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I've found many working memory tests online, but they all use either the digits 0-9, or the alphabet. Is there a working memory test that lets one choose the characters?
Ex.: If I input the characters: 0 1 2 3 then the test will output random sequences only containing those 4 characters.
This research was approved by the Commission for Ethics in Psychological Research, University of Tübingen, and all participants provided written informed consent prior to commencement of the study.
Fifty participants (37 women and 13 men), with a mean age of 26.4 years (SD = 4.2), partook in the study. The majority of participants were native speakers of German (72%), followed by Russian (8%), Spanish (6%), Chinese (4%), English, Hungarian, Persian, Serbian and Vietnamese (2% each). Seven (14%) participants did not complete the second half of the study (i.e., web-based testing). Additionally, participant numbers differed across test versions due to technical difficulties (i.e., participants entered their responses using the wrong keys [Web-based CVMT] and data was not correctly saved for one participant [Web-based MLAT5] see description and Table 1 below, and Discussion). Twenty-seven participants were graduate students (54%), and twenty-three were undergraduates (46%). Participants self-reported English proficiency, with most being advanced learners (82%), followed by intermediate (18%). All subjects gave informed consent and received €20 for participating.
Three cognitive tests were administered, one measuring working memory capacity, and two assessing verbal and nonverbal declarative memory abilities, respectively. In the lab-based setting, both working memory and nonverbal declarative memory tests were programmed and delivered via E-Prime v2.0  the verbal declarative memory test was given in paper-pencil form, as originally developed and delivered. Moreover, web-based versions of the three cognitive tests were developed for this study using Java with the GoogleWeb Toolkit (http://www.gwtproject.org), and were accessible from all browsers. A description of each test is given below.
An adapted version of the Automated Operation Span Task (OSpan ), a computerized form of the complex span task created by Turner and Engle , was used to gauge participants’ working memory capacity [9, 22]. Based on the Klingon Span Task implemented by Hicks et al. , this version consisted of using Klingon symbols instead of letters, the stimuli to be remembered in the original OSpan task. In Hicks et al.’ study, participants cheated by writing down the letter memoranda in the web-based version of the classic OSpan, motivating the change of the original stimuli. The task included a practice phase and a testing phase. In the practice phase, participants were first shown with a series of Klingon symbols on the screen, and then were asked to recall them in the order in which they had appeared after each trial (i.e., symbol recall). Next, participants were required to solve a series of simple equations (e.g., 8 * 4 + 7 = ?). Finally, subjects performed the symbol recall while also solving the math problems, as they would later do in the actual testing phase. Following the practice phase, participants were shown with the real trials, which consisted of a list of 15 sets of 3–7 randomized symbols that appeared intermingled with the equations. In sum, there were 75 symbols and 75 math problems. At the end of each set, participants were asked to remember the symbols in the sequence they had been presented. An individual time limit to answer the math problems in the real trials was calculated from the average response time plus 2.5 standard deviations taken during the math practice section. Following Unsworth et al. , a partial score (i.e., total number of correct symbols recalled in the correct order) was taken as the OSpan score (see , for a description of scoring procedures). The highest possible score was 75. The entire task took about 25 min.
Verbal declarative memory.
To measure verbal declarative memory, the Modern Language Aptitude Test, Part 5, Paired Associates (MLAT5 ), was used [9, 49, 50]. In the MLAT5, participants were required to memorize artificial, pseudo-Kurdish words and their meanings in English. Participants were first asked to study 24-word association pairs for two minutes, and then complete a two-minute practice section. The list of foreign words with their respective English meanings was made available for participants as they completed the practice session. Finally, subjects were instructed to complete a timed multiple-choice test (four minutes), by selecting the English meaning of each of the 24 pseudo-Kurdish words from five options previously displayed at the memorization stage. For each correct response, one point was given, yielding a total score of 24 points. The test duration was about 8 minutes.
Nonverbal declarative memory.
The Continuous Visual Memory Task (CVMT ) served as a measure of nonverbal declarative memory [9, 49, 50]. As a visual recognition test, the CVMT is entails asking participants to first view a collection of complex abstract designs on the screen, and then to indicate whether the image they just saw was novel (“new”) in the collection, or they had seen the image before (“old”). Seven of the designs were “old” (target items), and 63 were “new” (distractors). The target items appeared seven times (49 trials), and the distractors only once (63 trials) across the test. All items were shown in a random but fixed order, each one appearing on the screen for two seconds. Following the two seconds, participants were instructed to respond to the “OLD or NEW?” prompt on the screen. In the lab-based mode, subjects used mouse click for making their choice, left for “NEW”, or right for “OLD”. In the web-based mode, they responded by pressing either the “N” key for “NEW”, or the “O” key for “OLD” on the keyboard. The CVMT took 10 min to complete. A d’(d-prime) score  was calculated for each participant. The d’ score was used to reduce potential response bias.
As previously noted, participants underwent two cognitive testing sessions, one in the lab and one on the web. In the lab-based session, with the assistance of a proctor, each subject was tested individually. After providing informed consent, participants took the three cognitive tests under investigation in fixed order: OSpan, CVMT, and MLAT5. Upon finishing the MLAT5, subjects then filled out a background questionnaire. The whole lab-based session lasted about 40 min.
Regarding the web-based session, each subject was sent an email with a unique web link with a personalized code, which once clicked, took them to an interface that hosted the web-based versions of the cognitive tests. In order to avoid multiple responses by the same participant, the link was disabled once subjects had submitted their responses in the last test (i.e., MLAT5). In the email, participants were also informed that the web-based session lasted about 40 min, and that it had to be completed within a week. On the interface, following informed consent, subjects were provided with general instructions that reflected the nature of a web-based experiment. Such instructions included completing the experiment in a quiet place without interruption, and from start to finish in one sitting. Likewise, the use of the browser’s back button, refreshing the browser page, or closing the browser window were prohibited. Importantly, participants were instructed not to take any notes at any point during the entire experiment. The web-based tests were given in the same fixed order as in the lab-based session. On average, the mean period between the first and second testing was 45.7 days (SD = 4.1).
There is no convincing evidence that working memory training is NOT effective: A reply to Melby-Lervåg and Hulme (2015)
Our recent meta-analysis concluded that training on working memory can improve performance on tests of fluid intelligence (Au et al., Psychon Bull Rev, 22(2), 366-377, 2015). Melby-Lervåg and Hulme (Psychon Bull Rev, doi: 10.3758/s13423-015-0862-z) challenge this conclusion on the grounds that it did not take into consideration baseline differences on a by-study level and that the effects were primarily driven by purportedly less rigorous studies that did not include active control groups. Their re-analysis shows that accounting for baseline differences produces a statistically significant, but considerably smaller, overall effect size (g = 0.13 vs g = 0.24 in Au et al.), which loses significance after excluding studies without active controls. The present report demonstrates that evidence of impact variation by the active/passive nature of control groups is ambiguous and also reveals important discrepancies between Melby-Lervåg and Hulme’s analysis and our original meta-analysis in terms of the coding and organization of data that account for the discrepant effect sizes. We demonstrate that there is in fact no evidence that the type of control group per se moderates the effects of working memory training on measures of fluid intelligence and reaffirm the original conclusions in Au et al., which are robust to multiple methods of calculating effect size, including the one proposed by Melby-Lervåg and Hulme.
Emotions play a key role in the daily lives of humans, and regulation of emotions affects quality of life. Therefore, researchers and practitioners have endeavored to improve humans’ emotion regulation ability to protect against emotional disorders 1 . Although developing effective intervention methods to promote emotion regulation is difficult 2 , promising studies have been conducted.
Wadlinger and Isaacowitz 3 suggested that gaze pattern training is a valuable technique for promoting emotion regulation. This type of training, primarily conducted in the form of a dot-probe task, may modify the attention network functions of alerting and orientation. In addition, the dot-probe task requires one’s attention to be disengaged from negative information and reoriented toward positive or neutral information 3 . Gootjes, Franken, and Van Strien 4 and Menezes et al. 5 have investigated meditative practices as a means of promoting emotion regulation. Methods of emotion regulation involving meditative practices, including concentration meditation, mindfulness-based stress reduction, mindfulness-based cognitive therapy, and integrative body–mind training, likely require the entire attention network, which consists of the readiness and sustained attention component (alerting), selective attention (orientation), and inhibition of prominent distracters (executive control) 3,6,7,8,9 . Briefly, according to the Selection, Optimization, and Compensation with Emotion Regulation (SOC-ER) framework 10,11 , successful emotion regulation requires internal resources. In this framework, the frequently adopted internal resource refers to the ability to control one’s attention, and this ability is known as “working memory capacity” 10 .
Recent studies have indicated that working memory capacity, which is based on attention control, correlates with emotion regulation ability and relies heavily on the executive function processes in working memory 12 . Schmeichel, Volokhov, and Demaree 13 reported that in a down-regulation task, participants with higher working memory capacity were more successful than were those with lower working memory capacity, and also experienced and expressed fewer emotional responses. In addition, the participants with lower working memory capacity were more susceptible to emotional contagion and less successful in applying suppression and reappraisal strategies. McRae, Jacobs, Ray, John, and Gross 14 observed a positive correlation between individual differences in reappraisal ability and working memory capacity. A study based on emotional working memory training reported that individuals trained in emotion regulation exhibited markedly low levels of distress in response to negative images and considerable activity in the frontoparietal demand network 15 . These studies have established that working memory ability and emotion regulation are connected, and this connection is likely mediated by attention control.
Working memory is a universal processing ability, and its domain-general aspect is attention control 16,17 . Working memory capacity is used to process target-related information and eliminate not only the competitive response tendency but also interference from distractions 13 . According to Kane, Bleckley, Conway, and Engle 17 , working memory capacity refers specifically to attention control, whereas Fan and Posner 18 proposed that it comprises the attention network functions, namely alerting, orientation, and executive control. The alerting function is responsible for the cognitive control of wakefulness and arousal, the orientation function is actively involved in information selection and filtering, and executive control is responsible for monitoring and conflict resolution. When competitive conflict occurs between task-relevant and task-irrelevant information, attention control (including the orientation and executive control functions) processes the information and provides a response favorable to the task-relevant information 19 .
Individuals with attention control deficit may have insufficient attention resources or an inadequate capacity for emotion regulation 20 . Cognitive control and attention are critical in the face of competition for limited resources 13 . Negative emotional stimuli are distinct, and thus are prioritized in resource processing. These stimuli, which are similar to distractions, may interfere with or block cognitive tasks 21,22 . For individuals with low attention control ability, attention resources primarily focus on negative emotional information, thereby not only exaggerating the effects of such information but also leading to failure of emotion regulation 23 . Individuals with lower attention control ability have greater difficulty handling isolated negative emotional distracters 24,25 . Moreover, studies on depression- and anxiety-related disorders have established that an exaggerated effect of negative information may facilitate the maintenance or exacerbation of depression and anxiety symptoms 26,27 .
Based on the aforementioned studies, we hypothesized that working memory capacity increased through training can enhance attention control ability, and thus may subsequently improve emotion regulation ability. In other words, attention control may be a shared component of and bridge between working memory and emotion regulation. Therefore, in the present study, a running memory task 28 was performed and the attentional network test (ANT) was conducted to improve working memory and evaluate increases in attention control, respectively. In addition, we measured changes in emotion regulation and calculated correlations to assess the relationship between ANT components and emotion regulation outcomes.
In related studies, researchers commonly apply a specific emotional situation and ask participants to accomplish an emotion regulation task based on experimental manipulation. Subsequently, researchers analyze changes in participants’ emotion regulation ability based on changes in task indices (e.g., electrocardiogram, electroencephalography, and behavior performance results). In the present study, we selected a classic event-related potential (ERP) component, namely late positive potential (LPP), to assess its effect on emotion regulation. Generally, LPP amplitude is sensitive to emotional intensity 29,30 . Specifically, the higher the emotional intensity induced by a stimulus (emotional images were used as stimuli in the present study), the higher the LPP amplitude is. In addition, LPP amplitude decreases during emotion regulation 29 , and thus this phenomenon could be employed as an emotion regulation index 31,32 . Using these approaches, we conducted an ERP emotion regulation task where participants were required to view a set of emotional images and regulate their emotions. In the present study, it was expected that a decrease in LPP amplitude after a 20-day working memory training program would be observed and that the aforementioned three attention network functions would simultaneously undergo modification during training.
Theoretical Distinction between Tests
Achievement tests are designed to assess the extent to which a person has developed a specific motor skill or learned a specific body of knowledge. Typically, an achievement test is administered following a period of instruction designed to teach the motor or cognitive skill to be examined. The prototypical achievement test is the periodic classroom exam that is administered to determine how much the student has learned. Other examples include the written and driving tests taken to secure a driver’s license, the Scholastic Assessment Test (SAT) and American College Test (ACT) taken by high school students contemplating college, and the Graduate Records Examination (GRE) taken by college students who want to go to graduate school.
Theoretically, the purpose of the achievement test is descriptive—to measure the extent to which an examinee has mastered a motor skill or area of knowledge. In practice, however, achievement test results often are interpreted as an indicator of future performance. For example, while achievement tests such as the SAT and GRE evaluate the knowledge examinees have accrued as a result of their educational experiences, scores on those tests are used to predict the likelihood of success in more advanced and challenging programs of study. This common practice con-founds the performance assessment (i.e., descriptive) function of achievement tests with the prediction goals of aptitude tests.
Many achievement and aptitude tests are very similar in appearance, but the primary purpose of aptitude tests is prediction. They are designed to obtain information that can be used in predicting some aspect of the person’s future behavior. Aptitude tests assess the examinee’s ability to learn both cognitive and motor skills. Often, scores on a broadly based test of verbal comprehension are used to predict the examinee’s potential to learn (and use) new cognitive skills. In fact, the most common use of aptitude tests is to predict future performance in an educational program or occupational setting. However, some aptitude tests measure motor skills (e.g., eye-hand coordination or the time it takes to run a 40-yard dash). Scores on aptitude tests such as these are used to predict the examinee’s ability to learn (and use) desirable motor skills.
The distinction between aptitude and ability tests is subtle, and many psychologists and test publishers use the terms interchangeably. In general, however, ability tests assess cognitive and motor skill sets that have been acquired over a long period of time and that are not attributable to any specific program of instruction. For example, intelligence tests such as the Wechsler
Adult Intelligence Scale—Third Edition (WAIS-III) and the Stanford-Binet Intelligence Scales, Fifth Edition (SB5) measure verbal comprehension, working memory, perceptual organization, and processing speed. These abilities are not the result of any specific program of instruction. Instead, they are believed to be a function of the person’s native ability to learn from life experiences. Ability tests are descriptive in that they assess people’s knowledge and skills, but they are also predictive because they measure qualities that are presumed to influence the person’s ability to learn new skills and to solve novel problems.
In summary, psychologists distinguish among achievement, aptitude, and ability tests at a theoretical level. Achievement tests describe people’s present status, aptitude tests predict their future behavior, and ability tests assess their innate potential. In practice, however, achievement, aptitude, and ability tests are often similar in form and used for similar purposes.
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Lab requirements, as your research needs, might be quite unique. That is why we at Noldus offer you a wide range of tools, systems, and labs as customized as you need it to be. Even if you want to incorporate components your already own. Rely on our many years of experience with building setups and labs all over the world.
Examples of custom build setups are the Conditioned place preference testing (image on the left), or a large open field with NIR backlight.
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Behavioural code and custom Matlab analysis functions are publicly available at https://github.com/buschman-lab/. All other code is available from the authors upon reasonable request.
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The initial database searches returned 125,867 papers which, after screening for relevance and matching to inclusion criteria (Figure 1), resulted in 43 papers to be reviewed against the quality assessment criteria (Appendix 2 in Supplementary Material).
Characteristics of Included Studies
The included studies resulted in seven devices for review, these were (with number of studies) Cogmed (15), Lumosity (9), Insight and Brain Fitness by Posit Science (6), Cognifit (4), Neurotracker (4), Nintendo Big Brain Academy and Brain Age (4), and Dynavision (1). The participant samples included populations that were healthy and those with health conditions, 27 with participants from healthy young (㱠 years) or old (㹠 years) adult groups, four focusing on ADHD, nine on brain injury and cognitive impairments, two on cancer survivors and one on participants living with depression. There was one study with participants from the armed forces and only one in a sporting population.
Twenty-one studies assessed far transfer 3 , that is, to a measure other than a cognitive test, such as driving ability or soccer passing. Fourteen of these, however, were self-report measures such as quality of life, perceived cognitive function and health condition symptoms. The non-self-report transfer measures were expert ratings of motor skill and safety to drive, ability to perceive human motion, sleep quality, soccer passing ability, and two direct neural measures. Only two studies did not assess near transfer, both of which were studies assessing Neurotracker focusing on far transfer.
Summary of Evidence for CT Devices
An overview of each CCT device is provided in Table 2, and a summary of findings from each study is included in Table 3A (compensatory/restorative effects) and Table 3B (additive effects). Here we give an overview of the evidence for each device, in relation to the five critical questions.
Table 2. Summary of devices identified in the systematic review.
On the stage, memory researcher Henry L. Roediger, III, spoke random digits at a rate of one every 2 seconds. A few feet to his left, memory athlete Nelson Dellis sat in a chair absorbing each one. Dellis hunched over, his hands pressed over his eyes, his face a bit red with intensity. After Roediger announced the 100th digit, Dellis leaned back and asked for a moment to let it all sink in. He was going to recite the digits — all 100 — back to the audience, in order.
A crowd never sat so silent in anticipation.
Roediger and Dellis had spent the past hour revealing the secrets of mnemonic memory as part of the Bring the Family Address at the 2014 APS Annual Convention. Roediger, APS Past President and a psychological scientist at Washington University in St. Louis, has pivoted some research attention to the spectacular feats of extreme memorizers. Dellis, the reigning three-time US Memory Champion, helped him demonstrate to the crowd just how spectacular those feats are.
Mnemonic techniques go back to the days when ancient Greeks had to memorize lengthy speeches, said Roediger. Later, Romans trained bright slaves, known as graeculi, or Little Greeks, to memorize things for them. In the 16th century, the Jesuit priest Matteo Ricci famously created the so-called “memory palace” — a physical space he could roam in his mind to retrieve information based on the spatial retrieval cues.
Linking, Pegging, and Journeying
Roediger discussed three conventional favorites among mnemonic techniques. One is the “link” method, which strings together a series of images that remind users of a topic. Another is the “peg” method, which establishes a series of mental pegs to “hang” a memory on. The most popular mnemonic device is the “journey” or “loci” method. In the spirit of Ricci’s memory palaces, users of the journey method envision a physical path they can’t forget — such as the walk through their houses — and place items they want to remember in spots along it. All these mnemonic techniques rely on the power of mental imagery or visualization, the ability to imagine objects in spaces, which provides a powerful boost to remembering.
Roediger first studied the power of mnemonics several decades ago. He gave study participants three lists of words to memorize in order using one of the main three mnemonic techniques. Controls using no mnemonic recalled about five words in order. Participants using the link method doubled that, and those using the loci
and peg methods did even better, Roediger reported in a 1980 issue of the Journal of Experimental Psychology: Human Learning and Memory.
“Here without much effort, without much practice, we show recall is much better using simple techniques in a standard laboratory setting,” he said. He now regrets not pursuing this line of work at that time.
After a long hiatus, Roediger dived back into the world of mnemonics. He and his collaborators (APS Fellow David A. Balota, APS Fellow Kathleen B. McDermott, and Mary Pyc, all colleagues at Washington University) recently gathered seven world-class memory athletes (including Dellis) in the lab for a series of tests and compared their performances against that of 15 (unfortunate) college students. It wasn’t much of a match. Of a list of 100 words given 2 seconds apart, the athletes recalled about 70 and the controls about 10. On a surprise test a day later, athletes got about 50 words and controls got one or two.
Roediger was most impressed by how well the memory athletes performed on more complex working memory tasks. These tasks are thought to assess attentional control as much as memory, yet the athletes still excelled. For one task, the “computation span,” participants had to state whether an equation like 5+4=9 was true or false while also remembering the middle digit. In a series of seven span trials presented at a fast rate, the athletes got six or seven right, and the controls got only two. The memory athletes also did very well on another task that involves mental control, the Stroop color-word task.
“So a hallmark of being a memory athlete is not just having a great memory, it’s being able to control your attention really well,” said Roediger. “Besides using these mnemonic techniques, you really have to be able to focus.”
In the Cards
Focus is clearly not a problem for Nelson Dellis. He has memorized 310 consecutive digits in 5 minutes and 193 consecutive names in 15 minutes he holds a number of memory records, including the US national record for memorizing a deck of shuffled cards in 63 seconds. (The first thing he did upon taking the stage at the APS Convention was recite a deck that Roediger had shuffled and handed him before the show.) An avid mountaineer, Dellis decided to pursue intense memorization after watching his grandmother suffer from Alzheimer’s disease. He now heads Climb for Memory, a charity aimed at raising awareness about the disease.
What intrigued Dellis the first time he witnessed memory athletes in action was that none of them seemed to be naturals. On the contrary, he said, everyone who took part in competitive memory events claimed to have improved an average memory through training and practice.
“What I do, what all these memory athletes do, is learning,” he said. “At one point I didn’t have this skill. I read a book and just practiced a lot. That’s why I’m here.”
The two keys to memorization, in Dellis’s mind, are visualization and storage. Visualization means using an incredibly detailed image to represent the information you want to remember. That works better than simply trying to memorize a list of numbers, he believes, because our minds evolved to remember scenes with far greater accuracy.
For storage, Dellis relies primarily on the “journey”
mnemonic technique. To demonstrate its power, he showed the audience a list of 14 words on a screen for about a minute, then asked if anyone could recall them. No one volunteered. Then he showed a new list of 14 words and walked the crowd through the sort of process he’d use to lock them into mind.
Dellis divided the stage into seven locations, each of which became home to a pair of words. The word pairs were embellished with highly detailed images. So, giraffe and foot at the podium became a giraffe planting a huge human foot right beside the microphone, stink lines drifting upward from the toes. After Dellis walked the audience through all seven locations — without even setting aside time for direct memorization — the crowd recited all 14 words back to him without a problem.
“You’re going to go home tonight and you’re not going to forget these words — unfortunately,” he said. “The mere fact that we did this process, making it very visual and storing it in a way where you know where they are, you can close your eyes and picture where I was standing, and you’ll be able to remember those words pretty vividly for a long time.”
It wasn’t until the talks ended that Roediger challenged Dellis to remember the 100 digits. As his memory palace, Dellis said he was going to use a hotel in Kathmandu where he’d stayed before climbing Mt. Everest. The crowd quivered with a mixture of fear and delight as Dellis made his way through the list, shown on a screen behind him, two digits at a time. He missed only two numbers, tripped up by the image of Oscar de la Hoya eating a slice of pizza.
That felt a little disappointing to Dellis but made things all the more memorable to the audience. The usual memory span studied by psychologists is about 7 items, whereas for Dellis it was 98!