scholarly journals Is Contextual Cueing Unconscious? The Indirect Task Advantage in Implicit Learning

2021 ◽  
Vol 21 (9) ◽  
pp. 1831
Author(s):  
Sascha Meyen ◽  
Ulrike von Luxburg ◽  
Volker H. Franz
Keyword(s):  
Implicit Learning ◽  
Contextual Cueing

Selective attention modulates implicit learning

2001 ◽  
Vol 54 (4) ◽  
pp. 1105-1124 ◽  
Author(s):  
Yuhong Jiang ◽  
Marvin M. Chun
Keyword(s):  
Visual Search ◽  
Selective Attention ◽  
Implicit Learning ◽  
Target Location ◽  
Spatial Configuration ◽  
Contextual Cueing ◽  
Predictive Information

The effect of selective attention on implicit learning was tested in four experiments using the “contextual cueing” paradigm (Chun & Jiang, 1998, 1999). Observers performed visual search through items presented in an attended colour (e.g., red) and an ignored colour (e.g., green). When the spatial configuration of items in the attended colour was invariant and was consistently paired with a target location, visual search was facilitated, showing contextual cueing (Experiments 1, 3, and 4). In contrast, repeating and pairing the configuration of the ignored items with the target location resulted in no contextual cueing (Experiments 2 and 4). We conclude that implicit learning is robust only when relevant, predictive information is selectively attended.

Relation between working memory and implicit learning in the contextual cueing paradigm

2020 ◽  
Vol 28 (9) ◽  
pp. 470-483
Author(s):  
Chao Wang ◽  
Shree Venkateshan ◽  
Bruce Milliken ◽  
Hong-jin Sun
Keyword(s):  
Working Memory ◽  
Implicit Learning ◽  
Contextual Cueing

scholarly journals Stimulus homogeneity enhances implicit learning: Evidence from contextual cueing

2014 ◽  
Vol 97 ◽  
pp. 108-116 ◽  
Author(s):  
Tobias Feldmann-Wüstefeld ◽  
Anna Schubö
Keyword(s):  
Implicit Learning ◽  
Contextual Cueing

scholarly journals Attention Dependency in Implicit Learning of Repeated Search Context

2007 ◽  
Vol 60 (10) ◽  
pp. 1321-1328 ◽  
Author(s):  
Valeria Rausei ◽  
Tal Makovski ◽  
Yuhong V. Jiang
Keyword(s):  
Visual Search ◽  
Implicit Learning ◽  
Dwell Time ◽  
Contextual Cueing ◽  
Minimal Amount ◽  
Learning Tasks ◽  
Attentional Dwell Time

How much attention is needed to produce implicit learning? Previous studies have found inconsistent results, with some implicit learning tasks requiring virtually no attention while others rely on attention. In this study we examine the degree of attentional dependency in implicit learning of repeated visual search context. Observers searched for a target among distractors that were either highly similar to the target or dissimilar to the target. We found that the size of contextual cueing was comparable from repetition of the two types of distractors, even though attention dwelled much longer on distractors highly similar to the target. We suggest that beyond a minimal amount, further increase in attentional dwell time does not contribute significantly to implicit learning of repeated search context.

scholarly journals Implicit learning and exploitation of regularities involve hippocampal and prefrontal theta activity

2019 ◽  
Author(s):  
Eelke Spaak ◽  
Floris P. de Lange
Keyword(s):  
Visual Search ◽  
Implicit Learning ◽  
Computational Modelling ◽  
Theta Activity ◽  
Contextual Cueing ◽  
Spatial Context ◽  
Theta Band ◽  
Initial Learning ◽  
Statistical Regularities ◽  
Band Activity

AbstractObservers rapidly and seemingly automatically learn to predict where to expect relevant items when those items are repeatedly presented in the same spatial context. This form of statistical learning in visual search has been studied extensively using a paradigm known as contextual cueing. The neural mechanisms underlying the learning and exploiting of such regularities remain unclear. We sought to elucidate these by examining behaviour and recording neural activity using magneto-encephalography (MEG) while observers were implicitly acquiring and exploiting statistical regularities. Computational modelling of behavioural data suggested that after repeated exposures to a spatial context, participants’ behaviour was marked by an abrupt switch to an exploitation strategy of the learnt regularities. MEG recordings showed that the initial learning phase was associated with larger hippocampal theta band activity for repeated scenes, while the subsequent exploitation phase showed larger prefrontal theta band activity for these repeated scenes. Strikingly, the behavioural benefit of repeated exposures to certain scenes was inversely related to explicit awareness of such repeats, demonstrating the implicit nature of the expectations acquired. This elucidates how theta activity in the hippocampus and prefrontal cortex underpins the implicit learning and exploitation of spatial statistical regularities to optimize visual search behaviour.

scholarly journals 4216 A TL1 team approach to investigate attention and learning at the intracranial network level and assess the effect different cognitive rehabilitation strategies have on measures of attention and learning

2020 ◽  
Vol 4 (s1) ◽  
pp. 21-21
Author(s):  
Sarah E. Long ◽  
Catherine Tocci ◽  
Giridhar Kalamangalam ◽  
William Perlstein ◽  
Ayse Gunduz
Keyword(s):  
Implicit Learning ◽  
Cognitive Rehabilitation ◽  
Learning Rate ◽  
Contextual Cueing ◽  
Strategy Training ◽  
Team Approach ◽  
Epileptic Patients ◽  
Metacognitive Strategy Training ◽  
Cortical Regions ◽  
Rehabilitation Strategies

OBJECTIVES/GOALS: 1) Investigate the network level interactions of attention and learning during an attention network task (ANT) and an implicit learning contextual cueing (CC) task. 2) Assess the effect attention rehabilitation strategies have on behavioral and neural responses pre/post-attentional intervention. METHODS/STUDY POPULATION: This study involves refractory epilepsy patients with implanted intracranial electrodes and moderate-to-severe traumatic brain injury (m/sTBI) survivors. In epileptic patients, we will identify connectivity of cortical regions via the ANT, which probes components of attention (alerting, orienting, and executive control) and a CC task that probes implicit learning. We hypothesize that modulation of attention and learning can be seen at the network level. In TBI we will assess improvement following two attention rehabilitation paradigms behaviorally; and use our results from epileptic patients to guide measurement of treatment-related neuroplastic change via scalp electroencephalography. RESULTS/ANTICIPATED RESULTS: When the proposed objectives are complete, we expect to determine how the implicit learning rate in m/sTBI changes as a result of both direct attention and metacognitive-strategy training, and discern the neuroanatomical networks associated with attention and implicit learning based on connectivity results. We expect to identify intracranial regions and networks that exhibit modulatory effects associated with attention and implicit learning. Additionally, we anticipate that deficits in attention will be mitigated following training and hypothesize that implicit learning rate will improve in TBI patients as a result of both attentional rehabilitation paradigms. DISCUSSION/SIGNIFICANCE OF IMPACT: Characterizing intracranial activity in epilepsy patients will give electrophysiology data unattainable in TBI patients. This intracranial perspective will enable us to propose mechanisms of action that may result from our interventions and enable critique of current rehabilitation treatments.

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