Implicit Learning

Frensch, Peter A.; Rünger, Dennis

doi:10.1111/1467-8721.01213

Cited by 181 publications

(134 citation statements)

References 1 publication

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“…Additionally, Lewicki (1986;Lewicki et al, 1992Lewicki et al, , 1997 reported various demonstrations of implicit covariation learning (cf., Hendrickx et al, 1997aHendrickx et al, , 1997b. Given all this data, implicit learning seems to be a highly replicable and general phenomenon (although there will always be some debate over what constitutes evidence of implicit learning; see Frensch & Rünger, 2003, for a discussion of these issues).…”

Section: Discussionmentioning

confidence: 95%

Contingency learning without awareness: Evidence for implicit control

Schmidt

Crump

Cheesman

et al. 2007

Consciousness and Cognition

168

268

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The results of four experiments provide evidence for controlled processing in the absence of awareness. Participants identified the colour of a neutral distracter word. Each of four words (e.g., MOVE) was presented in one of four colours 75% of the time (Experiments 1 and 4) or 50% of the time (Experiment 2 and 3). Colour identification was faster when the words appeared in the colour they were most often presented in relative to when they appeared in another colour, even for participants who were subjectively unaware of any contingencies between the words and colours. An analysis of sequence effects showed that participants who were unaware of the relation between distracter words and colours nonetheless controlled the impact of the word on performance depending on the nature of the previous trial. A block analysis of contingencyunaware participants revealed that contingencies were learned rapidly in the first block of trials.Experiment 3 showed that the contingency effect does not depend on level of awareness, thus ruling out explicit strategy accounts. Finally, Experiment 4 showed that the contingency effect results from behavioural control and not from semantic association or stimulus familiarity. These results thus provide evidence for implicit control. Implicit Control 3Contingency Learning without Awareness: Evidence for Implicit Control Cognitive processes that are controlled are conventionally assumed to operate in a slow, effortful, and voluntary manner (Posner & Cohen, 1984;Posner & Snyder, 1975; Shiffrin & Schnieder, 1977). Thus, when researchers discuss the influence of "controlled" processes, it is typically assumed that such processes are explicit (i.e., conscious; cf., Besner & Stolz, 1999). As such, the term "implicit control" would seem to be nonsensical, because "implicit" (i.e., unconscious) seems to preclude the possibility of control. However, etymologically speaking this is not a necessary conclusion. The Oxford English Dictionary (2001) Evidence for cognitive control, which is assumed to be explicit and strategic in nature, has been drawn from the Stroop literature (Stroop, 1935). In the Stroop task, identification of the print colour of colour words is slower when the word and ink colour are incongruent (e.g., the word GREEN in orange; GREEN orange ) than when they are congruent (e.g., ORANGE orange ; see MacLeod, 1991, for a review). Probably the most important demonstration of putatively controlled processes in the Stroop literature is the proportion congruent effect. The proportion congruent effect refers to the finding that the size of the Stroop effect is influenced by the proportion of congruent items in a block of trials (Lindsay & Jacoby, 1994;Logan & Zbrodoff, 1979). Specifically, the Stroop effect is much larger in a high proportion congruent block of trials than in a low proportion congruent block of trials. This effect is commonly attributed to Implicit Control 4 participants explicitly learning to predict the colour from the word. Specifically, because the word us...

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Section: Discussionmentioning

confidence: 95%

Contingency learning without awareness: Evidence for implicit control

Schmidt

Crump

Cheesman

et al. 2007

Consciousness and Cognition

168

268

View full text Add to dashboard Cite

show abstract

“…They were asked to judge which of the two displays was more familiar. The recognition test (forced choice) is a simple way of testing for the implicit nature of memory (Frensch & Rünger, 2003;Tseng & Li, 2004).…”

Section: Contextual Configuration and Stimulimentioning

confidence: 99%

Rewarding context accelerates implicit guidance in visual search

Tseng

Lleras

2012

Atten Percept Psychophys

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It is well known that observers can implicitly learn the spatial context of complex visual searches, such that future searches through repeated contexts are completed faster than those through novel contexts, even though observers remain at chance at discriminating repeated from new contexts. This contextual-cueing effect arises quickly (within less than five exposures) and asymptotes within 30 exposures to repeated contexts. In spite of being a robust effect (its magnitude is over 100 ms at the asymptotic level), the effect is implicit: Participants are usually at chance at discriminating old from new contexts at the end of an experiment, in spite of having seen each repeated context more than 30 times throughout a 50-min experiment. Here, we demonstrate that the speed at which the contextual-cueing effect arises can be modulated by external rewards associated with the search contexts (not with the performance itself). Following each visual search trial (and irrespective of a participant's search speed on the trial), we provided a reward, a penalty, or no feedback to the participant. Crucially, the type of feedback obtained was associated with the specific contexts, such that some repeated contexts were always associated with reward, and others were always associated with penalties. Implicit learning occurred fastest for contexts associated with positive feedback, though penalizing contexts also showed a learning benefit. Consistent feedback also produced faster learning than did variable feedback, though unexpected penalties produced the largest immediate effects on search performance.

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“…While active exploration and systematic experimentation is the key strategy to test hypotheses about causal relations between own movements and changes in the object, the hypotheses to be tested might in part be derived from a rather passive subsystem that observes movements in the actor and the object. Research on implicit learning in humans (e.g., Frensch & Rünger, 2003) suggests that co-occurrence statistics about a multitude of features in the actor and the object might accumulate and the strongest of the co-variations may fuel active testing that can lead to causal knowledge and a symbolic level of representation. We thus propose that it may be beneficial to follow the human example, and develop robotic systems that combine active exploration with passive learning.…”

Section: Watching Vs Doingmentioning

confidence: 99%