Intelligence = Working Memory?

The cognitive functions that predict intelligence have been most often identified as working memory and processing speed. As stressed by Deary (2012), they represent an interim level of reductionism between the psychometric construct of intelligence (g) and biological intelligence. Furthermore, they provide explanations for the relation between g and activated brain areas visualized with neuroimaging techniques (e.g., fMRI, PET), although often such explanations do not go beyond cheap talk.  In this blog we will focus on working memory (WM). As stated by Colom et al. (2008), WM and intelligence are highly related constructs, but we still do not know why. 

Working memory –  short term memory

Working memory relates to a system that temporarily holds or manipulates information that we have just experienced or retrieved from long-term memory (Baddeley, 2012). The WM concept developed from an earlier one called short term memory; both terms are still used interchangeably. As put forward by Baddeley (2012), short-term-memory is often used in relation to its literal meaning: keeping a limited amount of information in mind for a short period of time. In contrast, working memory not only refers to storage of information, but also to manipulation of this information.

Probably the most popular and enduring conceptualization of WM is the one proposed by Baddeley and Hitch (1974) – the multi component model of WM. In its original form it consisted of 3 components: the central executive and two slave systems, the visuo-spatial sketch pad and the phonological loop. To increase the explanatory power of the model a third storage system was introduced – the episodic buffer, a temporary interface between short and long-term memory. In yet another updated version, the episodic buffer received a more central position: it was still defined as a passive system but with the crucial function of integrating information from different sources and modalities into chunks or episodes (Baddeley, 2012).

 Baddeley and Hitch (1974)

More recently, state-based models of working memory have gained prominence (D’Esposito & Postle, 2015). These models assume that allocation of attention to different representations in long term memory (either semantic, sensory or motor) governs temporary retention in working memory. The most well-known among these models is Cowan’s embedded-processes model in which working memory is defined as a cognitive condition that retains information in an accessible state (Cowan et al., 2005). Activation occurs in long-term memory, is temporary, and fades unless maintained by verbal rehearsal or continued attention. In the core of this new theoretical framework are two constructs: focus of attention and its capacity – scope of attention (Cowan et al., 2005).  

Cowan et al. (2005)

In state-based models as well as in the multi component model, attention is the process that is used to explain the main functions of working memory: bringing information from perception into the focus of attention – encoding, keeping this information in an active state – maintenance (removal of interfering information), and bringing it back to attention when needed – retrieval (Jonides et al., 2008).

Intelligence and WM

Psychometric research has revealed a positive relationship between performance on tasks of working memory and fluid intelligence, with correlations ranging from 0.60 to 0.90 (Buehner et al., 2005). Different working memory features were suggested as being central for intelligent reasoning.

Cowan et al. (2005) proposed that the scope-of-attention that does not include any processing component showed rather high correlation with intelligence. In the same direction points a large scale study by Colom et al. (2008), which revealed that simple short term storage largely accounted for the relation between intelligence and working memory.

In contrast, Engle (Engle et al., 1999; Unsworth & Engle, 2007), suggested that executive functioning, especially the control of attention over interference and conflict is the central process contributing to the shared variance with intelligence.  This attentional process is best assessed with complex span tasks requiring participants to engage in processing activity unrelated to the memory task. For instance in the operation span task, participants solve math problems while trying to remember unrelated items (letters).

IS    (8/2) – 1 = 1     YES     NO        A

IS    (6*1) – 2 = 4    YES     NO         R

IS    (8*2) – 5 = 11  YES     NO        C

IS    (8/4) + 5 = 7     YES     NO        D 

The respondent has to indicate if the equation is correct (yes or no) and to remember the letters subsequently presented. When prompted, the individual is required to recall the letters in the correct serial order (e.g., A, R, C, and D).

Yet another process identified as crucial for the intelligence-WM overlap was relational integration, defined as the ability to build new relations between elements thereby creating structural representations (Oberauer et al., 2008). For instance in the kinship task verbal descriptions of the relationship between two people (e.g., “Anne is Barbara’s sister”, “Barbara is Charlie’s mother”) are presented. Participants are asked to indicate the implied relationship between two of the people mentioned in several consecutive sentences (e.g., “Anne is Charlie’s?” the correct answer is “aunt”). 

A central problem of research into the relationship between problem solving and working memory is the immense diversity of tasks used to measure WM. Some of these tasks resemble those used in intelligence tests, which would mean that the criterion is predicted by another instance of the criterion. Especially the tasks assumed to measure relational integration have been criticized along these lines.

Neurocognitive underpinning of WM

From a neurocognitive perspective the fronto–parietal network has been associated with performance on working memory tasks. It has been further suggested that the central executive function of WM is linked to the frontal lobes, whereas the WM storage component is associated with parietal areas (Champod & Petrides, 2010; Sauseng et al., 2010; D’Esposito & Postle, 2015). Based on evidence from several brain imaging studies, the left intraparietal sulcus has been identified as a unique area responsible for amodal or multimodal storage of information (Cowan et al., 2011). Support for a fronto–parietal distinction related to the WM functions of processing and storing of information comes also from research employing neuroelectric brain imaging methods. Research indicates that theta oscillations are related to working memory processes. Furthermore, there is evidence to suggest that theta synchronizes during WM processes and serves as a gating mechanism, providing optimal neural conditions for specific processing (Sauseng et al., 2010).

It can be concluded that contemporary cognitive research of working memory has favored state-based models because they accommodate well to neuroscience data. The focus of attention can explain the two main functions of working memory: temporary storage of information and maintenance of stored information. The lateral prefrontal cortex, important for attentional control represents top-down influence on posterior sensory regions reactivating cortical memory traces – the memories themselves (Sreenivasan et al., 2014). The similarity with neural models of intelligence is obvious, but not unexpected given that working memory has sometimes been proposed as virtually synonymous with intelligence (e.g., Martínez et al., 2011). 

References

Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. A. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (pp. 47–89). New York: Academic press.

Baddeley, A. (2012). Working Memory: Theories, Models, and Controversies. Annual Review of Psychology, 63(1), 1–29. http://doi.org/10.1146/annurev-psych-120710-100422

Buehner, M., Krumm, S., & Pick, M. (2005). Reasoning=working memory≠attention. Intelligence, 33(3), 251–272. http://doi.org/10.1016/j.intell.2005.01.002

Champod, A. S., & Petrides, M. (2010). Dissociation within the Frontoparietal Network in Verbal Working Memory: A Parametric Functional Magnetic Resonance Imaging Study. Journal of Neuroscience, 30(10), 3849–3856. http://doi.org/10.1523/JNEUROSCI.0097-10.2010

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. http://doi.org/10.1016/j.intell.2008.01.002

Cowan, N., Elliott, E. M., Scott Saults, J., Morey, C. C., Mattox, S., Hismjatullina, A., & Conway, A. R. A. (2005). On the capacity of attention: Its estimation and its role in working memory and cognitive aptitudes. Cognitive Psychology, 51(1), 42–100. http://doi.org/10.1016/j.cogpsych.2004.12.001

Cowan, N., Li, D., Moffitt, A., Becker, T. M., Martin, E. A., Saults, J. S., & Christ, S. E. (2011). A neural region of abstract working memory. Journal of Cognitive Neuroscience, 23(10), 2852–2863.

Deary, I. J. (2012). Intelligence. Annual Review of Psychology, 63(1), 453–482. http://doi.org/10.1146/annurev-psych-120710-100353

D’Esposito, M., & Postle, B. R. (2015). The Cognitive Neuroscience of Working Memory. Annual Review of Psychology, 66(1), 115–142. http://doi.org/10.1146/annurev-psych-010814-015031

Engle, R.W., Tuholski, S.W., Laughlin, J.E., & Conway, A.R.A. (1999). Working memory, shortterm memory and general fluid intelligence: A latent variable approach. Journal of Experimental Psychology: General,128, 309–331.

Jonides, J., Lewis, R. L., Nee, D. E., Lustig, C. A., Berman, M. G., & Moore, K. S. (2008). The mind and brain of short-term memory. Annual Review of Psychology, 59, 193–224. http://doi.org/10.1146/annurev.psych.59.103006.093615

Martínez, K., Burgaleta, M., Román, F. J., Escorial, S., Shih, P. C., Quiroga, M. Á., & Colom, R. (2011). Can fluid intelligence be reduced to “simple” short-term storage? Intelligence, 39(6), 473–480. http://doi.org/10.1016/j.intell.2011.09.001

Oberauer, K., Süβ, H.-M., Wilhelm, O., & Wittmann, W. W. (2008). Which working memory functions predict intelligence? Intelligence, 36(6), 641–652. http://doi.org/10.1016/j.intell.2008.01.007

Sauseng, P., Griesmayr, B., Freunberger, R., & Klimesch, W. (2010). Control mechanisms in working memory: A possible function of EEG theta oscillations. Neuroscience & Biobehavioral Reviews, 34(7), 1015–1022. http://doi.org/10.1016/j.neubiorev.2009.12.006

Sreenivasan, K. K., Curtis, C. E., & D’Esposito, M. (2014). Revisiting the role of persistent neural activity during working memory. Trends in Cognitive Sciences, 18(2), 82–89. http://doi.org/10.1016/j.tics.2013.12.001

Unsworth, N., and Engle, R. W. (2007). The nature of individual differences in working memory capacity: Active maintenance in primary memory and controlled search from secondary memory. Psychological Review, 114, 104−132.