Is implicit learning spared in amnesia?

Channon, Shelley; Shanks, David R.; Johnstone, Theresa; Vakili, Kian; Chin, Jasmine; Sinclair, Elizabeth

doi:10.1016/s0028-3932(02)00037-4

Cited by 38 publications

(12 citation statements)

References 38 publications

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“…These different brain systems seem to support different aspects of AGL, as revealed by their connection to different strategies for expressing knowledge of string grammaticality: Hippocampal activity is associated with comparing the surface similarity of groups of items at test to items during exposure (Opitz & Friederici, 2004), whereas the striatum is associated with grammatical rule adherence independent of similarity (Lieberman et al, 2004). Indeed, in a version of the AGL task in which both patients with MTL damage and controls always rely on a similarity-based strategy, patients do show a deficit in AGL (Channon et al, 2002). The SL paradigm, as used in the current experiments, also tests surface similarity between groups of items at test and exposure, which helps reconcile our findings with the AGL literature.…”

Section: Discussionmentioning

confidence: 99%

The Necessity of the Medial Temporal Lobe for Statistical Learning

Schapiro¹,

Gregory

Landau

et al. 2014

Journal of Cognitive Neuroscience

298

228

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The sensory input that we experience is highly patterned, and we are experts at detecting these regularities. Although the extraction of such regularities, or statistical learning (SL), is typically viewed as a cortical process, recent studies have implicated the medial temporal lobe (MTL), including the hippocampus. These studies have employed fMRI, leaving open the possibility that the MTL is involved but not necessary for SL. Here, we examined this issue in a case study of LSJ, a patient with complete bilateral hippocampal loss and broader MTL damage. In Experiments 1 and 2, LSJ and matched control participants were passively exposed to a continuous sequence of shapes, syllables, scenes, or tones containing temporal regularities in the co-occurrence of items. In a subsequent test phase, the control groups exhibited reliable SL in all conditions, successfully discriminating regularities from recombinations of the same items into novel foil sequences. LSJ, however, exhibited no SL, failing to discriminate regularities from foils. Experiment 3 ruled out more general explanations for this failure, such as inattention during exposure or difficulty following test instructions, by showing that LSJ could discriminate which individual items had been exposed. These findings provide converging support for the importance of the MTL in extracting temporal regularities.

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Section: Discussionmentioning

confidence: 99%

The Necessity of the Medial Temporal Lobe for Statistical Learning

Schapiro¹,

Gregory

Landau

et al. 2014

Journal of Cognitive Neuroscience

298

228

View full text Add to dashboard Cite

show abstract

“…Given the high degree of overlap between the characteristics of statistical learning and other implicit learning paradigms, a role for the hippocampus is surprising at first glance; however, consideration of the processing capabilities of the hippocampus suggests that it may be a good candidate structure for the demands of statistical learning. In fact, hippocampal involvement has been documented for some versions of the AGL paradigm (e.g., balanced chunk-based designs [Lieberman, Chang, Chiao, Bookheimer, & Knowlton, 2004] and biconditional grammars [Channon et al, 2002]).…”

Section: Introductionmentioning

confidence: 99%

The Necessity of the Hippocampus for Statistical Learning

Covington

Brown‐Schmidt

Duff

2018

Journal of Cognitive Neuroscience

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Converging evidence points to a role for the hippocampus in statistical learning, but open questions about its necessity remain. Evidence for necessity comes from Schapiro and colleagues who report that a single patient with damage to hippocampus and broader medial temporal lobe cortex was unable to discriminate new from old sequences in several statistical learning tasks. The aim of the current study was to replicate these methods in a larger group of patients who have either damage localized to hippocampus or a broader medial temporal lobe damage, to ascertain the necessity of the hippocampus in statistical learning. Patients with hippocampal damage consistently showed less learning overall compared with healthy comparison participants, consistent with an emerging consensus for hippocampal contributions to statistical learning. Interestingly, lesion size did not reliably predict performance. However, patients with hippocampal damage were not uniformly at chance and demonstrated above-chance performance in some task variants. These results suggest that hippocampus is necessary for statistical learning levels achieved by most healthy comparison participants but significant hippocampal pathology alone does not abolish such learning.

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“…Theories based on memory for surface features (e.g. Channon et al, 2002;Vokey & Higham, 2005) or rule abstraction (e.g. Reber, 1967), hold that the structural effect should have increased with exemplar repetition as long as test probes were, on average, more similar to NC than NI items.…”

Section: Discussionmentioning

confidence: 99%

“…Dulany, Carlson, & Dewey, 1984;Knowlton & Squire, 1994;Perruchet & Pacteau, 1990). Surface features in this context might be individual letters or letter sequences, called chunks (Channon et al, 2002;Dienes et al, 1991;Jamieson & Mewhort, 2009a;Perruchet & Pacteau, 1990), or the extent to which letters are repeated in the consonant sequences (e.g. AABBCC rather than ABCDEF, see Whilst the results above concerned task dissociations and were simulating learning efficiency through manipulations of learning parameters rather than direct manipulations of repetition, the logic involved may still offer insight as to what might happen to the structural and episodic effects under repetition.…”

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confidence: 99%

Repeated exposure to exemplars does not enhance implicit learning: A puzzle for models of learning and memory

Neil

Higham

2019

Quarterly Journal of Experimental Psychology

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We learn regularities in the world around us, frequently without conscious effort, a phenomenon known as implicit learning. These regularities are often impossible to verbalise. One example of implicit learning is the structural effect, in which participants learn a rule set combining two factors, such as lexical frequency and concreteness. Theories of implicit learning predict that repetition of exemplar words would result in improved learning of the rule set, increasing the magnitude of the structural effect. Over four experiments, we demonstrate that this is, in fact, not the case. In Experiments 1 and 2, three repetitions of exemplar words result in superior item memory, but no change in the magnitude of the structural effect, compared with individually presented words. In Experiments 3 and 4, the structural effect is shown to be invariant to five repetitions of exemplar words and at high and low numbers of exemplars. In all four experiments, participants were unable to describe the rule set underlying the structural effect. However, confidence ratings demonstrated sensitivity to the structure and this sensitivity, unlike endorsements, increased with strength. The results are discussed in reference to differentiation, structural versus judgement knowledge, and flexible learning systems.

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Is implicit learning spared in amnesia?

Cited by 38 publications

References 38 publications

The Necessity of the Medial Temporal Lobe for Statistical Learning

The Necessity of the Medial Temporal Lobe for Statistical Learning

The Necessity of the Hippocampus for Statistical Learning

Repeated exposure to exemplars does not enhance implicit learning: A puzzle for models of learning and memory

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