Temporal Grouping Effects in Verbal And Musical Short-term Memory: Is Serial Order Representation Domain-general? Part 5

Results

As in the previous experiment, the analyses were performed with JASP (JASP Team, 2018), using the same default values for priors and applying the same analysis plan. 

Planning and memory are two extremely important abilities in human thinking. A plan is an arrangement of a series of steps designed to achieve a goal, a desire, or a task. Memory is an important ability to perceive, retain, and restore information, and is a way to acquire knowledge, experience, and skills.

Planning and memory are inextricably linked. We need to remember our plans, goals, and steps to be more efficient and organized in achieving them. Likewise, we need planning to help us improve our memory. For example, to improve their memory, many people use some planning techniques, such as the memory palace method, repeated exercises, and memory games.

Planning and memory also reinforce each other. When making a plan, you need to recall and organize past experiences, and you also need to record the things and details to be completed. In this way, we can better remember the content and steps of the plan. In the process of executing the plan, we continue to consolidate and deepen our memory of the content of the plan, which also allows us to execute the plan more smoothly.

In general, planning and memory are intertwined and mutually reinforcing abilities, and are the core of human intelligence. Only through proper planning skills and high-level memory skills can we live and work more efficiently and orderly. It can be seen that we need to improve memory, and Cistanche deserticola can significantly improve memory, because Cistanche deserticola has antioxidant, anti-inflammatory, and anti-aging effects, which can help reduce oxidation and inflammatory reactions in the brain, thereby protecting the health of the nervous system. In addition, Cistanche deserticola can also promote the growth and repair of nerve cells, thus enhancing the connectivity and function of neural networks. These effects can help improve memory, learning, and thinking speed, and may also prevent the development of cognitive dysfunction and neurodegenerative diseases.

Click Know to improve short-term memory

For each type of analysis (i.e., serial position curves, transposition gradients, and response latencies), data from trials presenting phonologically dissimilar and similar letters were analyzed separately.

Serial position curves. We computed the proportion of correct recall as a function of serial position and temporal grouping across all the dissimilar trials for each participant. We then performed a 2 × 6 repeated-measures ANOVA with serial position (1–6) and grouping condition (grouped vs. ungrouped) factors (see top-left of Figure 4). 

The results revealed that the best model was the model with the two main effects, preferred over the second best, the full model, by a factor of 4.44 (see "Serial position curves" rows in Table 3). 

This was confirmed by an analysis of the effect that provided decisive evidence for the two main effects (Grouping: BFInclusion=1.43e14; Position: BFInclusion=1.43e14), but anecdotal evidence against the presence of interaction (BFInclusion=0.90).

The same analysis was performed with data from trials presenting phonologically similar letters, revealing that the best model was the full model and was preferred over the second-best model by a factor of 1.67 (see top-right of Figure 4). 

Given the ambiguous evidence for preferring the best model over the second best model (see "Serial position curves" rows in Table 4), we performed an analysis of the effect. The results yielded decisive evidence in favor of the two main effects (Grouping: BFInclusion=2.70e11; Position: BFInclusion=6.67e13) and moderate evidence in favor of the existence of an interaction (BFInclusion=6.70). 

Transposition gradients. Note that for the analysis of transposition errors, we removed the participants that produced no error in at least one of the four experimental conditions, leading to a sample of 77 participants. For each participant, we computed the proportion of errors as a function of absolute distance displacement and temporal grouping across all the dissimilar errors. 

Then, we analyzed the data with a 2 × 2 × 5 repeated-measures ANOVA with absolute transposition distance (1–5) and grouping condition (grouped vs. ungrouped) as factors (see middle-left of Figure 4). The results provided strong evidence in favor of the best model containing only the effect of distance, being preferred over the second-best model with the two main effects by a factor of 12.92 (see "Transposition gradients" rows in Table 3). 

The same analysis has been reproduced with data from trials with phonologically similar letters (see middle-right of Figure 4). This provided strong evidence that the best model is the full model that was preferred over the second best model containing only the effect of distance by a factor of 1.02 (see "Transposition gradients" rows in Table 4). 

As the results were ambiguous, we performed an analysis of effects that revealed decisive and moderate evidence supporting the presence of an effect of distance (BFInclusion = ∞) and an interaction between distance and grouping (BFInclusion = 3.78), respectively. 

Given the moderate support for the interaction, we analyzed the rate of adjacent transpositions and interposition errors with a directed Bayesian paired samples t-test (adjacent errors: H1 = ungrouped > grouped; interpositions: H1 = ungrouped < grouped), as in the previous experiment. We obtained strong evidence against both an increase in interposition errors (BF01 = 12.21) and a decrease in adjacent transposition (BF01 = 25.02) in grouped trials.

Then, as in the previous experiment, we analyzed the rate of within-group and between-group transposition errors, distinguishing for the latest between interposition errors, group boundary transpositions, and other between-group transpositions (all comparisons involved undirected Bayesian paired samples t-test with default prior). 

As shown in Table 5, there is strong evidence that temporal grouping in dissimilar trials induced an increase in within-group transposition but a decrease in transpositions involving items at the group boundary. At the same time, there was moderate evidence supporting an absence of difference between the rates of interposition errors and other between-group transpositions. R

Regarding similar trials, the results reported in Table 6 show the same pattern as for dissimilar trials, except that there was strong evidence for a difference in the rate of other between-group transpositions.

Response latencies. For each participant, we determined the mean response latency for correct recall in dissimilar trials as a function of temporal grouping and serial position. The data were next analyzed via a 2 × 6 repeated-measures ANOVA with serial position (1–6) and grouping condition (grouped vs. ungrouped) factors (see bottom left of Figure 4). 

The results yielded decisive evidence in favor of the full model containing the two main effects and their interaction, this model is preferred over the second-best model by a factor of 2.93e8 (see Table 3). 

The same analysis has been performed with similar trials, leading to the same outcome (see bottom-right of Figure 4); the full model being the best and preferred over the second best by a factor of 2.16e6 (see Table 4).

Discussion

In Experiment 2, we observed that regardless of the phonological similarity of the material, grouped sequences were better recalled and characterized by a scalloped serial position curve compared with ungrouped sequences. 

In addition, the typical pattern of response latencies with a latency peak for the first item of the second group was found. However, in line with the results reported in Experiment 1 with musical material, no increase in interposition errors was observed in grouped sequences for both phonologically similar and dissimilar trials. 

At the same time, it should be noted that the performance can be seen as a ceiling and that, in such a context, it is difficult to exclude the possibility that the absence of an increase in interposition errors in the grouped sequences is simply because the overall number of errors was too low. 

To determine whether the lack of increase in interpositions is due to the ceiling or is specific to the 2 × 3 grouping structure used in Experiment 2, we conducted an additional experiment replicating the procedure used in Experiment 2 but with an end-of-list distractor aimed at reducing recall performance while keeping the same sequence structure.4

Experiment 3: serial recall of verbal order with end-of-list distractor task

The goal of this experiment was to test whether the absence of an increase in interpositions in grouped sequences in Experiment 2 was due to the very low number of errors induced by a ceiling effect or specific to the use of lists of 6 items grouped by three. 

The procedure was the same as in Experiment 2, except that the presentation of each list was followed by a parity judgment task asking participants to judge whether the numbers presented on the screen were even or odd. 

The purpose of this distracting task was to reduce the precision of the recall-and therefore increase the number of ordering errors-while keeping the same grouping structure as in Experiments 1 and 2.

Method

Sampling plan. Due to the COVID-19 pandemic situation, the experiment was conducted entirely online. As with Experiment 2, the sampling design was to let as many students and non-students from our participant pool take part in the study as possible. Participants. The experiment was approved by the ethics committee of the Faculty of Psychology of UniDistance Suisse. 

Participants were recruited through the UniDistance Suisse participant pool, which is composed mainly of German-speaking psychology students and German-speaking non-students interested in participating in experiments. Students received partial course credit for their participation and non-students participated in the experiment voluntarily. 

A total of 79 participants completed the online experiment. After excluding 14 participants who met the exclusion criteria, the final sample consisted of 55 participants (gender: 47 females and 8 males; age in years: M=35.83, SD=9.43). Exclusion criteria. We excluded participants with any learning or neurological disorder as well as those who were not fluent in German. 

Participants were also excluded from the analysis based on their performance in the end-of-list distracting task, to ensure that they were actively performing the task. Therefore, any participant with less than 60% accuracy in the end-of-list distraction task was excluded from the analysis. Stimuli. The stimuli were the same as in Experiment 2 but with two notable exceptions. 

First, due to the addition of a distraction task at the end of the list, the duration of a trial was increased compared with Experiment 2. Therefore, to keep the task to a similar duration as in Experiment 2, the total number of lists presented to the participant was 102 (25% phonologically similar and ungrouped, 25% phonologically similar and grouped, 25% phonologically dissimilar and ungrouped, and 25% phonologically dissimilar and grouped). Second, because the participants were German speakers, the phonologically dissimilar letters consisted of V, Y, X, Z, J, and Q, and the phonologically similar letters consisted of B, C, D, G, P, and T.

Procedure. The procedure was the same as in Experiment 2, except for the addition of the end-of-list distractor. After the last item was presented, a blank screen was presented for 1,000ms, followed by eight digits presented in the center of the screen (700ms on and 200ms off). 

Participants were instructed to press the S key as quickly as possible when the digit presented was even and to press L when the digit presented on the screen was odd. They were informed that they could press the keys during the presentation of the numbers as well as during the blank screen after each number was presented. The numbers were randomly selected with replacements. 

After the end-list distractor, the recall procedure proceeded as described in Experiment 2. During the training session, participants received feedback after each trial regarding the number of letters correctly recalled and the number of correct parity judgments. 

No feedback was given during the experimental trials. The task was programmed with lab.js, a free and open-source online study builder (Henninger et al., 2019), and implemented on a protected server with PHP. Participants accessed the experiment with a custom URL.

Hypotheses

The data from Experiments 1 and 2 support the view that temporal grouping has similar effects on musical and verbal STM. It is noteworthy that the observed pattern in both domains indicates that for lists of 6 items grouped into threes, there is no increase in interposition errors, contrary to what would be predicted from serial order models that best account for temporal grouping effects in STM (see, for example, Brown et al., 2000; Burgess & Hitch, 1999; Hartley et al., 2016; Henson, 1998). 

At the same time, the presence of a ceiling effect in recall accuracy in Experiment 2 limits this interpretation for the verbal domain. By adding an end-of-list distractor, this experiment aims to confirm the data from Experiment 2, namely that verbal lists of 6 items grouped into threes do not lead to an increase in interposition errors, as also observed in Experiment 1 with musical material. 

In other words, this experiment aimed to test whether verbal and musical STM are supported by common ordering mechanisms. The experiment also aimed to verify that the observation of increased interposition errors in recall of grouped lists is characteristic of longer sequences and/or sequences with more groups (e.g., a 3 × 3 grouping structure). 

If this hypothesis is correct, we would expect to observe the usual temporal grouping effects, except for the increase in interposition errors. As in Experiment 2, there was no specific prediction regarding the phonological similarity effect and its interaction with other factors, except that recall accuracy should be worse for phonologically similar sequences. 

As a reminder, this manipulation was introduced to have a closer comparison with musical material for which there is an inherent tonal proximity effect (Williamson et al., 2010).

Results

As in the previous experiment, the data were analyzed using JASP (version 0.14, JASP Team, 2018) with the same default values for priors and applying the same analysis plan. For each analysis (i.e., serial position curves, transposition gradients, and response latencies), data from trials presenting phonologically dissimilar and similar letters have been analyzed separately.

Serial position curves. We calculated for each participant the proportion of correct recalls as a function of serial position and temporal grouping first for phonologically dissimilar trials. The data were then submitted to a 2 × 6 repeated-measures ANOVA with serial position (1–6) and grouping condition (grouped vs. ungrouped) factors (see top-left of Figure 5). 

The results revealed that the best model was the one with the two main effects only, preferred over the second-best model (full model) by a factor of 32.76. This result represents strong evidence in favor of an effect of grouping on recall accuracy and serial position, but no interaction between the two factors (see "Serial position curves" rows in Table 7). 

The same analysis was performed with data from trials with phonologically similar letters, leading to the same pattern of data as for phonologically dissimilar letters, with the best model being the model with the two main effects, which was preferred to the full model by a factor of 68.68 (see top-right of Figure 5 and "Serial position curves" rows in Table 8).

Transposition gradients. Before statistical analysis of transposition errors, participants who produced no order errors in at least one of the four experimental conditions were removed. After the removal of these participants, the transposition error analysis was finally conducted on a sample of 51 participants. 

We calculated for each participant the proportion of errors, as a function of absolute distance shift and temporal grouping, among all order errors in the phonologically similar condition. We then analyzed the data with a 2 × 5 repeated-measures ANOVA with absolute transposition distance (1–5) and grouping condition (grouped vs. ungrouped) as factors (see middle-left of Figure 5). 

The results provided strong evidence in favor of the model containing only the distance effect as the best model, which was preferred to the second-best model with both main effects by a factor of 10.56 (see "Transposition gradients" rows in Table 7). The same analysis was repeated on data from trials with phonologically similar letters, leading to similar results to those obtained with phonologically dissimilar letters (see middle-right of Figure 5). 

The results provided strong evidence that the best model was the one with only a main effect of distance, preferred to the second best model with both main effects by a factor of 10.56 (see "Transposition gradients" rows in Table 8). 

As in previous experiments, we also analyzed the rate of within-group versus between-group transposition errors. For the latter, we distinguished between interposition errors, transpositions at group boundaries, and other between-group transpositions (all comparisons involved undirected Bayesian paired samples t-test with default prior as provided in JASP). 

As shown in Table 9 the phonologically dissimilar lists showed overall moderate evidence for an absence of difference between the two grouping conditions concerning different types of transposition errors. Regarding phonologically similar lists (see Table 10), we obtained decisive evidence of a decrease in transpositions at the group boundary and moderate evidence for an absence of an increase in interposition errors in grouped sequences.

For more information:1950477648nn@gmail.com