Ten students from Bielefeld University, Germany, participated in the experiment. Seven of them took part in a speed-stacking automatization study (Foerster et al., 2011) and the other three participants ran through the same speed-stacking training before participating in the present experiment. Participants' age ranged from 21 to 32 years with a mean of 26. All participants had either normal or corrected-to-normal vision, were naive with respect to the aims of the study, and were paid for their participation. The study was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki. All participants gave their informed consent to be included in the study.

A notebook with a 15.4 inch screen, with a resolution of 1024 × 768 pixels and speed-stacking equipment (cups, timer, and mat) were used for the experiment. Participants were seated in front of the screen and the speed-stacking equipment was placed in-between them and the screen. The distance to the screen was approximately 60 cm. Stimulus presentation of the WM task was controlled by the Experiment Builder software (SR Research, Ontario, Canada). Stimuli were displayed on a black background. The verbal memory stimuli were yellow consonants (B, F, J, L, N, Q, R, V, and X), appearing successively inside of a white frame (subtending approximately 2.86° of visual angle) centered on the screen. For the visuospatial WM-span task, gray filled white squares (again subtending approximately 2.86° of visual angle) were distributed in a fixed layout across the screen, and individual frames successively changed their inner color to yellow and back to gray, in a random order. The visuospatial task was similar to the Corsi Block task of De Renzi and Nichelli (1975). Neither a letter nor a location was repeated within a sequence. The poem consisted of four quatrains with rhyming couplets and iamb as measure (see Appendix).

We analyzed the data with repeated measures analyses of variance. In case of significant effects, data was analyzed further with planned t-tests. The within-subject variables were WM-span task (none, verbal, and visuospatial) and multi-step task (none, reciting, and stacking). WM-span condition was blocked starting with a multi-step task without WM-span task (single-task condition) as a first block, and the multi-step tasks with verbal and visuospatial WM-span task (dual-task conditions) as second and third block. The order of blocks 2 and 3 was counterbalanced across participants. The multi-step task conditions were intermixed within the two latter WM-span blocks. The first block of the experiment (no WM-span task) consisted of six stacking and six reciting trials. Each of the other two WM-span blocks (verbal and visuospatial) consisted of 18 experimental trials, with six trials each for the three multi-step task conditions (none, reciting, and stacking), adding up to a total of 48 trials. Two practice trials (one verbal WM-span trial and one visuospatial WM-span trial, both without multi-step task) at the beginning of the second block were added to ensure that the participants followed the instruction.

The dependent variables were percentage correct for the WM-span tasks as well as completion time and error rate for the speed-stacking task and the poem-reciting task. WM-span performance was considered correct when all memory items were reported in the correct order. Respectively, speed stacking and poem reciting were considered correct when all actions and words were correct. The performance measure of the multi-step tasks was the duration of a complete stacking or reciting sequence. We defined a stacking error as one or more cups falling or sliding down. Skipping, substituting, adding, or transposing of one or more words was defined as a reciting error.

Each experimental manipulation was preceded by a speed-stacking and a poem-reciting training period as well as a refreshment day directly before the experimental day. Speed stacking consists of a fixed sequence of stacking up and down pyramids of plastic cups as fast as possible. Number, order, and direction of the stacking movements are predetermined (for an illustrative video visit http://www.speedstacks.com/about/history.php). The speed-stacking training phase consisted of 14 days with 45 min practice each day (details are reported in Foerster et al., 2011). The poem-reciting training lasted 50 min on a single day consisting of 10 min silent memorization and 40 min reciting at maximum speed. This poem-reciting training was preceded and followed by reading aloud the poem three times. On the refreshment day, both stacking, and reciting had to be performed as fast as possible for 30 min each.

The last day was the experimental day and started with the first block of high-speed stacking and high-speed poem reciting without parallel WM-span task. The instruction was again to perform as fast as possible. This initial calculation of the participants' performance in stacking and reciting served as a baseline for the multi-step tasks. The trial speed of both multi-step tasks was measured by a timer and then transferred and stored on the notebook. The accuracy was marked by the experimenter.

Afterwards, the dual-task trials started with a written instruction appearing on the screen. Each trial started with a left mouse button press followed by the sequence of memory items, either four consonants or three locations. This difference in number of to-be-remembered items was necessary to ensure equal task difficulty (see Results section). Each item was shown for 400 ms with an inter-stimulus interval (ISI) of 400 ms. Following the stimulus sequence, a written message was shown on the screen for 20 s informing the participants about the activity they had to accomplish within this delay (none, reciting, or stacking). A tone signaled the start and the end of the delay. Participants were instructed to be as accurately as possible in the memory task.

For the verbal WM-span test, a central frame was shown on the screen and participants had to type in the letters in the correct order via the keyboard. Spatially distributed frames were shown on the screen for the visuospatial WM-span test, and participants had to select the locations via the mouse cursor in the correct order and confirm each selection with a left mouse click. The recording of the WM span stopped as soon as the participants had made an error or had reproduced the complete sequence correctly. The reproduction was followed by a feedback (“correct” or “incorrect”). Trial sequences for all six combinations of conditions are shown in Figure 1. The participants were supposed to memorize the items as accurately as possible and to stack and recite as fast as possible.

Stacking time decreased significantly from the first (38.83 s) to the last (18.49 s) training day [t₍₉₎ = 8.55, SE = 2.38, p < 0.001] and participants achieved a mean stacking time of 18.49 s with a mean best time of 12.63 s on the last training day. There was no further significant improvement from the 11th day on [day 11–14: t_{(1, 9)} = 2.00, SE = 0.85, p = 0.077; day 12–14: t_{(1, 9)} = 0.24, SE = 1.85, p = 0.815; day 13–14: t_{(1, 9)} = 0.37, SE = 0.72, p = 0.723]. Speed-stacking performance over training days is shown in Figure 2A.

Because the whole poem-reciting training took place on a single day, we split up the training trials of each participant into 14 equal bins and calculated means of reciting times for each bin. All participants learned the poem as reflected by the significant overall decrease of mean reciting time between the first bin (44.18 s) and the last bin (20.01 s) of all trials [t₍₉₎ = 4.63, SE = 5.23, p < 0.01]. There was no further significant improvement from the 8th bin on [bin 8–14: t_{(1, 9)} = 0.51, SE = 0.98, p = 0.625; bin 9–14: t_{(1, 9)} = 0.35, SE = 0.80, p = 0.734; bin 10–14: t_{(1, 9)} = 0.10, SE = 2.02, p = 0.922; bin 11–14: t_{(1, 9)} = 0.67, SE = 0.93, p = 0.518; bin 12–14: t_{(1, 9)} = 0.99, SE = 1.55, p = 0.348; bin 13–14: t_{(1, 9)} = 0.18, SE = 1.79, p = 0.865]. Participants achieved a mean best reciting time of 14.47 s that corresponds to a reciting rate of seven syllables per second. This best reciting time did not differ significantly from the mean best reading time of 14.41 s (seven syllables per second) before training [t_{(1, 9)} = 2.24, SE = 1.31, p > 0.05] nor from the mean best reading time of 12.43 s (eight syllables per second) after training [t_{(1, 9)} = 1.84, SE = 1.11, p > 0.05]. Poem-reciting performance over training bins is shown in Figure 2B.

Stacking and reciting speed and accuracy are depicted in Figure 3. To test whether the WM-span tasks affected stacking or reciting performance, we conducted two 2 × 3 analyses of variance for task completion time and error rate as dependent variables with multi-step task (reciting and stacking) and WM-span task (none, verbal, and visuospatial) as within-subject variables. The analysis of task completion time revealed a significant main effect of multi-step task [F_{(1, 9)} = 14.07, MSE = 351.19, p < 0.01], indicating that participants could recite the poem faster (14.01 s) than they could stack the cups (18.85 s). Neither the main effect of WM-span task [F_{(2, 18)} = 2.36, MSE = 3.28, p > 0.05] nor the interaction of multi-step task and WM-span task [F_{(2, 18)} = 2.50, MSE = 1.47, p > 0.05] were significant. The analysis of error rate revealed a significant main effect of multi-step task [F_{(1, 9)} = 17.28, MSE = 1.06, p < 0.01], indicating that participants made less errors when reciting the poem (7.27%) than when stacking the cups (33.87%). Neither the main effect of WM-span task [F_{(2, 18)} = 0.11, MSE = 0.002, p > 0.05] nor the interaction of multi-step task and WM-span task [F_{(2, 18)} = 0.14, MSE = 0.01, p > 0.05] were significant. Results indicate that stacking and reciting performance are not influenced by simultaneous WM retention.

Performance measures for the WM-span tasks are depicted in Figure 4. To test whether the multi-step tasks affected the verbal or visuospatial memory span, we conducted a 2 × 3 analysis of variance for the memory performance with WM-span task (verbal and visuospatial) and multi-step task (none, stacking, and reciting) as within-subject variables. The analysis revealed no significant effect of WM-span task [F_{(1, 9)} = 0.80, MSE = 0.06, p > 0.05], indicating that task difficulty was comparable. The main effect of multi-step task was significant [F_{(2, 18)} = 51.69, MSE = 1.37, p < 0.001] with the highest memory accuracy without multi-step task (85.83%), intermediate memory accuracy during stacking (67.50%), and worst memory accuracy during reciting (34.17%). The analysis also revealed a significant interaction between WM-span task and multi-step task [F_{(2, 18)} = 24.14, MSE = 0.73, p < 0.001]. Planned paired t-tests with Bonferroni-correction revealed that the verbal WM-span accuracy did not differ significantly between the single task condition (88.33%) and the stacking (90.00%) condition [t_{(1, 9)} = 0.36, SE = 0.05, p > 0.05], while it decreased significantly from 88.33% without dual task to 18.33% with simultaneous reciting [t_{(1, 9)} = 7.87, SE = 0.28, p < 0.001]. The visuospatial WM-span accuracy was reduced significantly from 83.33% without dual task to 45.00% in the stacking condition [t_{(1, 9)} = 4.64, SE = 0.08, p < 0.01], and also decreased significantly from 83.33% without dual task to 50.00% in the reciting condition [t_{(1, 9)} = 4.05, SE = 0.08, p < 0.05]. However, this cross-domain interference between the visuospatial WM span and reciting was significantly smaller than the domain-specific interference between reciting and the verbal WM span [t_{(1, 9)} = 2.80, SE = 0.13, p < 0.05].

The present study revealed interference between WM retention and the execution of automatized tasks, that is, tasks that have been trained up to a level on which no further improvement has been observed. This finding argues against a conceptualization of automatized and controlled processes as was proposed by Schneider and Shiffrin (1977a,b) implying that automatized processes should not interfere with other processes (see also, Neumann, 1984). Furthermore, our data challenge the suggestion that highly trained skills can be performed without recruiting WM (e.g., Fitts and Posner, 1967; Anderson, 1993; Beilock et al., 2002) including the idea that action-relevant parameters are directly specified via LTM information (Neumann, 1984, 1990; Logan, 1988, 1990). Finally, on the basis of our results, it seems difficult to retain a strict segregation of declarative and procedural WM (e.g., Oberauer, 2009, 2010). At least, the assumption that well-practiced procedures do not interfere with parallel retention of declarative material is called in question.

How might LTM-based control of attention in the overlearned multi-step tasks involve WM processes? In speed stacking, the learned information about important locations in the environment might be retrieved from LTM by writing into a visuospatial map of WM. The same visuospatial map might be involved in the attention-based rehearsal of visuospatial material in WM. This assumption is supported by results from the following studies. First, attention seems to be necessary for LTM retrieval (e.g., Wagner et al., 2005; Cabeza et al., 2008). Second, where to attend while performing a highly practiced sensorimotor task is largely controlled by LTM (Foerster et al., 2011, 2012). Third, there is evidence that the maintenance of visuospatial material in WM might be based on visuospatial attention (e.g., Smyth, 1996; Awh et al., 1998, 2000, 2006; Awh and Jonides, 2001; Theeuwes et al., 2011).

Complementary, the same attention processes might be required for retrieving verbal LTM content for poem reciting as well as for the subvocal articulatory process that constitutes verbal rehearsal (Salame and Baddeley, 1982; Baddeley et al., 1984; Awh et al., 1996). Behavioral and neuroimaging studies (e.g., Zhijian and Cowan, 2009; Majerus et al., 2012) showed that attention is involved in verbal short-term retention. Moreover, Wagner et al. (2005) reviewed neuroimaging studies showing that the posterior parietal cortex (PPC)—an important structure for WM (e.g., Funashi et al., 1989; Fiehler et al., 2011)—is also activated during episodic memory retrieval (see also, Cabeza et al., 2008). The authors proposed that the PPC is activated because memory representations have to be attended for retrieval. Therefore, attention for LTM retrieval during the execution of the multi-step tasks may have competed with attention-based rehearsal for the WM-span tasks.

We assume that attention, WM, and LTM interact during the execution of LTM-based multi-step tasks. Task-relevant information is selected from LTM structures by attention-based domain-specific activation in WM. In neurophysiological terms, long-term synaptic weights—LTM—are transferred into short-term continuous firing in neural circuits—WM (Olivers et al., 2011). Importantly, we assume that LTM representations can only be used for action control, if they have been selected by the same attentional mechanisms that also maintain domain-specific information in WM (see also, Schneider, 2013). Consequentially, a tight interaction should exist between attention, domain-specific WM, and LTM processes during the execution of highly practiced multi-step tasks.

Two further important findings of our study should be discussed. We start with the question, why poem reciting did not only reduce the verbal WM span, but also the visuospatial WM span, although to a smaller degree. In Baddeley's WM model (Baddeley and Hitch, 1974, 1994; Baddeley, 1986, 2003, 2012), such cross-domain interference can either be due to global WM load (within the central executive and the episodic buffer) or to interference within the visuospatial sketchpad, or the articulatory loop. Global WM load refers to the involvement of the central executive and the episodic buffer, so that tasks compete for processes within these multidimensional WM domains. Global WM load might be higher during poem reciting than during speed stacking. What justifies this assumption? When performing a sensorimotor task in the real world, humans usually gather visual (-spatial) information just when it is needed to perform a sub-action (Hayhoe et al., 2003). This phenomenon has also been observed in speed stacking (Foerster et al., 2011, 2012). This strategy of using the “world as external memory” (O'Regan, 1992) reduces WM load. During high-speed poem reciting, outsourcing of relevant information to the environment is not possible. Information for action programming and execution stems from LTM only. This higher LTM “load” may cause a higher WM load during reciting than during stacking.

However, it is also possible that the observed interference between reciting and visuospatial WM was due to specific interference within the visuospatial sketchpad. Poem reciting itself might imply visuospatial processing. A visual imagery process of words during reciting could have been introduced because of the visual presentation of the poem during initial learning. If participants imagined words while reciting, these words should take limited visuospatial attentional capacity (e.g., attentional weights, Bundesen, 1990) away from attentional selection of information for the multi-step task.

An additional supplementary question is why the interference effects between WM spans and multi-step tasks were unidirectional. While the WM retention suffered from the concurrent execution of the multi-step LTM-driven tasks, these tasks were unaffected by the simultaneous maintenance of information in WM. Participants seem to have prioritized the multi-step tasks over the WM tasks, so that they could maintain at least the performance level of the multi-step tasks to the disadvantage of the WM-span tasks. Future work has to investigate whether explicitly instructing participants to prioritize one task over the other changes the directionality of the interference.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.