Preverbal error-monitoring in stutterers and fluent speakers

Arnstein, Daniel; Lakey, Brian; Compton, Rebecca J.; Kleinow, Jennifer

doi:10.1016/j.bandl.2010.12.005

Cited by 32 publications

(15 citation statements)

References 61 publications

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“…For example, it remains unclear whether uniqueness point effects would be affected by word boundaries or metrical stress patterns included within their stimuli (i.e., noun phrases: e.g., “ hot dog ” and compound words: e.g., “ hotdog ”). Nonetheless, Sasisekaran and de Nil’s findings appear to contradict perception deficits in individuals who stutter (e.g., [68, 69]), as well as those of Arnstein et al [42], and challenge the notion of perception-based monitoring deficits in AWS.…”

Section: Discussioncontrasting

confidence: 40%

“…These findings are consistent with previous studies that suggest atypical, perhaps overly rigid, evaluation of external speech ([41]; cf. [43]) and internal speech [42] by the perceptual system in AWS. Previous silent phoneme monitoring studies which indicate overall slower C 1 –C 4 response latencies by AWS attributed these differences to phonological encoding difficulties [23-25].…”

Section: Discussionmentioning

confidence: 99%

“…Differences in perceptual evaluation of phonological code in AWS are not restricted to third-party spoken word production. Arnstein et al [42] found stronger activity in AWS in neural regions associated with error detection during a silent rhyme judgment task compared to AWNS, even in the absence of actual error, suggesting the preverbal monitor in AWS may be prone to overly rigid evaluation, similar to their external monitor. In the same study, error detection differences between AWNS and AWS approached but did not reach significance during a nonlinguistic flanker task, wherein participants must quickly and accurately judge congruence of 2 sets of arrows presented simultaneously.…”

Section: Speech Monitoring In Awsmentioning

confidence: 99%

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Uniqueness Point Effects during Speech Planning in Adults Who Do and Do Not Stutter

Coalson

Byrd

Kuylen

2017

Folia Phoniatr Logop

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Background/Aims: Previous studies employing a variety of tasks have demonstrated that adults who stutter (AWS) present with phonological encoding differences compared to adults who do not stutter (AWNS). The present study examined whether atypical preverbal monitoring also influenced AWS performance during one such paradigm – the silent phoneme monitoring task. Specifically, we investigated whether monitoring latencies for AWS were accelerated after the word’s uniqueness point – the phoneme that isolates the word from all lexical competitors – as observed for AWNS when monitoring internal and external speech. Methods: Twenty adults (10 AWS, 10 AWNS) completed a silent phoneme monitoring task using stimuli which contained either (a) early uniqueness points (EUP), (b) late uniqueness points, or (c) no uniqueness point (NUP). Response latency when identifying word-final phonemes was measured. Results: AWNS exhibited the expected uniqueness point effect when monitoring internal speech; word-final phonemes were accessed more rapidly for words with EUP than NUP. In contrast, AWS did not differ in the phoneme monitoring speed. That is, AWS did not exhibit the expected uniqueness point effects. Conclusion: Findings suggest that inefficient or atypical preverbal monitoring may be present in AWS and support theories that implicate the internal speech monitor as an area of deficit.

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Section: Discussioncontrasting

confidence: 40%

Section: Discussionmentioning

confidence: 99%

Section: Speech Monitoring In Awsmentioning

confidence: 99%

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Uniqueness Point Effects during Speech Planning in Adults Who Do and Do Not Stutter

Coalson

Byrd

Kuylen

2017

Folia Phoniatr Logop

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“…Somewhat notably, the type of task itself does not seem to play a role in whether a study will find a relative increase or a decrease in accuracy after errors. For example, while several studies using the flanker task have found increases in accuracy following errors compared to correct trials (Grutzmann, Endrass, Klawohn, & Kathmann, ; Marco‐Pallares, Camara, Munte, & Rodriguez‐Fornells, ; Pontifex et al, ; Seifert, von Cramon, Imperati, Tittgemeyer, & Ullsperger, ; Strozyk & Jentzsch, ), other studies using the same paradigm have shown either the opposite pattern (Arnstein, Lakey, Compton, & Kleinow, ; Fiehler, Ullsperger, & von Cramon, ; Franken, van Strien, Franzek, & van de Wetering, ) or no difference between the conditions (Moran, Bernat, Aviyente, Schroder, & Moser, ; van den Brink et al, ). The same picture is true for other tasks, with some studies showing post‐error increases in accuracy (Danielmeier et al, ; Dutilh et al, ; Forster & Cho, ; Klein et al, ), some showing decreases (Bombeke, Schouppe, Duthoo, & Notebaert, ; Carp & Compton, ; Houtman & Notebaert, ; Jentzsch & Dudschig, ; Jonker, Seli, Cheyne, & Smilek, ; Notebaert et al, ; Notebaert & Verguts, ; Van der Borght, Braem, Stevens, & Notebaert, ), and some showing no change (e.g., Hajcak et al, ).…”

Section: Section Ii: Behavioral Studies Of Post‐error Accuracy Are Inmentioning

confidence: 99%

An adaptive orienting theory of error processing

2017

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The ability to detect and correct action errors is paramount to safe and efficient goaldirected behaviors. Existing work on the neural underpinnings of error processing and post-error behavioral adaptations has led to the development of several mechanistic theories of error processing. These theories can be roughly grouped into adaptive and maladaptive theories. While adaptive theories propose that errors trigger a cascade of processes that will result in improved behavior after error commission, maladaptive theories hold that error commission momentarily impairs behavior. Neither group of theories can account for all available data, as different empirical studies find both impaired and improved post-error behavior. This article attempts a synthesis between the predictions made by prominent adaptive and maladaptive theories. Specifically, it is proposed that errors invoke a nonspecific cascade of processing that will rapidly interrupt and inhibit ongoing behavior and cognition, as well as orient attention toward the source of the error. It is proposed that this cascade follows all unexpected action outcomes, not just errors. In the case of errors, this cascade is followed by error-specific, controlled processing, which is specifically aimed at (re) tuning the existing task set. This theory combines existing predictions from maladaptive orienting and bottleneck theories with specific neural mechanisms from the wider field of cognitive control, including from error-specific theories of adaptive post-error processing. The article aims to describe the proposed framework and its implications for post-error slowing and post-error accuracy, propose mechanistic neural circuitry for post-error processing, and derive specific hypotheses for future empirical investigations. K E Y W O R D Sattention, cognitive control, error processing, inhibitory control, orienting, performance monitoring | IN TRO DUCT IO NThe ability to adapt behavior after erroneous actions is one of the key components of human cognitive control. Correcting current and avoiding future errors is paramount to survival. These abilities are the centerpiece of the scientific field of performance monitoring. Research into the neurophysiological and behavioral changes associated with error processing has generated several influential theories over the past few decades, which seek to explain how the human brain reacts to error commission. While many existing theories entail unique mechanisms and propose specific corollaries, one factor by which all theories can be roughly classified is whether they propose that psychological and neural processes triggered by error commission are maladaptive or adaptive. Empirically, this classification can be made based on whether a theory predicts that error commission is ultimately beneficial or detrimental to post-error behavior. Specifically, adaptive theories propose that errors trigger a cascade of neural processes that represents a remedial effort of the cognitive system, which is explicitly targeted at avoiding f...

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“…For example, a number of studies, some of them dating back decades, have compared known ERP components in AWS versus TFA. Among others, these studies have examined contingent negative variation (e.g., Zimmerman and Knott, 1974; Pinsky and McAdam, 1980; Prescott and Andrews, 1984; Prescott, 1988), P300 activity (e.g., Ferrand, Gilbert and Blood, 1991; Morgan et al, 1997; Hampton and Weber-Fox, 2008; Sassi et al, 2011), error-related components (Arnstein et al, 2011) and auditory evoked potentials (Hampton and Weber-Fox, 2008; Liotti et al, 2010; Maxfield et al, 2010). Of particular relevance is the work of Christine Weber-Fox and colleagues, who have used ERPs to investigate language processing in AWS in receptive mode (i.e., during word recognition and sentence processing).…”

Section: Introductionmentioning

confidence: 99%

Real-time processing in picture naming in adults who stutter: ERP evidence

Maxfield

Morris

Frisch

et al. 2015

Clinical Neurophysiology

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Objective The aim was to compare real-time language/cognitive processing in picture naming in adults who stutter (AWS) versus typically-fluent adults (TFA). Methods Participants named pictures preceded by masked prime words. Primes and target picture labels were Identical or mismatched. Priming effects on naming and picture-elicited ERP activity were analyzed. Vocabulary knowledge correlations with these measures were assessed. Results Priming improved naming RTs and accuracy in both groups. RTs were longer for AWS, and correlated positively with receptive vocabulary in TFA. Electrophysiologically, posterior-P1 amplitude negatively correlated with expressive vocabulary in TFA versus receptive vocabulary in AWS. Frontal/temporal-P1 amplitude correlated positively with expressive vocabulary in AWS. Identity priming enhanced frontal/posterior-N2 amplitude in both groups, and attenuated P280 amplitude in AWS. N400 priming was topographically-restricted in AWS. Conclusions Results suggest that conceptual knowledge was perceptually-grounded in expressive vocabulary in TFA versus receptive vocabulary in AWS. Poorer expressive vocabulary in AWS was potentially associated with greater suppression of irrelevant conceptual information. Priming enhanced N2-indexed cognitive control and visual attention in both groups. P280-indexed focal attention attenuated with priming in AWS only. Topographically-restricted N400 priming suggests that lemma/word form connections were weaker in AWS. Significance Real-time language/cognitive processing in picture naming operates differently in AWS.

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Preverbal error-monitoring in stutterers and fluent speakers

Cited by 32 publications

References 61 publications

Uniqueness Point Effects during Speech Planning in Adults Who Do and Do Not Stutter

Uniqueness Point Effects during Speech Planning in Adults Who Do and Do Not Stutter

An adaptive orienting theory of error processing

Real-time processing in picture naming in adults who stutter: ERP evidence

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