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Neural mechanisms of interference control underlie the relationship between fluid intelligence and working memory span.
Open accessAbstract
Fluid intelligence (gF) and working memory (WM) span predict success in demanding cognitive situations. Recent studies show that much of the variance in gF and WM span is shared, suggesting common neural mechanisms. This study provides a direct investigation of the degree to which shared variance in gF and WM span can be explained by neural mechanisms of interference control. The authors measured performance and functional magnetic resonance imaging activity in 102 participants during the n-back WM task, focusing on the selective activation effects associated with high-interference lure trials. Brain activity on these trials was correlated with gF, WM span, and task performance in core brain regions linked to WM and executive control, including bilateral dorsolateral prefrontal cortex (middle frontal gyrus; BA9) and parietal cortex (inferior parietal cortex; BA 40/7). Interference-related performance and interference-related activity accounted for a significant proportion of the shared variance in gF and WM span. Path analyses indicate that interference control activity may affect gF through a common set of processes that also influence WM span. These results suggest that individual differences in interference-control mechanisms are important for understanding the relationship between gF and WM span.
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“neuroimaging evidence has demonstrated functional overlap in the lateral prefrontal and parietal cortices, implicating shared neural resources that underlie both constructs (Burgess, Gray, Conway, & Braver, 2011).”
From Improving fluid intelligence with training on working memory: a meta-analysis (2015) · cites this paper as Burgess, Gray, Conway, & Braver, 2011
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“On theoretical grounds, the observed improvements are plausible, since Gf and n-back performance draw upon overlapping cognitive and neural processes, including shared demands on WM and interference resolution (Burgess et al., 2011;Buschkuehl, Hernandez-Garcia, Jaeggi, Bernard, & Jonides, 2014;von Bastian & Oberauer, 2013).”
From Improving fluid intelligence with training on working memory: a meta-analysis (2015) · cites this paper as Burgess et al., 2011
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“One of the most common tasks used in these WM training studies is the N-back, an updating task that correlates significantly with measures of higher-level cognition, such as Matrix Reasoning20–24.”
From Near transfer to an unrelated N-back task mediates the effect of N-back working memory training on matrix reasoning (2022) · cites this paper as [20]
In the citing paper
“the adjustment of distinct executive control strategies (proactive versus reactive), which have been proposed to support cognitive flexibility2 (Braver et al., 2009; Burgess et al., 2011; Braver, 2012).”
From Training on Working Memory and Inhibitory Control in Young Adults (2016) · cites this paper as Burgess et al., 2011
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“The AX-CPT is widely used to explore the dynamic adjustment of cognitive control strategies and it has shown to be very sensitive to individual differences in cognitive control (Braver et al., 2009; Burgess et al., 2011; Braver, 2012).”
From Training on Working Memory and Inhibitory Control in Young Adults (2016) · cites this paper as Burgess et al., 2011
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“This is despite previous data indicating notable correlations between n-back tasks and complex span tasks [57,58].”
From Dual N-back working memory training in healthy adults: A randomized comparison to processing speed training. (2016) · cites this paper as [57]
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Citations
Cites
1 retracted
Persson, J., & Reuter‐Lorenz, P. A. (2008) · Psychological Science · doi:10.1111/j.1467-9280.2008.02172.x · Cited by 109
RetractedStructural Equations with Latent Variables.
Clogg, C. C., & Bollen, K. A. (1991) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2072165 · Cited by 17,475
An Integrative Theory of Prefrontal Cortex Function
Miller, E. K., & Cohen, J. D. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.167 · Cited by 12,803
Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
Mediation in experimental and nonexperimental studies: New procedures and recommendations.
Shrout, P. E., & Bolger, N. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.4.422 · Cited by 11,335
Neural Mechanisms of Selective Visual Attention
Desimone, R., & Duncan, J. (1995) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.18.030195.001205 · Cited by 8,388
(1967) · Medical Entomology and Zoology · Cited by 7,532
(1998) · Cited by 4,172
Movement‐Related effects in fMRI time‐series
Friston, K. J., Williams, S., Howard, R., Frackowiak, R. S. J., & Turner, R. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910350312 · Cited by 3,774
(1996) · Choice Reviews Online · doi:10.5860/choice.34-2458 · Cited by 3,746
Flagged first, then by citations
Cited by
Sorted by citations
Function in the human connectome: task-fMRI and individual differences in behavior
Barch, D. M., Burgess, G. C., Harms, M. P., Petersen, S. E., Schlaggar, B. L., Corbetta, M., Glasser, M. F., Curtiss, S., Dixit, S., Feldt, C., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.033 · Cited by 1,529
Self-citationImproving fluid intelligence with training on working memory: a meta-analysis
Au, J., Sheehan, E., Tsai, N., Duncan, G. J., Buschkuehl, M., & Jaeggi, S. M. (2015) · Psychonomic Bulletin & Review · doi:10.3758/s13423-014-0699-x · Cited by 727
Redick, T. S., Shipstead, Z., Harrison, T. L., Hicks, K. L., Fried, D. E., Hambrick, D. Z., Kane, M. J., & Engle, R. W. (2013) · Journal of Experimental Psychology: General · doi:10.1037/a0029082 · Cited by 617
Global Connectivity of Prefrontal Cortex Predicts Cognitive Control and Intelligence
Cole, M. W., Yarkoni, T., Repovs, G., Anticevic, A., & Braver, T. S. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.0536-12.2012 · Cited by 613
Self-citationBeaty, R. E., & Silvia, P. J. (2012) · Psychology of Aesthetics, Creativity, and the Arts · doi:10.1037/a0029171 · Cited by 551
Revisiting the role of persistent neural activity during working memory
Sreenivasan, K. K., Curtis, C. E., & D’Esposito, M. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2013.12.001 · Cited by 456
Process Overlap Theory: A Unified Account of the General Factor of Intelligence
Kovacs, K., & Conway, A. R. A. (2016) · Psychological Inquiry · doi:10.1080/1047840x.2016.1153946 · Cited by 458
Self-citationBehavioral components of impulsivity.
Stahl, C., Voss, A., Schmitz, F., Nuszbaum, M., Tüscher, O., Lieb, K., & Klauer, K. C. (2014) · Journal of Experimental Psychology: General · doi:10.1037/a0033981 · Cited by 319
Complex span and n-back measures of working memory: A meta-analysis
Redick, T. S., & Lindsey, D. R. B. (2013) · Psychonomic Bulletin & Review · doi:10.3758/s13423-013-0453-9 · Cited by 305
Basten, U., Hilger, K., & Fiebach, C. J. (2015) · Intelligence · doi:10.1016/j.intell.2015.04.009 · Cited by 324
About the Distinction between Working Memory and Short-Term Memory
Aben, B., Stapert, S., & Blokland, A. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00301 · Cited by 275
The evolution of general intelligence
Burkart, J. M., Schubiger, M. N., & van Schaik, C. P. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x16000959 · Cited by 265
Nash Unsworth, A., & Robison, M. K. (2017) · Psychonomic Bulletin & Review · doi:10.3758/s13423-016-1220-5 · Cited by 277
Working Memory Capacity and Fluid Intelligence: Maintenance and Disengagement
Shipstead, Z., Harrison, T. L., & Engle, R. W. (2016) · Perspectives on Psychological Science · doi:10.1177/1745691616650647 · Cited by 238
Failure of Working Memory Training to Enhance Cognition or Intelligence
Thompson, T. W., Waskom, M. L., Garel, K.-L. A., Cardenas-Iniguez, C., Reynolds, G. O., Winter, R., Chang, P., Pollard, K., Lala, N., Alvarez, G. A., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063614 · Cited by 208
Low working memory capacity is only spuriously related to poor reading comprehension
Dyke, J. A. V., Johns, C. L., & Kukona, A. (2014) · Cognition · doi:10.1016/j.cognition.2014.01.007 · Cited by 197
A Strong Interactive Link between Sensory Discriminations and Intelligence
Melnick, M. D., Harrison, B. R., Park, S., Bennetto, L., & Tadin, D. (2013) · Current Biology · doi:10.1016/j.cub.2013.04.053 · Cited by 166
Clearing the garden-path: improving sentence processing through cognitive control training
Novick, J. M., Hussey, E. K., Teubner-Rhodes, S. E., Harbison, J. I., & Bunting, M. F. (2013) · Language Cognition and Neuroscience · doi:10.1080/01690965.2012.758297 · Cited by 176
Cowan, R., & Powell, D. (2013) · Journal of Educational Psychology · doi:10.1037/a0034097 · Cited by 138
Carruthers, P. (2015) · Consciousness and Cognition · doi:10.1016/j.concog.2015.04.009 · Cited by 133
When are fluid intelligence and working memory isomorphic and when are they not?
Chuderski, A. (2013) · Intelligence · doi:10.1016/j.intell.2013.04.003 · Cited by 120
EEG Microstate Correlates of Fluid Intelligence and Response to Cognitive Training
on behalf of Honeywell SHARP Team authors, Santarnecchi, E., Khanna, A. R., Musaeus, C. S., Benwell, C., Davila-Pérez, P., Farzan, F., Matham, S., Pascual‐Leone, Á., & Shafi, M. M. (2017) · Brain Topography · doi:10.1007/s10548-017-0565-z · Cited by 119
Gulbinaite, R., van Rijn, H., & Cohen, M. X. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00761 · Cited by 124
Hilger, K., Ekman, M., Fiebach, C. J., & Basten, U. (2016) · Intelligence · doi:10.1016/j.intell.2016.11.001 · Cited by 113
Cooper, S. R., Gonthier, C., Barch, D. M., & Braver, T. S. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.01482 · Cited by 112
Self-citationWorking Memory Delay Activity Predicts Individual Differences in Cognitive Abilities
Nash Unsworth, A., Fukuda, K., Awh, E., & Vogel, E. K. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00765 · Cited by 106
EEG microstates distinguish between cognitive components of fluid reasoning
Zappasodi, F., Perrucci, M. G., Saggino, A., Croce, P., Mercuri, P., Romanelli, R., Colom, R., & Ebisch, S. J. H. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.067 · Cited by 99
Training on Working Memory and Inhibitory Control in Young Adults
Maraver, M. J., Bajo, M. T., & Gomez-Ariza, C. J. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00588 · Cited by 96
“…version of the Continuous Performance Test) to explore whether WM and IC training might change the adjustment of distinct executive control strategies (proactive versus reactive), which have been proposed to support cognitive flexibility2 (Braver et al., 2009; Burgess et al., 2011; Braver, 2012).”
BackgroundHsu, N. S., Jaeggi, S. M., & Novick, J. M. (2017) · Brain and Language · doi:10.1016/j.bandl.2016.12.006 · Cited by 100
Remembering to prepare: The benefits (and costs) of high working memory capacity.
Richmond, L. L., Redick, T. S., & Braver, T. S. (2015) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0000122 · Cited by 95
Self-citationDrummond, S. P. A., Anderson, D. E., Straus, L. D., Vogel, E. K., & Perez, V. B. (2012) · PLoS ONE · doi:10.1371/journal.pone.0035653 · Cited by 103
Rapid Transfer of Abstract Rules to Novel Contexts in Human Lateral Prefrontal Cortex
Cole, M. W., Etzel, J. A., Zacks, J. M., Schneider, W., & Braver, T. S. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00142 · Cited by 105
Self-citationCognitive load in the multi-player prisoner's dilemma game: Are there brains in games?
Duffy, S., & Smith, J. B. (2014) · Journal of Behavioral and Experimental Economics · doi:10.1016/j.socec.2014.01.006 · Cited by 94
Lateral Prefrontal Cortex Contributes to Fluid Intelligence Through Multinetwork Connectivity
Cole, M. W., Ito, T., & Braver, T. S. (2015) · Brain Connectivity · doi:10.1089/brain.2015.0357 · Cited by 90
Self-citationStorbeck, J., & Maswood, R. (2015) · Cognition & Emotion · doi:10.1080/02699931.2015.1034091 · Cited by 100
Tang, R., & Braver, T. S. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00818 · Cited by 91
Self-citationAssem, M., Blank, I., Mineroff, Z., Ademoğlu, A., & Fedorenko, E. G. (2020) · Cortex · doi:10.1016/j.cortex.2020.06.013 · Cited by 92
Angelidis, A., Solis, E. C., Lautenbach, F., van der Does, W. A. J., & Putman, P. (2019) · PLoS ONE · doi:10.1371/journal.pone.0210824 · Cited by 100
Zakrzewska, M., & Brzezicka, A. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.00399 · Cited by 84
Frith, E., Kane, M. J., Welhaf, M. S., Christensen, A. P., Silvia, P. J., & Beaty, R. E. (2021) · Creativity Research Journal · doi:10.1080/10400419.2020.1855906 · Cited by 89
The role of suppression in resolving interference: Evidence for an age-related deficit.
Healey, M. K., Hasher, L., & Campbell, K. L. (2013) · Psychology and Aging · doi:10.1037/a0033003 · Cited by 91
A unified cognitive/differential approach to human intelligence: Implications for IQ Testing.
Kovacs, K., & Conway, A. R. A. (2019) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2019.05.003 · Cited by 82
Self-citationStanovich, K. E., West, R. F., & Toplak, M. E. (2011) · The Cambridge Handbook of Intelligence · doi:10.1017/cbo9780511977244.040 · Cited by 77
The effects of bilingualism on conflict monitoring, cognitive control, and garden-path recovery
Teubner-Rhodes, S. E., Mishler, A., Corbett, R., Andreu, L., Sanz‐Torrent, M., Trueswell, J. C., & Novick, J. M. (2016) · Cognition · doi:10.1016/j.cognition.2016.02.011 · Cited by 86
Lawlor-Savage, L., & Goghari, V. M. (2016) · PLOS ONE · doi:10.1371/journal.pone.0151817 · Cited by 74
“” This is despite previous data indicating notable correlations between n-back tasks and complex span tasks [57,58].”
ResultThe Benefits of Executive Control Training and the Implications for Language Processing
Hussey, E. K., & Novick, J. M. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00158 · Cited by 78
Suppressive mechanisms in visual motion processing: From perception to intelligence
Tadin, D. (2015) · Vision Research · doi:10.1016/j.visres.2015.08.005 · Cited by 71
Frischkorn, G. T., Schubert, A., & Hagemann, D. (2019) · Intelligence · doi:10.1016/j.intell.2019.05.003 · Cited by 77
The relational integration task explains fluid reasoning above and beyond other working memory tasks
Chuderski, A. (2013) · Memory & Cognition · doi:10.3758/s13421-013-0366-x · Cited by 71
Dunning, D. L., Westgate, B., & Adlam, A. (2016) · Neuropsychology · doi:10.1037/neu0000285 · Cited by 74
Distinct functional and structural neural underpinnings of working memory
Owens, M. M., Duda, B., Sweet, L. H., & MacKillop, J. M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.022 · Cited by 73
Development of the updating executive function: From 7-year-olds to young adults.
Carriedo, N., Corral, A., Montoro, P. R., Herrero, L., & Rucián, M. (2016) · Developmental Psychology · doi:10.1037/dev0000091 · Cited by 67
Modulating fluid intelligence performance through combined cognitive training and brain stimulation
Brem, A., Almquist, J. N.-F., Mansfield, K. L., Plessow, F., Sella, F., Santarnecchi, E., Orhan, U., McKanna, J. A., Pavel, M., Mathan, S. A., et al. (2018) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2018.04.008 · Cited by 71
The mechanisms of far transfer from cognitive training: Review and hypothesis.
Greenwood, P. M., & Parasuraman, R. (2016) · Neuropsychology · doi:10.1037/neu0000235 · Cited by 62
Increased parietal activity after training of interference control
Oelhafen, S., Nikolaidis, A., Padovani, T., Blaser, D., Koenig, T. W., & Perrig, W. J. (2013) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2013.08.012 · Cited by 66
The contribution of working memory to fluid reasoning: Capacity, control, or both?
Chuderski, A., & Necka, E. (2012) · Journal of Experimental Psychology: Learning, Memory, and Cognition · doi:10.1037/a0028465 · Cited by 60
Context Processing and Cognitive Control
Chiew, K. S., & Braver, T. S. (2017) · Wiley eBooks · doi:10.1002/9781118920497.ch9 · Cited by 64
Self-citationCognitive Load and Strategic SophisticationPreprint
Allred, S., Duffy, S., & Smith, J. B. (2013) · SSRN Electronic Journal · doi:10.1016/j.jebo.2016.02.006 · Cited by 55
Individual Differences in Intelligence and Working Memory
Conway, A. R. A., & Kovacs, K. (2013) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/b978-0-12-407237-4.00007-4 · Cited by 58
Self-citationFunctional brain activation associated with working memory training and transfer
Clark, C. M., Lawlor‐Savage, L., & Goghari, V. M. (2017) · Behavioural Brain Research · doi:10.1016/j.bbr.2017.07.030 · Cited by 57
Engelhardt, P. E., Nigg, J. T., & Ferreira, F. (2016) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2016.1178785 · Cited by 57
Montgomery, J. W., Evans, J. L., Fargo, J. D., Schwartz, S., & Gillam, R. B. (2018) · Journal of Speech Language and Hearing Research · doi:10.1044/2018_jslhr-l-17-0421 · Cited by 49
Plucker, J. A., Esping, A., Kaufman, J. C., & Avitia, M. J. (2014) · Springer eBooks · doi:10.1007/978-1-4939-1562-0_19 · Cited by 52
Gillam, R. B., Montgomery, J. W., Evans, J. L., & Gillam, S. L. (2019) · International Journal of Speech-Language Pathology · doi:10.1080/17549507.2018.1559883 · Cited by 46
How knowing the rules affects solving the Raven Advanced Progressive Matrices Test
Lösche, P., Wiley, J., & Hasselhorn, M. (2014) · Intelligence · doi:10.1016/j.intell.2014.10.004 · Cited by 42
Covey, T. J., Shucard, J. L., & Shucard, D. W. (2018) · Cognition · doi:10.1016/j.cognition.2018.08.012 · Cited by 44
Working Memory and Intelligence
Conway, A. R. A., Getz, S. J., Macnamara, B. N., & de Abreu, P. E. (2011) · Cambridge University Press eBooks · doi:10.1017/cbo9780511977244.021 · Cited by 42
Self-citationWongupparaj, P., Kumari, V., & Morris, R. G. (2015) · Intelligence · doi:10.1016/j.intell.2015.10.007 · Cited by 49
Neural signatures for active maintenance and interference during working memory updating
Vilà‐Balló, A., Salmi, J., Soveri, A., Rodríguez‐Fornells, A., Lehtonen, M., & Laine, M. (2018) · Biological Psychology · doi:10.1016/j.biopsycho.2018.01.007 · Cited by 42
Interference and memory capacity limitations.
Endress, A. D., & Szabó, S. (2017) · Psychological Review · doi:10.1037/rev0000071 · Cited by 40
A role for executive functions in explanatory understanding of the physical world
Bascandziev, I., Powell, L. J., Harris, P. L., & Carey, S. E. (2016) · Cognitive Development · doi:10.1016/j.cogdev.2016.04.001 · Cited by 40
Wongupparaj, P., Sumich, A. L., Wickens, M., Kumari, V., & Morris, R. G. (2018) · Biological Psychology · doi:10.1016/j.biopsycho.2018.10.009 · Cited by 39
Stroux, D., Shushakova, A., Geburek, A. J., Ohrmann, P., Rist, F., & Pedersen, A. (2015) · Clinical Neurophysiology · doi:10.1016/j.clinph.2015.05.021 · Cited by 39
Covey, T. J., Shucard, J. L., Benedict, R. H. B., Weinstock‐Guttman, B., & Shucard, D. W. (2018) · Multiple Sclerosis Journal - Experimental Translational and Clinical · doi:10.1177/2055217317747626 · Cited by 39
Yang, S., Zhao, Z., Cui, H., Zhang, T., Zhao, L., He, Z., Liu, H., Guo, L., Liu, T., Becker, B., et al. (2019) · Frontiers in Neural Circuits · doi:10.3389/fncir.2019.00036 · Cited by 37
Montgomery, J. W., Gillam, R. B., & Evans, J. L. (2021) · Language Speech and Hearing Services in Schools · doi:10.1044/2021_lshss-20-00128 · Cited by 36
Bernstein, L. J., Edelstein, K., Sharma, A. E., & Alain, C. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.08.024 · Cited by 38
Hu, Z., Barkley, C. M., Marino, S. E., Wang, C., Rajan, A., Bo, K., Samuel, I. B. H., & Ding, M. (2019) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01461 · Cited by 38
Pahor, A., Seitz, A. R., & Jaeggi, S. M. (2022) · Nature Human Behaviour · doi:10.1038/s41562-022-01384-w · Cited by 40
Loosli, S. V., Rahm, B., Unterrainer, J. M., Weiller, C., & Kaller, C. P. (2013) · Developmental Psychology · doi:10.1037/a0035231 · Cited by 39
Working memory capacity and task goals modulate error-related ERPs
Coleman, J. R., Watson, J. M., & Strayer, D. L. (2018) · Psychophysiology · doi:10.1111/psyp.12805 · Cited by 33
Román, F. J., Iturria‐Medina, Y., Martínez, K., Karama, S., Burgaleta, M., Evans, A. C., Jaeggi, S. M., & Colom, R. (2017) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2017.03.010 · Cited by 33
Clark, C. M., Lawlor‐Savage, L., & Goghari, V. M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0177707 · Cited by 34
Theta–gamma cross-frequency coupling relates to the level of human intelligence
Pahor, A., & Jaušovec, N. (2014) · Intelligence · doi:10.1016/j.intell.2014.06.007 · Cited by 32
Gray matter responsiveness to adaptive working memory training: a surface-based morphometry study
Román, F. J., Lewis, L. B., Chen, C., Karama, S., Burgaleta, M., Martínez, K., Lepage, C., Jaeggi, S. M., Evans, A. C., Kremen, W. S., et al. (2015) · Brain Structure and Function · doi:10.1007/s00429-015-1168-7 · Cited by 34
How working memory enables fluid reasoning
Dehn, M. J. (2017) · Applied Neuropsychology Child · doi:10.1080/21622965.2017.1317490 · Cited by 30
Sequential dynamics in visual short-term memory
Kool, W., Conway, A. R. A., & Turk‐Browne, N. B. (2014) · Attention Perception & Psychophysics · doi:10.3758/s13414-014-0755-7 · Cited by 29
Self-citationChuderski, A. (2014) · Intelligence · doi:10.1016/j.intell.2014.07.010 · Cited by 29
Shimi, A. G., & Scerif, G. (2017) · Cognition · doi:10.1016/j.cognition.2017.08.005 · Cited by 31
The cost of proactive interference is constant across presentation conditions
Endress, A. D., & Siddique, A. (2016) · Acta Psychologica · doi:10.1016/j.actpsy.2016.08.001 · Cited by 28
Colom, R., Hua, X., Martínez, K., Burgaleta, M., Román, F. J., Gunter, J. L., Carmona, S., Jaeggi, S. M., & Thompson, P. M. (2016) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2016.07.034 · Cited by 29
Birney, D. P., & Beckmann, J. F. (2022) · Journal of Intelligence · doi:10.3390/jintelligence10030049 · Cited by 31
Working memory’s workload capacity
Heathcote, A., Coleman, J. R., Eidels, A., Watson, J. M., Houpt, J. W., & Strayer, D. L. (2015) · Memory & Cognition · doi:10.3758/s13421-015-0526-2 · Cited by 33
Kepinska, O., de Rover, M., Caspers, J., & Schiller, N. O. (2016) · Behavioural Brain Research · doi:10.1016/j.bbr.2016.12.015 · Cited by 31
The role of proactive interference in working memory training and transfer
Redick, T. S., Wiemers, E. A., & Engle, R. W. (2019) · Psychological Research · doi:10.1007/s00426-019-01172-8 · Cited by 30
Schubert, A., Hagemann, D., Löffler, C., Rummel, J., & Arnau, S. (2020) · Journal of Experimental Psychology General · doi:10.1037/xge0000865 · Cited by 27
Kaller, C. P., Loosli, S. V., Rahm, B., Gössel, A., Schieting, S., Hornig, T., Hennig, J., van Elst, L. T., Weiller, C., & Katzev, M. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.03.012 · Cited by 26
Lee, H. W., Lo, Y., Li, K.-H., Sung, W.-S., & Juan, C.-H. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00802 · Cited by 30
What Is Fluid Intelligence? Can It Be Improved?
Kyllonen, P. C., & Kell, H. J. (2016) · Methodology of educational measurement and assessment · doi:10.1007/978-3-319-43473-5_2 · Cited by 29
Zając-Lamparska, L., & Trempała, J. (2016) · Health Psychology Report · doi:10.5114/hpr.2016.56846 · Cited by 27
Metadata
- Authors
- Burgess, G. C., Gray, J. R., Conway, A. R. A., & Braver, T. S.
- Affiliations
- Washington University in St. Louis (US)
- Yale University (US)
- Princeton University (US)
- Venue
- Journal of Experimental Psychology: General
- Published
- 2011-11
- Volume
- 140
- Issue
- 4
- Pages
- 674-692
- ISSN
- 0096-3445 (ISSN-L)
- 1939-2222
- PMC
- PMC3930174
- OpenAlex
- W2163420224
- Cited by
- 231
- References
- 120
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 5 · 2023: 4 · 2022: 12 · 2021: 23 · 2020: 11 · 2019: 15 · 2018: 15 · 2017: 20 · 2016: 24 · 2015: 25 · 2014: 22 · 2013: 20 · 2012: 11
- FWCI
- 23.91
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Experimental Psychology General (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (R01 MH66088, RO1 MH66078)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neurobiology of Language and Bilingualism
- Keywords
- fluid intelligence, working memory span, interference control, shared variance, n-back task, dorsolateral prefrontal cortex, inferior parietal cortex, executive function, individual differences, neural mechanisms
- MeSH terms
- Adolescent, Adult, Female, Humans, Individuality, Intelligence, Magnetic Resonance Imaging, Male, Memory, Short-Term, Neuropsychological Tests, Parietal Lobe, Models, Statistical, Prefrontal Cortex, Young Adult, Executive Function
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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