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. 2017 Oct 17;60(10):2906-2923.
doi: 10.1044/2017_JSLHR-L-16-0309.

Semantic and Phonological Encoding Times in Adults Who Stutter: Brain Electrophysiological Evidence

Affiliations

Semantic and Phonological Encoding Times in Adults Who Stutter: Brain Electrophysiological Evidence

Nathan D Maxfield. J Speech Lang Hear Res. .

Abstract

Purpose: Some psycholinguistic theories of stuttering propose that language production operates along a different time course in adults who stutter (AWS) versus typically fluent adults (TFA). However, behavioral evidence for such a difference has been mixed. Here, the time course of semantic and phonological encoding in picture naming was compared in AWS (n = 16) versus TFA (n = 16) by measuring 2 event-related potential (ERP) components: NoGo N200, an ERP index of response inhibition, and lateralized readiness potential, an ERP index of response preparation.

Method: Each trial required a semantic judgment about a picture in addition to a phonemic judgment about the target label of the picture. Judgments were mapped onto a dual-choice (Go-NoGo/left-right) push-button response paradigm. On each trial, ERP activity time-locked to picture onset was recorded at 32 scalp electrodes.

Results: NoGo N200 was detected earlier to semantic NoGo trials than to phonemic NoGo trials in both groups, replicating previous evidence that semantic encoding generally precedes phonological encoding in language production. Moreover, N200 onset was earlier to semantic NoGo trials in TFA than in AWS, indicating that semantic information triggering response inhibition became available earlier in TFA versus AWS. In contrast, the time course of N200 activity to phonemic NoGo trials did not differ between groups. Lateralized readiness potential activity was influenced by strategic response preparation and, thus, could not be used to index real-time semantic and phonological encoding.

Conclusion: NoGo N200 results point to slowed semantic encoding in AWS versus TFA. Discussion considers possible factors in slowed semantic encoding in AWS and how fluency might be impacted by slowed semantic encoding.

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Figures

Figure 1.
Figure 1.
Grand-averaged waveforms for the typically fluent adults group to semantic Go trials (black) versus semantic NoGo trials (light gray) at each of 14 electrodes. Arrows point to NoGo N200 activity at FP1 and FP2.
Figure 2.
Figure 2.
Grand-averaged waveforms for the typically fluent adults group to phonemic Go trials (black) versus phonemic NoGo trials (light gray) at each of 14 electrodes. Arrows point to NoGo N200 activity at FP1 and FP2.
Figure 3.
Figure 3.
Grand-averaged waveforms for the adults who stutter group to semantic Go trials (black) versus semantic NoGo trials (light gray) at each of 14 electrodes. Arrows point to NoGo N200 activity at FP1 and FP2.
Figure 4.
Figure 4.
Grand-averaged waveforms for the adults who stutter group to phonemic Go trials (black) versus phonemic NoGo trials (light gray) at each of 14 electrodes. Arrows point to NoGo N200 activity at FP1 and FP2.
Figure 5.
Figure 5.
Grand-averaged difference waves at frontal electrodes (FP1 and FP2), plotted separately for each group in each linguistic condition (semantic vs. phonological). Latencies on each graph give the first time point (in ms) at which N200 was detected. AWS = adults who stutter; TFA = typically fluent adults.
Figure 6.
Figure 6.
Grand-averaged lateralized readiness potentials (LRPs) shown separately for each group in each response condition (left column = phonemic judgments drove Go/NoGo decisions; right column = semantic judgments drove Go/NoGo decisions). LRPs were derived as described in the Method section. Latencies on each graph give the first time point (in ms) at which LRP activity was detected (if at all). AWS = adults who stutter; TFA = typically fluent adults.

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