Individual differences in emotion word processing: A diffusion model analysis

Abstract

The exploratory study investigated individual differences in implicit processing of emotional words in a lexical decision task. A processing advantage for positive words was observed, and differences between happy and fear-related words in response times were predicted by individual differences in specific variables of emotion processing: Whereas more pronounced goal-directed behavior was related to a specific slowdown in processing of fear-related words, the rate of spontaneous eye blinks (indexing brain dopamine levels) was associated with a processing advantage of happy words. Estimating diffusion model parameters revealed that the drift rate (rate of information accumulation) captures unique variance of processing differences between happy and fear-related words, with highest drift rates observed for happy words. Overall emotion recognition ability predicted individual differences in drift rates between happy and fear-related words. The findings emphasize that a significant amount of variance in emotion processing is explained by individual differences in behavioral data.

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

“…Although the affective information from image, video, and audio stimuli has been extensively studied, olfactory stimuli [26], written words [27][28][29][30][31][32], food stimuli (enriched by emotional stimuli) [33], and games have been used as elicitation methods in a number of studies as ways to assess human emotional state by investigating physiological signals [34][35][36][37].…”

“…Because individual emotional differences impact word processing, differences in interpreting a string of words may elicit different emotional responses. These varying emotional responses are caused by involuntary (implicit) semantic processing, lexical decision tasks (LDTs), and interpretations of perceived positive or negative emotional words [29,31,32,150,160].…”

Electrophysiological correlates of the drift diffusion model in visual word recognition

“…The lexical decision task is one of the most prominent paradigms in visual word recognition (e.g., Grainger and Jacobs, ) and is known to reflect bottom–up perceptual and top–down semantic and affective processing (Hofmann and Jacobs, ; Jacobs et al, ). The DDM framework has been successfully applied to assess behavioral aspects of the lexical decision task several previous times (Mueller and Kuchinke, ; Ratcliff et al, 2004a, 2004b; White et al, ). If the effects from perceptual decision making are transferable to more high‐level cognitive decision making, we expect individual differences in evidence accumulation as represented by the drift rate parameters to be related to ERP amplitudes (Philiastides et al, ) and power values in the theta frequency band (van Vugt et al, ).…”

“…Condition‐wise examinations of the drift rate parameter have revealed to also capture differences in stimulus quality, for example, in terms of differences in word emotionality (Mueller and Kuchinke, ). In the second step, this study simultaneously examined two aspects of stimulus quality in the lexical decision task: item repetition effects and emotionality.…”

The mediational role of distracting stimuli in emotional word recognition

“…In other words, to deal with emotional valence could be also considered a cognitive cost. Other authors have stipulated that accuracy and speed processing might be accommodated through several parameters such as decision components and variability (Mueller & Kuchinke 2016;Ratcliff, Smith, Brown, & McKoon 2016). In terms of memory processing, recognition might include some retrievalbased processing (Racsmány, Szőllősi, & Bencze 2017).…”