Temporal Grouping Effects in Verbal And Musical Short-term Memory: Is Serial Order Representation Domain-general? Part 1

Abstract

The question of the domain-general versus domain-specific nature of the serial order mechanisms involved in short-term memory is currently under debate. The present study aimed to address this question through the study of temporal grouping effects in short-term memory tasks with musical material, a domain that has received little interest so far. 

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The goal was to determine whether positional coding-currently the best account of grouping effect in verbal short-term memory-represents a viable mechanism to explain grouping effects in the musical domain. 

In the first experiment, non-musicians performed serial reconstruction of 6-tone sequences, where half of the sequences were grouped by groups of three items and the other half presented at a regular pace. 

The overall data pattern suggests that temporal grouping exerts on tone sequence reconstruction the same effects as in the verbal domain, except for ordering errors which were not characterised by the typical increase of interpositions. 

This pattern has been replicated in two additional experiments with verbal material, using the same grouping structure as in the musical experiment. 

The findings support that verbal and musical short-term memory domains are characterized by similar temporal grouping effects for the recall of 6-item lists grouped by three, but it also suggests the existence of boundary conditions to observe an increase in interposition errors predicted by positional theories.

Keywords

Serial order; music; verbal; grouping; domain-general; working memory.

Daily life activities such as remembering a phone number, having a discussion, or listening attentively to a piece of music all require the processing of serially organized information that unfolds over time and draws on short-term memory (STM) resources. 

The question of whether the mechanisms contributing to the maintenance of serially organized memoranda are domain-general or domain-specific is currently under debate in the STM literature (Hurlstone et al., 2014; Jones et al., 1995; Logie et al., 2016; Majerus, 2013; Soemer & Saito, 2016; Vandierendonck, 2016). 

Previous research comparing serial order STM for verbal and visuospatial items supported the view that the representation of serial order in STM is supported by domain-general mechanisms (for a review, see Hurlstone et al., 2014). 

However, the extent to which the domain-generality hypothesis applies to STM for music remains unanswered. Given its inherent rhythmic and sequential structure, music represents an appropriate candidate to further our understanding of the ordering mechanisms involved in STM, as well as to address the question of the domain generality of these mechanisms.

Contrary to the verbal domain, there are only a few models of musical STM (see Berz, 1995; Ockelford, 2007), none of which provide a comprehensive account of the processes responsible for representing the serial order of musical sequences. 

For instance, Ockelford (2007) suggested that serial order is coded in musical working memory through the action of a tagging mechanism in which each item serves as a retrieving cue for the next item (for more details regarding the notion of tagging, see Kieras et al., 1999). 

However, to the best of our knowledge, there is no direct empirical evidence that such a tagging mechanism plays a role in the representation of musical order in STM. Moreover, the tagging notion relies on a chaining account of serial order representation that has been challenged by a recent study on serial order STM for music (see Gorin et al., 2018a).

Several serial order effects considered benchmark phenomena in the verbal STM domain (Hurlstone et al., 2014; Lewandowsky & Farrell, 2008) have also been observed in a recent series of musical STM experiments (Gorin et al., 2016, 2018a, 2018b). 

The authors interpreted these results as evidence for the existence of domain-general processes to represent serial order information in the musical domain. This interpretation is also in line with the notion that verbal and musical STM systems involve common sequential processes even though they rely on different representational stores (Williamson et al., 2010). 

Thus, these results suggest that basic ordering principles work in the two domains. In addition, they justify the use of verbal order theories as a framework for exploring the nature of ordering mechanisms in musical STM and assessing the generality of these mechanisms. The best account of benchmark order phenomenon in the verbal domain comes from models relying on positional codes to represent serial order information (see, for example, Brown et al., 2000; Burgess & Hitch, 1999; Hartley et al., 2016; Henson, 1998; Lewandowsky & Farrell, 2008). 

In positional models, serial order is represented by associations between items and independent markers representing positions. The main strength of this class of models is its ability to account for temporal grouping effects. Temporal grouping is characterized by the insertion of additional pauses between some items during sequence presentation, inducing the perception of temporally distinct sub-groups of items. 

With verbal material, such manipulations lead to the well-replicated phenomena that constraint serial order models of STM (see Frankish, 1985, 1989; Hartley et al., 2016; Henson, 1996; Hitch et al., 1996; Maybery et al., 2002; Ng & Maybery, 2002, 2005; Ryan, 1969a, 1969b). 

For grouped sequences, a recall advantage, as well as a multiply-bowed shape serial position curve, are usually observed. An increase in the proportion of interposition errors, or between-group displacements of items that keep their initial within-group serial position, is also characteristic of the recall of grouped sequences. 

For instance, in a 6-item sequence composed of two groups of three items, an interposition error would be to recall the item from Position 2 (i.e., Position 2 in the first group) at Position 5 (Position 2 in the second group). 

The study of temporal grouping effects is of particular interest to help determine the precise nature of serial order representation in STM. For example, models relying on ordinal codes such as activation gradients to represent serial order (see, for example, Farrell & Lewandowsky, 2002; Page & Norris, 1998) can accommodate the main effects induced by temporal grouping manipulations, the recall advantage, and the scalloped serial position curve. 

However, to account for a wider range of effects induced by temporal grouping (i.e., an increase in interposition errors in addition to the recall advantage and the scalloped appearance of the serial position curve), it is necessary to assume the existence of positional codes. Positional models accommodate the increase in interposition errors by representing serial order hierarchically. Items are associated with positional markers representing within-group positions, as well as markers representing the position of the groups/items in the sequence (see Brown et al., 2000; Burgess & Hitch, 1999; Hartley et al., 2016; Henson, 1998). 

The hierarchical representation of serial order makes the items in grouped sequences more distinctive than in ungrouped ones, accounting for the recall advantage and the multiply-bowed shape of the serial position curve. Moreover, this hierarchical representation of serial order increases the similarity between items in different groups that share the same within-group position, thus accounting for the increase in interposition errors observed in grouped sequences (see Figure 1 markers for a graphical example). 

In the musical domain, a great deal of work has been devoted to studying the psychophysical and musical components influencing how adult listeners process and maintain musical information in STM (for a review, see Deutsch, 2013a, 2013b). 

However, little is known about the cognitive mechanisms involved in the short-term maintenance of musical information, particularly those required to represent and maintain the order of a series of tones. In non-musicians, serial order reconstruction of verbal and musical sequences is characterized by similar serial order effects, suggesting that verbal ordering principles could be extended to the musical domain (Gorin et al., 2018a). 

In another study using a serial recognition task, researchers observed temporal grouping effects that are comparable to those usually observed in verbal STM tasks, suggesting that the positional markers described in verbal STM models of serial order could play a role in STM for music (Gorin et al., 2016). 

More precisely, the authors showed that in non-musicians, the rate of correct serial recognition for matching probes is higher for grouped versus ungrouped sequences, and that recognition as a function of position adopted a shape reflecting the grouping structure used in the experiment, replicating previous results obtained with musicians (Deutsch, 1980).

However, the conclusions drawn by Gorin et al. (2018b) are limited as the assessment of temporal grouping on interposition errors was not possible due to the use of a recognition procedure. At the same time, there is evidence of the existence of interposition-like errors in serial-order production tasks requiring experts to retrieve and play short musical excerpts on the piano from memory (Mathias et al., 2015). 

In comparison to shorter musical excerpts, for which the similarity between elements sharing the same metrical accent (strong or weak) in the sequence is reduced, longer musical excerpts are characterized by increased long-distance transpositions between positions with the same metrical accent. Interestingly, this phenomenon can be accounted for by a model of musical sequence production assuming that to-be-produced musical events are represented hierarchically (see Mathias et al., 2015; Palmer & Pfordresher, 2003; Pfordresher et al., 2007). 

This model represents musical events according to their serial position and their metrical status strength, which is similar to the hierarchical coding of serial order proposed in positional models of verbal STM described above (see Brown et al., 2000; Burgess & Hitch, 1999; Hartley et al., 2016; Henson, 1998). As mentioned earlier, a growing body of evidence shows that benchmark serial phenomena characterizing verbal STM are also observed in visuospatial STM tasks (for a review, see Hurlstone et al., 2014), and to some extent in the musical domain as well (Gorin et al., 2018b). 

This evidence supports the first account that the processing of serial order information is supported by processes shared across domains. At the same time, some authors consider that the presence of similar ordering phenomena across domains is also compatible with the existence of domain-specific mechanisms, but with functional similarities (see, for example, Logie et al., 2016; Saito et al., 2008). 

Indeed, observing the same serial order phenomena across STM domains is compatible with both a single domain-general mechanism and with domain-specific mechanisms coding serial order in a similar manner, and only this second account assumes that the existence of functionally similar domain-specific mechanisms can account for both differences and similarities across domains (Logie et al., 2016). 

Another account would be that serial order mechanisms are shared across modalities (e.g., auditory or visual) but not specific domains (e.g., verbal, visual, and musical). In other words, we could envisage that both verbal and musical materials similarly draw on auditory STM resources, the latter being underpinned by auditory domain-general processes responsible for coding serial order information for both types of material. 

This is in line with a recent proposal from Hartley et al. (2016) suggesting that cross-domain sequential principles are responsible for processing order information but function in parallel with domain-specific mechanisms responsible for perceptual input. 

They proposed a stimulus-driven mechanism responsible for processing and encoding order information in auditory–verbal sequences based on the activity of neuronal oscillators tracking amplitude variations of the speech envelope at different timescales. Interestingly, it has been suggested that the encoding of rhythmic features in both speech and music could be governed by a similar stimulus-driven oscillatory mechanism (see, for example, Musacchia et al., 2014). 

Thus, considering the evidence for domain-specificity in processing musical information (Peretz & Coltheart, 2003; Zatorre et al., 2002), a more parsimonious account would be that domain-specific features interact with domain-general ordering mechanisms (see Majerus, 2013).

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