Working memory and intelligence

Transcription

1 Personality and Individual Differences 34 (2003) Working memory and intelligence Roberto Colom a, *, Carmen Flores-Mendoza b, Irene Rebollo a a Facultad de Psicologı a, Universidad Autónoma de Madrid, Madrid, Spain b Departamento de Psicologı a, Universidade Federal de Minas Gerais UFMG, Brazil Received 17 August 2001; received in revised form 29 November 2001; accepted 3 January 2002 Abstract The correlation perspective shows that working memory (WM) is strongly related to psychometric intelligence. Although there are numerous psychometric abilities, there is a powerful single source of variance, namely, g. g Is evidenced by the positive correlation between all psychometric cognitive abilities. The construct of WM distinguishes contents (verbal, numerical, spatial) and operations (storage and processing). However, some studies found a high correlation between several diverse WM tasks, which supports the construct validity of the concept of WM as one general cognitive resource. This study explores the structure of WM drawing on the methodology of intelligence structure research. Then, WM is related to intelligence. One hundred and eighty-seven participants took part in the study. WM was assessed through eight computerized tasks, while intelligence was assessed through the Raven Matrices or the PMA-R. The results show that WM can be considered as one general cognitive resource and that this resource is strongly related with intelligence (r=+0.7). The statement that there is something underlying WM and intelligence is discussed. # 2002 Elsevier Science Ltd. All rights reserved. Keywords: Working memory; Storage; Processing; Intelligence; Raven Progressive Matrices; PMA-R 1. Introduction Working memory (WM) has become a central cognitive construct for theories of psychometric intelligence (Colom, Palacios, Kyllonen, & Juan-Espinosa, submitted for publication; Jensen, 1998; Kyllonen & Christal, 1990; Oberauer, Süss, Schulze, Wilhelm, & Wittmann, 2000; Stauffer, Ree, & Carretta, 1996). Carpenter, Just and colleagues studied individual differences in complex mental activities, like language comprehension (Just & Carpenter, 1992) or performance on the The research referred to in this article was supported by a grant funded by the Spanish Ministerio de Educación y Cultura (Grant No. PB ). * Corresponding author. Tel.: ; fax: address: roberto.colom@uam.es (R. Colom) /02/$ - see front matter # 2002 Elsevier Science Ltd. All rights reserved. PII: S (02)

2 34 R. Colom et al. / Personality and Individual Differences 34 (2003) Raven Progressive Matrices (Carpenter, Just & Shell, 1990). The concept of WM has a strong appeal to these researchers (Just, Carpenter & Keller, 1996). Kyllonen and Christal (1990) reported an influential factor-analytic study claiming that reasoning, measured through psychometric ability tests, is closely related to WM capacity. Confirmatory factor analyses yielded high estimates of the correlation between WM and reasoning ability. Stauffer et al. (1996) found a correlation of between a factor representing general intelligence (g) and a factor representing WM. Colom et al. (submitted for publication) found that a higher-order factor representing g strongly predicts an endogenous first-order factor representing WM. These authors show that WM is not distinguishable from g after the results observed in several confirmatory factor analyses. Thus, the correlation perspective says that the construct of WM is strongly related to some central abilities. However, although g is the single most powerful source of variance evidenced by psychometric tests, there are several doubts about the structure of WM. Is there a powerful single source of variance underlying the variety of WM tasks employed in laboratory research? There is a serious obstacle to answer this question: WM is usually operationalized through a single task, although there are some attempts to operationalize WM drawing on the methodology of intelligence structure research. Thus, for example Oberauer et al. (2000) found that simultaneous storage and transformation of information on WM were inseparable. Furthermore, tasks that involve no transformation of the information measured the same as tasks for simultaneous storage and transformation. The addition of a processing component was not crucial for defining WM. However, they found a separation between spatial and verbal numerical WM tasks. Some relevant questions are: (1) is there a general WM capacity? (2) Are there several specific WM systems distinguished by the function facets or the content domains? (3) Has WM a hierarchical structure with a general resource underlying several specific facets? Intelligence structure research postulates a general factor (g) located at the apex within a hierarchy of several diverse cognitive abilities (Carroll, 1993; Jensen, 1998). Can WM be characterized in the same way? According to Oberauer et al. (2000) the same picture now emerges for the construct of WM capacity. The high positive inter-correlation of all WM tasks used in this study strongly supports the construct validity of the concept of WM as one general cognitive resource (p. 1041, italics added). The present research explores the structure of WM. The correlation between WM and intelligence is also analyzed. WM is operationalized through several diverse computerized tasks, while intelligence is measured through a typical marker. 2. Method 2.1. Participants One hundred and eighty-seven participants took part in the study. Seventy-one were tested in Brazil and 116 were tested in Spain. The Brazilian sample comprised high-school students, while the Spanish sample comprised mostly university undergraduates, but also non-university people. The mean age was (S.D.=3.49, age range=14 47). Sixty-one were males (mean age=17.93, S.D.=4.66) and 121 females (mean age=18.26, S.D.=2.77).

3 R. Colom et al. / Personality and Individual Differences 34 (2003) Table 1 Descriptive statistics, correlation matrix (the residual matrix is shown below the diagonal) and factor matrix Descriptives Correlation matrix Factor matrix Mean S.D Matrix span Letter span Digit span Matrix scan ABC numerical ABCD Gram Alphabet Digit ordering PMA-R Raven Measures and procedures Eight WM tasks were considered. They were computer administered. Raven Matrices (SPM) was the intelligence measure for the Brazilian sample, while PMA-R was the intelligence measure for the Spanish sample (see Appendix for task description). The participants took the WM tasks in a single session lasting 2h and 30 min. However, a rest of 20 min was introduced between a block of tasks and the other. Half of the participants took a block of tasks before the rest period, while the other half took the same block of tasks after that period. The participants were required to take the intelligence test another day Analyses The correlation matrix was submitted to a factor analysis. A MINRES analysis was performed. Then, factor scores were obtained through the Bartlett method. Finally, factor scores were correlated with the scores obtained on the intelligence tests. 3. Results The descriptive statistics, the correlation matrix, and the factor matrix are shown in Table 1. All the correlations are significant at P<0.001 (the residual matrix is shown below the diagonal in Table 1). The inspection of the residual matrix is favorable to the thesis that WM is unitary, because the values are very small. Note that span tasks correlate as high between them as with the remaining tasks. The same can be said for verbal, numerical and figurative WM tasks. The factor analysis extracted one single powerful factor explaining almost 70% of the common variance. The solution converged in five iterations.

4 36 R. Colom et al. / Personality and Individual Differences 34 (2003) Factor scores were obtained after the solution shown in Table 1. These factor scores were correlated with the intelligence tests scores. For the Brazilian sample, the Pearson correlation was (P<0.001, N=62). For the Spanish sample, the Pearson correlation was (P<0.001, N=55). Therefore, the result suggests that a factor representing general WM strongly correlates with a standard measure of intelligence. 4. Discussion This study shows that WM can be considered as one general cognitive resource: all the correlations are high, between +0.6 and +0.8 (Table 1) irrespective of the content domain or the differentiation between span and storage+processing WM tasks. This general cognitive resource is strongly related to intelligence: the factor score corresponding to a statistical representation of general WM is highly correlated with intelligence. Note that the value of the correlation is the same for the Spanish and the Brazilian samples (around +0.7), which increases one s confidence in the result. Therefore, there is a large source of variance common to both WM and intelligence. Intelligence is strongly related with the mental operations claimed in typical WM tasks. The best measures of intelligence involve complex cognitive operations (inductive and deductive reasoning, as well as abstraction). Furthermore, laboratory tasks correlate with psychometric cognitive abilities. Although different laboratory tasks can be devised to elicit different elements of the information processing system, individual differences remain invariant across tasks (Jensen, 1998; Stauffer et al., 1996). These facts could help to explain the high correlation found in this study between a composite measure of WM and measures of intelligence. The high correlation could result from the recruitment of similar mental resources. Functions like monitoring the contents of WM, switching between tasks requiring WM, and so forth, have some component in common. The component could be something that monitors operations performed on WM or something responsible for the maintenance of the goal structure needed to guide processing in any cognitive task. Prabhakaran, Smith, Desmond, Glover, and Gabrieli (1997) discovered strong links between WM and performance on the Raven Matrices. They proposed that the link occurs because both WM tasks and the Raven Matrices involve common neural systems. Raven performance activated not only areas associated with rehearsing and storing domain-specific information, but also areas associated with the executive WM systems. Duncan et al. (2000) compared spatial, verbal, and perceptuo-motor tasks with high-g involvement and matched low-g control tasks. High-g tasks did not show diffuse recruitment of multiple brain regions. Despite very different task content in several high-g and low-g cognitive tasks, lateral frontal recruitment was similar. Their conclusion was that g derives from a specific frontal system important in the control of cognitive actions. In summary, the mental resources claimed for WM tasks and intelligence tests could be related to functions of the frontal cortex. These functions could help to explain the high correlation found in this study. However, future research is needed to find out the germane functions.

5 Acknowledgements R. Colom et al. / Personality and Individual Differences 34 (2003) We thank Arthur Jensen for reviewing a first draft of this article. We also thank Sybil Eysenck for editing the manuscript. A1. Appendix. Task description A1.1. Working memory tasks Matrix span (adapted from Detterman, Mayer, Caruso, Legree, Conners, & e Taylor, 1992): five empty squares are displayed on the middle of the computer screen and one empty square is displayed at the top of the computer screen. After a warning signal, the five empty squares are sequentially filled by a 44 matrix (each square for 1 s). When the next square is filled, the previous display disappears. The inter-stimulus interval was 500 ms. To avoid learning, the sequence of stimuli was presented at random from 15 possible matrices. The participant s task is to remember the appearance of each of the five squares in order to decide where the display that appears at the top of the computer screen was located within the five middle squares. The percentage correct after 75 trials was used as the participant s score. Letter span. Several letters are sequentially displayed on the computer screen. The task begins with three letters, increasing their number until the participant cannot accurately reproduce the sequence using the keyboard (three errors of five attempts). There are two conditions: reproduction in a direct order and reproduction in a reverse order. The mean number of accurately reproduced letters in the direct and the reverse condition is obtained as the participant s score. Digit span. Several single digits are sequentially displayed on the computer screen. The task begins with three digits, increasing their number until the participant cannot accurately reproduce the sequence using the keyboard (three errors of five attempts). There are two conditions: reproduction in a direct order and reproduction in a reverse order. The mean number of accurately reproduced digits in the direct and the reverse condition is obtained as the participant s score. Matrix scan (adapted from Detterman et al., 1992): a warning signal appears for 500 ms, and then two empty squares appear on the middle of the computer screen. One, two or three filled 44 squares (each square for 1.5 s) appear at the top of the computer screen. After this presentation, the square located at the left of the middle of the computer screen is filled by a pattern matrix of black and white squares; the square located at the right of the middle of the computer screen remains unfilled. The participant s task is to decide if the filled square was positive (match) or negative (not match) with some of the filled squares sequentially presented at the top of the computer screen. If this is the case, then the filled square must be selected. The percentage correct after 75 trials (37 trials matching and 38 not matching) was obtained as the participant s score. ABC numerical (adapted from Kyllonen & Christal, 1990): there are two types of items within this task. In the first one, two equations are sequentially displayed (for 1.5 s each). For instance: A=B+1:B=3::A=? The participant is asked to retain the first equation while waiting for the second equation. Then the B value must be mentally replaced in the first equation to compute the value corresponding to A. In the second type of item, three equations are sequentially displayed. For instance: A=B+2:B=C+4:C=1::A=? B=? Only when the third equation is presented

6 38 R. Colom et al. / Personality and Individual Differences 34 (2003) can the participant compute the value of B and then the value of A. Each equation was displayed for 3 s, with a delay of 750 ms. The percentage correct was obtained after 45 trials as the participant s score. ABCD Gram (adapted from Kyllonen & Christal, 1990). Three sentences are sequentially displayed (for 4 s each). The first two sentences refer to the relative position of two single letters, while the third sentence refers to the relative position of the letters considered in the first (pair A and B) and second sentences (pair C and D). For instance: D before C:B not before A::Sentence 1 not before sentence The participant must decide which of four alternatives represents the position of the four letters. For instance: ABCD:DCAB:BADC:CDAB. The percentage correct was obtained after 32trials as the participant s score. Alphabet (Adapted from Craik, 1986). Several words are sequentially displayed on the computer screen (for 1.5 s each, delay of 750 ms). The participant must retain the first letter of each word. After a delay of 2s, she must reproduce through the keyboard the retained letters, but according to their position within the alphabet. The percentage correct after 30 trials was obtained as the participant s score. Digit ordering. Pairs of single digits are sequentially presented on the computer screen (2.5 s each pair, delay of 300 ms). For instance 1 4:27:4 2: The participant s task is to mentally add each pair of digits retaining the result of the summation. Then, she must reproduce through the keyboard the numbers in ascending order. In the example, the reproduced sequence must be: The percentage correct after 30 trials was obtained as the participant s score. A1.2. Intelligence tests PMA-R. This is the letter series test from the Primary Mental Abilities Test (Thurstone, 1938). The participant is asked to select a letter taking into account the inductive relationships established between several letters serving as the item domain. The test includes 30 items and has a time limit of 6 min. Standard Progressive Matrices. This is the well-known test designed by J. Raven (CEPA, 1993). The SPM includes 60 items. It was administered without a time limit. References Carpenter, P. A., Just, M. A., & Shell, P. (1990). What one intelligence test measures: a theoretical account of the processing in the Raven progressive matrices test Psychological review, 97(3), Carroll, J. B. (1993). Human cognitive abilities. Cambridge: Cambridge University Press. Centro editor de psicologia aplicada (1993). Testes das Matrizes Progressivas de Raven Escala Geral. Adapted by Francisco Campos; Revised by Suzana Ezequiel da Cunha. RJ: CEPA. Colom, R., Palacios, A., Kyllonen, P. C., & Juan-Espinosa, M. (submitted for publication). Working memory is not distinguishable from g. Craik, F. I. M. (1986). A functional account of age differences in memory. In F. Kilx, & H. Hagendorf (Eds.), Human memory and cognitive capabilities (pp ). North-Holland: Elsevier. Detterman, D. K., Mayer, J. D., Caruso, D. R., Legree, P. J., Conners, F. A., & e Taylor, R. (1992). Assessment of basic cognitive abilities in relation to cognitive deficits American Journal on Mental Retardation, 97(3), Duncan, J., Seitz, R., Kolodny, J., Bor, D., Herzog, H., Ahmed, A., Newell, F., & Emslie, H. (2000). A neural basis for general intelligence Science, 289(21 July),

7 R. Colom et al. / Personality and Individual Differences 34 (2003) Jensen, A. (1998). The g factor. Westport: Praeger. Just, M., & Carpenter, P. (1992). A capacity theory of comprehension: individual differences in working memory Psychological review, 99(1), Just, M., Carpenter, P., & Keller, T. (1996). The theory of comprehension: new frontiers of evidence and arguments Psychological review, 103(4), Kyllonen, P., & Christal, R. (1990). Reasoning ability is (little more than) working memory capacity? Intelligence, 14, Oberauer, K., Su ss, H., Schulze, R., Wilhelm, O., & Wittmann, W. (2000). Working memory capacity facets of a cognitive ability construct Personality and Individual Differences, 29(6), Prabhakaran, V., Smith, J., Desmond, J., Glover, G., & Gabrieli, J. (1997). Neural substrates of fluid reasoning: an fmri study of neocortical activation during performance of the Raven s Progressive Matrices test Cognitive Psychology, 33, Stauffer, J., Ree, M., & Carretta, T. (1996). Cognitive-components tests are not much more than g: an extension of Kyllonen s analyses The Journal of General Psychology, 123(3), Thurstone, L. L. (1938). Primary mental abilities Psychometric Monographs, 1.