Dataset Information

(Early) context effects on event-related potentials over natural inputs.

ABSTRACT: Language understanding requires the integration of the input with preceding context. Event-related potentials (ERPs) have contributed significantly to our understanding of what contextual information is accessed and when. Much of this research has, however, been limited to experimenter-designed stimuli with highly atypical lexical and context statistics. This raises questions about the extent to which previous findings generalize to everyday language processing of natural stimuli with typical linguistic statistics. We ask whether context can affect ERPs over natural stimuli early, before the N400 time window. We re-analyzed a data set of ERPs over ~700 visually presented content words in sentences from English novels. To increase power, we employed linear mixed effects regression simultaneously modeling random variance by subject and by item. To reduce concerns about Type I error inflation common to any type of time series analysis, we introduced a simple approach to model and discount auto-correlations at multiple, empirically determined, time lags. We compared this approach to Bonferroni correction. Planned follow-up analyses used Generalized Additive Mixture Models to assess the linearity of contextual effects, including lexical surprisal, found within the N400 time window. We found that contextual information affects ERPs in both early (~200ms after word onset) and late (N400) time windows, supporting a cascading, interactive account of lexical access.

SUBMITTER: Yan S

PROVIDER: S-EPMC7331969 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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(Early) context effects on event-related potentials over natural inputs.

Yan Shaorong S Jaeger T Florian TF

Language, cognition and neuroscience 20190330 5

Language understanding requires the integration of the input with preceding context. Event-related potentials (ERPs) have contributed significantly to our understanding of what contextual information is accessed and when. Much of this research has, however, been limited to experimenter-designed stimuli with highly atypical lexical and context statistics. This raises questions about the extent to which previous findings generalize to everyday language processing of natural stimuli with typical li ...[more]

PMID: 32617349

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Project description:Previous research has pointed out that the combination of orthographic and semantic-associative training is a more advantageous strategy for the lexicalization of novel written word-forms than their single orthographic training. However, paradigms used previously involve explicit stimuli categorization (lexical decision), which likely influence word learning. In the present study, we used a more automatic task (silent reading) to determine the advantage of the associative training, by comparing the brain electrical signals elicited in combined (orthographic and semantic) and single (only orthographic) training conditions. In addition, the learning effect (in terms of similar neurophysiological activity between novel and known words) was also tested under a categorization paradigm, enabling determination of the possible influence of the training task in the lexicalization process. Results indicated that novel words repeatedly associated with meaningful cues showed a higher attenuation of N400 responses than those trained in the single orthographic condition, confirming the higher facilitation in the lexico-semantic processing of these stimuli, as a consequence of semantic associations. Moreover, only when the combined training was carried out in the reading task did novel words show similar N400 responses to those elicited by known words, suggesting the achievement of a similar lexical processing to known words. Crucially, when the training is carried out under a demanding task context (lexical decision), known words exhibited positive enhancement within the N400 time window, contributing to maintaining N400 differences with novel trained words and confounding the outcome of the learning. Such deflection-compatible with the modulation of the categorization-related P300 component-suggests that novel word learning could be influenced by the activation of categorization-related processes. Thus, the use of low-demand tasks arises as a more appropriate approach to study novel word learning, enabling the build-up process of mental representations, which probably depends on pure lexical and semantic factors rather than being guided by categorization demands.

Dataset Information

(Early) context effects on event-related potentials over natural inputs.

Publications

(Early) context effects on event-related potentials over natural inputs.

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