The Time-Based Resource Sharing Model of Barrouillet and Camos

Cross-domain associations

1.3. The Time-Based Resource Sharing Model of Barrouillet and Camos

The time-based resource sharing (TBRS) model originated from an in depth analysis of the factors that could explain the underlying mechanism within complex span tasks. These complex span tasks are typical working memory tasks as they combine within one task a maintenance and a processing component. The most traditional complex span tasks concern the reading span (Daneman & Carpenter, 1980), the counting span (Case, 1985) and the operation span (Turner & Engle, 1989). Within these tasks, the maintenance and processing components are completely intertwined. One is for example asked to read a phrase, count dots on a card or execute a mental calculation and to maintain the last word of the phrase, the number of dots or the solution to the calculation. Following is presented a new phrase, dots card or mental calculation for which one has to maintain once again the last word, the number of dots or the calculation solution. After a series of phrases, dot cards or calculations, the maintained words, number of dots or calculation solutions have to be recalled. Series of increasing number of phrases, dot cards or calculations are presented and a given participant’s span corresponds to the highest number of words, number of dots or calculation solutions he or she can still recall.

It had been observed that the more attention the processing task required, the lower the maintenance capacities were (e.g., Anderson, Reder, & Lebiere, 1996; Case, Kurland, &

Goldberg, 1982), corroborating the suggested interplay between maintenance and processing activities. While this interplay is generally accepted within working memory theories,

different accounts have been presented to fund this interplay. From a developmental point of view, Case et al. (1982) proposed a sharing of a central resource. They posited that each individual owns a “total processing space” with a fixed capacity that does not change with age. This mental space has to be devoted to processing activities as well as to maintenance.

Processing activities occupy a certain amount of the total processing space, the “operation space”, and the remaining space is available for maintenance activities, the “short term storage space”. Older children’s increase in span as measured by these complex span task would be the result of more efficient processing, resulting in less of the total processing space occupied by the operation space leaving available a larger short term storage space. This hypothesis was however challenged by Towse and Hitch (1995; Towse, Hitch, & Hutton, 1998), who esteemed that it is rather the duration of the retention interval that explains the

developmental increase within complex span tasks, and not the amount of resources one has to put within the processing task. They argued that during the retention interval between the presentation of the information and its recall, memory traces decay as a function of time.

Longer retention intervals lead thus to more decay and hence lower span scores. They agreed with Case that as children grow older their processing efficiency increases. Yet, according to Towse and Hitch, it is not the resulting increase in short term storage space that explains the increase in span, but the shorter retention intervals. Within these complex span tasks, memory items have to be maintained over a retention interval which corresponds to the processing time. Higher processing efficiency results in shorter processing times and this implies thus shorter retention intervals. Thus, instead of accepting the sharing of a central resource as proposed by Case, Towse and Hitch prioritized an explanation in terms of decay and task switching.

Barrouillet and Camos (2001) were not convinced by the experimental design used by Towse and Hitch (1995). They contrasted anew the resource sharing and the decay

hypotheses, still within a developmental perspective. They manipulated both the cognitive demand of the processing task as well as its duration. To do so, they slightly changed the paradigm of the counting or calculation span. Instead of having the children maintain the number of dots counted or the calculation solutions, they inserted letters for further recall in between the dots or calculation cards (see Figure 1.12). Barrouillet and Camos compared this version of the counting or calculation span with a complex span task in which participants had to pronounce “baba” as the processing activity and maintain the same letters as in the

counting or calculation span. Repeatedly articulating “baba” is not assumed to place a considerable demand on cognitive resources, in contrast to calculating or counting. The comparison between a counting or calculation span and a baba span allowed hence for a comparison in terms of cognitive demands. The temporal parameters were controlled by setting up the baba span in such a way that the duration of its processing intervals matched the duration of the processing intervals in the counting or calculation intervals (see Figure 1.12).

Any difference observed between the counting or calculation span and the baba span could consequently be attributed to cognitive load only, as the retention intervals in both tasks were equal. While no difference was found between the counting span and the baba span, favoring the decay hypothesis, a clear difference was found between the calculation span and the baba span, favoring the resource sharing hypothesis. Evidence for both hypotheses was thus found.

Barrouillet et al. (2004) further investigated these constraints on working memory, this time within an adult population. Towse et al. (1998) had proposed a task switching model which assumes participants to switch to the maintenance of items after each processing phase.

Barrouillet et al. (2004) reasoned that it might as well be the case that brief attentional switches to the memory items take place while performing the processing activities. This would occur as soon as the task allows it. For example within a mental calculation, a brief attentional switch would be possible after each intermediate step. This idea was based on the fact that, in the calculation task used in the study described above (Barrouillet & Camos, 2001), despite the relatively long time (around ten seconds) it took the children to execute the calculations, the decay of the memory traces was not at all dramatic. Barrouillet et al. (2004) proposed hence a time-based resource sharing model, a model accounting for both resource sharing and temporal decay. The model relies on the following assumptions. It is first of all assumed that both the maintenance and processing of information rely on the same resource, i.e., attention. This attentional resource has thus to be shared. Secondly, memory traces are prone to temporal decay. As soon as attention is switched away from these traces, decay acts upon these traces. To counteract this decay, one has to refresh these traces through attentional focusing, a concept borrowed from Cowan (e.g., Cowan, 1988, 1995). Thirdly, maintenance and processing activities are constrained by a central bottleneck that relies on attention (Pashler, 1998). Only one activity and in addition on one representation can be performed at the same time. As a result, when the bottleneck is occupied by processing activities, the memory traces suffer from temporal decay. A rapid switching mechanism between

maintenance and processing is hence supposed to counteract the complete loss of memory traces. The idea of a bottleneck to explain working memory performance had already been suggested by Baddeley and Hitch (1974) who stated that processing activities may be

postponed for memory consolidation. The TBRS model generalized this proposition however to all working memory activities.

The model was subsequently submitted to a stringent test of these assumptions (Barrouillet et al., 2004). In order to allow for a strict control of temporal parameters, a new type of complex span task was designed: the computer-paced complex span task. Within the existing complex span tasks, the processing task was always executed in a self-paced way.

Participants performed each processing item at their own rhythm and once finished, a new processing item was presented. Barrouillet and Camos (2001) had already slightly changed the traditional paradigm by inserting maintenance items instead of maintaining components of the processing phase itself. Within the new computer-paced complex span tasks, letters to be maintained were alternated with processing phases for which the temporal characteristics were strictly controlled and which could contain several items to be processed. These computer-paced processing phases allowed hence for a strict temporal control, as well as a control of the cognitive demands of the processing task. For example, one could present either three or six processing items within a processing phase without changing the time allowed to process them (see Figure 1.13, panel a and b). This means that the duration of the retention interval remains the same, while the resources needed to perform the processing task are increased in case of six items. As relatively more of the time will be spent on processing within the processing phase with six items as compared to three, more decay of the memory traces will occur and less time will be available to refresh these memory traces. In case of equal retention intervals, the TBRS predicts thus lower memory performance when more processing items have to be treated. Inversely, one could present three processing items while allowing more or less time to process them (see Figure 1.13, panel a and c). Strictly spoken, the cognitive resources implied are the same but these are however spread over a different retention interval. The same amount of decay will thus act on the memory traces but less time will be available to counteract this decay in the condition with the shortest retention interval (panel c). In case of equal processing demands, the TBRS predicts that shorter retention intervals will lead to lower memory spans. Panel d of Figure 1.13 represents the use of a processing task that necessitates more time. Compared to panel a, the same number of processing items is to be performed within the same time interval. Due to the longer time it takes to execute the processing task in panel d, more decay of the memory traces will take place and additionally less time is available to refresh these traces. The TBRS predicts hence lower memory performance for processing tasks that necessitates more time.

Figure 1.13: Manipulation of the cognitive load according to the TBRS model.

a) baseline cognitive load b) increase of cognitive load by increasing the number of processing items c) increase of cognitive load by reducing the available time d) increase of the cognitive load by increasing the duration time of the processing items.

Based on these principles, the TBRS proposed to define the cognitive load of a task as the time during which it captures attention divided by the time allowed to perform it. The calculation of the cognitive load of a task can only be estimated approximatively, as it is impossible to temporally separate the processes that are executed based on attentional processes and those that are not. The time it takes from the presentation of the item until the response provides nevertheless an estimation of the cognitive load of a task. The estimation of the cognitive load can then be approached in two ways. It can be approximated beforehand based on the mean reaction times to perform a processing task. If one knows that the mean reaction time to treat a processing item is for example 400 milliseconds and one allows the participant 1000 milliseconds to execute this treatment, then the cognitive load would be .4.

The cognitive load of the four examples given in Figure 1.13 would hence correspond to a) 400/1000 = .4 b) 400/500 = .8 c) 400/600 = .667 d) 700/1000 = .7. This is however a rough approximation as the actual time a person takes to treat a processing item will vary around this mean. It is possible to calculate a more exact approximation of the cognitive load

afterwards based on the actual time participants took to perform the processing activity (thus for each person separately, e.g., Barrouillet et al., 2004; Vergauwe et al., 2010). In that case, one has to sum the actual processing times and divide them through the sum of the allowed times. In the rare cases where no response was produced, this has been considered as if no processing had taken place and a response time of zero was hen attributed.

Studies designed within the TBRS framework have shown a linear relationship between complex span performance and cognitive load (see Figure 1.14). This linear relationship was first reported in 2004 (Barrouillet et al.) and has ever since been replicated on many occasions (e.g., Barrouillet et al., 2007; Vergauwe, Barrouillet, & Camos, 2009;

Vergauwe et al., 2010). In the results shown in Figure 1.14, participants performed a complex span task with letters as memoranda and a location or parity task as processing task. In case of the location task, participants had to decide whether a digit was shown in the upper or lower half of the screen. In case of the parity task, participants had to decide whether the digit shown was odd or even. Participants were shown series of letters of increasing length, intertwined with processing phases of 6400 ms. Within these processing phases, four, six or eight digits were shown, equally spread over the interval of the processing phase. As

explained above, increasing the number of processing items in a same time interval increases cognitive load (see Figure 1.13, line a and b). Barrouillet et al. (2007) calculated an

approximation of the cognitive load per participant in the six different conditions: processing task (parity or location) * number of processing items (four, six or eight). For each condition, the mean cognitive load was plotted against the mean span score. Figure 1.14 shows that there was no difference observed between the two processing tasks. Hence independently of the kind of processing task (as long as it depends on attention), the mean span score linearly follows from the cognitive load.

According to the TBRS model, attention is thus the main resource working memory functioning depends on. A further development of the model has however shown that next to attentional focusing, maintenance of verbal information can as well be accomplished by a mechanism of articulatory rehearsal, corresponding to the one described by Baddeley

(Baddeley, 1986; Baddeley & Hitch, 1974). Camos, Lagner, and Barrouillet (2009) used a complex span task for which they could manipulate the attentional demand or articulatory suppression. In a first experiment, participants had to maintain letters while performing an attention demanding task aloud. The cognitive load of the task was manipulated by having participants read mathematical problems (low cognitive load) or solve them (high cognitive load). Increasing the cognitive load resulted in a clear decrease in memory performance. In a second experiment, participants once again had to maintain letters. As processing task, they had to judge the spatial location of a square (upper or lower half of the screen). This could be done aloud (articulatory suppression condition) or silently (no articulatory suppression condition). The results showed that the articulatory suppression condition clearly resulted in lower memory performance. Two further experiments orthogonally varied the cognitive load and articulatory suppression, showing that both effects add up. Camos et al. (2009) showed thus clear evidence that the maintenance of verbal information could be achieved by either attentional refreshing or verbal rehearsal.

As one might have noticed from the preceding explanations, the TBRS- model has especially focused on the functional aspects of working memory. Concerning the

representation of information within the working memory structure, the TBRS model has mainly made reference to already existing frameworks. The model proposes an architecture that regroups the best of existing frameworks. Although its structure is hence not

revolutionary, it is able to account for a wide range of phenomena.

1.3.1. The representation of single features

For several years, the TBRS model has remained rather vague regarding the

architectural framework that could best underpin its premises. Reference has been made to the multi-component model after its inclusion of the episodic buffer (Baddeley, 2000) as well as to the structure of models like Cowan’s embedded process model (1999) that suppose short term memory to be the activated part of long term memory. Recently, a personalized

structural framework incorporating the entirety of TBRS assumptions was however presented (Figure 1.15, Barrouillet & Camos, 2015). As one can see, the structure of the model has remained quite faithful to the multi-component model of 2000. Several adaptations have however been implemented in order to customize the architecture in the light of empirical evidence gathered within a TBRS context. A main difference concerns the fact that according

to the TBRS model, all working memory representations are held within a central

maintenance buffer, called the episodic buffer. The multi-component model disposes of an episodic buffer as well, but it is however not assumed to be the main structure to maintain single features, as these are maintained in the domain-specific buffers. According to the TBRS model, approximately four items can be maintained by this episodic buffer. Items in the episodic buffer can be built with information retrieved from sensory buffers or from long-term memory. The sensory buffers included within the model are the verbal and visuo-spatial buffer, but the authors leave open the possibility to include other kinds of sensory buffers.

While four items can be present in this central episodic buffer, only one item at a time can be taken care of. It is the goal buffer that decides whether the attended item has to be

processed/transformed or maintained in a state of activation for further use. This action is then accomplished by the production system. This production system can be compared to the central executive in the multi-component model.

Information within working memory is thus represented within the episodic buffer.

Features in the sensory buffers are considered as only very short term perceptual

representations. A consolidation process is needed in order to prevent these representations from decay. It is this consolidation process that transfers these representations to the episodic buffer and makes them available within a working memory context. This consolidation process does not only strengthen the representations, it also enriches the representation with information from other sensory buffers and long-term memory. Sometimes only one

characteristic is of importance and needs to be maintained. Its working memory

representation within the episodic buffer consists nevertheless of much more information than this single characteristic.

Due to the functioning of working memory, the representations are prone to decay and interference as soon as attention is switched away. The process to counteract loss of the memory trace is a reconstruction rather than a retrieval process. That is, some of the contextual factors may have been lost or altered while attention was diverted, and other characteristics may be added throughout the reconstruction of the memory trace. The temporary representation of a feature is thus never exactly the same on two occasions.

Although we continue to use the term single features to refer to a single characteristic that is of importance, each representation within the episodic buffer contains thus a certain number of characteristics.

1.3.2. The representation of feature associations

Within the TBRS model, all working memory representations are maintained within the episodic buffer, both the single features and the feature associations. As explained in the preceding paragraph, according to the TBRS model, each representation contains a number of characteristics of different kinds of modalities. Then what constitutes the difference between

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