N-back

Last updated

The n-back task is a continuous performance task that is commonly used as an assessment in psychology and cognitive neuroscience to measure a part of working memory and working memory capacity. [1] The n-back was introduced by Wayne Kirchner in 1958. [2] N-Back games are purported to be a training method to improve working memory and working memory capacity and also increase fluid intelligence, although evidence for such effects are lacking. [3]

Contents

The task

The subject is presented with a sequence of stimuli, and the task consists of indicating when the current stimulus matches the one from n steps earlier in the sequence. The load factor n can be adjusted to make the task more or less difficult.

To clarify, the visual n-back test is similar to the classic memory game of Concentration. However, instead of different items that are in a fixed location on the game board, there is only one item, that appears in different positions on the game board during each turn. "1-back" means that you have to remember the position of the item, one turn back. "2-back" means that you have to remember the position of the item two turns back, and so on.

For example, an auditory three-back test could consist of the experimenter reading the following list of letters to the test subject:

T L H C H O C Q L C K L H C Q T R R K C H R

The subject is supposed to indicate when the letters marked in bold are read, because those correspond to the letters that were read three steps earlier.

The n-back task captures the active part of working memory. When n equals 2 or more, it is not enough to simply keep a representation of recently presented items in mind; the working memory buffer also needs to be updated continuously to keep track of what the current stimulus must be compared to. To accomplish this task, the subject needs to both maintain and manipulate information in working memory. [1]

Dual n-back

The dual-task n-back task is a variation that was proposed by Susanne Jaeggi et al. in 2003. [4] In the dual-task paradigm, two independent sequences are presented simultaneously, typically using different modalities of stimuli, such as one auditory and one visual.

Several smart phone apps and online implementations of the dual n-back task exist. [5]

Applications

Assessment

The n-back task was developed by Wayne Kirchner for his research into short-term memory; he used it to assess age differences in memory tasks of "rapidly changing information". [2]

Construct validity

There is some question about the construct validity of the n-back task. While the task has strong face validity and is now in widespread use as a measure of working memory in clinical and experimental settings, there are few studies which explore the convergent validity of the n-back task with other measures of working memory. [6] Those studies have largely revealed weak or modest correlations between individuals' performance on the n-back task and performance on other standard, accepted assessments of working memory. [6] [7]

There are two main hypotheses for this weak correlation between the n-back task and other working memory assessments. One proposal is that the n-back task assesses different "sub-components" of working memory than do other assessments. A more critical explanation is that rather than primarily assessing working memory, performance on the n-back task depends on "familiarity- and recognition-based discrimination processes," whereas valid assessments of working memory demand "active recall." [7] Whatever the cause of the performance differences between the n-back and other assessments of working memory, some researchers stress the need for further exploration of the construct validity of the n-back task. [6]

Performance on the n-back task seems to be more closely correlated with performance on measures of fluid intelligence than it is with performance on other measures of working memory (which is also correlated with performance on measures of fluid intelligence). [7] In the same vein, training on the n-back task appears to improve performance on subsequent fluid intelligence assessments, especially when the training is at a higher n-value. [7]

Treatment

A 2008 research paper claimed that practicing a dual n-back task can increase fluid intelligence (Gf), as measured in several different standard tests. [8] This finding received some attention from popular media, including an article in Wired . [9] However, a subsequent criticism of the paper's methodology questioned the experiment's validity and took issue with the lack of uniformity in the tests used to evaluate the control and test groups. [10] For example, the progressive nature of Raven's Advanced Progressive Matrices (APM) test may have been compromised by modifications of time restrictions (i.e., 10 minutes were allowed to complete a normally 45-minute test). The authors of the original paper later addressed this criticism by citing research indicating that scores in timed administrations of the APM are predictive of scores in untimed administrations. [11]

The 2008 study was replicated in 2010 with results indicating that practicing single n-back may be almost equal to dual n-back in increasing the score on tests measuring Gf (fluid intelligence). The single n-back test used was the visual test, leaving out the audio test. [11] In 2011, the same authors showed long-lasting transfer effect in some conditions. [12]

Two studies published in 2012 failed to reproduce the effect of dual n-back training on fluid intelligence. These studies found that the effects of training did not transfer to any other cognitive ability tests. [13] [14] In 2014, a meta-analysis of twenty studies showed that n-back training has small but significant effect on Gf and improve it on average for an equivalent of 3–4 points of IQ. [15] In January 2015, this meta-analysis was the subject of a critical review due to small-study effects. [16]

A more recent and extended meta-analysis in January 2017 [17] also found that n-back training produces a medium improvement in unrelated n-back training tasks, but a small improvement in unrelated working memory (WM) tasks:

The present meta-analysis on the efficacy of n-back training shows medium transfer effects to untrained versions of the trained n-back tasks and small transfer effects to other WM tasks, cognitive control, and Gf [fluid intelligence]. Our results suggest that previous meta-analyses investigating the effects of WM training have overestimated the transfer effects to WM by including untrained variants of the training tasks in their WM transfer domain. Consequently, transfer of n-back training is more task-specific than has previously been suggested.

The question of whether n-back training produces real-world improvements to working memory remains controversial. [18] New research seems to show transfer effects to other cognitive tasks. [19]

Use in tutoring and rehabilitation

The n-back is now in use outside experimental, clinical, and medical settings. Tutoring companies utilize versions of the task (in conjunction with other cognitive tasks) to allegedly improve the fluid intelligence of their clients. [20] Tutoring companies and psychologists also utilize the task to improve the focus of individuals with ADHD [20] and to rehabilitate sufferers of traumatic brain injury; [21] experiments have found evidence that practice with the task helps these individuals focus for up to eight months following training. [21] However, much debate remains about whether training on the n-back and similar tasks can improve performance in the long run or whether the effects of training are transient, [20] [21] and if the effects of training n-back generalize to general cognitive processing, for instance, to fluid intelligence. [22] Despite the claims of commercial providers, there are some researchers who question whether the results of memory training are transferable. Researchers from the University of Oslo published results of the meta-analytical review analyzing various studies on memory training techniques (including n-back) and concluded that "training programs give only near-transfer effects, and there is no convincing evidence that even such near-transfer effects are durable." [23]

Neurobiology of n-back task

Meta-analysis of 24 n-back neuroimaging studies have shown that during this task the following brain regions are consistently activated: lateral premotor cortex; dorsal cingulate and medial premotor cortex; dorsolateral and ventrolateral prefrontal cortex; frontal poles; and medial and lateral posterior parietal cortex. [24]

See also

Related Research Articles

<span class="mw-page-title-main">Intelligence quotient</span> Score from a test designed to assess intelligence

An intelligence quotient (IQ) is a total score derived from a set of standardised tests or subtests designed to assess human intelligence. The abbreviation "IQ" was coined by the psychologist William Stern for the German term Intelligenzquotient, his term for a scoring method for intelligence tests at University of Breslau he advocated in a 1912 book.

Working memory is a cognitive system with a limited capacity that can hold information temporarily. It is important for reasoning and the guidance of decision-making and behavior. Working memory is often used synonymously with short-term memory, but some theorists consider the two forms of memory distinct, assuming that working memory allows for the manipulation of stored information, whereas short-term memory only refers to the short-term storage of information. Working memory is a theoretical concept central to cognitive psychology, neuropsychology, and neuroscience.

Human intelligence is the intellectual capability of humans, which is marked by complex cognitive feats and high levels of motivation and self-awareness. Using their intelligence, humans are able to learn, form concepts, understand, and apply logic and reason. Human intelligence is also thought to encompass our capacities to recognize patterns, plan, innovate, solve problems, make decisions, retain information, and use language to communicate.

The g factor is a construct developed in psychometric investigations of cognitive abilities and human intelligence. It is a variable that summarizes positive correlations among different cognitive tasks, reflecting the fact that an individual's performance on one type of cognitive task tends to be comparable to that person's performance on other kinds of cognitive tasks. The g factor typically accounts for 40 to 50 percent of the between-individual performance differences on a given cognitive test, and composite scores based on many tests are frequently regarded as estimates of individuals' standing on the g factor. The terms IQ, general intelligence, general cognitive ability, general mental ability, and simply intelligence are often used interchangeably to refer to this common core shared by cognitive tests. However, the g factor itself is a mathematical construct indicating the level of observed correlation between cognitive tasks. The measured value of this construct depends on the cognitive tasks that are used, and little is known about the underlying causes of the observed correlations.

The concepts of fluid intelligence (gf) and crystallized intelligence (gc) were introduced in 1963 by the psychologist Raymond Cattell. According to Cattell's psychometrically-based theory, general intelligence (g) is subdivided into gf and gc. Fluid intelligence is the ability to solve novel reasoning problems and is correlated with a number of important skills such as comprehension, problem-solving, and learning. Crystallized intelligence, on the other hand, involves the ability to deduce secondary relational abstractions by applying previously learned primary relational abstractions.

<span class="mw-page-title-main">Wisconsin Card Sorting Test</span> Neuropsychological test

The Wisconsin Card Sorting Test (WCST) is a neuropsychological test of set-shifting, which is the capability to show flexibility when exposed to changes in reinforcement. The WCST was written by David A. Grant and Esta A. Berg. The Professional Manual for the WCST was written by Robert K. Heaton, Gordon J. Chelune, Jack L. Talley, Gary G. Kay, and Glenn Curtiss.

<span class="mw-page-title-main">Executive functions</span> Cognitive processes necessary for control of behavior

In cognitive science and neuropsychology, executive functions are a set of cognitive processes that are necessary for the cognitive control of behavior: selecting and successfully monitoring behaviors that facilitate the attainment of chosen goals. Executive functions include basic cognitive processes such as attentional control, cognitive inhibition, inhibitory control, working memory, and cognitive flexibility. Higher-order executive functions require the simultaneous use of multiple basic executive functions and include planning and fluid intelligence.

Brain training is a program of regular activities purported to maintain or improve one's cognitive abilities. The phrase “cognitive ability” usually refers to components of fluid intelligence such as executive function and working memory. Cognitive training reflects a hypothesis that cognitive abilities can be maintained or improved by exercising the brain, analogous to the way physical fitness is improved by exercising the body. Cognitive training activities can take place in numerous modalities such as cardiovascular fitness training, playing online games or completing cognitive tasks in alignment with a training regimen, playing video games that require visuospatial reasoning, and engaging in novel activities such as dance, art, and music.

<span class="mw-page-title-main">Effects of meditation</span> Surveys & evaluates various meditative practices & evidence of neurophysiological benefits

The psychological and physiological effects of meditation have been studied. In recent years, studies of meditation have increasingly involved the use of modern instruments, such as fMRI and EEG, which are able to observe brain physiology and neural activity in living subjects, either during the act of meditation itself or before and after meditation. Correlations can thus be established between meditative practices and brain structure or function.

<span class="mw-page-title-main">Cattell–Horn–Carroll theory</span> Psychological theory

The Cattell–Horn–Carroll theory, is a psychological theory on the structure of human cognitive abilities. Based on the work of three psychologists, Raymond B. Cattell, John L. Horn and John B. Carroll, the Cattell–Horn–Carroll theory is regarded as an important theory in the study of human intelligence. Based on a large body of research, spanning over 70 years, Carroll's Three Stratum theory was developed using the psychometric approach, the objective measurement of individual differences in abilities, and the application of factor analysis, a statistical technique which uncovers relationships between variables and the underlying structure of concepts such as 'intelligence'. The psychometric approach has consistently facilitated the development of reliable and valid measurement tools and continues to dominate the field of intelligence research.

Environment and intelligence research investigates the impact of environment on intelligence. This is one of the most important factors in understanding human group differences in IQ test scores and other measures of cognitive ability. It is estimated that genes contribute about 20–40% of the variance in intelligence in childhood and about 80% in adulthood. Thus the environment and its interaction with genes account for a high proportion of the variation in intelligence seen in groups of young children, and for a small proportion of the variation observed in groups of mature adults. Historically, there has been great interest in the field of intelligence research to determine environmental influences on the development of cognitive functioning, in particular, fluid intelligence, as defined by its stabilization at 16 years of age. Despite the fact that intelligence stabilizes in early adulthood it is thought that genetic factors come to play more of a role in our intelligence during middle and old age and that the importance of the environment dissipates.

Working memory training is intended to improve a person's working memory. Working memory is a central intellectual faculty, linked to IQ, ageing, and mental health. It has been claimed that working memory training programs are effective means, both for treating specific medical conditions associated with working memory deficit, as and for general increase in cognitive capacity among healthy neurotypical adults.

It has been estimated that over 20% of adults suffer from some form of sleep deprivation. Insomnia and sleep deprivation are common symptoms of depression, and can be an indication of other mental disorders. The consequences of not getting enough sleep could have dire results, not only to the health, cognition, energy level and the mood of the person, but also to those around them. Sleep deprivation increases the risk of human-error related accidents, especially with vigilance-based tasks involving technology.

<span class="mw-page-title-main">Evidence-based education</span> Paradigm of the education field

Evidence-based education (EBE) is the principle that education practices should be based on the best available scientific evidence, rather than tradition, personal judgement, or other influences. Evidence-based education is related to evidence-based teaching, evidence-based learning, and school effectiveness research. For example, research has shown that spaced repetition "leads to more robust memory formation than massed training does, which involves short or no intervals".

<span class="mw-page-title-main">Inhibitory control</span> Cognitive process

Inhibitory control, also known as response inhibition, is a cognitive process – and, more specifically, an executive function – that permits an individual to inhibit their impulses and natural, habitual, or dominant behavioral responses to stimuli in order to select a more appropriate behavior that is consistent with completing their goals. Self-control is an important aspect of inhibitory control. For example, successfully suppressing the natural behavioral response to eat cake when one is craving it while dieting requires the use of inhibitory control.

Cognitive flexibility is an intrinsic property of a cognitive system often associated with the mental ability to adjust its activity and content, switch between different task rules and corresponding behavioral responses, maintain multiple concepts simultaneously and shift internal attention between them. The term cognitive flexibility is traditionally used to refer to one of the executive functions. In this sense, it can be seen as neural underpinnings of adaptive and flexible behavior. Most flexibility tests were developed under this assumption several decades ago. Nowadays, cognitive flexibility can also be referred to as a set of properties of the brain that facilitate flexible yet relevant switching between functional brain states.

<span class="mw-page-title-main">Cogmed</span> Cognitive training software program

Cogmed is a cognitive training software program created in the lab of Torkel Klingberg, a neuroscientist at the Karolinska Institute. Dr. Klingberg was using it to present working memory challenges to people while he studied their brains using fMRI, to try to learn about neuroplasticity. When the studies appeared to show that the challenges improved working memory, Klingberg founded Cogmed in 2001, with financial backing from the Karolinska Institute and venture capitalists.

<span class="mw-page-title-main">Memory improvement</span> Act of improving ones memory

Memory improvement is the act of enhancing one's memory. Research on improving memory is driven by amnesia, age-related memory loss, and people’s desire to enhance their memory. Research involved in memory improvement has also worked to determine what factors influence memory and cognition. There are many different techniques to improve memory some of which include cognitive training, psychopharmacology, diet, stress management, and exercise. Each technique can improve memory in different ways.

<span class="mw-page-title-main">Neurobiological effects of physical exercise</span> Neural, cognitive, and behavioral effects of physical exercise

The neurobiological effects of physical exercise involve possible interrelated effects on brain structure, brain function, and cognition. Research in humans has demonstrated that consistent aerobic exercise may induce improvements in certain cognitive functions, neuroplasticity and behavioral plasticity; some of these long-term effects may include increased neuron growth, increased neurological activity, improved stress coping, enhanced cognitive control of behavior, improved declarative, spatial, and working memory, and structural and functional improvements in brain structures and pathways associated with cognitive control and memory. The effects of exercise on cognition may affect academic performance in children and college students, improve adult productivity, preserve cognitive function in old age, preventing or treating certain neurological disorders, and improving overall quality of life.

Sex differences in cognition are widely studied in the current scientific literature. Biological and genetic differences in combination with environment and culture have resulted in the cognitive differences among males and females. Among biological factors, hormones such as testosterone and estrogen may play some role mediating these differences. Among differences of diverse mental and cognitive abilities, the largest or most well known are those relating to spatial abilities, social cognition and verbal skills and abilities.

References

  1. 1 2 Gazzaniga, Michael S.; Ivry, Richard B.; Mangun, George R. (2009). Cognitive Neuroscience: The Biology of the Mind (2nd ed.).
  2. 1 2 Kirchner, W. K. (1958). "Age differences in short-term retention of rapidly changing information". Journal of Experimental Psychology. 55 (4): 352–358. doi:10.1037/h0043688. PMID   13539317.
  3. Lawlor-Savage, L.; Goghari, V. M. (2016). "Dual N-Back Working Memory Training in Healthy Adults: A Randomized Comparison to Processing Speed Training". PLOS ONE. 11 (4): e0151817. Bibcode:2016PLoSO..1151817L. doi: 10.1371/journal.pone.0151817 . PMC   4820261 . PMID   27043141.
  4. Jaeggi, Susanne M; Seewer, Ria; Nirkko, Arto C; Eckstein, Doris; Schroth, Gerhard; Groner, Rudolf; Gutbrod, Klemens (June 2003). "Does excessive memory load attenuate activation in the prefrontal cortex? Load-dependent processing in single and dual tasks: functional magnetic resonance imaging study". NeuroImage. 19 (2): 210–225. doi: 10.1016/S1053-8119(03)00098-3 . PMID   12814572. S2CID   13807924.
  5. Roizen, Michael; Oz, Mehmet (2018-01-12). "Playing brain games may help sharpen your skills". Houston Chronicle. Hearst. Retrieved 10 November 2018.
  6. 1 2 3 Kane, Michael J.; Conway, Andrew R. A.; Miura, Timothy K.; Colflesh, Gregory J. H. (May 2007). "Working memory, attention control, and the n-back task: A question of construct validity" (PDF). Journal of Experimental Psychology: Learning, Memory, and Cognition. 33 (3): 615–622. doi:10.1037/0278-7393.33.3.615. PMID   17470009.
  7. 1 2 3 4 Jaeggi, S.M., Buschkuehl, M., Perrig, W.J., & Meier, B. (2010). "The concurrent validity of the N-back task as a working memory measure". Memory. 18 (4): 394–412. doi:10.1080/09658211003702171. PMID   20408039. S2CID   42767249.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  8. Jaeggi, Susanne M.; Buschkuehl, Martin; Jonides, John; Perrig, Walter J. (13 May 2008). "Improving fluid intelligence with training on working memory". Proceedings of the National Academy of Sciences of the United States of America. 105 (19): 6829–6833. Bibcode:2008PNAS..105.6829J. doi: 10.1073/pnas.0801268105 . PMC   2383929 . PMID   18443283.
  9. Alexis Madrigal, Forget Brain Age: Researchers Develop Software That Makes You Smarter, Wired, April 2008
  10. Moody, D. E. (2009). "Can intelligence be increased by training on a task of working memory?". Intelligence. 37 (4): 327–328. doi:10.1016/j.intell.2009.04.005.
  11. 1 2 Jaeggi, Susanne M.; Studer-Luethi, Barbara; Buschkuehl, Martin; Su, Yi-Fen; Jonides, John; Perrig, Walter J. (2010). "The relationship between n-back performance and matrix reasoning -- implications for training and transfer". Intelligence. 38 (6): 625–635. doi:10.1016/j.intell.2010.09.001.
  12. Jaeggi, S. M.; Buschkuehl, M.; Jonides, J.; Shah, P. (21 June 2011). "Short- and long-term benefits of cognitive training". Proceedings of the National Academy of Sciences. 108 (25): 10081–10086. Bibcode:2011PNAS..10810081J. doi: 10.1073/pnas.1103228108 . PMC   3121868 . PMID   21670271.
  13. Redick, T. S.; Shipstead, Z.; Harrison, T. L.; Hicks, K. L.; Fried, D. E.; Hambrick, D. Z.; Kane, M. J.; Engle, R. W. (2012). "No Evidence of Intelligence Improvement After Working Memory Training: A Randomized, Placebo-Controlled Study". Journal of Experimental Psychology: General. 142 (2): 359–379. doi:10.1037/a0029082. PMID   22708717. S2CID   15117431.
  14. Chooi, W. T.; Thompson, L. A. (2012). "Working memory training does not improve intelligence in healthy young adults". Intelligence. 40 (6): 531–542. doi:10.1016/j.intell.2012.07.004.
  15. Au, Jacky; Sheehan, Ellen; Tsai, Nancy; Duncan, Greg J.; Buschkuehl, Martin; Jaeggi, Susanne M. (April 2015). "Improving fluid intelligence with training on working memory: a meta-analysis". Psychonomic Bulletin & Review. 22 (2): 366–377. doi:10.3758/s13423-014-0699-x. PMID   25102926. S2CID   10433282.
  16. Bogg, Tim; Lasecki, Leanne (22 January 2015). "Reliable gains? Evidence for substantially underpowered designs in studies of working memory training transfer to fluid intelligence". Frontiers in Psychology. 5: 1589. doi: 10.3389/fpsyg.2014.01589 . PMC   4010796 . PMID   25657629.
  17. Soveri, Anna; Antfolk, Jan; Karlsson, Linda; Salo, Benny; Laine, Matti (1 August 2017). "Working memory training revisited: A multi-level meta-analysis of n-back training studies". Psychonomic Bulletin & Review. 24 (4): 1077–1096. doi: 10.3758/s13423-016-1217-0 . PMID   28116702.
  18. Soveri, Anna; Antfolk, Jan; Karlsson, Linda; Salo, Benny; Laine, Matti (1 August 2017). "Working memory training revisited: A multi-level meta-analysis of n-back training studies". Psychonomic Bulletin & Review. 24 (4): 1077–1096. doi: 10.3758/s13423-016-1217-0 . PMID   28116702.
  19. Li, Wenjuan; Zhang, Qiuzhu; Qiao, Hongying; Jin, Donggang; Ngetich, Ronald K.; Zhang, Junjun; Jin, Zhenlan; Li, Ling (4 February 2021). "Dual n-back working memory training evinces superior transfer effects compared to the method of loci". Scientific Reports. 11 (1): 3072. Bibcode:2021NatSR..11.3072L. doi:10.1038/s41598-021-82663-w. PMC   7862396 . PMID   33542383.
  20. 1 2 3 Hurley, Dan (2012-10-31). "The Brain Trainers". The New York Times. Retrieved 9 November 2012.
  21. 1 2 3 Hurley, Dan (2012-04-18). "Can You Make Yourself Smarter?". The New York Times. Retrieved 9 November 2012.
  22. Daniel Willingham (2012-06-19). "New study: Fluid intelligence not trainable" . Retrieved 2013-04-22.
  23. Monica Melby-Lervåg & Charles Hulme (2013). "Is Working Memory Training Effective? A Meta-Analytic Review" (PDF). Developmental Psychology. 49 (2): 270–291. doi:10.1037/a0028228. PMID   22612437. S2CID   12370312.
  24. Owen, Adrian M.; McMillan, Kathryn M.; Laird, Angela R.; Bullmore, Ed (2005). "N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies". Human Brain Mapping. 25 (1): 46–59. doi:10.1002/hbm.20131. PMC   6871745 . PMID   15846822.