Abstract
Reading is a complex process that includes the integration of information about letters (graphemes) and sounds (phonemes). In many circumstances, such as noisy environments, response inhibition is an additional factor that plays a marked role in successful oral reading. Response inhibition can take the form of task relevant inhibition (i.e., foils in a go/no-go task) and task irrelevant inhibition (i.e., distractor information). Here we investigated task relevant inhibition by having participants (N = 30) take part in two tasks: go/no-go naming with nonwords foils (GNG-NW) and go/no-go naming with pseudohomophones foils (GNG-PH). Also, we investigated the addition of task irrelevant inhibition by having participants (N = 28) take part in two tasks: GNG-NW + information masking and GNG-PH + information masking. We provide evidence that during a task relevant inhibition task, sub-word sound level information can be successfully inhibited, as evidenced by comparable response times for regular words and exception words, provided the foils do not contain familiar sound-based information (GNG-NW). In contrast, regular words were read aloud faster than exception words in a GNG-PH task, indicating that sub-word level interference occurs when the foils contain familiar sound-based information. The addition of task irrelevant inhibition (i.e., information masking at the phoneme level), served to increase response time overall, but did not impact the pattern of response times between regular words and exception words. Together these findings provide useful information regarding the role of response inhibition in word recognition and may be useful in computational models of word recognition and future work may benefit from accounting for the effects outlined in this paper.
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Notes
The lexical procedure is thought to provide no output for nonwords.
Parallel distributed process (PDP) theories do not subscribe to a distinction between GPC rules and whole-word procedures, but instead describe the interaction of units of information (orthographic (O), phonological (P), and semantic (S)) that are capable of deriving an appropriate response for all types of input (regular words, exception words, nonwords) (Plaut et al. 1996; Harm and Seidenberg 2004). While the architecture of the computational word recognition models are fundamentally different, both dual-route and PDP models can accurately model the effects of regularity, whereby the latencies for regular words are faster than exception words.
We used a database dictionary resource (MRC Psycholinguistic Database: Machine Usable Dictionary, Version 2.0, http://www.psy.uwa.edu.au/mrcdatabase/mrc2.html), which provides a count of the number of occurrences of particular linguistic properties, to evaluate our stimuli on several characteristics. Regular and exception words did not differ on bigram sum (sum of frequencies for consecutive bigrams), bigram mean, bigram frequency by position, written frequency (both HAL and KF counts per million), length (number of letters in a word), phonological neighborhood (number of correctly sounding words that can be made by replacing one phoneme at a time) or orthographic neighborhood (all p’s > .10). Yap and Balota (2009) consistency ratings were used to retrieve consistency ratings for the regular words (Mean = .86, SD = .11) and exception words (Mean = .81, SD = .11).
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Funding
The experiment outlined was partially supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada (Grant No. 386617-2012) through a research grant to author JC.
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The authors declare that they have no conflict of interest.
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Consent was obtained according to the Declaration of Helsinki (2013, http://www.wma.net/en/10home/index.html) and the experiment was performed in compliance with the relevant laws and institutional guidelines and was approved by the host University Health Research Ethics Board.
Appendices
Appendix A
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Appendix B
ANOVA Results
Question 1
There was a significant response time difference between exception words and regular words, t(29) = 3.007, p = .005, with exception words being read aloud 12 ms faster than regular words (see Fig. 1). By-item analysis showed no difference between exception words (571 ms) and regular words (582 ms), t(49) = .942, p = .351. With respect to accuracy, there was a significant difference between exception words and regular words, t(29) = 3.342, p = .002, with regular words being more accurate (97%) than exception words (95%).
Question 2
There was a significant word type × task interaction, F(1, 29) = 50.01, p < .001. Follow-up t tests showed that regular words were named 20 ms faster than exception words in the GNG-PH task, t(29) = 7.245, p < .001. By-item analysis were consistent with this result. There was a significant word type × task interaction, F(1, 49) = 5.54, p = .023. Follow-up t tests showed that regular words were named 30 ms faster than exception words in the GNG-PH task, t(49) = 2.552, p = .014. With respect to accuracy, there was a main effect of foil, F(1, 29) = 6.638, p = .015 with greater accuracy in the GNG-PH (97.1%) condition compared to the GNG-NW condition (95.9%). There was also a main effect of word type, F(1, 29) = 27.639, p < .001, with regular words (97.8%) being read more accurately than exception words (95.2%).
Question 3
There was a significant main effect of masking, F(1, 56) = 28.465, p < .001, with the masking condition increasing overall response times by 83.74 ms. With respect to by-item analyses, there was a significant main effect of masking, F(1, 97) = 188.9, p < .001, with masking increasing the overall response times by 76 ms. Follow-up t tests indicated that there was no regularity effect in the GNG-NW task, t(27) = 1.194, p = .243 (by items, t(49) = .174, p = .862); however, the regularity effect was maintained in the GNG-PH condition with information masking, t(27) = 2.542, p = .017 (by items, t(49) = 2.232, p = .030). The magnitude of this effect was similar to the GNG-PH without information masking, 17 versus 20 ms, respectively. There was no main effect of masking on accuracy, p > .10.
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Cummine, J., Aalto, D., Ostevik, A. et al. “To Name or Not to Name: That is the Question”: The Role of Response Inhibition in Reading. J Psycholinguist Res 47, 999–1014 (2018). https://doi.org/10.1007/s10936-018-9572-9
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DOI: https://doi.org/10.1007/s10936-018-9572-9