3.3. The predisposition for stuttering

3.3.1. Attention deficits, hyperactivity

A misallocation of attention during speech has been assumed to be the primary cause for the development of stuttering in the present theory; hence, the question arises: What is the cause of the cause? Why do stutterers tend to a misallocation of attention while speeaking? One important factor was already discussed extensively in Section 2.4: The higher demands of speech planning – more precisely: a new quality of demands – when children start forming sentences. A second factor – particularly if stuttering onsets later in childhood, in adolescence or adulthood, may be conditions or experiences that strain and burden communication, making a person to devote much attention to overcareful speech planning or to worry about the listeners’ resction. However, the question now arises as to why some individuals are more sensitive to such factors than the majority who do not develop stuttering. Empirical findings point in two directions: (1) a deficit in the automatic control of attention in general; (2) a deficit in central auditory processing that impairs the automatic control of auditory attention.

Let us, first, consider attention control in general: The prevalence of attention-deficit hyperactivity disorder (ADHD) in school-age children is 3–6 % (Donaher, Healey, and Soffer, 2013; percentages vary depending on diagnostic criteria). Similar to persistent developmental stuttering, ADHD is more frequently diagnosed in males than in females (Ramtekkar et al., 2010). Data on the prevalence of ADHD in school-aged children who stutter range from 4 % to 26 % (Healey & Reid, 2003; Alm, 2014); Conture (2001) suggested that 10–20 % of children who stutter might exhibit ADHD. Donaher and Richels (2012) found 58 % of children and adolescents who stuttered to show symptoms that could warrant a referral to a specialist for a possible ADHD diagnosis. Donaher, Healey, and Soffer (2013) point out that “clinical findings often report that significant attention and impulsivity issues, without a current diagnosis of ADHD, negatively affect the outcome of stuttering treatment.”

In an electroencephalographic (EEG) study of attention-related brain function, Ratcliff-Baird (2001) found “strong similarities in the EEG, morphology, and behavior of stutterers and individuals with with ADHD”. Karras et al. (2006) asked parents of 65 stuttering and 56 non-stuttering preschool children to complete a questionnaire in order to examine emotional reactivity, and regulation. Findings indicated that when compared to controls, stuttering children were significantly more reactive, less able to regulate their emotions, and less able to flexibly control their attention (read more).

A special combination of deficient attention regulation, on the one hand, and hyperactivity, on the other hand, seems to play a role in childhood stuttering: a tendency to focus attention too much on a target, or to prematurely shift attention from the current step of a sensorimotor sequence to the next one, or from perception to action. Jansson-Verkasalo et al. (2012) found that children who stutter, as a group, showed significantly more premature responses than age-matched normal fluent controls in a task aimed at measuring auditory attention. Similarly, adults who stutter, as a group compared to normal fluent controls, showed a significantly greater number of false alarms in a syllable recognition task (Bosshardt, 1993), and stuttering children exhibited more false alarms and premature responses than controls in Go/No Go paradigms (Chou, 2014; Eggers, De Nil, & Van den Bergh, 2013), suggesting deficient inhibitory control. Adults who stutter as well showed deficiency in motor inhibition (increased stop-signal reaction times) in two tasks that did not rely on speech production (Markett et al., 2016). Piispala et al. (2016) could not confirm significant differences in inhibitory control between stuttering children and controls in a visual Go/Nogo paradigm, but they found longer ERP latencies suggesting atypical attentional processing.

In the large-scale Early Language of Victoria Study, however, Reilly et al. (2013) did not find group differences regarding hyperactivity between children who developed stuttering up to the age of 4 years and their peers who did not develop stuttering up to this age. From that, we must conclude that the tendency to hyperactivity may be typical only of persistent stuttering, but not for the transient developmental stuttering in early childhood. Thus, hyperactivity does not seem to be a factor contributing to the emergence of childhood stuttering, but it may be a factor in the maintenance of the disorder, i.e., a factor of chronification. This would provide one explanation of why stuttering becomes more often persistent in boys than in girls: As already mentioned, ADHD is more prevalent in males than in females too; the ratio seems to be similar to that in stuttering (Novik et al,, 2006 – see diagram; Ramtekkar et al., 2010).

An additional factor may be responsible for the different prevalence of stuttering in males and females: Foundas et al. (2004b) examined the ability of adult stutterers and controls to focus auditory attention on one ear in a dichotic verbal listening task. Male stutterers, as a group, did not differ from controls (left-handed men who stutter were able to shift attention to the left and right ear even better than any other group). Right-handed women who stutter, by contrast, made most errors and were relatively unable to direct attention selectively left or right (a group of left-handed woman who stutter could not be recruited). The results suggest that there are two subtypes in respect of the kind of attention deficit: One group – the majority of the men who stutter? – is well able to control auditory attention if they do it consciously, and if they have only to listen (which does not mean that their attention is appropriately allocated automatically during speech). The other group – the majority of the women who stutter? – has a basic deficit in the control of auditory attention that is possibly genetically caused. The last assumption is supported by the fact that the percentage of women in familial stuttering is much greater than in extra-familial stuttering (Drayna, Kilshaw, & Kelly, 1999), thus genes seem to play a greater role in the persistent stuttering of women than of men.

Unfortunately, attention was not examined in the Victoria Study, hence we have no data about the prevalence of attention deficits in the children who later began to stutter compared to those who did not. We only have findings of attention deficits in adults and in children who already stuttered at the time of examination. Anderson and Wagovich (2010), Eggers, De Nil, and Van den Bergh (2012), as well as Alm (2014) give comprehensive overviews of the recent literature concerning stuttering and attention. Findings suggest that stutterers tend to be less efficient in attention regulation, less able to devide attention under dual task conditions (read more), and that they are more prone to exhibit attention disorders. Eggers, De Nil, and Van den Bergh (2012) concluded from their findings that the orienting network that plays an important role in the allocation of attention appears to be less efficient in children who stutter. Kaganovich, Hampton Wray, and Weber-Fox (2010) concluded from an examination of auditory processing in preschool-aged children who stutter, that stuttering may be associated with less efficient attention allocation.

It is of interest in our context that ADHD, despite its label as an attention deficit disorder, is recently more considered as an attention allocation deficit, i.e., as a problem in the voluntary control of attention as opposed to a pure deficit in the ability to pay attention (see this briefing paper of the DANA Foundation by Whitman and Goldberg, 2010). I do not believe that stutterers are generally inattentive; or more distractible. To the contrary, I assume that they often too much focus on a target – during speech, for example, on the thoughts or emotions they want to express, on sentence formulation, or on the attempt to avoid stuttering – with the effect that other important information is poorly perceived and/or poorly processed.

This conjecture is supported by empirical findings: Using a norm-referenced parent-report questionnaire, Anderson et al. (2003) found stuttering preschoolers (mean age: 4 years) to be significantly less distractible (hypervigilant) as a group, compared to age-matched normal developing children. Clark et al. (2015) investigated the distractibility of preschool-age children who stutter and controls. They found that stuttering boys, as a group, were less distractible than both stuttering and non-stuttering girls. For the stuttering boys, less distractibility, i.e., greater (!) selective attention was associated with more speech-language dissociations (imbalances among subcomponents of speech-language planning and production). A propensity to focus attention on only one target and to ignore everything else is beneficial in many respects (read more), but, perhaps, it is a factor raising the risk for stuttering.

By means of fMRI, Chang et al. (2017) investigated the resting state connectivity within several intrinsic connectivity networks in stuttering children, in children who had recovered from stuttering, and nomal fluent controls. They summarize that “...persistent stuttering seems to be associated with connectivity differences that primarily involve DMN and its connectivity with attention and executive control networks. Alternatively, recovered children exhibit similar connectivity deficits to persistent children in many respects, but normalized connectivity involving DMN and attention and executive control networks may help them recover.” (cf. Discussion, Section 4.5; DMN = default mode network, a set of brain regions that are deactivated during goal directed tasks; functionally, the DMN is associated with introspective behaviors, cf. Section 1.2) (read more).

Doneva, Davis, and Cavenagh (2017) investigated the attentional performance of adult stutterers. They used the Test of Everyday Attention (TEA) which comprises eight subtests that pose differential demands on sustained attention, selective attention, attentional switching, and divided attention. The stutterers performed significantly worse on tasks tapping into visual selective and divided attentional resources. The first corresponds to the surprising finding of reduced functional connectivity in the visual network found by Chang et al. (2017) in stuttering children (the study reported about in the preceding paragraph); the second confirms the results of several earlier studies (see above). Further, there was a trend for stuttering to be associated with poorer performance on two subtests measuring attentional switching and one tapping into auditory selective attention. There was a negative association between stuttering severity and performance on two TEA subtests measuring visual selective attention.

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3.3.2. Auditory deficits

Numerous studies were conducted in order to examine hearing and central auditory processing of stutterers. Both children and adults who stutter, as groups, showed deviant auditory processing of verbal stimuli and/or performed more poorly than controls (Andrade et al., 2008; Beal et al., 2010, 2011; Blood & Blood, 1984a; Blood, 1996; Chang et al., 2009; Corbera et al., 2005; Halag-Milo et al., 2016; Hall & Jerger, 1978; Lu et al., 2016; Neef et al., 2012; Tahaei et al., 2014). Some findings indicate a poorer processing of auditory feedback in stutterers compared to normal fluent controls: Cai et al. (2012; 2014a) as well as Loucks, Chon, and Han (2012) found weaker-than-normal compensatory responses to unexpected alterations of auditory feedback in adults who stutter.

Stutterers differ from normal fluent speakers not only in the processing of verbal, but also in that of non-verbal auditory stimuli (Chang et al., 2009; Dietrich, Barry, & Parker, 1995; Hampton & Weber-Fox, 2009; Howell et al., 2000; Howell, Davis, & Williams, 2006; Prestes et al., 2016). Some results suggest a higher sensitivity to non-verbal auditory stimuli, or a lower ability to filter out useless acoustic information: MacCulloch and Eaton (1971) as well as Brown, Sambrooks, and MacCulloch (1975) found that children who stutter, as a group, had a reduced mean threshold for auditory discomfort compared to controls. Kikuchi et al. (2011), using click sounds as stimuli in an MEG study, found adults who stutter to have a less effective auditory sensory gating on the left hemisphere (i.e., they are less able to suppress the processing of redundant acoustic information) and an expanded tonotopic map on the right hemisphere, suggesting a higher sensitivity to nonverbal acoustic stimuli. Evidence for reduced auditory gating was also found by Saltuklaroglu et al. (2017) in an EEG study. By contrast, Liotti et al. (2010), using speech sounds as stimuli, did not find auditory gating deficits in adults who stutter. Possibly, gating deficits in stutterers affect mainly nonverbal acoustic stimuli, but perhaps also the sound/noise component of speech.

Another group of studies dealt with abnormalities in auditory processing in stutterers on brainstem level. Tahaei et al. (2014) found adult stutterers, compared to controls, to have longer latencies for the onset and offset peaks in auditory brainstem response to the presented syllable /da/. They further found significant correlations between some of these latencies and stuttering severity. They concluded that the neural response to rapid acoustic transients was less synchronous in the stuttering participants. Other investigators as well had pointed to the brainstem as a possible origin for a central auditory deficit in stutterers (Blood & Blood, 1984b; Khedr et al., 2000; Kramer, Green, & Guitar, 1987). Tahaei et al. (2014) hypothesize that their results may either be linked to timing disturbance in the auditory pathways resulting in asynchronous transmission of auditory afferent information, or to top-down influences from the auditory cortex (memory, language experience, and attention) through the corticofugal system. The latter assumption is especially interesting in the context of the present theory.

Deficits in central auditory processing even seem to be a factor influencing persistence in/recovery from stuttering. In a backward-masking experiment, Howell et al. (2000) found stuttering children between age 8–12 to have a higher threshold of perception than normal fluent controls when required to detect a short probe tone (20ms in duration) presented immediately before a burst of a white noise masker. In the stuttering group, the backward-masking thresholds were positively correlated with the frequency of stuttering. It is assumed that backward-masking performance reflects the operation of central auditory processing mechanisms, especially of temporal structure. Howell, Davis, and Williams (2006) compared children who persisted in stuttering and children who had recovered, and they found an appropriately 10 decibel higher mean backward-masking threshold in the persistent group. The difference was statistically significant, however, there was a high variability in the persistent group, therefore, the authors concluded that an auditory deficit may be sufficient, but not necessary, for the disorder to persist.

Rousey, Goetzinger, and Dirks (1959) reported stutterers to have difficulty with sound localization (I myself have this difficulty too). Salmelin et al. (1998) found the basic functional organization (interhemispheric balance) of the auditory cortices to be different in stutterers and nonstutterers. The sensitivity of the brain hemispheres to the side of stimulation was different in stutterers and controls (read more). The authors concluded: “The interhemispheric balance is more unstable in stutterers than in fluent speakers and is readily disturbed by increase in work load. Such disturbance may cause transient, unpredictable abnormalities in auditory perception, which could well initiate stuttering and facilitate the emergence of other, related disturbances in the control of speech.” (p. 2229)

In some studies, correlations between auditory evoked brain potentials and stuttering severity were found: While speaking the vowel /a/ with natural auditory feedback, children who most severely stuttered had, on average, the smallest M50 amplitude (M50 = event-related electromagnetic brain potential about 50ms after stimulus onset) on the left, speech-dominant hemisphere (Beal et al. 2011); however, this correlation was not statistically significant. Using a sound discrimination task, Jansson-Verkasalo et al. (2014) found children who stutter, as a group, to have a significantly smaller amplitude of the mismatch negativity (MMN) than their normal fluent peers. MMN amplitude at central scalp positions correlated positively with stuttering severity. The authors concluded that children who stutter may have difficulties receiving sufficient auditory support for speech production. Maxfield et al. (2010; 2012) found group differences between adult stutterers and controls in the N400 response to verbal stimuli. They concluded from their 2010 study that adults who stutter possibly allocated attentional resources differently than controls during the task. In a dual-task experiment, Maxfield et al. (2016) found hightened demands on speech planning (word selection) to be associated with reduced capacity (P3 weaker or not detectable) for auditory perception in stutterers, but not in controls.

A relationship between auditory processing and stuttering severity was also found in adults who stutter: When speaking a word with natural auditory feedback, the M100 latency on the right hemisphere was significantly correlated with stuttering severity (Beal et al., 2010). Liotti et al. (2010) found a statistically significant, but moderate correlation between inter-hemispheric unbalance and stuttering frequency in adults who were listening to the vowel /a/. Blood (1996) did not find a statistically significant correlation, but the participants who stuttered more severely displayed the poorest scores in three tasks of a battery of auditory perception tests.

In a new analysis of their above-mentioned MEG data, Kikuchi et al. (in press) found the left N100m latency to be significantly prolonged relative to the right one in adults who stutter, while controls did not show any inter-hemispheric differences in latency. An analysis indicating the degree of local phase synchronization demonstrated enhanced alpha-band synchrony in the stutterers’ right auditory area. An analysis of inter-hemispheric synchronization demonstrated significant elevations in the beta band between the right and left auditory cortices. In addition, phase synchronization on the right hemisphere aas well as inter-hemispheric phase synchrony were positively correlated with stuttering frequency. The authors assume “that increased right hemispheric local phase synchronization and increased inter-hemispheric phase synchronization are electrophysiological correlates of a compensatory mechanism for impaired left auditory processing in people who stutter.” All these findings suggest that an auditory processing disorder (APD) seems to play a role in the predisposition for stuttering (read more) .

In a large longitudinal study, Chow and Chang (2017) investigated white matter development in children with persistent stuttering, in those who recovered, and in normal fluent controls, age range 3-12 years. The researchers found, among others, a cluster of reduced fractional anisotropy (FA) in the splenium of the corpus callosum in the persistent group compared to both recovered children and controls (Cluster 4 in Fig. 1 in the paper). The difference is great already with the youngest children, and there is no much overlap between the persistent group and the recovered+control group (who range equally), therefore, it can hardly be a consequence of stuttering. Interestingly, Chow, Liu, Bernstein Ratner, and Braun found a strong relation between the FA in the splenium and stuttering severity in adults who stutter (unpublished DTI study; the results were presented at the 2014 ASHA Convention). The affected fibers of the splenium probably connect bilateral temporal regions (Kuvazeva, 2013), and the lower FA in the persistent group may be related to a less effective labor division between hemispheres in auditory processing.

In summary, deficits in attention control, particularly of auditory attention, a subtle anomaly in central auditory processing, and hyperactivity and impulsivity seem to contribute to a predisposition for stuttering.

Deficits in the control of auditory attention and in auditory gating may possibly be two sides of the same coin: Auditory gating inhibits the processing of redundant acoustic information (simply said: of noise), thus it is the basic process of the control of auditory attention. If this basic process does not work well, the person must compensate for the deficit on a higher, volitionally influenceable level of control. The relationship may be as follows: A less effective auditory gating frequently results in an overload of the auditory processing system. Consequently, affected children early get into the habit of averting attention from the auditory channel to prevent the overload. Their attention is directed to the auditory channel only when they are actively listening, but in all other situations, e.g., while speaking, attention is detracted from hearing (read more).

However, the recent findings of deficits in visual attention associated with stuttering (Doneva, Davis, & Cavenagh, 2017) and in the visual brain network in stuttering children (Chang et al. 2017) suggest an alternative view, namely that the attention network as a whole may be differently developed and organized in stutterers compared to normal fluent speakers, and deficits in particular sensory modalities may result from this general difference – or there is an interaction between the development of attention control and sensory processing, which is atypical in stutterers.

Theory of stuttering: predisposition, psychic and environmental factors

Figure 12: Factors contributing to a predisposition for stuttering, and factors that influence the frequency and severity of symptoms (the cycle has been rotated here, compared to Fig. 9, only for reasons of depiction). Note that the main interface between the vicious cycle and all influencing factors is the misallocation of attention.

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3.3.3. Motor or language deficits?

In many studies, speech- and non-speech motor abilities of stutterers were examined to find out whether a motor deficit causes stuttering. The results are inconsistent. Longer reaction times or a less accurate performance were often found with stutterers as a group, compared to normal fluent controls (see Bloodstein and Bernstein Ratner, 2008, for an overview). In other studies, no significant group differences were found (Arenas, Zebrowski, & Moon, 2012; Daliri, Prokonenko, & Max, 2013; Juste et al., 2012). For example, Coalson, Byrd, and Davis (2012) found the phonetic complexity of words to have no significant influence on the likelihood of stuttering in young children (mean age 3 years, 7 months), and Max and Yudman (2003) did not find adult stutterers to differ from nonstutterers in the ability to generate temporal movement patterns with an isochronous rhythm.

It is important to consider that motor tasks are always sensorimotor tasks, and therefore, they are not independent of perception and attention. Often, participants have to start action on an acoustic cue, or the movement itself, i.e., its kinesthetic, tactile, visual, or acoustic feedback must be perceived to achieve an accurate performance. If, for example, participants prematurely focus attention on a movement they have to perform, instead of listening for the start cue, then their reaction may be delayed because the cue comes, in a sense, unexpected for them, compared to participants who simply waited for the cue. Accuracy may become lower if participants direct much attention to conscious control and too little attention to feedback – for instance, in rhythmic finger tapping, feeling and hearing the beat is much more helpful than volitionally trying to tap in equal intervals.

Falk, Müller, and Dalla Balla (2015) tested school-age children and adolescents who stutter and controls on their ability to synchronize their finger taps with periodic tone sequences and with a musical beat. 40 % of children and 90 % of adolescents who stutter displayed poor synchronization, and the interesting thing was that the stutterers tended to tap earlier in relation to the acoustic pacing stimulus, in contrast to controls who were rather a little late. Taken together with the above mentioned about premature responses and false alarms with stutterers (Bosshardt, 1993; Eggers, De Nil, & Van den Bergh, 2013; Jansson-Verkasalo et al., 2012), the findings suggest that the problem is not a motoric, but an attentional or perceptual one – which is confirmed by Wieland et al. (2015), who found a rhythm perception deficit in school-age children with persistent stuttering (read more).

Finally, some studies must be mentioned that were conducted to address the question of whether language processing is different in stutterers and normal fluent speakers, even if no speech is produced. In fact, group differences were found in event-related brain potentials (ERPs) elicited during listening to spoken sentences that contained semantic, grammatic, or syntactic errors: Whereas ERPs of normal fluent adults displayed an expected N400 for semantically unexpected words and a typical P600 for verb-agreement violations, both N400s and P600s for the semantic and verb-agreement conditions were observed in the ERP of adults who stutter (Weber-Fox & Hampton, 2008) – as if the stutterers’ brain could not as quickly as the nonstutterers’ brain distinguish between a semantic and a syntactic problem.

Atypical ERPs during perceptive language processing were found not only in adults who stutter, but also in young children near the onset of stuttering: Preschool-aged children who stutter, as a group, had longer N400 peak latencies suggesting that the first, automatic stage of semantic processing was somewhat delayed, compared to controls. Syntactic violations elicited greater negative amplitudes for the early time window (150–350ms) in the stuttering children – as if they were more surprised by the phrase structure violations than their normal fluent peers (the early negativity indicates the unexpectedness of a stimulus). Additionally, the amplitude of the P600 elicited by syntactic violations was significant over the left hemisphere for the normal fluent children, but showed the reverse pattern in the stuttering children, namely a robust effect only over the right hemisphere (Weber-Fox, Hampton Wray, & Hayley, 2013).

Have we necessarily to conclude from those results that perceptive language processing is abnormal, and that this is a causal factor in stuttering? In the study last mentioned, the children were concurrently watching a sequence of cartoon videos and listening to a corresponding story containing the semantic and syntactic errors. We don’t know how the children’s attention was distributed (1) between looking at the cartoons and listening to the story, (2) between the sound/prosodic and the lexical aspect of the story, and (3) between the presented stimuli in all and the children’s own upcoming thoughts and emotions. How quickly words are semantically processed, how unexpected a syntactic violation is (after some similar errors were presented), and whether language processing is lateralized leftward or rightward – all this might be influenced by the allocation of attention (read more).

Likewise, in Weber-Fox and Hampton (2008), participants had concurrently to listen to sentences, to look at a fixation point on a screen, and to judge whether each sentence was a good English sentence and made sense, or not. That are three tasks in parallel, and the distribution of attention (of perceptual and processing capacity) between visual perception, listening, and thinking may influence how quickly the brain can distinguish semantic from grammatic errors. Remember that a typical feature of the stutterers’ deficit in attention control is a reduced ability to devide attentional resources under dual task conditions (see above).

On the other hand, an anomaly in syntactic processing during speech perception would not be surprising because of the structural deficits in the left superior longitudinal fasciculus (SLF), that were found in stuttering children and adults (see Chapter 4) – the left SLF plays a role in syntactic processing (Griffith et al., 2013). However, I assume that the structural deficits in the SLF are due to a delay in fiber maturation resulting from the misallocation of attention during speech (see Section 4.1), hence an anomaly in syntactic processing, if existing, would be a side effect, but not a causal factor in stuttering. Indeed, I assume that the onset of childhood stuttering, in most cases, is triggered by difficulty in the transition to incremental sentence formation (see Section 2.2). But I think that all children, including those who persist in stuttering, overcome these initial problems with time.

 

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Footnotes

Attention deficits

Riley and Riley (2000) found that approximately one quarter of their CWS (26%) met their criteria for the presence of a significant attentional deficit. Moreover, among several candidate predictor variables that they examined, the presence of pretreatment attentional problems was found to be the single best predictor of poor treatment outcome at follow-up; that is, children in this sample who stuttered and had poor attention were found to be significantly less likely than those with adequate attention to have a positive treatment outcome at 24-48 months posttreatment, regardless of factors such as pretreatment stuttering severity.

Hamilton et al. (2008) found lower fractional anisotropy, (a deficit in the microstructure of white matter in the brain) in the superior longitudinal fasciculus in children and adolescents with ADHD, compared to controls age-matched without ADHD. Interestingly, lower fractional anisotropy in the superior longitudinal fasciculus was also found in children, adolescents, and adults who stutter – see Section 4.1. (return)
 

Dual task conditions

“Interestingly, results point to greater ‘costs’ of divided attention among people who stutter for nonverbal measures. Studies in finger tapping suggest consistently that, in contrast to typically fluent individuals, people who stutter lag in their finger tapping performance under concurrent conditions, both verbal (Greiner, Fitzgerald, & Cooke, 1986; Sussman, 1982) and nonverbal (Smits-Bandstra, De Nil, & Rochon, 2006; people who stutter also exhibited lower color recognition accuracy). Notably, significantly lower finger tapping rates under verbally demanding concurrent tasks were also reported among children who stutter (Brutten & Trotter, 1986). Cognitive–linguistic costs associated with concurrent verbal loads are evident as well. Bosshardt, Ballmer, and De Nil (2002) and De Nil and Bosshardt’s (2000) findings suggest that concurrent conditions elicited less sophisticated linguistic performance, such as fewer propositions and reduced rhyming accuracy, among people who stutter than typically fluent individuals.” (cited from Bajaj, 2007, p. 228 f.)

Maxfield et al. (2016) investigated speech production in an attention-demanding dual-task condition: Adults who stutter and normal fluent controls named pictures overlaid with printed distracting words and, at the same time, monitored acoustic stimuli: low tones versus high tones, presented in several versions. During these tasks, the P3 component of the event-related brain potential was measured (P3 indexes a late stage of processing). The authors detected a P3 effect in the controls in all dual task conditions. In the stuttering participants, by contrast, P3 effect was attenuated or undetectable if the tone was presented timely close to the picture. The researchers concluded that, for adults who stutter, the availability of attentional resources for secondary task processing was reduced. (return)
 

Advantage and disadvantage

In a presentation, Prof. Harald Euler from the University Frankfurt/Main voiced the following thought: If it is, first, true that stuttering is a genetically caused disorder, and if it is, second, true that people who stutter are handicapped in social life and professional career and, therefore, have difficulty finding a partner, thus their reproductive success is lower on average than that of the normal fluent population – if all that has been true since the time when humans became able to talk, then stuttering should have gone extinct. But stuttering hasn’t gone extinct, therefore, stutterers must have something (special abilities?) that has compensated for the handicap. – Of course, this speculation is somewhat social Darwinist and was not meant quite seriously. (return)
 

Auditory processing disorder (APD)

Brewer et al. (2016) wrote: “A person with an APD typically has difficulty understanding speech in background noise despite having normal pure-tone hearing sensitivity. The estimated prevalence of APD may be as high as 10% in the pediatric population, yet the causes are unknown and have not been explored by molecular or genetic approaches.” They determined the heritability of frequency and temporal resolution for auditory signals and speech recognition in noise in 96 identical or fraternal twin pairs, aged 6-11 years. The study provided evidence of significant heritability, ranging from 0.32 to 0.74, for individual measures of diverse non-speech-based auditory processing skills that are crucial for understanding spoken language. It might be very interesting to compare the genetic variants associated with APD and those associated with developmental stuttering. (return)
 

Motor timing deficit

Olander, Smith, and Zelaznik (2010) wrote: “It is possible that differences in nonspeech motor coordination and timing as well as differences in speech movement variability are more obvious in people who stutter when the task is more demanding. In fact, many studies of more complex tasks have revealed differences in the nonspeech motor timing of adults who stutter. For example, when a finger sequencing task was used, people who stutter produced slower response initiations, made more errors (Webster, 1986), and were more variable than controls (Smits-Bandstra, De Nil, & Rochon, 2006). Increasing task difficulty by requiring participants to produce bimanual, rather than unimanual, movements also has resulted in observations of greater variability in performance in people who stutter. Differences in relative phase variability (a measure of intereffector coordination that captures the relative timing of two effectors on repeated cycles of a rhythmic behavior) between adults who stutter and controls have been found with a bimanual finger-waving task (Zelaznik et al., 1997) and a bimanual hand-tapping task (Hulstijn et al., 1992). Hulstijn et al. (1992) also found greater variability in adults who stuttered than in normally fluent controls when they performed a dual task of simultaneously synchronizing speech and hand movement to a metronome. These differences were not found when the same participants completed less complex timing tasks. ” (p. 877; see there for references).

More complex tasks, bimanual and dual tasks, however, impose higher requirements on the participant’s ability to divide and to allocate their attention – and just that seems to be a greater challenge for many stutterers. Therefore, the group differences between stutterers and non-stutterers in more complex motor tasks may reflect a deficit in attention allocation rather than a deficit in motor control or timing. In their own study, Olander, Smith, and Zelaznik (2010) found a greater timing variability in stuttering children (4–6 years of age) compared to normal fluent controls in an hand clapping task. However, Hilger, Zelaznik, and Smith (2016) could not replicate the result with a larger group of participants. (return)
 

Stuttering related to a deficit in syntactic processing?

In a more recent study with 6–7-year-old,stuttering children, recovered children, and normal fluent children (CWS, CWS-rec, CWNS), Usler and Weber-Fox (2015) could not confirm the earlier finding of a right-shift of the P600 related to syntactic errors (see main text). They wrote: “ ...we observed that all three groups exhibited qualitatively similar neural activity facilitating syntactic processing of simple English sentences. Furthermore, the morphology of the P600s elicited in CWS-Rec and CWS-Per appears consistent with P600 waveforms of typically developing 6- and 7-year-old children elicited by syntactic phrase structure violations” (p. 17 in the PDF. There is an obvious error in the original: it says CWNS instead of CWS-Per, which makes no sense). Also N400 related to semantic errors did not differ between the three groups (no longer latency, as was previously found in adult stutterers; see main text).

The procedure in Usler and Weber-Fox (2015) was similar to that in Weber-Fox, Hampton Wray, and Harley (2013), but they added a so called Jabberwocky condition, in which all content words were replaced by pseudowords in order to examine syntactic processing while reducing semantic context. Only in this Jabberwocky condition, a group difference was found between stuttering children, on one hand, and recovered and normal fluent children, on the other hand: Syntactic errors (phrase structure violations) in Jabberwocky sentences elicited a P600 in normal fluent and in recovered children, but an N400-like effect in children with persistent stuttering. The authors conclude that “neural mechanisms associated with the processing of syntactic structure may be less mature in 6–7-year-old children whose stuttering persisted compared to their fluent or recovered peers.“

In fact, the left superior longitudinal fasciculus (SLF), that plays a role in syntactic processing (Griffith et al., 2013) was found to be less maturated in stuttering children (Chang et al., 2008). However, I assume that the delay in fiber maturation results from the misallocation of attention during speech (see Chapter 4), thus an anomaly in syntactic processing would be a side effect. Further, the structural deficit in the SLF affects phonological processing (see Section 4.4 about the dual stream model) and, with that, the comprehension of pseudowords. In fact, stuttering children were found to have more difficulty with pseudowords, compared to normal fluent children (Anderson, Wagovich, & Hall, 2006; Anderson & Wagovich,2010; Pelczarski & Yaruss, 2016; Sasisekaran & Byrd, 2013). Maybe the stuttering children were more confused by the Jabberwocky sentences (presented in parallel with the pictures of a cartoon video!), such that their response to the phrase structure violations was more like „don’t understand“ (N400) than like „that’s wrong“ (P600). (return)
 

Salmelin et al. (1998)

Whereas the left hemisphere was more sensitive in controls, the ratio was reversed in stutterers. In controls, the sensitivity of the right hemisphere to the side of stimulation was higher with (external) auditory feedback of speech, compared to silent conditions. In stutterers, the right hemisphere did not distinguish between tasks with and without external auditory feedback; sensitivity in the silent conditions was as high as during reading aloud. On the left hemisphere, the sensitivity to the side of stimulation was generally lower in stutterers, but increased during reading aloud, i.e., during stuttered speech (Salmelin et al., 1998).

It is important to mention that these results were obtained in conditions in which participants were reading – either silently or aloud (solo and in chorus). That means after my theory that their attention was directed either to the internal or to the external auditory feedback (see Section 3.1), with the only exclusion of the reading aloud (solo) condition in the stutterers’ group. And just in this condition, the overall pattern was broken: Iinterhemisperic balance in the stutterer group was closer to that in the control group. The authors wrote: “...the unusual interhemispheric balance in stutterers was broken during reading aloud because of a sudden reduction in the ipsilateral vs contralateral response ratio in the left hemisphere. This may be a serious problem for the stutterers’ auditory system and could well cause abrupt non-optimal interpretation of the auditory input and, thus, disturb self-monitoring and on-line adjustment of speech.” (p. 2229).

I agree, but with the supplement that not the anomaly in auditory processing per se may cause stuttering, but rather its interaction with the allocation of attention: The reading aloud solo condition was the only one in which attention to auditory feedback (internal or external, resp.) was not necessary, and I think stutterers detracted their attention from the auditory channel in this condition, and controls did not. The event-related potential (N100m) recorded in this study was the response to a probe tone; this early response after about 100ms occurs attention-independent, but is modulated by attention. (return)
 

Otoacoustic emissions and the control of auditory attention

A study by Arcuri, Schiefer, and Azevedo (2017) provides new suggestions to an auditory processing disorder at least in a subgroup of stutterers. The authors found that the suppression of otoacoustic emissions was present in only 7 of 15 stuttering participants, but in 14 of 15 controls. The chance of an individual in the stuttering group to not exhibit a suppression effect was 16 times that of an individual in the control group.

Otoacoustic emissions (OAEs) result from the resonance of outer hair cells in the cochlea. They amplify incoming acoustic stimuli and, in this way, support auditory perception and the control of auditory attention. OAEs are automatically elicited by resonance, thus they must be suppressed so that they do not occur, e.g., in the case of redundant information or noise. Suppression takes place via the olivocochlear tracts that connect both ears with each other, but also with the corticofugal tract, via which the cochlear activity can be controlled by the cerebrum. Outer hair cells in the cochlea are tonotopically organized, so that their resonance occurs frequency-depending, and also OAE suppression can affect specific frequencies. The functioning of OAE suppression has not yet been completely understood, but there seem to be two ways, one of them attention-independent, the other one depending on attention.

The attention-independent way is that the ear at which an acoustic signal arrives first or more strongly inhibits the OAEs to this signal in the other ear via the olivocochlear tracts. This simple mechanism supports quick the localization of sound sources as well as the suppression of background noise that reaches both ears equally (which might result in mutual OAE suppression); that is, the mechanism supports quick adaptation to an acoustic situation and provides the basis for the control of selective auditory attention (see, e.g., Markevych et al., 2011; Srinivasan et al., 2012; Suga et al., 2000 for overviews).

The second way of OAE suppression is controlled by the cerebrum via the corticofugal pathway. It servers for the selective suppression of redundant, disturbing, or distracting auditory input. This mechanism is depending on selective attention because the brain must first know what is the target of the processing (e.g., speech, a certain person’s voice), and which sounds or sound components (frequencies) are redundant (e.g., noise or music in the background). Selective OAE suppression supports exact adjustment and maintenance of selective attention – there seems to be an interaction between OAE suppression and auditory attention and, as was found by Markevych et al. (2011), even between OAE suppression and the lateralization of speech processing on the cortex (see last Section, here).

In the Arcuri et al. (2017) study, this mechanism was less efficient in the stuttering group because the participants’ attention was directed to the click sounds. Further suggestions that the top-down control of OAE suppression may not work well in some stutterers come from reports they perceive sounds or their own voice as loud, booming, or unpleasant (see, e.g., this report in an online forum). Perhaps, OAEs to redundant low frequencies are not sufficiently suppressed in such cases.

However, the first, attention-independent mechanism which forms the basis of the second, attention-depending one, seems to be impaired as well in a subgroup of stutterers. As already mentioned in the main text, Rousey, Goetzinger, and Dirks (1959) found that stutterers had difficulty with the localization of sound sources, and MacCulloch and Eaton (1971) as well as Brown, Sambrooks, and MacCulloch (1975) found that children who stutter, as a group, had a reduced mean threshold for auditory discomfort compared to controls. The latter finding suggests that their auditory sensitivity does not very well adapt to the volume of noise. As mentioned in the main text as well, Howell et al. (2000) and Howell, Davis, and Williams (2006) found a higher mean backward-masking threshold – suggesting a reduced ability to perceive short sounds in noise – in stuttering children and especially in those who persisted in stuttering. (return)
 

Network architecture – resting state connectivity

The authors write that. in the course of child development, the connectivity between default mode network (DMN) and other intrinsic connectivity networks (ICNs) becomes lower in favor of behavioral control by “task positive” networks. Looking at the figures, especially at Figure 6, one can see many blue lines between DMN and other ICNs, indicating lower connectivity. Seemingly, the segregation between networks is generally more (prematurely) progressed in children who stutter, which may interfere with the gradual, balanced development of the integration of attention, perception and motor control (I think in the common term ‘sensorimotor integration’, the important role of attention is sometimes neglected).

Component 5 (Figure 3) which predicts persistence in stuttering shows many decreased connectivities, but also hyperconnectivities, particularly between frontoparietal network (FPN) and DMN and between dorsal attention network (DAN) and DMN. This may indicate an imbalance in attention control, possibly a too close link between executive control and top-down attention (focused on targets), to the detriment of feedback processing which may be more depending on bottom-up attention. (return)
 

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