This article on working memory illustrates how cognitive abilities such as fluid reasoning depend heavily on working memory.

By Milton J. Dehn
January 2017
Copyrighted Material

Humans rely on fluid reasoning (Gf) whenever they draw inferences, identify relationships, comprehend implications, solve problems, generalize, and apply other forms of reasoning, especially when solving unfamiliar problems. Individuals with higher levels of Gf tend to acquire more knowledge and at faster rates. Consequently, Gf has strong correlations with crystallized intelligence (Gc) academic
knowledge, and attaining expertise. Kyllonen and Christal (1990) proposed that working memory (WM) accounts for most of the individual differences in Gf. It is therefore important to understand the relations between Gf and WM and to consider any common underlying latent traits. For practitioners who work with children, such understanding may alter the interpretation of neuropsychological assessment results and lead to more effective treatment recommendations.

In 1941, Raymond Cattell concluded that Spearman’s g was best explained by splitting g into general fluid intelligence (now referred to as fluid reasoning) and general crystallized intelligence. The definition of the fluid reasoning (Gf) construct varies somewhat, but generally Gf is thought of as the ability to solve problems using inductive and deductive reasoning, especially when dealing with novel
situations. Later, John Horn added other cognitive abilities to Cattell’s theory, but Gf and Gc remained as the primary abilities. Strong support for Horn-Cattell theory was provided by Carroll in 1993 when he completed his meta-analysis of numerous 20 th century studies of intelligence testing. Carroll also confirmed that induction and deduction are “narrow” Gf abilities, while adding quantitative reasoning to
the mix. Interestingly, Carroll recognized possible relations between Gf and WM as indicated by the final statement in his chapter on fluid reasoning: “Also to be further investigated is the possibility, proposed by Kyllonen and Christal (1990), that capacity of working memory is centrally involved in many reasoning tasks” (p. 247).

Research on and measurement of WM has expanded greatly in the past two decades. Basically, WM is the ability to hold information in mind while processing the same or other information. WM plays a supervisory role over auditory and visual-spatial short-term storage components. As the amount of cognitive processing (referred to as cognitive load) supported by WM increases, it becomes more difficult
to hold all of the relevant information in short-term storage until the processing goal is accomplished. Increasing cognitive load also slows down the processing that WM is enabling. It is well established (Dehn, 2008) that WM plays a crucial role in all aspects of academic learning. Accordingly, children with WM deficits are at high risk for learning problems and disorders. In addition to WM, Gf plays an
important role in academic learning and performance.

To perform many skills, both Gf (a form of cognitive load) and WM are required, as evidenced by several studies that have reported high correlations between Gf and WM capacity. In research reviewed by Kane and Engle (2002), correlations between WM span and Gf tasks ranged from .60 and .90, with a median of .72. The prevalent explanation for this strong relationship is that WM provides the mental
processing “workspace” that Gf needs in order to function. WM also retains the information that Gf is using to complete a reasoning task. Specifically, WM holds the information in a span of awareness while the elements of the problem are apprehended, the relationships among the elements are identified, and the implications of the relationships are worked out. For example, comprehending text requires adequate WM to hold the decoded pieces of information until Gf draws a conclusion or inference. Although it may appear that Gf and WM are identical constructs, the consensus is that they are not (Kyllonen & Christal, 1990). Despite Gf’s apparent dependence on WM, they can be differentiated.

Support for Gf’s dependence on WM and also for differentiation is provided by studies which discovered the influence that time constraints have on the relationship. For example, Chuderski and Necka (2012) reported that when subjects were allowed to complete a Raven’s Progressive Matrices test without time limits, WM accounted for only 38% of the variance in Gf. However, when strict time limits
were applied, WM explained all of the variance in Gf. Apparently, WM capacity is not as strong a contributor to Gf when reasoning tasks are untimed. For instance, if one has time to process the information slowly and start over as needed, Gf can be accomplished with minimal support from WM. However, when time is of the essence, adequate to strong WM capacity facilitates Gf by allowing the
maintenance and processing of relevant information without having to backtrack or start over. Chuderski and Necka’s findings suggest that we may be seriously underestimating Gf ability by utilizing assessment tasks that have strict time limits, especially when examinees have a low WM span. In such cases it might be prudent to compare an examinee’s timed and untimed performance on a Gf task. Nonetheless, highly speeded tests may be valid indicators of the ability to cope with the demands of a complex, real-world environment in which cognitive load is high.

What accounts for the influence of speed on the Gf-WM relation? The underlying latent trait is most likely some aspect of the executive ability to control attention. Undoubtedly, Gf and other cognitive tasks can be completed quicker when an individual is able to maintain focused attention. When focus is lost and iteration is necessary, it will take longer to complete a cognitive task. Thus, the high correlations
between Gf and WM under timed conditions probably result from some aspects of controlled attention (Engle, Tuholski, Laughlin, & Conway, 1999). Additional support for this claim is provided by Salthouse and Pink (2008) who discovered that the relation between WM and Gf is not dependent on the amount of information that must be maintained or on the complexity of the mental processes involved. With these two variables eliminated, it seems safer to conclude that the ability to maintain focused attention is what mediates the Gf-WM relation.

The specific attentional control function that makes the difference during Gf processing is thought to be inhibition, which includes the abilities to resist distracting thoughts, inhibit responses, and control interference (Kane & Engle, 2002). Inhibition and interference control allow attention to remain focused and to shift efficiently as needed. Studies examining the relations between attentional control and WM
have previously speculated that inhibition is the underlying latent trait (Holmes et al., 2014). This hypothesis is consistent with the observation that children (whose inhibitory abilities are less developed) score lower on Gf tests than adolescents and adults even though children as young as six years of age can effectively reason (Ferrer, O’Hare, & Bunge, 2009). Less developed inhibitory control is also
characteristic of individuals with ADHD who, not surprisingly, perform more poorly on fluid reasoning tasks (Tamm & Juranek, 2012). Moreover, cognitive training programs (with ADHD and typically developing participants) targeting attention, WM, and/or inhibition have found a positive impact on Gf even though the construct was not specifically targeted by the training intervention (Tamm & Juranek).

Neuroanatomy can also account for the intertwining of Gf, WM, inhibition, and executive control of attention (Burgess, Gray, Conway, & Brayer, 2011) Neuroimaging (fMRI) studies have confirmed that the same regions of the prefrontal cortex (PFC) are active during Gf and WM functioning (Kane & Engle, 2002). Neuroimaging studies have also demonstrated that a region in the anterior prefrontal cortex, known
as the rostrolateral prefrontal cortex (RLPFC), is active while examinees complete Raven’s Progressive Matrices tasks (Ferrer et al., 2009). Furthermore, dorsolateral PFC (dPFC) circuitry is known to be a critical structure for executive attention functions. The dPFC also serves as a source of inhibitory control over other brain functions. Consequently, any delayed development or impairment of PFC structures will
impact inhibition, attentional control, WM, and Gf. The apparent role of the PFC during Gf processing is to maintain information in WM in a highly active, easily accessible state. This maintenance occurs when attention is focused, shifts as needed, and inhibitory control resists interference and distraction (Engle et al., 1999).

Despite the nonreasoning latent traits (focused attention and inhibition) that underlie performance on WM and Gf tasks, Gf should remain as one of the valuable constructs that explain human cognitive abilities and development. Neither WM nor inhibitory control should be allowed to supplant Gf, given that Gf can function semi-independently of WM when time constraints are reduced. However, low Gf and
WM test performance by ADHD subjects and young children should be viewed differently. It may not be Gf or WM span that they are lacking.


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