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Related Experiment Video

Updated: May 18, 2026

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

How Noisy is Lexical Decision?

Kevin Diependaele¹, Marc Brysbaert, Peter Neri

¹Ghent University Ghent, Belgium.

Frontiers in Psychology

|September 28, 2012

Summary

This summary is machine-generated.

Participant responses in lexical decision tasks show significant inconsistency, meaning reaction times (RTs) for correct word trials include unrecognized stimuli. This internal noise affects theoretical conclusions derived from word recognition research.

Keywords:

internal noise lexical decision lexicon projects megastudies signal detection

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Area of Science:

Cognitive Psychology
Psycholinguistics
Computational Neuroscience

Background:

Lexical decision tasks are standard in word recognition research.
Theoretical conclusions often rely on linear models of reaction times (RTs) from correct trials only.
These models assume noise-free categorization of words and non-words.

Purpose of the Study:

To quantify internal response inconsistency in lexical decision tasks.
To assess the impact of this noise on theoretical conclusions.
To evaluate the reliability of current modeling approaches.

Main Methods:

Applied signal detection theory methods to estimate internal noise in response choices.
Analyzed response consistency across repeated stimulus presentations.
Extended analysis to reaction times (RTs) to estimate trial-level variance.

Main Results:

Participant response choices exhibit significant internal noise, with only 83-91% explained by an optimal choice model.
Response consistency drops sharply for low-frequency words (below 10 per million).
RT noise estimates were approximately three times higher than response choice noise, with only 8% consistent trial-level variance.

Conclusions:

Standard linear models of lexical decision tasks overestimate the reliability of behavioral data.
Internal response inconsistency significantly limits the conclusions that can be drawn from RT data.
Current trial-level models may need to account for this substantial source of noise.