Tracy Alloway,University of Durham
Glenda Andrews, Griffith University Australia
Valérie Camos, University of Burgundy
Nelson Cowan, University of Missouri
Andreas Demetriou, University of Cyprus
Graham Hitch, University of York
Chris Jarrold, University of Bristol
Juan Pascual Leone, York University Toronto
Anik de Ribaupierre, University of Geneva
Lee Swanson, University of California
John Towse, University of Lancaster
I argue that a main maturational-growth component of working memory is mental (endogenous) attention. Mental attention must be contrasted with perceptual (focal, selective, scanning) attention. Perceptual attention is influenced mostly by learning, but mental attention expresses maturational growth, i.e., “development proper” (or learning potential) as Piaget and other constructivists have understood it. In facilitating situations both sorts of attention work together. In misleading situations, however, schemes are in conflict and compete, and situational-perceptual cues often are misleading: Mental- attention strategies must be mobilized to control or override task-irrelevant perceptual strategies that initially dominate. Developmental intelligence, the growth with age of fluid intelligence, is a result of maturational growth in mental attention. Mental attention often is not clearly recognized because it results from the dynamic/dialectical synthesis of four “hidden” organismic variables. In my theory these are called hidden (“hardware”) operators: M-capacity, I-interruption (i.e., attentional inhibition), a neo-Gestaltist Field (F- ) factor that causes cognitive closure, and attentional executive functions (when they are properly defined as organismic processes). This model of mental attention is a central part of the neoPiagetian theory of constructive operators (TCO), which also contains other organismic factors such as learning operators (i.e., logical-structural or L operator, and content-associative or C operator), etc. The TCO examines how maturational growth of mental attention interacts with the various other organismic factors to produce cognitive development. I will summarize this theory focusing on mental attention and the M-operator, and will show with the help of various tasks across content domains, how this theoretical approach permits (using a theory-based task analysis) a new kind of fundamental measurement of mental-processing complexity (i.e., working memory, mental attention). This fundamental measurement method exhibits parameter (i.e., measurement) invariance across content domains as diverse as visuospatial, verbal, linguistic etc., within misleading situations. The heuristic importance of these methods of task analysis and fundamental measurement is emphasized.
Working memory is now a central construct in cognitive science and development. It is used on the one hand as a specific experimental model that comprises a particular cognitive architecture and which can be subjected to fine-grained or micro-level experimental analysis of its cognitive components and processes. Dual task methodologies are especially prominent here. On the other hand working memory capacity is deployed as a more general construct for exploring and understanding individual differences in cognition. Such macro-level approaches involve greater attention to psychometric issues, and the emphasis is often on establishing the factors that mediate the relationship between working memory and criterion cognitive skills. I will argue that we can gain the greatest benefit from viewing these two perspectives as complementary and potentially symbiotic. I will draw on empirical evidence from children and adults to exemplify this argument.
Considerable evidence suggests that the development of rehearsal undergoes a qualitative shift around the age of seven years; children aged less than seven appear not to engage in spontaneous subvocal rehearsal of to-be-remembered verbal information in serial recall tasks, whereas such rehearsal is apparent in older individuals. However, there is little corresponding evidence of a qualitative change in individuals’ working memory performance around this age. This talk explores two potential explanations of this apparent discrepancy. First, it may be that the previous evidence suggesting that young children do not rehearse is flawed in some way, and I present data that address this issue by looking at probed recall and at correlations between memory span and speech rate in young children and in individuals with learning difficulties functioning below the 7-year level. Second, there is a relative lack of empirical data on the working memory abilities of children aged younger than seven years, and I present details of a recent study that compares the impact of rehearsal status on working memory abilities in 6- and 8-year old children. Taken together, the data are consistent with a shift in rehearsal strategy around age seven, but suggest this shift may be less discrete than previously thought, and that children may be able to engage in some forms of maintenance activity prior to this age.
According to Baddeley & Hitch (1974) working memory consists of a set of limited capacity interacting subsystems and control processes for altering the flow of information and plays a central role in cognition. The original model specified two limited capacity temporary stores - a phonological loop and a visuo-spatial sketchpad specialised for storing verbal and visuo-spatial material respectively. A third component, a limited capacity central executive directs the way the stores are used. This model was offered as a broad, simplistic account of working memory in mature adults. Although it said nothing about developmental change, the model has nevertheless generated some interesting insights into developmental differences that constrain accounts of development. In turn, studies of working memory in children have generated theoretical implications for the adult model. These themes are illustrated by considering children's performance in standard short-term memory (STM) tasks and long-term learning that involve the storage of visual and verbal materials.
It has long been recognised that use of subvocal rehearsal in STM tasks is absent in early childhood. According to the Baddeley & Hitch (1974) model, rehearsal is a function of the phonological loop and access to the phonological loop is automatic for auditory-verbal stimuli but depends on active subvocalization for nameable visual stimuli. Consistent with this account, older (rehearsing) children show evidence of using the phonological loop in STM regardless of whether stimuli are spoken words or nameable pictures. In contrast, younger (non-rehearsing) children show evidence of using the phonological loop in STM for spoken words but use the visuo-spatial sketchpad for nameable pictures. Older children also show good transfer of long- term sequence learning when the stimuli are switched from spoken words to corresponding pictures or from pictures to words. In contrast, younger children show little or no such transfer. Taken together these observations are consistent with the multi-component model and have implications for the interface with long-term memory and for the detailed operation of the temporary stores. The results may also have broader practical implications for young children's ability to generalise learning in educational settings.
The results of three studies will be reviewed in my presentation. Two studies will focus on the relationship between growth in WM and its influence on Math and Reading performance. The third study reviews preliminary data on strategy instruction and working memory performance.
Study 1-math disabilities
The influence of cognitive growth in working memory (WM) on mathematical problem solution accuracy was examined in elementary school children (N=353) at risk and not at risk for serious math problem solving difficulties. A battery of tests was administered that assessed problem solving, achievement, and cognitive processing (WM, inhibition, naming speed, phonological coding) in children in first, second and third grade across three testing waves. The results were that: (a) children identified as at risk for serious math problem solving difficulties in wave 1 showed less growth rate and lower levels of performance on cognitive measures than children not at risk; (b) fluid intelligence and two components of WM (central executive, visual-spatial sketchpad) in wave 1 (year 1) predicted wave 3 word problem solving solution accuracy; and (c) growth in the central executive and phonological storage component of WM was related to growth in solution accuracy.
Study 2-reading disabilities
A three-year longitudinal study determined whether (a) subgroups of children with reading disabilities (RD) (children with RD-only, children with both reading and arithmetic deficits, and low verbal IQ readers) and skilled readers varied in working memory (WM) and short-term memory (STM) growth, and (b) whether growth in an executive system and/or phonological storage system mediated growth in reading performance. A battery of memory and reading measures were administered to 84 children (ages 11 to 17) across three testing waves spaced one year apart. The results showed that skilled readers yielded higher WM growth estimates than the RD groups. No significant differentiation between subgroups of children with RD on growth measures emerged. The Hierarchical Linear Modeling showed that WM (controlled attention), rather than STM (phonological loop), was related to growth in reading comprehension and reading fluency. The results suggest that deficient growth in the executive component of WM underlies RD.
Study 3-pilot data on intervention training
Two experiments investigated the relationship between working memory (WM), strategy knowledge and training in children with reading disabilities (RD). Experiment 1 examined the relationship between strategy knowledge and WM performance in children (mean chronological age 10.8 yrs) as a function of initial, gain, and maintenance conditions. Three findings emerged: (1) verbal and visual-spatial WM performance in children without RD was superior to children with RD, (2) stable strategy choices, rather than specific strategy choices, predicted WM span, and (3) WM performance under cued conditions contributed significant variance to predictions of reading comprehension. Experiment 2 examined the effects of strategy instruction on WM performance. Children (Mean CA 11.2 yrs) were randomly assigned to rehearsal strategy instruction or control conditions to improve performance on an operation span task. Children with and without RD improved on the operation span task as a result of strategy training as well as showed transfer to listening span performance. However, the correlations between WM and reading before and after strategy training were statistically comparable suggesting that strategies play a minor role in predicting reading performance. Overall, these results suggest that stable strategy choices, cued performance, and strategy instruction bolster WM performance, but capacity limitations underlie RD children’s performance.
Working memory refers to the capacity to store and manipulate information for brief periods of time and is closely associated with various aspects of learning. The primary aim of the present talk is to understand the extent to which deficits in subcomponents of working memory may differentiate these groups as measured by verbal and visuo- spatial tasks. The present review discusses the profile of working memory in different groups of typical children as well as atypical children: those with dyslexia, Specific Language Impairment (SLI), Developmental Coordination Disorder (DCD), Attention Deficit and Hyperactive Disorder (ADHD), and Autistic Spectrum Disorder (ASD). We report findings confirming differential memory profiles on the basis of developmental disorders. Specifically, language impairments (dyslexia and SLI) were associated with selective deficits in verbal short-term and working memory, while motor impairments (DCD) with selective deficits in visuo-spatial short-term and working memory. Children with attentional problems were selectively impaired in verbal working memory, visuo- spatial short-term and working memory, but not verbal short-term memory. The profile of children with ASD mirrored those with ADHD in that they had deficits in verbal short- term memory but not in any other memory component. The implications of these findings are discussed in light of support for learning.
In Relational Complexity (RC) Theory (Halford, 1993; Halford, Wilson & Phillips, 1998) higher cognitive processes such as reasoning and some executive functions are conceptualized as involving relational processing. Cognitive development occurs as children acquire the capacity to process relations of higher complexity. Relational complexity corresponds to the number of variables that are required to perform each step in a cognitive task. Thus unary relations involve a single variable and are processed at a median age of 1 year. Binary relations involve two variables and are processed at a median age of 2 years. Ternary relations involve three variables and are processed at a median age of 5 years. Quaternary relations involve four variables and are processed at a median age of 11 years. There is an approximate correspondence between these levels of complexity and Piaget’s four major stages of cognitive development. RC theory incorporates principles for quantifying task complexity and the resulting processing load. One principle is that complexity analyses are applied to information that is being processed in the current step of the task rather than to information that is being stored for future processing. Another principle is that tasks cannot be segmented into separate, less complex steps if the variables to be considered interact. These principles will be demonstrated. RC theory will be discussed in relation to (i) new conceptions of working memory which emphasis dynamic mapping to a coordinate system, (ii) recent findings from cognitive neuroscience that demonstrate the involvement of specific sub-regions of the prefrontal cortex in relational processing, and (iii) the proposed distinction between cool and hot executive functions. Relevant empirical data will be presented.
We have conducted several studies aiming to understand how processing affects the measurement of working memory capacity in children and adults. One study shows that the childhood development of working memory for a set of object colors is influenced by the process of filtering out objects defined as irrelevant according to shape. Another study suggests that the childhood development of working memory for associations between verbal and spatial information depends largely on verbal rehearsal, and only secondarily on basic capacity. We show how various processes (attentional filtering, rehearsal, and chunking) complicate the attempt to examine basic working memory capacity, which nevertheless does appear to increase to an important extent with development.
Increase in working memory capacity is often mentioned as a main source of cognitive development (Case, 1985; Pascual-Leone, 1970; Halford, 1993). Recently, we proposed a new model of working memory, the Time-Based Resource-Sharing model (TBRS ; Barrouillet, Bernardin, & Camos, 2004 ; Barrouillet & Camos, 2007). This model assumes that, during complex working memory span tasks, attention is frequently and surreptiously switched from processing to reactivate decaying memory traces before their complete loss. According to the TBRS model, three main sources of the development of working memory are identified : the amount of available attention, the phenomenon of decay, and the efficiency of the mechanism of reactivation of memory traces through rapid attentional switching. The first part of this talk will report previous studies that documented the impact of age-related changes in the amount of attention (Barrouillet & Camos, 2001; Barrouillet & Gavens, 2004). In a second part, two series of experiments will focus on the age-related changes in the capacity to refresh and reactivate memory items in working memory span tasks. The first series will show the increase in efficiency of the refreshment mechanism from 8 to adolescence. The second series will explore the qualitative change that occurs between 5 and 7 in maintenance mechanisms.
This address will first outline a general model of the structure and development of the human mind. The model integrates the traditions of Piagetian, the psychometric, and the information processing tradition. The model claims that the mind involves general purpose processes underlying processing efficiency and representational capacity, general inferential processes underlying information management, general executive and self-awareness processes underlying self-understanding and self-regulation, and domain-specific processes underlying understanding and problem solving in different domains.
We will then summarize on a series of studies which aimed to highlight the development and dynamic relations between these processes during development. These studies involved participants from 4 to 60 years of age who were examined by tasks addressed to various aspects of processing efficiency (i.e., speed of processing, perceptual discrimination, perceptual control, and conceptual control), working memory, reasoning in different domains, and self- awareness. Using structural equation modelling we show that these processes are organized hierarchically so that simpler and more general processes are embedded in more complex processes. There are four main levels of organization: (1) processing efficiency, including general efficiency reflected by speed and more specialized executive processes reflected by control; (2) representational processes, involving sheer storage and organizational processes underlying information storage and recall; (3) reasoning, involving general inferential mechanisms; (4) domain-specific processes. Processes within organizational levels are hierarchically organized so that speed influences control, storage influences executive working memory, and general inferential processes influence reasoning in different domains. In addition, each of these levels involves processes germane to itself. The three levels are also hierarchically structured as general processing efficiency predicts working memory later in time and this, in turn, predicts general reasoning and domain-specific reasoning even latter. The weaving of these processes into stage-like ensembles of reasoning and problem solving is also explicated. The implications for the general theory of intelligence and intellectual development are discussed.
Strikingly similar hypotheses were advanced, in the last two decades, in different fields of developmental psychology to explain age differences in working memory capacity, and more generally, in cognitive resources, whether in childhood or in older adulthood. They all refer to the influence of a few general mechanisms such as activation (or speed of processing), and/or inhibition: An increase (decrease) in the quantity of information that can be activated and in the efficiency in inhibiting irrelevant information is thus considered to account for the increase (decrease) in working memory capacity with age. For instance, Pascual-Leone’s model proposes that developmental change in attentional capacity consists in an increase both in mental power for activating information and in inhibition. As concerns cognitive aging, Hasher and Zacks suggested that less efficient inhibitory processes account for a lower WM capacity in older adults, while processing speed is considered by Salthouse to explain a large part of age- related variance in WM span tasks. Moreover, working memory is considered both by child developmentalists and by cognitive aging researchers to account for age differences in other cognitive tasks, leading to the hypothesis that most of cognitive development, or of cognitive aging, is accounted for by changes in working memory capacity. Yet, few studies have attempted to compare developmental differences across the lifespan, using the same tasks; this is the main goal of this presentation
Three sets of studies will be briefly presented. First, a large multivariate study, in which working memory, inhibition and processing speed tasks were administered to children, young and older adults, showed that inhibition and speed of processing accounted together for a large part of age differences in working memory capacity; however, inhibition played a larger role to explain age differences between young and older adults whereas speed of processing accounted for more age differences between children and young adults. A second study showed that working memory capacity explained a very large part of age-related variance in the Piagetian Balance task, in children. Finally, a third study demonstrated that working memory and speed of processing accounted for most age differences in the Raven’s task, both in children and in adults. Altogether, our data indicated that the same processes underlie age differences in working memory capacity across the lifespan, but vary in their relative contribution. Also, working memory capacity accounts for age differences in other cognitive tasks both in children and in adults, but to a different extent.