, W., Wight, E., & Thomson, N. (1975) Imagery and visual working memory. In: Attention and Performance V (eds P. M. A. Rabbitt & S. Dornic), pp. 205-17. Academic Press, London.
Baddeley, A.D. (1992). Working memory. Science, 255, 556-559.
Baddeley, A.D. (1996). Exploring the central executive. The Quarterly Journal of Experimental Psychology, 49A, 5-28.
Barrouillet, P., Bernardin, S., Portrat, S., Vergauwe, E., & Camos, V. (2007). Time and cognitive load in working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 570-585.
Barton, B., Ester, E. F., & Awh, E. (2009). Discrete resource allocation in visual working memory. Journal of Experimental Psychology: Human Perception & Performance, 35, 1359-1367.
Bo, J., & Seidler, R. D. (2009). Visuospatial working memory capacity predicts the organization of acquired explicit motor sequences. Journal of Neurophysiology, 101, 3116-3125.
Cabeza, R., Dolcos, F., Graham, R., & Nyberg, L. (2002). Similarities and differences in the neural correlates of episodic memory retrieval and working memory. NeuroImage, 16, 317-330.
Carpenter, P.A., Just, M.A., & Reichle, E.D. (2000). Working memory and executive function: Evidence from neuroimaging. Current Opinion in Neurobiology, 10, 195-199.
Chooi, W. T., & Thompson, L. A. (2012). Working memory training does not improve intelligence in healthy young adults. Intelligence, 40, 531-542. doi:10.1016/j.intell.2012.07.004
Cocchini, G., Logie, R. H., Della Sala, S., MacPherson, S. E., & Baddeley, A. D. (2002). Concurrent performance of two memory tasks: Evidence for domain-specific working memory systems. Memory & Cognition, 30, 1086-1095.
Colom, R., Flores-Mendoza, C., Quiroga, M., & Privado, J. (2005). Working memory and general intelligence: The role of shortterm storage. Personality & Individual Differences, 39, 1005-1014.
Courtney, S. M., Petit, L., Maisog, J. M., Ungerleider, L. G., & Haxby, J. V. (1998). An area specialized for spatial working memory in human frontal cortex. Science, 279, 1347-1351.
Cowan, N. (2001). The magical number 4 in short-term memory: A reconsideration of mental storage capacity. Behavioral & Brain Sciences, 24, 87-114.
Cowan, N., Chen, Z., & Rouder, J. N. (2004). Constant capacity in an immediate serial-recall task: A logical sequel to Miller (1956). Psychological Science, 15, 634-640.
Cowan, N., Elliott, E. M., Saults, J. S., Morey, C. C., Mattox, S. M., Hismjatullina, A., & Conway, A. R. A. (2005). On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes. Cognitive Psychology, 51, 42-100.
Cowan, N., Fristoe, N. M., Elliott, E. M., Brunner, R. P., & Saults, J. S. (2006). Scope of attention, control of attention, and intelligence in children and adults. Memory & Cognition, 34, 1754-1768.
Cowan, N., Morey, C. C., AuBuchon, A. M., Zwilling, C. E., & Gilchrist, A. L. (2010). Seven-year-olds allocate attention like adults unless working memory is overloaded. Developmental Science, 13, 120-133.
Cusack, R., Lehmann, M., Veldsman, M., & Mitchell, D. J. (2009). Encoding strategy and not visual working memory capacity correlates with intelligence. Psychonomic Bulletin & Review, 16, 641-647.
Daneman, M., & Carpenter, P. A. (1980). Individual differences in working memory and reading. Journal of Verbal Learning & Verbal Behavior, 19, 450-466.
D'Esposito, M., Postle, B. R., & Rypma, B. (2000). Prefrontal cortical contributions to working memory: Evidence from event-related fMRI studies. Experimental Brain Research, 133, 3-11.
Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in Psychological Science, 11, 19-23.
Engle, R. W., Tuholski, S. W., Laughlin, J., & Conway, A. R. A. (1999). Working memory, short-term memory and general fluid intelligence: A latent variable model approach. Journal of Experimental Psychology: General, 128, 309-331.
Flanagan, D. P., & Harrison, P. L. (Eds.). (2005). Contemporary intellectual assessment: Theories, tests, and issues (2nd ed.) New York: Guilford Press.
Floresco, S. B., & Phillips, A. G. (2001). Delay-dependent modulation of memory retrieval by infusion of a dopamine D1 agonist into the rat medial prefrontal cortex. Behavioral Neuroscience, 115, 934-939.
Franco-Watkins, A. M., Rickard, T. C., Pashler, H. (2010). Taxing executive processes does not necessarily increase impulsive decision making. Experimental Psychology, 57, 193-201.
Fukuda, K., & Vogel, E. K. (2009). Human variation in overriding attentional capture. Journal of Neuroscience, 29, 8726-8733.
Fukuda, K., Vogel, E., Mayr, U., & Awh, E. (2010). Quantity, not quality: The relationship between fluid intelligence and working memory capacity. Psychonomic Bulletin & Review, 17, 673-679.
Gold, J. M., Fuller, R. L., Robinson, B. M., McMahon, R. P., Braun, E. L., & Luck, S. J. (2006). Intact attentional control of working memory encoding in schizophrenia. Journal of Abnormal Psychology, 115, 658-673.
Gray, J. (2001). Emotional modulation of cognitive control: Approach- withdrawal states double-dissociate spatial from verbal two-back task performance. Journal of Experimental Psychology: General, 130, 436-452. doi:10.1037/0096-34188.8.131.526
Gray, J. (2004). Integration of emotion and cognitive control. Current Directions in Psychological Science, 13, 46-48. doi:10.1111/j.0963-7214.2004.00272.x
Haenschel, C., Linden, D.E., Bittner, R.A., Singer, W., & Hanslmayr, S. (2010). Alpha phase locking predicts residual working memory performance in schizophrenia. Biol Psychiatry, 68, 595-598.
Halford, G. S., Cowan, N., & Andrews, G. (2007). Separating cognitive capacity from knowledge: A new hypothesis. Trends in Cognitive Sciences, 11, 236-242.
Hinson, J. M., Jameson, T. L., & Whitney, P. (2002). Somatic markers, working memory, and decision making. Cognitive, Affective, & al Neuroscience, 2, 341-353.
Hinson, J. M., Jameson, T. L., & Whitney, P. (2003). Impulsive decision making and working memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 298-306.
Hinson, J. M., & Whitney, P. (2006). Working memory load and decision making: A reply to Franco-Watkins et al. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 448-450.
Hoffman, W., Gschwendner, T., Friese, M., Wiers, R., & Schmitt, M. (2008). Working memory capacity and self-regulatory behaviour: Toward an individual differences perspective on behaviour determination by automatic versus controlled processes. Journal of Personality and Social Psychology, 95, 962-977.
Houben, K., Wiers, R. W., & Jansen, A. (2011). Getting a grip on drinking behavior: Training working memory to reduce alcohol abuse. Psychological Science, 22, 968-975. doi: 10.1177/0956797611412392
Hudjetz, A., & Oberauer, K. (2007). The effects of processing time and processing rate on forgetting in working memory: Testing four models of the complex span paradigm. Memory & Cognition, 35, 1675-1684.
Jaeggi, S. M., Buschkuehl, M., Jonides, J., & Perrig,W. J. (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences of the United States of America, 105, 6829-6833.
Jennings, J. R., Frederik, M., van der Veen, F. M., & Meltzera, C. C. (2006). Verbal and spatial working memory in older individuals: A positron emission tomography study. Brain Research, 1092, 177-189.
Jiang, Y. V., Shim, W. M., & Makovski, T. (2008). Visual working memory for line orientations and face identities. Perception & Psychophysics, 70, 1581-1591.
Jonides, J., Lacey, S. C., & Nee, D. E. (2005). Processes of working memory in mind and brain. Current Directions in Psychological Science, 14, 2-5.
Jonides, J., Smith, E. E., Koeppe, R. A., Awh, E., Minoshima, S., & Mintun, M. A. (1993). Spatial working memory in humans as revealed by PET. Nature, 363, 623-625.
Joormann, J., Levens, S. M., & Gotlib, I. H. (2011). Depression and rumination are associated with difficulties manipulating emotional material in working memory. Psychological Science . doi: 10.1177/0956797611415539.
Kane, M. J. (2005). Full frontal fluidity? Looking in on the neuroimaging of reasoning and intelligence. In O. Wilhelm & R. W. Engle (Eds.), Handbook of understanding and measuring intelligence (pp. 141-163). Thousand Oaks, CA: Sage.
Kane, M. J., & Engle, R. W. (2002). The role of prefrontal cortex in working-memory capacity, executive attention, and general fluid intelligence: An individual-differences perspective. Psychonomic Bulletin & Review, 9, 637-671.
Kieras, D. E., & Meyer, D. E. (1997). An overview of the EPIC architecture for cognition and performance with application to human- computer interaction. Human-Computer Interaction, 12, 391-438.
Kimberg, D. Y., D'Esposito, M., & Farah, M. J. (1997). Effects of bromocriptine on human subjects depend on working memory capacity. Neuroreport, 8, 3581-3585.
Klingberg, T., Forssberg, H., & Westerberg, H. (2002a). Increased brain activity in frontal and parietal cortex underlies the development of visuo-spatial working memory capacity during childhood. Journal of Cognitive Neuroscience, 14, 1-10.
Klingberg, T., Forssberg, H., & Westerberg, H. (2002b). Training of working memory in children with ADHD. Journal of Clinical and Experimental Neuropsychology, 24, 781-791.
Kondo, H., Morishita, M., Osaka, N., Osakam, M., Fukuyama, H., & Shibasaki, H. (2004). Functional roles of the cingulo-frontal network in performance on working memory. NeuroImage, 21I, 2-14.
Kyllonen, P. C., & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity?! Intelligence, 14, 389-433.
Logel, C., & Cohen, G. L. (2011). The role of the self in physical health: Testing the effect of a values-affirmation intervention on weight loss. Psychological Science, 23, 53-55. doi:10.1177/0956797611421936
Logie, R. H., Delia Sala, S., Beschin, A., & Denis, M. (2005). Dissociating mental transformations and visuo-spatial storage in working memory: Evidence from representational neglect. Memory, 13, 430-434.
Love, T., Haist, F., Nicol, J., & Swinney, D. (2006). A functional neuroimaging investigation of the roles of structural complexity and task-demand during auditory sentence processing. Cortex, 42, 577-590.
Luck, S. J., & Vogel, E. K. (1997). The capacity of visual working memory for features and conjunctions. Nature, 390, 279-281.
Mantyla, T., Carelli, M. G., & Forman, H. (2007). Time monitoring and executive functioning in children and adults. Journal of Experimental Child Psychology, 96, 1-19.
McCarthy, G., Puce, C., Constable, R. T., Krystal, J. H., Gore, J. C., & Rakic, P. (1996). Activation of human prefrontal cortex during spatial and nonspatial working memory tasks measured by functional MRI. Cerebral Cortex, 6, 600-611.
McCollough, A. W., Machizawa, M. G., & Vogel, E. K. (2007). Electrophysiological measures of maintaining representations in visual working memory. Cortex, 43, 77-94.
McNab, F., & Klingberg, T. (2008). Prefrontal cortex and basal ganglia control access to working memory. Nature Neuroscience, 11, 103-107.
Micic, D., Ehrlichman, H., & Chen, R. (2010). Non-visual gaze patterns (NVGPs) involve saccades and fixations that spontaneously occur in cognitive activities that are not ostensibly visual. Brain and Cognition, 74, 210-224.
Mogle, J. A., Lovett, B. J., Stawski, R. S., & Sliwinski, M. J. (2008). What's so special about working memory? An examination of the relationships among working memory, secondary memory, and fluid intelligence. Psychological Science, 19, 1071-1077.
Nagel, B. J., Ohannessian, A., & Cummins, K. (2007). Performance dissociation during verbal and spatial working memory tasks. Perceptual & Motor Skills, 105, 243-250.
Nolen-Hoeksema, S., Wisco, B., & Lyubomirsky, S. (2008). Rethinking rumination. Perspectives on Psychological Science, 3, 400-424.
Nystrom, L. E., Braver, T. S., Sabb, F. W., Delgado, M. R., Noll, D. C., & Cohen, J. D. (2000). Working memoiy for letters, shapes, and locations: fMRI evidence against stimulus-based regional organization in human prefrontal cortex. Neuroimage, 11, 424-446.
Oberauer, K., & Bialkova, S. (2009). Accessing information in working memory: Can the focus of attention grasp two elements at the same time? Journal of Experimental Psychology: General, 138, 64-87.
Oberauer, K., Sub, H., Wilhelm, O., & Wittmann, W. W. (2008). Which working memory functions predict intelligence? Intelligence, 36, 641-652. doi:10.1016/j.intell.2008.01.007
Olesen, P. J., Westerberg, H., & Klingberg, T. (2004). Increased prefrontal and parietal brain activity after training of working memory. Nature Neuroscience, 7, 75-79.
Owen, A. M., McMillan, K. M., Laird, A. R., & Bullmore, E. (2005). N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25, 46-59.
Oztekin, I., Davachi, L., & McElree, B. (2010). Are representations in working memory distinct from representations in long-term memory? Neural evidence in support of a single source. Psychological Science, 21, 1123-1133.
Padilla, C., Perez, L., Andres, P., & Parmentier, F. B. R. (2013). Exercise improves cognitive control: Evidence from the stop signal task. Applied Cognitive Psychology, 27, 505-511 doi: 10.1002/acp.2929
Palladino, P., Mammarella, N., & Vecchi, T. (2003). Modality-specific effects in inhibitory mechanisms: The interaction of peripheral and central components in working memory. Brain and Cognition, 53, 263-267.
Pe, M. L., Raes, F., Koval, P., Brans, K., Verduyn, P., & Kuppens, P. (2013). Interference resolution moderates the impact of rumination and reappraisal on affective experiences in daily life. Cognition and Emotion, 27, 492-501. doi: 10.1080/02699931.2012.719489
Ragland, J. D., Turetsky, B. I., Gur, R. C., Gunning-Dixon, F., Turner, T., Schroeder, L., et al. (2002). Working memory for complex figures: An fMRI comparison of letter and fractal n-back tasks. Neuropsychology, 16, 370-379.
McRae, K., Jacobs, S. E., Ray, R. D., John, O. P., & Gross, J. J. (2012). Individual differences in reappraisal ability: Links to reappraisal frequency, well-being, and cognitive control. Journal of Research in Personality, 46, 2-7.
Saults, J. S., & Cowan, N. (2007). A central capacity limit to the simultaneous storage of visual and auditory arrays in working memory. Journal of Experimental Psychology: General, 136, 663-684.
Schaefer, S., Lovden, M., Wieckhorst, B., & Lindenberger, U. (2010). Cognitive performance is improved while walking: Differences in cognitive-sensorimotor couplings between children and young adults. European Journal of Developmental Psychology, 7(3), 371-389. doi: 10.1080/17405620802535666
Scolari, M., Vogel, E. K., & Awh, E. (2008). Perceptual expertise enhances the resolution but not the number of representations in working memory. Psychonomic Bulletin & Review, 15, 215-222.
Smith, S. R., Servesco, A. M., Edwards, J. W., Rahban, R., Barazani, S., Nowinski, L. A., Little, J. A., Blazer, A. L., & Green, J. G. (2008). Exploring the validity of the comprehensive trail making test. Clinical Neuropsychologist, 22, 507-518.
Storbeck, J., & Watson, P. (2015). Verbal makes it positive, spatial makes it negative: Working memory biases judgments, attention, and moods. Emotion, 14, 1072
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