Elsevier

NeuroImage

Volume 59, Issue 4, 15 February 2012, Pages 3881-3888
NeuroImage

Time course of word production in fast and slow speakers: A high density ERP topographic study

https://doi.org/10.1016/j.neuroimage.2011.10.082Get rights and content

Abstract

The transformation of an abstract concept into an articulated word is achieved through a series of encoding processes, which time course has been repeatedly investigated in the psycholinguistic and neuroimaging literature on single word production. The estimates of the time course issued from previous investigations represent the timing of process duration for mean processing speed: as production speed varies significantly across speakers, a crucial question is how the timing of encoding processing varies with speed. Here we investigated whether between-subjects variability in the speed of speech production is distributed along all encoding processes or if it is accounted for by a specific processing stage. We analysed event-related electroencephalographical (ERP) correlates during overt picture naming in 45 subjects divided into three speed subgroups according to their production latencies. Production speed modulated waveform amplitudes in the time window ranging from about 200 to 350 ms after picture presentation and the duration of a stable electrophysiological spatial configuration in the same time period. The remaining time windows from picture onset to 200 ms before articulation were unaffected by speed. By contrast, the manipulation of a psycholinguistic variable, word age-of-acquisition, modulated ERPs in all speed subgroups in a different and later time period, starting at around 400 ms after picture presentation, associated with phonological encoding processes. These results indicate that the between-subject variability in the speed of single word production is principally accounted for by the timing of a stable electrophysiological activity in the 200-350 ms time period, presumably associated with lexical selection.

Highlights

► Production speed significantly varies across speakers. ► Production speed and word age-of-acquisition module ERP in two distinct time-windows. ► Variability in production speed depends on the timing of lexical selection.

Introduction

Speakers produce two to three words per second in connected speech, with some variability due to individual speech rate (Miller et al., 1984). Between-subjects variability in speech rate involves differences in the articulation rate and in the number and duration of pauses. Even at slow speech rates, speakers transform an abstract idea into the articulation of physical speech sounds corresponding to a single word in a couple of hundreds of milliseconds. Research on speech production has analysed the specific cognitive processes involved in the transformation of an idea into an articulatory plan (Garrett, 1975, Levelt, 1989). There is a general agreement between different models of speech production that the speaker encodes a pre-linguistic concept into a lexical–semantic representation leading to the selection of the appropriate word (lexical selection); then the phonological makeup of the sentence (the word form) is encoded (phonological encoding), which drives the selection of the appropriate muscle commands to start articulating. Psycholinguistic experimental investigations coupled with neuroimaging studies allowing high temporal resolution (electroencephalography, EEG and magnetoencephalography, MEG) have provided accurate estimates of the time course of these different encoding processes from concept to articulation (Indefrey and Levelt, 2004). The time course of single word production has particularly been investigated using picture naming tasks, in which speakers have to produce a word corresponding to a concept represented by a picture. In this kind of speech production task, visual and conceptual processes are estimated to take place from 0 to about 150–175 ms after picture presentation, followed by lexical–semantic (lexical selection) processes until about 275 ms. The encoding of the phonological form is thought to occur between 275 and 400–450 ms after picture onset, followed by phonetic encoding and motor execution. The timing of single word encoding has been repeatedly confirmed in recent ERP studies, in particular regarding lexical selection and phonological encoding processes (Costa et al., 2009, Laganaro et al., 2009, Maess et al., 2002, Perret and Laganaro, 2012, Strijkers et al., 2010, Vihla et al., 2006). These estimates represent an average timing across different words and different speakers. However, specific linguistic properties of the words, such as their frequency of use (Oldfield and Wingfield, 1965) or their age-of-acquisition (Morrison et al., 1992), are known to affect the speed of word production. More importantly for our purpose here, it is also widely known that the overall processing time for identical words varies across speakers. For instance, in simple picture naming tasks production latencies can vary by a factor of two, even among subjects from a homogeneous population (i.e. undergraduate students).

Given the between-subject variability in processing speed, the estimates of the time course of encoding processes presented above represent an average including both, slow and fast speakers. Therefore, we may wonder whether differences in processing speed are distributed across all encoding processes or if only certain specific cognitive processes vary according to the speed of speech production. In other words, the question is whether all encoding processes from concept to articulation are stretched in slow speakers relative to fast speakers, or if processing speed is associated with variable encoding times for a particular process. Schuhmann et al. (2009) had to deal with the interpretation of which encoding process was associated with a specific time period in subjects with very short production latencies (during the production of a limited number of monosyllabic words): They hypothesized that speed affects all the processes involved in speech production equally. Alternatively, one may hypothesize that production speed depends on a specific encoding process, either at pre-linguistic levels (conceptualisation) or during word encoding (lexical selection, phonological or phonetic encoding). To our knowledge this question has never been addressed directly.

Here we investigated the variability in processing speed during speech production by comparing event-related electroencephalographical (ERP) correlates during picture naming in fast and slow subjects. Taking advantage of topographic (spatio-temporal) ERP analyses (Murray et al., 2008, Michel et al., 2009), we examined the duration of specific electrophysiological patterns (functional microstates, Lehmann, 1987, Michel et al., 2009) across slow and fast speakers and their correlation with production latencies. If speed of word production is distributed along all the speech encoding processes as hypothesised by Schuhmann et al. (2009), then differences between slow and fast speakers should be observed in several time windows from the moment a picture appears on the screen to articulation. On the other hand, if differences in processing speed are linked to a specific encoding process, then ERP divergences between slow and fast speakers should be limited to a given time window, which can be associated to a specific encoding process. As an additional comparison point to index specific encoding processes we manipulated a psycholinguistic variable known to reliably affect production latencies, namely word age-of-acquisition (AoA hereafter). Effects of AoA on production latencies have been repeatedly reported in picture naming paradigms independently of other psycholinguistic variables (Alario et al., 2004, Bonin et al., 2002, Chalard et al., 2003, Cuetos et al., 1999, Morrison and Ellis, 1995) and of production speed (Morrison et al., 2002). In addition, there is converging evidence from psycholinguistic (Chalard and Bonin, 2006, Morrison et al., 1992), neuropsychological (Kittredge et al., 2008) and ERP investigation (Laganaro and Perret, 2011) in favour of a lexical–phonological locus of the AoA effect. The double comparison of the time period modulated by speed with (1) the estimates of timing of speech encoding processes issued from previous studies, and (2) the time window affected by AoA, will enable us to conclude as to whether a specific encoding process accounts for the differences in production speed, or if variations in processing speed are distributed along several/all word encoding processes.

Section snippets

Subjects

45 undergraduate students (8 men) participated in the study. They were all native French speakers, aged 18–35 (mean = 24.06). All were right-handed as determined by the Edinburgh Handedness Scale (Oldfield, 1971). The participants gave their informed consent and were paid for their participation.

The 45 subjects were divided in three subgroups of 15 subjects each, according to their mean production latencies (slow-, mean- and fast-speed subgroups, see behavioural results). There was no significant

Behavioural results (RTs)

Production latencies above 1400 ms and below 400 ms as well as errors were removed from the analysis (7.6% of the data). Mean RT on the whole group of 45 subjects was 818 ms (SD = 95.67 ms). The 45 subjects were divided into 3 subgroups of 15 subjects each according to their mean production speed (see Table 2).

Early-acquired words were produced 59 ms faster than late-acquired words (F(1, 5145) = 23.23, MS = 452,425, p < .0001) without interaction with speed subgroups F(1, 5145) = 3.23, MS = 48,699, p = .145).

Discussion

We investigated whether the between-subject variability in processing speed is distributed along all encoding processes or if it is due to specific encoding processes involved in speech production. Converging results from the waveform analysis and the topographic pattern analysis point to an effect of production speed in the time window ranging from 200 to 350 ms after picture presentation. By contrast, the manipulated psycholinguistic word property (AoA) modulated ERPs in a different and later

Conclusion

The present investigation showed that production speed and word age of acquisition modulated ERPs in two distinct time windows. The largest part of between-subject variability in the speed of speech production is accounted for by the timing of a stable electrophysiological activity observed in the time period presumably associated with lexical selection. The duration of the stable electrophysiological activity starting around 200 ms varied with speed, shifting the onset of the following stable

Acknowledgements

This research was supported by Swiss National Science Foundation grant no. PP001-118969/1 to Marina Laganaro.

References (51)

  • M. Vihla et al.

    Cortical dynamics of visual/semantic vs phonological analysis in picture naming

    NeuroImage

    (2006)
  • F.X. Alario et al.

    A set of 400 pictures standardized for French: norms for name agreement, image agreement, familiarity, visual complexity, image variability, and age of acquisition

    Behav. Res. Methods Instrum. Comput.

    (1999)
  • F.X. Alario et al.

    Predictors of picture naming speed

    Behav. Res. Methods Instrum. Comput.

    (2004)
  • S. Aristei et al.

    Electrophysiological chronometry of semantic context effects in language production

    J. Cogn. Neurosci.

    (2011)
  • D.M. Bates et al.

    Lmer4: Linear mixed-effects models using S4 classes, R package version 0.99875-6

    (2007)
  • P. Boersma et al.

    Praat: doing phonetics by computer. Institute of Phonetic Sciences of the University of Amsterdam

  • P. Bonin et al.

    The determinants of spoken and written picture naming latencies

    Br. J. Psychol.

    (2002)
  • P. Bonin et al.

    A new set of 299 pictures for psycholinguistic studies: French norms for name agreement, image agreement, conceptual familiarity, visual complexity, image variability, age of acquisition, and naming latencies

    Behav. Res. Methods Instrum. Comput.

    (2003)
  • Brunet, D., Murray, MM. Michel, C.M., in press. Spatio-temporal analysis of multichannel EEG: CARTOOL. Comput. Intell....
  • M. Chalard et al.

    Objective age-of-acquisition AoA norms for a set of 230 objects names in French: relationships with psycholinguistic variables, the English data from Morrison et al. 1997, and naming latencies

    Eur. J. Cogn. Psychol.

    (2003)
  • M. Chalard et al.

    Age-of-acquisition effects in picture naming: are they structural and/or semantic in nature?

    Vis. Cogn.

    (2006)
  • A. Costa et al.

    The time course of word retrieval revealed by event-related brain potentials during overt speech

    Proc. Natl. Acad. Sci.

    (2009)
  • F. Cuetos et al.

    Naming times for the Snodgrass and Vanderwart pictures in Spanish

    Behav. Res. Methods Instrum. Comput.

    (1999)
  • G.S. Dell

    A spreading activation theory of retrieval in sentence production

    Psychol. Rev.

    (1986)
  • V.S. Ferreira et al.

    Central bottleneck influences on the processing stages of word production

    J. Exp. Psychol. Learn. Mem. Cogn.

    (2002)
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