Phonological neighbors influence word naming through the least supported phoneme.

Yates, Mark; Friend, John; Ploetz, Danielle M.

doi:10.1037/a0011633

Cited by 11 publications

(23 citation statements)

References 41 publications

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“…To ensure that the semantic neighbours do not inhibit processing of the target word, the within‐level inhibition in the semantic system would have to be lowered and/or the facilitatory activation from semantic primitives would have to be increased. This is in line with previous research simulating facilitative orthographic and phonological neighbourhood density effects by adjusting similar parameters in the orthographic and phonological systems of the dual‐route cascaded model (Coltheart et al, ; Yates, ; Yates, Friend & Ploetz, ). The common theme for both the localist and distributed approaches is that SN speeds processing within the semantic system.…”

Section: Discussionsupporting

confidence: 89%

The influence of semantic neighbours on visual word recognition

Yates

2010

Journal Research in Reading

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Although it is assumed that semantics is a critical component of visual word recognition, there is still much that we do not understand. One recent way of studying semantic processing has been in terms of semantic neighbourhood (SN) density, and this research has shown that semantic neighbours facilitate lexical decisions. However, it is not clear if this facilitation reflects actual word recognition processes or is instead due to participant strategies used during the lexical decision task. To address this, the current research used college students as participants and tested the effect of SN density using the semantic categorisation and progressive demasking tasks. Both of these tasks require word identification and are not susceptible to the participant strategies that are seen when using the lexical decision task. The results show that SN facilitates responding in both tasks, indicating that SN effects are not due to task-specific strategies.Most visual word recognition research has been concerned with understanding how orthography, phonology and semantics interact during processing. Of this research, the influence of orthography and phonology has received the greatest attention, and because of this research, many current computational models contain very detailed and wellspecified orthographic and phonological systems (e.g. Coltheart, Rastle, Perry, Langdon these models, the semantic representation tends to be less well specified or completely absent (although see Harm and Seidenberg [2004] for a model that does include a strong semantic component). A potential reason for this may be that it is not clear exactly how semantics should be defined. For example, in terms of phonology, it is apparent that phonemes are an integral part of the phonological representation. Likewise, letters and graphemes are obviously important to coding the orthographic representation. Unfortunately, what defines the semantic representation of a word is not as clear. Thus, an important avenue for research is to identify what semantic variables are important to word recognition, and thereby gain a better understanding of how to define semantics.One of the first and most studied semantic-level variables is semantic ambiguity (i.e. lexical ambiguity). Previous research has shown that lexical decisions and naming latencies are facilitated for words with multiple meanings, but semantic categorisations are inhibited (Hino, Lupker & Pexman, 2002). In terms of a distributed model, when a task relies primarily on orthography (e.g. lexical decision) or phonology (e.g. naming)

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Section: Discussionsupporting

confidence: 89%

The influence of semantic neighbours on visual word recognition

Yates

2010

Journal Research in Reading

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“…Although we have discussed the spread effect in terms of distributed representations, we do not mean to imply that these results could not be explained in terms of a localist architecture such as that used within the dual-route cascaded (DRC) model (Coltheart et al, 2001). In fact, the DRC model has been used to successfully simulate phonological neighborhood effects in the naming task (Mulatti, Reynolds, & Besner, 2006;Yates, 2010;Yates et al, 2008). In terms of the present research, however, it is not clear how the model could simulate the spread effect in lexical decision as the model does not include units that represent the pairing of phonemes (i.e., CV_, _VC, C_C).…”

Section: Discussionmentioning

confidence: 96%

“…The stimuli used in the current experiment were originally used by Vitevitch (2007) in a series of auditory word recognition experiments and were subsequently used to investigate phonological processing within visual word recognition (Yates, 2009a;Yates, Friend, & Ploetz, 2008). The stimuli consisted of 92 words that have a CVC phonological structure.…”

Section: Lexical Decision Stimulimentioning

confidence: 99%

“…For the other half, a phonological neighbor can be formed across all three phoneme positions (P = 3). As reported in previous studies (Vitevitch, 2007;Yates, 2009a;Yates et al, 2008), the words are controlled on many variables known to influence visual word recognition (see Table 1). In addition, we verified that the two groups of words did not differ significantly on the more recent subtitle word frequency and subtitle contextual diversity norms of Brysbaert and New (2009), both p > .55.…”

Section: Lexical Decision Stimulimentioning

confidence: 99%

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Individual differences in spelling ability influence phonological processing during visual word recognition

Yates

Slattery

2019

Cognition

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In the research reported here, we investigated how phonological processing in the lexical decision task is influenced by individual differences in the reading and spelling abilities of participants. We used phonological neighborhood spread as a measure of phonological processing. Spread refers to the number of phoneme positions in a word that can be changed to form a phonological neighbor. Replicating previous research, we found that words forming neighbors across three positions (P3) were recognized more rapidly than those forming neighbors across only two positions (P2). Importantly, we found that this spread effect interacted with spelling ability. The difference between P3 and P2 was largest when spelling recognition was high and spelling production low. These opposing effects of spelling ability are explained in terms of a language system that consists of separate orthographic systems for reading and spelling. Although these two orthographic systems are separate, they share information through a shared response buffer (Jones & Rawson, 2016). Within this framework, it is argued that lexical decisions are made once the information in the response buffer reaches threshold and that time to reach this threshold is influenced by two sources. One is the quality of the orthographic connections in the reading system and is measured by spelling recognition. The other is the quality of the orthographic connections in the spelling system and is measured by spelling production.

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“…Another important consideration is the clustering or spread of neighbors, which has been shown to affect spoken (Chan & Vitevitch, 2009; Vitevitch, 2007) and visual (Mathey & Zagar, 2000) word recognition and word production (Yates et al, 2008). We have focused on the effects of neighbors on target word processing, but the neighbors also affect one another, which should have indirect but measurable effects on target processing.…”

Section: Discussionmentioning

confidence: 99%

Competition and cooperation among similar representations: Toward a unified account of facilitative and inhibitory effects of lexical neighbors.

Chen

Mirman

2012

Psychological Review

162

211

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One of the core principles of how the mind works is the graded, parallel activation of multiple related or similar representations. Parallel activation of multiple representations has been particularly important in the development of theories and models of language processing, where co-activated representations (“neighbors”) have been shown to exhibit both facilitative and inhibitory effects on word recognition and production. Researchers generally ascribe these effects to interactive activation and competition, but there is no unified explanation for why the effects are facilitative in some cases and inhibitory in others. We present a series of simulations of a simple domain-general interactive activation and competition model that is broadly consistent with more specialized domain-specific models of lexical processing. The results showed that interactive activation and competition can indeed account for the complex pattern of reversals. Critically, the simulations revealed a core computational principle that determines whether neighbor effects will be facilitative or inhibitory: strongly active neighbors exert a net inhibitory effect and weakly active neighbors exert a net facilitative effect.

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Phonological neighbors influence word naming through the least supported phoneme.

Cited by 11 publications

References 41 publications

The influence of semantic neighbours on visual word recognition

The influence of semantic neighbours on visual word recognition

Individual differences in spelling ability influence phonological processing during visual word recognition

Competition and cooperation among similar representations: Toward a unified account of facilitative and inhibitory effects of lexical neighbors.

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