Literature DB >> 33442811

The Timescale of Control: A Meta-Control Property that Generalizes across Tasks but Varies between Types of Control.

Abhishek Dey1, Julie M Bugg2.   

Abstract

Prominent models of control assume that conflict and the probability of conflict are signals used by control processes that regulate attention. For example, when conflict is frequent across preceding trials (i.e., high probability of conflict), control processes bias attention toward goal-relevant information on subsequent trials. An important but underspecified question regards the meta-control property of timescale-that is, how far back does the control system "look" to determine the probability of conflict? To address this question, Aben, Verguts, and Van den Bussche (2017) developed a statistical model quantifying the timescale of control. In a flanker task, they observed short timescales for lists with a low probability of conflict (which induce reactive control) and long timescales for lists with a high probability of conflict (which induce proactive control). To investigate the domain generality of these timescales, we applied their model to two additional conflict tasks that manipulated the list-wide probability of conflict. Our findings replicated Aben et al. suggesting meta-control may be task general with respect to timescales operating on the list level. We subsequently modified their model to examine timescale differences for items in the same list that differed in their probability of conflict but not the type of control engaged. We failed to detect a difference in timescales between items. Collectively, the findings demonstrate that differences in the timescale of control are task general and suggest that timescale differences are driven by the type of control engaged and not by the probability of conflict per se.

Keywords:  Cognitive control; Item-specific proportion congruence; Learning rate; List-wide proportion congruence; Timescale of control

Year:  2021        PMID: 33442811     DOI: 10.3758/s13415-020-00853-x

Source DB:  PubMed          Journal:  Cogn Affect Behav Neurosci        ISSN: 1530-7026            Impact factor:   3.282


  22 in total

1.  Conflict monitoring and cognitive control.

Authors:  M M Botvinick; T S Braver; D M Barch; C S Carter; J D Cohen
Journal:  Psychol Rev       Date:  2001-07       Impact factor: 8.934

2.  Why it is too early to lose control in accounts of item-specific proportion congruency effects.

Authors:  Julie M Bugg; Larry L Jacoby; Swati Chanani
Journal:  J Exp Psychol Hum Percept Perform       Date:  2011-06       Impact factor: 3.332

3.  Item-specific adaptation and the conflict-monitoring hypothesis: a computational model.

Authors:  Chris Blais; Serje Robidoux; Evan F Risko; Derek Besner
Journal:  Psychol Rev       Date:  2007-10       Impact factor: 8.934

4.  Behavioral and neural evidence for item-specific performance monitoring.

Authors:  Chris Blais; Silvia Bunge
Journal:  J Cogn Neurosci       Date:  2010-12       Impact factor: 3.225

5.  It's more than just conflict: The functional role of congruency in the sequential control adaptation.

Authors:  Anja Berger; Rico Fischer; Gesine Dreisbach
Journal:  Acta Psychol (Amst)       Date:  2019-05-16

6.  Revealing list-level control in the Stroop task by uncovering its benefits and a cost.

Authors:  Julie M Bugg; Mark A McDaniel; Michael K Scullin; Todd S Braver
Journal:  J Exp Psychol Hum Percept Perform       Date:  2011-10       Impact factor: 3.332

7.  Dynamic adjustments of attentional control in healthy aging.

Authors:  Andrew J Aschenbrenner; David A Balota
Journal:  Psychol Aging       Date:  2017-02

8.  Additive effects of word frequency and stimulus quality: the influence of trial history and data transformations.

Authors:  David A Balota; Andrew J Aschenbrenner; Melvin J Yap
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2013-04-08       Impact factor: 3.051

9.  Conflict-triggered top-down control: default mode, last resort, or no such thing?

Authors:  Julie M Bugg
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2013-11-25       Impact factor: 3.051

Review 10.  Measuring Adaptive Control in Conflict Tasks.

Authors:  Senne Braem; Julie M Bugg; James R Schmidt; Matthew J C Crump; Daniel H Weissman; Wim Notebaert; Tobias Egner
Journal:  Trends Cogn Sci       Date:  2019-07-19       Impact factor: 20.229

View more
  2 in total

1.  Distinct but correlated latent factors support the regulation of learned conflict-control and task-switching.

Authors:  Christina Bejjani; Rick H Hoyle; Tobias Egner
Journal:  Cogn Psychol       Date:  2022-04-08       Impact factor: 3.746

2.  The shaping of cognitive control based on the adaptive weighting of expectations and experience.

Authors:  Jihyun Suh; Julie M Bugg
Journal:  J Exp Psychol Learn Mem Cogn       Date:  2021-09-27       Impact factor: 3.140

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.