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A model of cognitive control in task switching is developed in which controlled performance depends on the system maintaining access to a code in episodic memory representing the most recently cued task. The main constraint on access to the current task code is proactive interference from old task codes. This interference and the mechanisms that contend with it reproduce a wide range of behavioral phenomena when simulated, including well-known task-switching effects, such as latency and error switch costs, and effects on which other theories are silent, such as with-run slowing and within-run error increase. The model generalizes across multiple task-switching procedures, suggesting that episodic task codes play an important role in keeping the cognitive system focused under a variety of performance constraints.
Altmann, E. M. (2007). Cue-independent task-specific representations in task switching: Evidence from backward inhibition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 892-899
The compound-cue model of cognitive control in task switching explains switch cost in terms of a switch of task cues rather than a switch of tasks. The present study asks whether the model generalizes to lag-2 repetition cost (also known as backward inhibition), a related effect in which the switch from B to A in ABA task sequences is costlier than the same switch in CBA task sequences. The model suggests that lag-2 repetition cost should be absent from A'BA task sequences, where A' and A are different cues for the same task. The cost is robust on such sequences, suggesting that cue-independent, task-specific representations are necessary to explain task-switching performance, and that the compound-cue model has limited explanatory power.
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Altmann, E. M. (2007). Comparing switch costs: Alternating runs and explicit cuing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 475-483.
The task-switching literature routinely conflates different operational definitions of switch cost, its predominant behavioral measure. This article is an attempt to draw attention to differences between the two most common definitions, alternating-runs switch cost (ARS) and explicit-cuing switch cost (ECS). ARS appears to include both the costs of switching tasks and switch-independent costs specific to the first trial of a run, with the implication that it should generally be larger than ECS, but worse is that the alternating-runs procedure does not allow these costs to be separated. New data are presented to make these issues concrete, existing data are surveyed for evidence that ARS is larger than ECS, and implications of conflating these measures are examined for existing theoretical constructs.
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Altmann, E. M. (2006). Task switching is not cue switching. Psychonomic Bulletin & Review, 13, 1016-1022
With the aim of reducing cognitive control in task switching to simpler processes, researchers have proposed in a series of recent studies that there is little more to switching tasks than switching cues. The present study addresses three questions concerning this reduction hypothesis. First, does switching cues account for all relevant variance associated with switching tasks? Second, how well does this hypothesis generalize beyond the experimental procedure from which it was developed? Third, how well does this new procedure preserve relevant measures like task-switch cost? The answers (no, not very, not very) suggest that task switching does not reduce to cue switching.
Altmann, E. M. (2005). Repetition priming in task switching: Do the benefits dissipate? Psychonomic Bulletin & Review, 12, 535-540.
In task-switching research, one process that has been implicated as a possible source of switch cost is repetition priming. Four experiments examine the claim that repetition priming dissipates over the interval between trials and thereby causes switch cost to decrease with increases in the response-cue interval (RCI). In Experiments 1 and 2, RCI was manipulated within subjects, producing the standard RCI effect on switch cost. In Experiments 3 and 4, RCI was manipulated between subjects, and had no effect on switch cost. The role of experimental design, and the mixed pattern of effects on switch and repeat trials in Experiments 1 and 2, suggest that a passive architectural process like priming dissipation is not responsible for the RCI effect on switch cost. Repetition priming may still be responsible for some or all of switch cost, but appears to be more stable over time than previously thought.
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Altmann, E. M. (2004). Advance preparation in task switching: What work is being done? Psychological Science, 15, 616-622.
The preparation effect in task switching is usually interpreted to mean that a switching process makes use of the interval between task-cue onset and trial-stimulus onset (the cue-stimulus interval, or CSI) to accomplish some of its work ahead of time. This study undermines the empirical basis for this interpretation and suggests that task activation, not task switching, is the functional process in cognitive control. Experiments 1 and 2 use an explicit cueing paradigm, and Experiments 3 and 4 use a variation in which the trial after a task cue is followed by several cueless trials, requiring retention of the cue in memory. Experiments 1 and 3 replicate the preparation effect on switch cost, and Experiments 2 and 4 show that this effect vanishes when CSI is manipulated between subjects, leaving only a main effect of CSI when the task cue is a memory load.
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Altmann, E. M. (2004). The preparation effect in task switching: Carryover of SOA. Memory & Cognition, 32, 153-163.
A common finding in task switching studies is switch preparation (commonly known as the preparation effect), in which a longer interval between task cue and trial stimulus (i.e., a longer stimulus onset asynchrony, or SOA) reduces the cost of switching to a different task. Three experiments link switch preparation to within-subject manipulations of SOA. In Experiment 1, SOA was randomized within subjects, producing switch preparation that was more pronounced when the SOA switched from the previous trial than when the SOA repeated. In Experiment 2, SOA was blocked within subjects, producing switch preparation but not on the first block of trials. In Experiment 3, SOA was manipulated between subjects with sufficient statistical power to detect switch preparation, but the effect was absent. The results favor an encoding view of cognitive control, but show at least that any putative switching mechanism reacts lazily when exposed to only one SOA.
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Altmann, E. M. (2003). Task switching and the pied homunculus: Where are we being led? Trends in Cognitive Sciences, 7, 340-341.
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Altmann, E. M. (2002). Functional decay of memory for tasks. Psychological Research, 66, 287-297.
Correct performance often depends on remembering the task one has been instructed to do. When the task periodically changes, memory for the current task must decay (lose activation) to prevent it from interfering with memory for the next task when that is encoded. Three task-switching experiments examine this decay process. Each shows within-run slowing, a performance decline occurring as memory for the current task decays. In experiment 1, slowing is attenuated when memory for the task is optional, suggesting that memory is indeed causal. Experiment 2 finds slowing despite a flat hazard rate for task instructions, suggesting that slowing is not an artifact of instruction anticipation. Experiment 3 finds slowing in the familiar alternating-runs paradigm (Rogers & Monsell, 1995), suggesting that it may lurk elsewhere. A process model of activation explains within-run slowing and relates it to switch cost and "restart cost" (Allport & Wylie, 2000) in functional terms.
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Functional decay theory proposes that decay and interference, historically viewed as competing accounts of forgetting, are instead functionally related. The theory posits (a) that when an attribute must be updated frequently in memory, its current value decays to prevent interference with later values, and (b) the decay rate adapts to the rate of memory updates. Behavioral predictions of the theory were tested in a task-switching paradigm in which memory for the current task had to be updated every few seconds, hundreds of times. RT and error both increased gradually between updates, reflecting decay of memory for the current task. This performance decline was slower when updates were less frequent, reflecting a decrease in the decay rate following a decrease in the update rate. A candidate mechanism for controlled decay is proposed, the data are reconciled with practice effects, and implications are discussed for models of executive control.
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