Relationship Between Working Memory, Fluid Intelligence and Age Based on the Results of Mediation and Moderation Analyses

Ludmiła Zając-Lamparska

doi:10.18290/rpsych21242-3s

Ludmiła Zając-Lamparska Kazimierz Wielki University in Bydgoszcz https://orcid.org/0000-0003-4618-547X

DOI: https://doi.org/10.18290/rpsych21242-3s

Abstrakt

The positive relationship between working memory (WM) and fluid intelligence (Gf) is a well-established phenomenon, yet numerous studies reveal the age-related decline in both WM and Gf. From the perspective of the changes that WM and Gf undergo in adult development it may be assumed that accounting for age in studies of the relationship between these two is important, particularly in age-diverse groups. However, the issue of the WM-Gf link has rarely been considered from a developmental perspective, especially in adults. The analyses presented here focused on the role of age in the relationship between WM and Gf. The study sample comprised 63 participants in early adulthood (N = 33, aged 20–34) and late adulthood (N = 30, aged 60–73). They performed a computerised n-back task on 6 difficulty levels (from 1-back to 6-back) and Raven’s Standard Progressive Matrices (SPM) in Polish standardisation. The obtained results indicated that although WM and Gf were found to be inferior among older than young adults, age was not a significant moderator of the association between WM and Gf. The relationship between age and Gf was not mediated by WM, which does not confirm that age-related changes in Gf may partially result from the developmental trajectory of WM. At the same time, age fully mediated the relationship between WM and Gf, suggesting the existence of a general factor of cognitive aging and implying that it may underlie an apparent relationship between WM and Gf in age-diverse groups.

Bibliografia

Ackerman, P. L., Beier, M. E., & Boyle, M. O. (2005). Working memory and intelligence: The same or different constructs? Psychological Bulletin, 131(1), 30–60. https://doi.org/10.1037/0033-2909.131.1.30

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. SAGE Publications. https://doi.org/10.1016/0886-1633(93)90008-d

Akoglu, H. (2018). User’s guide to correlation coefficients. Turkish Journal of Emergency Medicine, 18(3), 91–93. https://doi.org/10.1016/j.tjem.2018.08.001

Barbey, A. K., Colom, R., Paul, E. J., & Grafman, J. (2014). Architecture of fluid intelligence and working memory revealed by lesion mapping. Brain Structure and Function, 219(2), 485–494. https://doi.org/10.1007/s00429-013-0512-z

Basak, C., & Verhaeghen, P. (2011). Aging and switching the focus of attention in working memory: Age differences in item availability but not in item accessibility. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 66 B(5), 519–526. https://doi.org/10.1093/geronb/gbr028

Bopp, K. L., & Verhaeghen, P. (2005). Aging and verbal memory span: A meta-analysis. Journals of Gerontology - Series B Psychological Sciences and Social Sciences, 60(5), 223–233. https://doi.org/10.1093/geronb/60.5.P223

Borella, E., Carretti, B., & De Beni, R. (2008). Working memory and inhibition across the adult life-span. Acta Psychologica, 128(1), 33–44. https://doi.org/10.1016/j.actpsy.2007.09.008

Braver, T. S., & West, R. (2008). Working memory, executive control, and aging. In F. I. . Craik & T. A. Salthouse (Eds.), The handbook of aging and cognition (3rd ed.). (pp. 311–372). Psychology Press.

Burgess, G. C., Gray, J. R., Conway, A. R. A., & Braver, T. S. (2011). Neural mechanisms of interference control underlie the relationship between fluid intelligence and working memory span. Journal of Experimental Psychology: General, 140(4), 674–692. https://doi.org/10.1037/a0024695

Burgoyne, A. P., Hambrick, D. Z., & Altmann, E. M. (2019). Is working memory capacity a causal factor in fluid intelligence? Psychonomic Bulletin and Review, 26(4), 1333–1339. https://doi.org/10.3758/s13423-019-01606-9

Cabeza, R., & Dennis, N. A. (2012). Frontal lobes and aging. Deterioration and compensation. In D. T. Stuss & R. T. Knight (Eds.), Principles of Frontal Lobe Function (2nd ed., pp. 628–652). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195134971.001.0001

Chatham, C. H., Herd, S. A., Brant, A. M., Hazy, T. E., Miyake, A., O’Reilly, R., & Friedman, N. P. (2011). From an executive network to executive control: A computational model of the n-back task. Journal of Cognitive Neuroscience, 23(11), 3598–3619. https://doi.org/10.1162/jocn_a_00047

Chen, T., & Li, D. (2007). The roles of working memory updating and processing speed in mediating age-related differences in fluid intelligence. Aging, Neuropsychology, and Cognition, 14(6), 631–646. https://doi.org/10.1080/13825580600987660

Chen, Y. N., Mitra, S., & Schlaghecken, F. (2008). Sub-processes of working memory in the N-back task: An investigation using ERPs. Clinical Neurophysiology, 119(7), 1546–1559. https://doi.org/10.1016/j.clinph.2008.03.003

Chuderski, A. (2014). How well can storage capacity, executive control, and fluid reasoning explain insight problem solving. Intelligence, 46(1), 258–270. https://doi.org/10.1016/j.intell.2014.07.010

Chuderski, A. (2015). The broad factor of working memory is virtually isomorphic to fluid intelligence tested under time pressure. Personality and Individual Differences, 85, 98–104. https://doi.org/10.1016/j.paid.2015.04.046

Chuderski, A., & Nęcka, E. (2012). The contribution of working memory to fluid reasoning: Capacity, control, or both? Journal of Experimental Psychology: Learning Memory and Cognition, 38(6), 1689–1710. https://doi.org/10.1037/a0028465

Chuderski, A., Taraday, M., Nęcka, E., & Smoleń, T. (2012). Storage capacity explains fluid intelligence but executive control does not. Intelligence, 40(3), 278–295. https://doi.org/10.1016/j.intell.2012.02.010

Cochrane, A., Simmering, V., & Green, S. (2019). Fluid intelligence is related to capacity in memory as well as attention: Evidence from middle childhood and adulthood. PloS ONE, 14(8), Article e0221353. https://doi.org/10.1371/journal.pone.0221353

Colom, R., Abad, F. J., Quiroga, M. Á., Shih, P. C., & Flores-Mendoza, C. (2008). Working memory and intelligence are highly related constructs, but why? Intelligence, 36(6), 584–606. https://doi.org/10.1016/j.intell.2008.01.002

Colom, R., Abad, F. J., Rebollo, I., & Shih, P. C. (2005). Memory span and general intelligence: A latent-variable approach. Intelligence, 33(6), 623–642. https://doi.org/10.1016/j.intell.2005.05.006

Colom, R., Flores-Mendoza, C., & Rebollo, I. (2003). Working memory and intelligence. Personality and Individual Differences, 34(1), 33–39. https://doi.org/10.1017/9781108770422.022

Colom, R., Privado, J., García, L. F., Estrada, E., Cuevas, L., & Shih, P. C. (2015). Fluid intelligence and working memory capacity: Is the time for working on intelligence problems relevant for explaining their large relationship? Personality and Individual Differences, 79, 75–80. https://doi.org/10.1016/j.paid.2015.01.051

Colom, R., Rubio, V. J., Shih, P. C., & Santacreu, J. (2006). Fluid intelligence, working memory and executive functioning. Psicothema, 18(4), 816–821.

Conway, A. R. A, Cowan, N., Bunting, M. F., Therriault, D. J., & Minkoff, S. R. B. (2002). A latent variable analysis of working memory capacity, short-term memory capacity , processing speed , and general f luid intelligence. Intelligence, 30(2), 163–184. https://doi.org/10.1016/S0160-2896(01)00096-4

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 and Cognition, 34(8), 1754–1768. https://doi.org/10.3758/BF03195936

Dang, C. P., Braeken, J., Colom, R., Ferrer, E., & Liu, C. (2014). Why is working memory related to intelligence? Different contributions from storage and processing. Memory, 22(4), 426–441. https://doi.org/10.1080/09658211.2013.797471

Dehn, M. J. (2017). How working memory enables fluid reasoning. Applied Neuropsychology: Child, 6(3), 245–247. https://doi.org/10.1080/21622965.2017.1317490

Dodson, C. S., Bawa, S., & Krueger, L. E. (2007). Aging, metamemory, and high-confidence errors: A misrecollection account. Psychology and Aging, 22(1), 122–133. https://doi.org/10.1037/0882-7974.22.1.122

Engle, R. W., & Kane, M. J. (2004). Executive attention, working memory capacity, and a two-factor theory of cognitive control. The Psychology of Learning and Motivation, 44, 145–199. https://doi.org/10.1016/S0079-7421(03)44005-X

Engle, R. W., Kane, M. J., & Tuholski, S. W. (1999a). Individual differences in working memory capacity and what they tell us about controlled attention, general fluid intelligence, and functions of the prefrontal cortex. In A. Miyake & P. Shah (Eds.), Models of working memory: Mechanisms of active maintenance and executive control (pp. 102–134). Cambridge University Press. https://doi.org/10.1037/a0021324

Engle, R. W., Tuholski, S. W., Laughlin, J. E., & Conway, A. R. A. (1999b). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology. General, 128(3), 309–331. https://doi.org/10.1037/0096-3445.128.3.309

Eriksson, J., Vogel, E. K., Lansner, A., Bergström, F., & Nyberg, L. (2015). Neurocognitive architecture of working memory. Neuron, 88(1), 33–46. https://doi.org/10.1016/j.neuron.2015.09.020

Faul, F., Erdfelder, E., Lang, A. G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146

Filippi, R., Ceccolini, A., Periche-Tomas, E., & Bright, P. (2020). Developmental trajectories of metacognitive processing and executive function from childhood to older age. Quarterly Journal of Experimental Psychology, 73(11), 1757–1773. https://doi.org/10.1177/1747021820931096

Frischkorn, G. T., & Oberauer, K. (2021). Intelligence test items varying in capacity demands cannot be used to test the causality of working memory capacity for fluid intelligence. Psychonomic Bulletin and Review, 28, 1423–1432. https://doi.org/10.3758/s13423-021-01909-w

Fry, A. F., & Hale, S. (1996). Processing speed, working memory, and fluid intelligence: Evidence for a Developmental Cascade. Psychological Science, 7, 237–241. https://doi.org/10.1111/j.1467-9280.1996.tb00366.x

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(5), 673–679. https://doi.org/10.3758/17.5.673

Gray, J. R., Chabris, C. F., & Braver, T. S. (2003). Neural mechanisms of general fluid intelligence. Nature Neuroscience, 6(3), 316–322. https://doi.org/10.1038/nn1014

Harada, C. N., Love, M. C. N., & Triebel, K. (2013). Normal cognitive aging. Clinics in Geriatric Medicine, 29(4), 737–752. https://doi.org/10.1016/j.cger.2013.07.002.Normal

Harrison, T. L., Shipstead, Z., & Engle, R. W. (2015). Why is working memory capacity related to matrix reasoning tasks? Memory & Cognition, 43(3), 389–396. https://doi.org/10.3758/s13421-014-0473-3

Hartshorne, J. K., & Germine, L. T. (2015). When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the lifespan. Psychological Science, 26(4), 433–443. https://doi.org/10.1177/0956797614567339

Hasher, L., & Zacks, R. T. (1988). Working memory, comprehension, and aging: A review and a new view. In G. H. Bower (Ed.), The psychology of learning and motivation (pp. 193–225). Academic Press. https://doi.org/https://doi.org/10.1016/S0079-7421(08)60041-9.

Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis. A regression-based approach. The Guilford Press.

Hertzog, C., & Dunlosky, J. (2011). Metacognition in later adulthood: Spared monitoring can benefit older adults’ self-regulation. Current Directions in Psychological Science, 20(3), 167–173. https://doi.org/10.1177/0963721411409026.Metacognition

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. https://doi.org/10.1080/09658211003702171

Jaroslawska, A. J., & Rhodes, S. (2019). Adult age differences in the effects of processing on storage in working memory: A meta-analysis. Psychology and Aging, 34(4), 512–530. https://doi.org/10.1037/pag0000358

Jastrzębski, J., Ciechanowska, I., & Chuderski, A. (2018). The strong link between fluid intelligence and working memory cannot be explained away by strategy use. Intelligence, 66, 44–53. https://doi.org/10.1016/j.intell.2017.11.002

Kane, M. J., Conway, A. R. A., Miura, T. K., & Colflesh, G. J. (2007). Working memory, attention control, and the N-back task: A question of construct validity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(3), 615–622. https://doi.org/2007-06096-010 [pii]r10.1037/0278-7393.33.3.615

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(4), 637–671. https://doi.org/10.3758/BF03196323

Kane, M. J., Hambrick, D. Z., & Conway, A. (2005). Working memory capacity and fluid intelligence are strongly related constructs: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131(1), 66–71. https://doi.org/10.1037/0033-2909.131.1.66

Kovacs, K., & Conway, A. R. A. (2016). Process overlap theory: A unified account of the general factor of intelligence. Psychological Inquiry, 27(3), 151–177. https://doi.org/10.1080/1047840X.2016.1153946

Kyllonen, P. C., & Christal, R. E. (1990). Reasoning ability is (little more than) working-memory capacity?! Intelligence, 14(4), 389–433. https://doi.org/10.1016/S0160-2896(05)80012-1

Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863. https://doi.org/10.3389/fpsyg.2013.00863

Lustig, C., Hasher, L., & Zacks, R. T. (2007). Inhibitory deficity theory: Recent developments in a "new view". In D. S. Gorfein & C. M. MacLeod (Eds.), Inhibition in cognition (pp. 145–162). American Psychological Association.

Manard, M., Carabin, D., Jaspar, M., & Collette, F. (2014). Age-related decline in cognitive control: the role of fluid intelligence and processing speed. BMC Neuroscience, 15, Article 7. https://doi.org/10.1186/1471-2202-15-7

Nęcka, E., & Lulewicz, A. (2016). Capacity, control, or both – Which aspects of working memory contribute to children’s general fluid intelligence? Polish Psychological Bulletin, 47(1), 21–28. https://doi.org/10.1515/ppb-2016-0003

Nettelbeck, T., & Burns, N. R. (2010). Processing speed, working memory and reasoning ability from childhood to old age. Personality and Individual Differences, 48(4), 379–384. https://doi.org/10.1016/j.paid.2009.10.032

Oberauer, K., Wilhelm, O., Schulze, R., & Süß, H. M. (2005). Working memory and intelligence – Their correlation and their relation: Comment on Ackerman, Beier, and Boyle (2005). Psychological Bulletin, 131(1), 61–65. https://doi.org/10.1037/0033-2909.131.1.61

Peirce, J. W. (2009). Generating stimuli for neuroscience using PsychoPy. Frontiers in Neuroinformatics, 2, 10. https://doi.org/10.3389/neuro.11.010.2008

Rey-Mermet, A., Gade, M., Souza, A. S., von Bastian, C. C., & Oberauer, K. (2019). Is executive control related to working memory capacity and fluid intelligence? Journal of Experimental Psychology: General, 148(8), 1335–1372. https://doi.org/10.1037/xge0000593

Rose, N. S. (2013). Individual differences in working memory, secondary memory, and fluid intelligence: Evidence from the levels-of-processing span task. Canadian Journal of Experimental Psychology, 67(4), 260–270. https://doi.org/10.1037/a0034351

Salthouse, T. A. (1991). Mediation of adult age differences in cognition by reductions in working memory and speed of processing. Psychological Science, 2(3), 179–183. https://doi.org/10.1111/j.1467-9280.1991.tb00127.x

Salthouse, T. A. (1996a). Constraints on theories of cognitive aging. Psychonomic Bulletin & Review, 3(3), 287–299. https://doi.org/10.3758/BF03210753

Salthouse, T. A. (1996b). The processing-speed theory of adult age differences in cognition. Psychological Review, 103(3), 403–428. https://doi.org/10.1037/0033-295X.103.3.403

Salthouse, T. A. (2009). When does age-related cognitive decline begin? Neurobiology of Aging, 30(4), 507–514. https://doi.org/10.1016/j.neurobiolaging.2008.09.023

Salthouse, T. A. (2011). Consequences of age-related cognitive declines. Annual Review of Psychology, 63, 201–226. https://doi.org/10.1146/annurev-psych-120710-100328

Salthouse, T. A. (2014). Relations between running memory and fluid intelligence. Intelligence, 43, 1–7. https://doi.org/10.1016/j.intell.2013.12.002

Salthouse, T. A. (2016). Continuity of cognitive change across adulthood. Psychonomic Bulletin & Review, 23(3), 932–939. https://doi.org/10.3758/s13423-015-0910-8

Salthouse, T. A., Fristoe, N., McGuthry, K. E., & Hambrick, D. Z. (1998). Relation of task switching to speed, age, and fluid intelligence. Psychology and Aging, 13(3), 445–461. https://doi.org/10.1037/0882-7974.13.3.445

Salthouse, T. A., & Pink, J. E. (2008). Why is working memory related to fluid intelligence? Psychonomic Bulletin & Review, 15(2), 364–371.

Schmiedek, F., Lövdén, M., & Lindenberger, U. (2014). A task is a task is a task: Putting complex span, n-back, and other working memory indicators in psychometric context. Frontiers in Psychology, 5, Article 1475. https://doi.org/10.3389/fpsyg.2014.01475

Schretlen, D., Pearlson, G. D., Anthony, J. C., Aylward, E. H., Augustine, A. M., Davis, A., & Barta, P. (2000). Elucidating the contributions of processing speed, executive ability, and frontal lobe volume to normal age-related differences in fluid intelligence. Journal of the International Neuropsychological Society, 6(1), 52–61. https://doi.org/10.1017/S1355617700611062

Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., Amorim, P., Janavs, J., Weiller, E., Hergueta, T., Baker, R., & Dunbar, G. C. (1998). The Mini-International Neuropsychiatric Interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. The Journal of clinical psychiatry, 59 Suppl 20, 22–57.

Shelton, J. T., Elliott, E. M., Matthews, R. A., Hill, B. D., & Gouvier, W. D. (2010). The relationships of working memory, secondary memory, and general fluid intelligence: Working memory is special. Journal of Experimental Psychology. Learning, Memory, and Cognition, 36(3), 813–820. https://doi.org/10.1037/a0019046

Shipstead, Z., Harrison, T. L., & Engle, R. W. (2016). Working memory capacity and fluid intelligence: Maintenance and disengagement. Perspectives on Psychological Science, 11(6), 771–799. https://doi.org/10.1177/1745691616650647

Shipstead, Z., Redick, T. S., Hicks, K. L., & Engle, R. W. (2012). The scope and control of attention as separate aspects of working memory. Memory, 20(6), 608–628. https://doi.org/10.1080/09658211.2012.691519

Smolen, T., & Chuderski, A. (2015). The quadratic relationship between difficulty of intelligence test items and their correlations with working memory. Frontiers in Psychology, 24(6), Article 1270. https://doi.org/10.3389/fpsyg.2015.01270

Waris, O., Soveri, A., Ahti, M., Hoffing, R. C., Ventus, D., Jaeggi, S. M., Seitz, A. R., & Laine, M. (2017). A latent factor analysis of working memory measures using large-scale data. Frontiers in psychology, 8, Article 1062. https://doi.org/10.3389/fpsyg.2017.01062

Stanislaw, H., & Todorov, N. (1999). Calculation of signal detection theory measures. Behavior Research Methods, Instruments, & Computers, 3(1), 137–149.

Süß, H. M., Oberauer, K., Wittmann, W. W., Wilhelm, O., & Schulze, R. (2002). Working-memory capacity explains reasoning ability – And a little bit more. Intelligence, 30(3), 261–288. https://doi.org/10.1016/S0160-2896(01)00100-3

Thomas, P., Rammsayer, T., Schweizer, K., & Troche, S. (2015). Elucidating the functional relationship between working memory capacity and psychometric intelligence: A fixed-links modeling approach for experimental repeated-measures designs. Advances in Cognitive Psychology, 11(1), 3–13. https://doi.org/10.5709/acp-0166-6

Tucker-Drob, E. M., Brandmaier, A. M., & Lindenberger, U. (2019). Coupled cognitive changes in adulthood: A meta-analysis how many causes are there of aging-related decrements in cognitive functioning? Psychological Bulletin, 145(3), 273–301. https://doi.org/10.1037/bul0000179

Unsworth, N., Fukuda, K., Awh, E., & Vogel, E. K. (2014). Working memory and fluid intelligence: Capacity, attention control, and secondary memory retrieval. Cognitive Psychology, 71, 1–26. https://doi.org/10.1016/j.cogpsych.2014.01.003

Unsworth, N., & Spillers, G. J. (2010). Working memory capacity: Attention control, secondary memory, or both? A direct test of the dual-component model. Journal of Memory and Language, 62(4), 392–406. https://doi.org/10.1016/j.jml.2010.02.001

Unsworth, N., Spillers, G. J., & Brewer, G. A. (2009). Examining the relations among working memory capacity, attention control, and fluid intelligence from a dual-component framework. Psychology Science, 51(4), 388–402.

West, R. (1996). An application of prefrontal cortex function theory to cognitive aging. Psychological Bulletin, 120(2), 272–292. https://doi.org/10.1037/0033-2909.120.2.272

Wiley, J., Jarosz, A. F., Cushen, P. J., & Colflesh, G. J. H. (2011). New rule use drives the relation between working memory capacity and Raven’s Advanced Progressive Matrices. Journal of Experimental Psychology: Learning Memory and Cognition, 37(1), 256–263. https://doi.org/10.1037/a0021613

Zakrzewski, A. C., Sanders, E. C., & Berry, J. M. (2021). Evidence for Age-Equivalent and Task-Dissociative Metacognition in the Memory Domain. Frontiers in psychology, 12, Article 630143. https://doi.org/10.3389/fpsyg.2021.630143