Model-generated lexical activity predicts graded ERP amplitudes in lexical decision

Abstract

. These studies relate the orthographic neighborhood density of letter strings to the amount of global lexical activity in the brain, generated by a hypothetical mental lexicon as speculated in an early paper by [Jacobs, A.M. and Carr, T.H. (1995). Mind mappers and cognitive modelers: Toward crossfertilization, Behav. Brain. Sci. 18 362-363]. The present study uses model-generated stimuli theoretically eliciting graded global lexical activity and relates this activity to activation of lexical processing networks using event-related potentials (ERPs). The results from a lexical decision task provide evidence for an effect of lexicality around 350 ms post-stimulus and also a graded effect of global lexical activity for nonwords around 500 ms post-stimulus. The data are interpreted as reflecting two different decision processes: an identification process based on local lexical activity underlying the 'yes' response to words and a temporal deadline process underlying the 'no' response to nonwords based on global lexical activity. IntroductionStudies of visual word recognition focusing on lexical access employ a number of variables assumed to influence this process (e.g., word frequency or neighborhood density) in a number of tasks (e.g., lexical or semantic decision, naming, or perceptual identification). One of the most prominent variables is neighborhood density, i.e., the number of orthographic neighbors, which can be generated by changing one letter of a given word, often referred to as the N-metric (Coltheart et al., 1977). When participants make a lexical decision, a standard finding is that responses to words of large neighborhoods (so called high-N words) are faster than to words having small neighborhoods (Andrews, 1989(Andrews, , 1992(Andrews, , 1997; Carreiras et al.,

Time course and task dependence of emotion effects in word processing

“…Also confirming previous reports (e.g., Braun et al, 2006;Chwilla et al, 1995), ERPs showed the expected effect of lexicality, consisting of a greater negativity for pseudowords than for correct words, starting around 320 msec. Effects of emotional valence began approximately 50 msec after the onset of the lexicality effect and were similar for positive and negative verbs.…”

“…For instance, on the basis of ERP findings in repetition masking, Holcomb andGrainger (2006, 2007) postulated a sequence of distinguishable orthographic, lexical, and postlexical semantic-processing stages, taking place, in order, from 150 to 200 msec, from 250 to 400 msec, and after 400 msec following word presentation onset. The suggested latency of the lexical stage is in line with most reports of the latency of the so-called lexicality effect, which appears after about 300 msec (e.g., Braun et al, 2006;Chwilla, Brown, & Hagoort, 1995;Hutz ler et al, 2004). The lexicality effect consists of an enhanced negativity to orthographically and phonologically legal but nonexistent pseudowords or to illegal nonwords, when they have to be distinguished from existing words in lexical decision tasks.…”

Deficits in Processing Characters in Chinese Developmental Dyslexia: Preliminary Results From Event-related Potentials and Time Frequency Analyses

“…The polarities of the ERP components at these sites are correlated with ease of processing as previously reported (Bentin, Mouchetant-Rostaing, Giard, Echallier, & Pernier, 1999;Braun, Jacobs, Hahne, Ricker, Hofmann, & Hutzler, 2006). The time windows of the components show a pattern of activities early on in left occipital and right frontal, followed by activities in right occipital and left frontal, respectively, and responses beginning around 400ms post-stimulus in the central region.…”

Stimulus onset asynchrony and the timeline of word recognition: Event-related potentials during sentence reading

“…Providing temporal conditions and constraints, our results may contribute to the advancement of theoretical accounts, and hence to a cross-fertilization between cognitive models and neuroscience (Braun, Jacobs, Hahne, Ricker, Hofmann, & Hutzler, 2006;Barber & Kutas, 2007;Grainger & Holcomb, 2008, 2009Jacobs & Carr, 1995) Second, while some effects were rather similar across SOAs, the results also demonstrate that the time course of word recognition is modulated by the rate at which words are presented. This seems particularly critical for the precise tracking of the chronology of effects under normal reading rate; results obtained with unnaturally long SOAs do not necessarily translate one to one to fast reading.…”