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Never seem to find the time: evaluating the physiological time course of visual word recognition with regression analysis of single-item event-related potentials

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TLDR
This article examined the time course of influence of variables ranging from relatively perceptual (e.g., bigram frequency) to relatively semantic on ERP responses, analysed at the single-item level.
Abstract
Visual word recognition is a process that, both hierarchically and in parallel, draws on different types of information ranging from perceptual to orthographic to semantic. A central question concerns when and how these different types of information come online and interact after a word form is initially perceived. Numerous studies addressing aspects of this question have been conducted with a variety of techniques [e.g., behaviour, eye-tracking, event-related potentials (ERPs)], and divergent theoretical models, suggesting different overall speeds of word processing, have coalesced around clusters of mostly method-specific results. Here, we examine the time course of influence of variables ranging from relatively perceptual (e.g., bigram frequency) to relatively semantic (e.g., the number of lexical associates) on ERP responses, analysed at the single-item level. Our results, in combination with a critical review of the literature, suggest methodological, analytic and theoretical factors that may have led to inconsistency in results of past studies; we will argue that consideration of these factors may lead to a reconciliation between divergent views of the speed of word recognition.

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Citations
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Journal ArticleDOI

On the Time Course of Visual Word Recognition: An Event-related Potential Investigation using Masked Repetition Priming

TL;DR: A strong modulation of the N400 and three earlier ERP components (P150, N250, and the P325) that the authors propose reflect sequential overlapping steps in the processing of printed words are shown.
Journal ArticleDOI

Brainprint: Assessing the uniqueness, collectability, and permanence of a novel method for ERP biometrics

TL;DR: There are robustly identifiable features of the ERP that enable labeling of ERPs as belonging to individuals with accuracy reliably above chance, and these features are stable over time, as indicated by continued accurate identification of individuals from ERPs after a lag of up to six months.
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CEREBRE: A Novel Method for Very High Accuracy Event-Related Potential Biometric Identification

TL;DR: It is argued that the averaged event-related potential (ERP) may provide the potential for more accurate biometric identification, as its elicitation allows for some control over the cognitive state of the user to be obtained through the design of the challenge protocol.
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Regression-based estimation of ERP waveforms: I. The rERP framework.

TL;DR: The regression-based rERP framework is introduced, which extends ERP averaging to handle arbitrary combinations of categorical and continuous covariates, partial confounding, nonlinear effects, and overlapping responses to distinct events, all within a single unified system.
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Revisiting the incremental effects of context on word processing: Evidence from single‐word event‐related brain potentials

TL;DR: Modelling word-level variability in ERPs reveals mechanisms by which different sources of information simultaneously contribute to the unfolding neural dynamics of comprehension, as well as probing the continuous and incremental effects of semantic and syntactic context on multiple aspects of lexical processing during sentence comprehension.
References
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Journal ArticleDOI

Measuring word recognition in reading: eye movements and event-related potentials.

TL;DR: It is suggested that these two on-line methodologies, eye movements and event-related potentials, can be used in complementary ways to produce a better picture of the mental action the authors call reading.
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Concreteness effects in semantic processing: ERP evidence supporting dual-coding theory.

TL;DR: The merits of dual-coding and context-availability theories were investigated by examining the topographic distribution of event-related brain potentials in 2 experiments and different scalp distributions of an N400-like negativity were elicited by concrete and abstract words.
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Lexical Representation and Process

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N400-like magnetoencephalography responses modulated by semantic context, word frequency, and lexical class in sentences.

TL;DR: Results help identify a distributed cortical network that supports online semantic processing and correspond well with those previously demonstrated with direct intracranial recordings, and suggested by functional magnetic resonance imaging (fMRI).
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A Nonstochastic Interpretation of Reported Significance Levels

TL;DR: In this paper, an alternative interpretation of a reported significance level, valid in considerable generality, is proposed. But the approach involves permuting observed residuals; the classical randomization approach involves permitting unobservable, or perhaps nonexistent, stochastic disturbance terms.
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