Jerome Daltrozzo

Neurocognitive mechanisms of statistical-sequential learning: what do event-related potentials tell us?

Statistical-sequential learning (SL) is the ability to process patterns of environmental stimuli, such as spoken language, music, or one’s motor actions, that unfold in time. The underlying neurocognitive mechanisms of SL and the associated cognitive representations are still not well understood as reflected by the heterogeneity of the reviewed cognitive models. The purpose of this review is: (1) to provide a general overview of the primary models and theories of SL, (2) to describe the empirical research – with a focus on the event-related potential (ERP) literature – in support of these models while also highlighting the current limitations of this research, and (3) to present a set of new lines of ERP research to overcome these limitations. The review is articulated around three descriptive dimensions in relation to SL: the level of abstractness of the representations learned through SL, the effect of the level of attention and consciousness on SL, and the developmental trajectory of SL across the life-span. We conclude with a new tentative model that takes into account these three dimensions and also point to several promising new lines of SL research.

Cortical Information Processing in Coma

ObjectivesTo evaluate cortical information processing (particularly, semantic processing) in acute nontraumatic coma by means of event-related brain potentials (ERPs). MethodsThe tests included measures of obligatory auditory processing (N100), automatic (Mismatch Negativity) and controlled (P300) detection of stimulus deviance, and semantic processing (ERP effects in word pairs and sentences). The tests were presented to 20 healthy participants and 42 coma patients with Glasgow Coma Scale <9. ResultsResponders (ie, patients whose ERP data indicate that their brain was able to process the corresponding stimuli) were found in each ERP test, and their distribution was statistically different from that expected by chance. Particularly, 7 responders were found in the word pair paradigm and 3 responders in the sentence paradigm. The P300 responsiveness highly correlated with other ERP responses, with Glasgow Coma Scale and with the future development of coma (ie, P300 on day 4 was related to the clinical state on day 20). ConclusionsResults suggest a wide range of cortical information processing in coma, including semantic processing. The question is discussed of whether, and to what extent, these processing operations are related to conscious awareness of stimuli.

The N400 and Late Positive Complex (LPC) Effects Reflect Controlled Rather than Automatic Mechanisms of Sentence Processing

This study compared automatic and controlled cognitive processes that underlie event-related potentials (ERPs) effects during speech perception. Sentences were presented to French native speakers, and the final word could be congruent or incongruent, and presented at one of four levels of degradation (using a modulation with pink noise): no degradation, mild degradation (2 levels), or strong degradation. We assumed that degradation impairs controlled more than automatic processes. The N400 and Late Positive Complex (LPC) effects were defined as the differences between the corresponding wave amplitudes to incongruent words minus congruent words. Under mild degradation, where controlled sentence-level processing could still occur (as indicated by behavioral data), both N400 and LPC effects were delayed and the latter effect was reduced. Under strong degradation, where sentence processing was rather automatic (as indicated by behavioral data), no ERP effect remained. These results suggest that ERP effects elicited in complex contexts, such as sentences, reflect controlled rather than automatic mechanisms of speech processing. These results differ from the results of experiments that used word-pair or word-list paradigms.

Visual statistical learning is related to natural language ability in adults: An ERP study

HighlightsRelationship between sequential learning and language performance.Visual sequential learning task.Sequential learning was assessed through event‐related potentials.Receptive vocabulary, syntactic processing, and word prediction in sentences.Sequential learning depends on language performance. ABSTRACT Statistical learning (SL) is believed to enable language acquisition by allowing individuals to learn regularities within linguistic input. However, neural evidence supporting a direct relationship between SL and language ability is scarce. We investigated whether there are associations between event‐related potential (ERP) correlates of SL and language abilities while controlling for the general level of selective attention. Seventeen adults completed tests of visual SL, receptive vocabulary, grammatical ability, and sentence completion. Response times and ERPs showed that SL is related to receptive vocabulary and grammatical ability. ERPs indicated that the relationship between SL and grammatical ability was independent of attention while the association between SL and receptive vocabulary depended on attention. The implications of these dissociative relationships in terms of underlying mechanisms of SL and language are discussed. These results further elucidate the cognitive nature of the links between SL mechanisms and language abilities.

ENHANCING IMPLICIT LEARNING WITH POSTHYPNOTIC SUGGESTION: An ERP Study

Abstract Can posthypnotic suggestion (PHS) enhance cognitive abilities? The authors tested behaviorally and with event-related potentials (ERP) if sequential learning (SL), the ability to learn statistical regularities, can be enhanced with PHS. Thirty adults were assessed with the Stanford Hypnotic Susceptibility Scale (Form C) and an auditory SL task. Before this task, half the sample received a PHS to enhance SL, and the other half received the same suggestion under normal waking state. Response times and ERPs indicated a strong effect of PHS. Compared to the control group, PHS inverted, attenuated, or left unaffected the response time SL effect in low, medium, and high hypnotizability participants, respectively. These results suggest that PHS cannot be used to enhance SL.

Effect of pattern awareness on the behavioral and neurophysiological correlates of visual statistical learning

Abstract Statistical learning is the ability to extract predictive patterns from structured input. A common assumption is that statistical learning is a type of implicit learning that does not result in explicit awareness of learned patterns. However, there is also some evidence that statistical learning may involve explicit processing to some extent. The purpose of this study was to examine the effect of pattern awareness on behavioral and neurophysiological correlates of visual statistical learning. Participants completed a visual learning task while behavioral responses and event-related potentials were recorded. Following the completion of the task, awareness of statistical patterns was assessed through a questionnaire scored by three independent raters. Behavioral findings indicated learning only for participants exhibiting high pattern awareness levels. Neurophysiological data indicated that only the high-pattern awareness group showed expected P300 event-related potential learning effects, although there was also some indication that the low awareness groups showed a sustained mid- to late-latency negativity. Linear mixed-model analyses confirmed that only the high awareness group showed neurophysiological indications of learning. Finally, source estimation results revealed left hemispheric activation was associated with statistical learning extending from frontal to occipital and parietal regions. Further analyses suggested that left insula, left parahippocampal, and right precentral regions showed different levels of activation based on pattern awareness. To conclude, we found that pattern awareness, a dimension associated with explicit processing, strongly influences the behavioral and neurophysiological correlates of visual statistical learning.