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PubMed2006

Implicit learning and statistical learning: one phenomenon, two approaches.

The domain-general learning mechanisms elicited in incidental learning situations are of potential interest in many research fields, including language acquisition, object knowledge formation and motor learning. They have been the focus of studies on implicit learning for nearly 40 years. Stemming from a different research tradition, studies on statistical learning carried out in the past 10 years after the seminal studies by Saffran and collaborators, appear to be closely related, and the similarity between the two approaches is strengthened further by their recent evolution. However, implicit learning and statistical learning research favor different interpretations, focusing on the formation of chunks and statistical computations, respectively. We examine these differing approaches and suggest that this divergence opens up a major theoretical challenge for future studies.

Attention↗

PubMed2026

Implicit and explicit statistical learning in reading: Evidence from a randomized controlled-learning study and computational modeling.

A key challenge in reading acquisition is understanding how learners extract the complex probabilistic mappings between print, meaning, and sound. Statistical learning (SL) theory offers a mechanistic account of how such mappings are acquired, whether implicitly through exposure or explicitly through instruction. We conducted a randomized controlled-learning study in Chinese, a writing system characterized by multiple sub-lexical regularities linking orthography, semantics, and phonology. Ninety-five 2nd-3rd graders with or at risk for dyslexia were randomly assigned to one of three groups: an implicit-SL training group exposed to repeated lexical and sublexical orthography-semantics-phonology associations, an explicit-SL training group receiving the same input plus explicit instruction on the sublexical print-sound mapping, and a no-SL control group. Both SL groups outperformed controls on the characters they were trained on, as well as on untrained characters that required generalization. However, only the explicit group demonstrated abstraction of print-sound mapping to novel items. Neural network simulations further revealed distinct mechanisms supporting implicit and explicit SL, consistent with a dual-system account of reading acquisition. Together, these findings (1) clarify how implicit and explicit learning distinctly support the discovery of statistical structure in written language and (2) underscore the implicit-explicit dual learning mechanism underlying reading acquisition.

Humans↗

PubMed1999

Further evidence for feature correlations in semantic memory.

The role of feature correlations in semantic memory is a central issue in conceptual representation. In two versions of the feature verification task, participants were faster to verify that a feature (< is juicy >) is part of a concept (grapefruit) if it is strongly rather than weakly intercorrelated with the other features of that concept. Contrasting interactions between feature correlations and SOA were found when the concept versus the feature was presented first. An attractor network model of word meaning that naturally learns and uses feature correlations predicted those interactions. This research provides further evidence that semantic memory includes implicitly learned statistical knowledge of feature relationships, in contrast to theories such as spreading activation networks, in which feature correlations play no role.

Humans↗

PubMed2004

Implicit learning of musical timbre sequences: statistical regularities confronted with acoustical (dis)similarities.

The present study investigated the influence of acoustical characteristics on the implicit learning of statistical regularities (transition probabilities) in sequences of musical timbres. The sequences were constructed in such a way that the acoustical dissimilarities between timbres potentially created segmentations that either supported (S1) or contradicted (S2) the statistical regularities or were neutral (S3). In the learning group, participants first listened to the continuous timbre sequence and then had to distinguish statistical units from new units. In comparison to a control group without the exposition phase, no interaction between sequence type and amount of learning was observed: Performance increased by the same amount for the three sequences. In addition, performance reflected an overall preference for acoustically similar timbre units. The present outcome extends previous data from the domain of implicit learning to complex nonverbal auditory material. It further suggests that listeners become sensitive to statistical regularities despite acoustical characteristics in the material that potentially affect grouping.

Acoustics↗

PubMedDate not supplied

Children's implicit learning of graphotactic and morphological regularities.

In French, the transcription of the same sound can be guided by both probabilistic graphotactic constraints (e.g., /epsilon t/ is more often transcribed ette after -v than after -f) and morphological constraints (e.g., /epsilon t/ is always transcribed ette when used as a diminutive suffix). Three experiments showed that pseudo-word spellings of 8-to 11-year-old children and adults were influenced by both types of constraints. The influence of graphotactic regularities persisted when reliance on morphological rules was possible, without any falling off as a function of age. This suggests that rules are not abstracted, even after massive amounts of exposure to a rule-based material. These results can be accounted for by a statistical model of implicit learning.

Child↗

PubMed2006

Dynamical statistical shape priors for level set-based tracking.

In recent years, researchers have proposed introducing statistical shape knowledge into level set-based segmentation methods in order to cope with insufficient low-level information. While these priors were shown to drastically improve the segmentation of familiar objects, so far the focus has been on statistical shape priors which are static in time. Yet, in the context of tracking deformable objects, it is clear that certain silhouettes (such as those of a walking person) may become more or less likely over time. In this paper, we tackle the challenge of learning dynamical statistical models for implicitly represented shapes. We show how these can be integrated as dynamical shape priors in a Bayesian framework for level set-based image sequence segmentation. We assess the effect of such shape priors "with memory" on the tracking of familiar deformable objects in the presence of noise and occlusion. We show comparisons between dynamical and static shape priors, between models of pure deformation and joint models of deformation and transformation, and we quantitatively evaluate the segmentation accuracy as a function of the noise level and of the camera frame rate. Our experiments demonstrate that level set-based segmentation and tracking can be strongly improved by exploiting the temporal correlations among consecutive silhouettes which characterize deforming shapes.

Algorithms↗

PubMed2002

Implicit power motivation predicts men's testosterone changes and implicit learning in a contest situation.

This study tested the hypothesis that implicit power motivation moderates men's testosterone responses to victory or defeat in a contest situation. It also explored to what extent postvictory testosterone increases are associated with enhanced implicit learning of behavior instrumental for winning a contest. Salivary testosterone levels were assessed in 66 male adults several times before and after a contest whose outcome (winning or losing against a competitor on an implicit learning task) was varied experimentally. Among participants low in activity inhibition, a measure of impulse control, the power motive was a significant positive predictor of testosterone increases (15 min postcontest; r = 0.71, P = 0.01) and implicit learning (r = 0.68, P < 0.05) after a victory, whereas it was a significant negative predictor of implicit learning (r = -0.58, P = 0.01) but not of testosterone increases (r = -0.08, ns) after a defeat. Moreover, among participants low in activity inhibition testosterone increases were associated with enhanced implicit learning (r = 0.38, P < 0.05) and there was statistical evidence that in winners testosterone increases mediated the effect of power motivation on implicit learning. Participants high in activity inhibition did not display this pattern of results.

Adult↗

PubMed2005

Towards an explicit account of implicit learning.

PURPOSE OF REVIEW: The human brain supports acquisition mechanisms that can extract structural regularities implicitly from experience without the induction of an explicit model. Reber defined the process by which an individual comes to respond appropriately to the statistical structure of the input ensemble as implicit learning. He argued that the capacity to generalize to new input is based on the acquisition of abstract representations that reflect underlying structural regularities in the acquisition input. We focus this review of the implicit learning literature on studies published during 2004 and 2005. We will not review studies of repetition priming ('implicit memory'). Instead we focus on two commonly used experimental paradigms: the serial reaction time task and artificial grammar learning. Previous comprehensive reviews can be found in Seger's 1994 article and the Handbook of Implicit Learning. RECENT FINDINGS: Emerging themes include the interaction between implicit and explicit processes, the role of the medial temporal lobe, developmental aspects of implicit learning, age-dependence, the role of sleep and consolidation. SUMMARY: The attempts to characterize the interaction between implicit and explicit learning are promising although not well understood. The same can be said about the role of sleep and consolidation. Despite the fact that lesion studies have relatively consistently suggested that the medial temporal lobe memory system is not necessary for implicit learning, a number of functional magnetic resonance studies have reported medial temporal lobe activation in implicit learning. This issue merits further research. Finally, the clinical relevance of implicit learning remains to be determined.

Brain↗

PubMed2001

Statistical learning in a serial reaction time task: access to separable statistical cues by individual learners.

The ability of adult learners to exploit the joint and conditional probabilities in a serial reaction time task containing both deterministic and probabilistic information was investigated. Learners used the statistical information embedded in a continuous input stream to improve their performance for certain transitions by simultaneously exploiting differences in the predictability of 2 or more underlying statistics. Analysis of individual learners revealed that although most acquired the underlying statistical structure veridically, others used an alternate strategy that was partially predictive of the sequences. The findings show that learners possess a robust learning device well suited to exploiting the relative predictability of more than I source of statistical information at the same time. This work expands on previous studies of statistical learning, as well as studies of artificial grammar learning and implicit sequence learning.

Adult↗

PubMed2004

Memory impairment and auditory evoked potential gating deficit in schizophrenia.

Impaired sensory gating and memory function were reported in a study of 10 schizophrenic patients and 10 age- and sex-matched normal subjects. The P50 component of the auditory evoked potential was used as an index of gating. Explicit memory was tested with the Wechsler Memory Scale and implicit memory by artificial grammar learning. The schizophrenic patients showed deficits in both verbal paired associate and visual reproduction tasks. They demonstrated impaired implicit learning in color patterns but not letter strings. They also showed impaired P50 sensory gating. Three-dimensional brain mapping revealed a differential distribution of brain potentials in the processing of S1 and S2 at either P50 or N100 in both groups. However, the group difference was not statistically confirmed. In the controls, both implicit letter-string learning and explicit verbal paired associates were positively correlated with N100 gating, suggesting an association of the early attentive component with lexicons. In the schizophrenic patients, color-pattern implicit learning was positively correlated with P50 gating. The modality-specific impairment of implicit learning in schizophrenia may reflect a failure of adaptive filtering on the flooding input from color patterns.

Adult↗

PubMed2004

Functional MRI study of a serial reaction time task in Huntington's disease.

The aim of this study was to investigate pathophysiological changes at an early stage of clinical Huntington's disease (HD) using a functional magnetic resonance imaging (fMRI) study and a serial reaction time task paradigm. Mildly affected and presymptomatic HD subjects (n = 8) and healthy normal controls (NC, n = 12) were studied. A group behavioral effect of implicit learning was seen only in the control population. Individual statistical parametric mapping (SPM) analysis showed more consistent activation of the caudate nucleus and putamen in the NC group. In the HD group, the group average SPM showed significant activation in the right head of caudate nucleus, as well as bilateral thalami, left middle temporal, right superior temporal, right superior frontal, right middle and inferior frontal and right postcentral gyri. In the comparison of between-group differences (NC-HD), reduced activation in the HD group relative to NC was observed in the right middle frontal, left middle occipital, left precuneus, and left middle frontal gyri. The variable striatal activity in the Huntington's group suggests early functional loss possibly associated with previously demonstrated early atrophy of these same neural structures.

Adult↗

PubMedDate not supplied

The relevance of the nature of learned associations for the differentiation of human memory systems.

In a previous functional magnetic resonance imaging (fMRI) study we demonstrated an involvement of the medial temporal lobe (MTL) during an implicit learning task. We concluded that the MTL was engaged because of the complex contingencies that were implicitly learned. In addition, the basal ganglia demonstrated effects of a paralleled proceduralization of fixed stimulus-response associations. In the present study we directly tested the hypothesis that the MTL activation depends upon implementing the complex regularity in task material, whereas activation of basal ganglia does not. Therefore, we rearranged task material such that it did not contain any complex regularity. The statistical comparison of behavioral and fMRI data between the materials allowed for isolating effects that were directly related to the implicit learning process regarding the complex regularity. The results showed a reliable difference of fMRI signal limited to the MTL, indicating a specific functional role of the MTL in implicit learning of complex contingencies. Furthermore, no difference of BOLD (Blood-Oxygenation Level Dependent) signal in the basal ganglia and cerebellum were detected, supporting the assumption of a functional involvement of the structures in proceduralization of simple stimulus-response associations but not in implicitly learning complex relations. We therefore conclude that the nature of the learned associations is relevant for determining the neuronal focus of learning, rather than the accompanying awareness.

Adult↗

PubMed2005

The automaticity of visual statistical learning.

The visual environment contains massive amounts of information involving the relations between objects in space and time, and recent studies of visual statistical learning (VSL) have suggested that this information can be automatically extracted by the visual system. The experiments reported in this article explore the automaticity of VSL in several ways, using both explicit familiarity and implicit response-time measures. The results demonstrate that (a) the input to VSL is gated by selective attention, (b) VSL is nevertheless an implicit process because it operates during a cover task and without awareness of the underlying statistical patterns, and (c) VSL constructs abstracted representations that are then invariant to changes in extraneous surface features. These results fuel the conclusion that VSL both is and is not automatic: It requires attention to select the relevant population of stimuli, but the resulting learning then occurs without intent or awareness.

Attention↗

PubMed1999

Learning-related effects and functional neuroimaging.

A fundamental problem in the study of learning is that learning-related changes may be confounded by nonspecific time effects. There are several strategies for handling this problem. This problem may be of greater significance in functional magnetic resonance imaging (fMRI) compared to positron emission tomography (PET). Using the general linear model, we describe, compare, and discuss two approaches for separating learning-related from nonspecific time effects. The first approach makes assumptions on the general behavior of nonspecific effects and explicitly models these effects, i.e., nonspecific time effects are incorporated as a linear or nonlinear confounding covariate in the statistical model. The second strategy makes no a priori assumption concerning the form of nonspecific time effects, but implicitly controls for nonspecific effects using an interaction approach, i.e., learning effects are assessed with an interaction contrast. The two approaches depend on specific assumptions and have specific limitations. With certain experimental designs, both approaches may be used and the results compared, lending particular support to effects that are independent of the method used. A third and perhaps better approach that sometimes may be practically unfeasible is to use a completely temporally balanced experimental design. The choice of approach may be of particular importance when learning-related effects are studied with fMRI.

Adult↗

PubMed1997

Evaluative learning with "subliminally" presented stimuli.

Evaluative learning refers to the change in the affective evaluation of a previously neutral stimulus (NS) that occurs after the stimulus has been associated with a second, positive or negative, affective stimulus (AS). Four experiments are reported in which the AS was presented very briefly. Significant evaluative learning was observed in participants who did not notice the presentation of the affective stimuli (ASi) (Experiment 2) or could not discriminate between the briefly presented positive and negative ASi when asked to do so (Experiment 3). In two other experiments (Experiments 1 and 4), no significant learning effect was obtained. A meta-analysis performed on the present and previously reported results (De Houwer, Baeyens, & Eelen, 1994) gave evidence for a small, though statistically reliable evaluative learning effect when ASi are presented "subliminally." This finding supports the hypothesis that evaluative associations can be learned implicitly.

Adult↗

PubMed2006

Is implicit sequence learning impaired in Parkinson's disease? A meta-analysis.

The aim of the present study was to examine impairment of implicit learning in Parkinson's disease (PD) by means of a meta-analysis of studies that used the serial reaction time (SRT) task. The authors performed a systematic review and meta-analysis of published journal articles (1987-2005) that used the SRT task with patients with PD. The principal outcome measures used to compare studies were (a) the difference in reaction time between the last block of ordered sequence trials and the randomized block for PD and control participants and (b) fixed and random effects pooled estimates by the inverse weighting method. Six studies, including 67 patients with PD, met the inclusion criteria. The meta-analysis showed that implicit learning was impaired in PD, relative to healthy controls, with a standardized mean difference of 0.73 (95% confidence interval = 0.38, 1.07). Implicit sequence learning appears to be impaired in patients with PD. Some common methodological weaknesses and limitations in the reporting of statistical data are discussed.

Aged↗

PubMed2006

The striatum and probabilistic implicit sequence learning.

The distinction between implicit (unconscious) and explicit (conscious) learning is controversial. Some argue that explicit learning is dependent on the medial temporal lobes, whereas implicit learning is mediated by the basal ganglia and others propose that all learning is explicit. The purpose of the present study was to investigate the involvement of the basal ganglia in implicit learning by examining learning of a probabilistic sequence of targets, in patients with Parkinson's disease (PD) and controls. Following learning, we assessed participants' awareness of the sequence structure by asking them to generate or withhold sequence consistent responses (process dissociation procedure) and to perform a recognition test in which measures of priming and recognition were obtained concurrently. Although the PD group demonstrated evidence of probabilistic sequence learning in this study, learning was significantly attenuated compared to controls. Residual learning in the PD group was genuinely implicit in nature because (a) PD patients were not able to control the expression of their acquired knowledge, and (b) their knowledge supported subsequent priming of sequence-consistent responses but recognition ratings were at chance. In contrast, following learning controls were capable of above chance recognition indicating that their sequential knowledge was acquired in a more explicit way. The results support the view that (i) the basal ganglia contribute to probabilistic implicit sequence learning (ii) that such learning can occur implicitly without explicit knowledge in PD patients.

Aged↗

PubMed2003

Probabilistic methods in BCI research.

This paper suggests a probabilistic treatment of the signal processing part of a brain-computer interface (BCI). We suggest two improvements for BCIs that cannot be obtained easily with other data driven approaches. Simply by using one large joint distribution as a model of the entire signal processing part of the BCI, we can obtain predictions that implicitly weight information according to its certainty. Offline experiments reveal that this results in statistically significant higher bit rates. Probabilistic methods are also very useful to obtain adaptive learning algorithms that can cope with nonstationary problems. An experimental evaluation shows that an adaptive BCI outperforms the equivalent static implementations, even when using only a moderate number of trials. This suggests that adaptive translation algorithms might help in cases where brain dynamics change due to learning effects or fatigue.

Algorithms↗