Control of task sequences: what is the role of language?

Language is often thought to play a pivotal role in organizing complex thought and action (Vygotsky, 1986). However, there is surprisingly little known about how exactly we might use language for this purpose. One way in which language may be helpful is in that it allows us to cue upcoming demands in a proactive manner. Verbal labels may become associated with non-verbal, action-relevant codes that represent aspects such as where to direct attention or which motor actions to select (Hommel, Pratt, Colzato, & Godijn, 2001). Articulating verbal labels activates the associated codes and thus prepares their fluent application. In fact, work with the task-switching paradigm has demonstrated that verbalizing task labels reduces task-switch costs (Goschke, 2000; Kray, Eber, & Karbach, 2008). Moreover, in situations in which people need to select tasks according to an internal sequential rule, articulatory suppression produces substantial interference with performance (Baddeley, Chincotta, & Adlam, 2001) and it has been specifically argued that articulatory suppression interferes with preparatory self-cueing (Miyake, Emerson, Padilla, & Ahn, 2004). The notion of preparatory control during complex sequential action is also consistent with standard models of serial-order control. Such models assume that complex sequences are organized hierarchically in terms of chunks of 2–4 sequential elements and these chunks themselves can become recursively embedded within higher-order chunks (Klapp, 1976; Rosenbaum, Kenny, & Derr, 1983). Executing such a sequence requires retrieving the currently relevant chunk into working memory, which explains why inter-response times between successive chunks are usually much larger than within-chunk inter-response times. Mayr (2009), using a paradigm that required executing complex sequences of tasks (Schneider & Logan, 2006) recently reported evidence for another type of sequence-structure effect, namely positional interference. For example, when three different tasks A, B, and C are combined in the two-chunk sequence ABC-ACB, retrieval of the task C in the middle of the second chunk is impaired because of interference from that task's association with the final position of the first chunk (see also Koch, Philipp, & Gade, 2006; Schneider, 2007).1 Undoubtedly, most proponents of the standard model of serial-order control would assume that verbal self-cuing should help with exactly these types of retrieval-related costs. Thus, if speaking during sequencing is in fact used in a proactive manner (i.e., before the relevant action needs to be executed) then it should lead to a marked reduction or even elimination of such sequence-structure effects. Traditionally, research on serial-order control has used paradigms in which people executed complete sequences (e.g., of key-presses) from memory, which allows no control over inter-response timing and thus does not allow explicit tests of the effects of preparation and/or verbal self-cuing. This has changed with the so-called task-span procedure (Koch, 2003; Mayr, 2009; Schneider & Logan, 2006), where subjects work through memorized sequences of tasks. Given that here a response can be executed only after the stimulus has been presented, the time available for preparation—the interval between the previous response and the next stimulus (RSI)—is under full experimentor control. For example, Schneider and Logan (2006) reported a study in which subjects had to work through multi-chunk sequences. Chunk-initiation times were slightly reduced for long RSIs. However, this preparation-related reduction was much smaller than would be expected if proactive, verbal self-cuing actually allows loading upcoming sequential elements into working memory. Similarly, Koch (2003) had asked subjects to alternate between two tasks in runs of two trials (AA–BB) and found no evidence for reduced task-switch costs (which here are confounded with chunk-initiation times) as a result of increased RSIs. Finally, in the above-mentioned study (Mayr, 2009) large RT and error effects of both positional interference and chunk-initiation were observed despite a 1000 ms RSI, a duration that should have easily sufficed to retrieve the next sequential element into working memory. Given that there can be little doubt that language is critical during complex sequencing demands (e.g., Baddeley et al., 2001) and given the generally assumed role of language in allowing to plan and precue upcoming behavior, the results summarized here clearly present a puzzle. What is missing is research that directly assesses and experimentally manipulates the role of speech during serial-order control.