Diard, Julien

Phénix, Thierry

Valdois, Sylviane

Hal - Université Grenoble Alpes

Reconciling opposite neighborhood frequency effects in lexical decision: Evidence from a novel probabilistic model of visual word recognition

International audienceA new Bayesian model of visual word recognition is used to simulate neighborhood frequency effects in lexical decision. These effects have been reported as being either facilitatory or inhibitory in behavioral experiments. Our model manages to simulate the apparently contradictory findings. Indeed, studying the dynamic time course of information accumulation in the model shows that effects are facilitatory early, and become inhibitory at later stages. The model provides new insights on the mechanisms at play and their dynamics, leading to better understand the experimental conditions that should yield a fa-cilitatory or an inhibitory neighborhood frequency effect

HAL Université de Savoie

A new Bayesian model of visual word recognition is used tosimulate neighborhood frequency effects in lexical decision.These effects have been reported as being either facilitatory orinhibitory in behavioral experiments. Our model manages tosimulate the apparently contradictory findings. Indeed, study-ing the dynamic time course of information accumulation inthe model shows that effects are facilitatory early, and becomeinhibitory at later stages. The model provides new insights onthe mechanisms at play and their dynamics, leading to betterunderstand the experimental conditions that should yield a fa-cilitatory or an inhibitory neighborhood frequency effect

Reconciling opposite neighborhood frequency effects in lexical decision: Evidence from a novel probabilistic model of visual word recognition

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Hal - Université Grenoble Alpes

HAL Université de Savoie

Hal - Université Grenoble Alpes

HAL Université de Savoie

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