Seeing the Meaning: Top–Down Effects on Letter Identification

Abstract

Most models of reading agree that visual word recognition is underpinned by a highly interactive network in which both bottom–up and top–down processes contribute. What remains unknown is whether evidence of top–down effects upon letter processing are restricted to word-form level information, or whether meaning-level information also plays a role. Here we sought to investigate top–down semantic influences upon letter detection using semantic manipulations of real word imageability and semantic priming, as well as a manipulation of nonword orthographic and phonological composition which varied degree of similarity to real words. A continuous adaptive staircase procedure was used, allowing us to assess the exposure duration needed for accurate letter perception in different stimulus types. Results revealed that in terms of both exposure duration and decision reaction times, words showed an advantage over pseudohomophones and pseudowords, which in turn showed advantages over consonant strings. High imageability words were processed more efficiently than low imageability words, both in terms of the exposure duration required for accurate letter identification and also decision reaction times. The presence of a related as opposed to unrelated semantic prime significantly shortened exposure duration, but also lengthened decision reaction times. This inhibitory semantic priming effect in reaction time was attributed to the interference at the decision stage by stronger activation of the prime letters in the case of related relative to unrelated trials. Taken together, the present results establish for the first time that the semantic dimensions of imageability and semantic priming exert significant effects on letter identification, indicating meaning-level influences on the very earliest stages of written word recognition.

Transition From Sublexical to Lexico-Semantic Stimulus Processing

“…Most work has been done with respect to orthographic processing within the left occipitotemporal cortex and fusiform gyrus. Here, a modulation through phonological (Perea et al, 2016) and semantic properties (Whaley et al, 2016;Evans et al, 2017) was found that facilitates performance and neuronal responsiveness (Strijkers et al, 2015). In addition, intrinsic connection between sublexical (sub-word processing within SPL) and orthographic representation (whole-word processing within fusiform gyrus) were found to be modulated by task-intention (Deng et al, 2012), that is not reflected in current models of language decoding (like CDP+; see Figure 1).…”

Norms of conceptual familiarity for 3,596 French nouns and their contribution in lexical decision

“…decision latencies. Lexical decision is the most frequently used task in the visual word recognition literature to examine semantic effects (Balota & Chumbley, 1984;Cortese & Schock, 2013;Evans et al, 2017). The results of our regression model showed that conceptual familiarity significantly contributed to lexical decision latencies, over and beyond the contribution of other psycholinguistic and semantic variables that have previously shown a facilitatory effect on lexical decision latencies.…”

“…It is widely accepted that word-form (e.g., word length), lexical (e.g., objective word frequency) and semantic variables (e.g., imageability, age of acquisition or AoA) influence language processing of written stimuli, as observed using both lexical decision and word naming tasks (Alario & Ferrand, 1999;Baluch & Besner, 2001;Cortese & Schock, 2013;Evans, Lambon Ralph, & Woollams, 2017;Ferrand et al, 2008;Strain & Herdman, 1999;Strain, Patterson, & Seidenberg, 1995;Zevin & Balota, 2000). Some of these variables are mostly based on objective measures (i.e., the number of letters or syllables, the first letter or phoneme of a stimulus, objective word frequencies based on film subtitles All the co-authors contributed equally on this work.…”

Matrices of the frequency and similarity of Arabic letters and allographs

“…More recently, research has come to focus on understanding the visual system and how it represents and processes letters as visual objects, without losing interest, however, in attempting to make written text more comprehensible or helping learners to acquire reading skills more easily (Boles & Clifford, 1989;Fiset et al, 2009;Liu & Arditi, 2001;Mueller & Weidemann, 2012). Collectively, these studies have played a fundamental role in enabling the design and implementation of many well-controlled empirical studies seeking to pin down the dynamics of letter processing (e.g., Evans, Lambon Ralph, & Woollams, 2017;Grainger, Dufau, Montant, Ziegler, & Fagot, 2012;Kinoshita & Kaplan, 2008;Schelonka, Graulty, Canseco-Gonzalez, & Pitts, 2017).…”