Figure 1 - uploaded by Oren Civier
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Schematic of the GODIVA and DIVA models producing the first syllable of "go.di.və". DIVA model
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... well-learned syllables, whereas GODIVA (Gradient Order DIVA) models higher-level aspects of speech production, including syllable sequence planning and readout (controlled initiation) of successive plan constituents. The GODIVA model circuit outputs to the DIVA circuit through a premotor cortex stage that consists of speech sound map (SSM) cells (Fig. 1). Each SSM cell represents a premotor neuron population that encodes the motor program for a specific well-learned syllable. The GODIVA model decides which SSM cell should be active at each point, and the DIVA model controls an articulatory synthesizer (represented in the figure by a cartoon of a vocal tract) to execute the articulatory ...
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... a premotor neuron population that encodes the motor program for a specific well-learned syllable. The GODIVA model decides which SSM cell should be active at each point, and the DIVA model controls an articulatory synthesizer (represented in the figure by a cartoon of a vocal tract) to execute the articulatory program coded by that cell. Fig. 1 shows the models' contribution when fluently producing the syllable "go" of the syllable sequence "go.di.və" ("go diva"). The syllables "di" and "və" are produced in a similar fashion. The order of events in Fig. 1 is as ...
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... synthesizer (represented in the figure by a cartoon of a vocal tract) to execute the articulatory program coded by that cell. Fig. 1 shows the models' contribution when fluently producing the syllable "go" of the syllable sequence "go.di.və" ("go diva"). The syllables "di" and "və" are produced in a similar fashion. The order of events in Fig. 1 is as ...
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... the /g/ and /o/ phoneme cells have the highest activity in their corresponding queues within the IFS, these cells drive initial activity in the premotor cortex. Multiple SSM cells representing motor programs for syllables become active, each partially matching the phonological sequence representation in the IFS. Three such cells are depicted in Fig. 1: "go", "god", and "ko". These cells compete with each other for a variable time interval that depends on inputs via the BG- thalamus. Under normal conditions, these inputs promote competitive selection in favor of the cell with the best match to the phonological sequence representation. In this case, the "go" SSM cell (see dotted ...
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... Fig. 1: "go", "god", and "ko". These cells compete with each other for a variable time interval that depends on inputs via the BG- thalamus. Under normal conditions, these inputs promote competitive selection in favor of the cell with the best match to the phonological sequence representation. In this case, the "go" SSM cell (see dotted arrows in Fig. 1. Arrowheads and circles indicate excitation and inhibition, ...
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... competitive selection, the SSM cell for "go" reads out the motor program for that syllable, while inhibiting other SSM cells (e.g., the cells for "di" and "və"). The motor cortex stage of the DIVA model articulates the commands of the program, sending to the BG a copy of each executed command (see dashed arrows in Fig. ...
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... Impaired ability of the basal ganglia to produce timing cues is believed to be the primary reason for impaired speech fluency (Alm, 2004). This is postulated to be secondary to high density of D2 receptors and low D1:D2 ratio in the putamen (Civier et al., 2011), aberrant dopamine release, and focal lesions of the basal ganglia-thalamocortical circuits (Van Borsel et al., 1998). These provide a basis for using dopamine receptor antagonists in PDS. ...
... All of the above studies have only been conducted with adults who stutter, and have not been tested in children who stutter. Others have conducted modelling work to test hypotheses on the potential effect of dopamine imbalance in stuttering (Civier et al., 2011) as well as white matter abnormalities (Civier et al., 2013). Using a neurobiologically plausible model of speech production (Guenther et al., 2006;Bohland et al., 2010), the authors tested the hypothesis that an excess in dopamine would cause overexcitation of the thalamus, in effect disrupting the basal ganglia input to the ventral premotor cortex. ...
... According to this model, ventral premotor cortex normally enables selection and execution of the next syllable to be produced. When there is dopamine excess, however, the normal process of selecting the intended syllable while inhibiting all other unwanted syllables is affected, and hence the speaker cannot move on to the next syllable, resulting in a stuttered block or prolongation (Civier et al., 2011(Civier et al., , 2013. White matter abnormalities similarly may lead to 'transmission errors, and those translate to generation of a weaker contextual signal in the putamen D2 receptor cells'. ...
Affecting 1% of the general population, stuttering impairs the normally effortless process of speech production, which requires precise coordination of sequential movement occurring among the articulatory, respiratory, and resonance systems, all within millisecond time scales. Those afflicted experience frequent disfluencies during ongoing speech, often leading to negative psychosocial consequences. The aetiology of stuttering remains unclear; compared to other neurodevelopmental disorders, few studies to date have examined the neural bases of childhood stuttering. Here we report, for the first time, results from functional (resting state functional magnetic resonance imaging) and structural connectivity analyses (probabilistic tractography) of multimodal neuroimaging data examining neural networks in children who stutter. We examined how synchronized brain activity occurring among brain areas associated with speech production, and white matter tracts that interconnect them, differ in young children who stutter (aged 3-9 years) compared with age-matched peers. Results showed that children who stutter have attenuated connectivity in neural networks that support timing of self-paced movement control. The results suggest that auditory-motor and basal ganglia-thalamocortical networks develop differently in stuttering children, which may in turn affect speech planning and execution processes needed to achieve fluent speech motor control. These results provide important initial evidence of neurological differences in the early phases of symptom onset in children who stutter.
... Potential mechanisms by which incomplete myelination and excess dopamine could influence the speed with which speech plans become activated have recently been investigated by Civier (Civier, 2010;Civier, Bullock, Max, & Guenther, 2011) using GODIVA: a neurophysiologically plausible computational model of speech sequencing and planning (Bohland, Bullock, & Guenther, 2010) which incorporates a 'speech sound-map selection threshold' that is conceptually very similar to the release threshold of the VRT hypothesis. Simulations of excess dopamine led to delays to the moment when speech plans for initial syllables reached the selection threshold; and simulations of deficient white matter (in tracts underlying the ventral premotor cortex) led to delays to the moment when speech plans for non-initial syllables reached the selection threshold; with each abnormality resulting in a corresponding type of stuttering-like disfluency. ...
... As explained in Section 6.1.1, computer modeling using GODIVA (with a fixed release threshold) has demonstrated how failure of speech plans to attain an execution threshold in a timely manner can result in the production of stuttered (or stuttering-like) disfluencies (Civier, 2010;Civier et al., 2011). The researchers were then able to demonstrate how these simulated speech plan activation levels correlated with the blood-oxygenation level-dependent (BOLD) responses observed in brain regions associated with speech planning and execution in imaging studies of syllable and word production in PWS. ...
Unlabelled:
This paper reviews Bloodstein's (1975) Anticipatory Struggle Hypothesis of stuttering, identifies its weaknesses, and proposes modifications to bring it into line with recent advances in psycholinguistic theory. The review concludes that the Anticipatory Struggle Hypothesis provides a plausible explanation for the variation in the severity of stuttered disfluencies across speaking situations and conversation partners. However, it fails to explain the forms that stuttered disfluencies characteristically take or the subjective experience of loss of control that accompanies them. The paper then describes how the forms and subjective experiences of persistent stuttering can be accounted for by a threshold-based regulatory mechanism of the kind described in Howell's (2003) revision of the EXPLAN hypothesis. It then proposes that shortcomings of both the Anticipatory Struggle and EXPLAN hypotheses can be addressed by combining them together to create a 'Variable Release Threshold' hypothesis whereby the anticipation of upcoming difficulty leads to the setting of an excessively high threshold for the release of speech plans for motor execution. The paper also reconsiders the possibility that two stuttering subtypes exist: one related to formulation difficulty and other to difficulty initiating motor execution. It concludes that research findings that relate to the one may not necessarily apply to the other.
Learning outcomes:
After reading this article, the reader will be able to: (1) summarize the key strengths and weaknesses of Bloodstein's Anticipatory Struggle Hypothesis; (2) describe two hypothesized mechanisms behind the production of stuttered disfluencies (tension and fragmentation & release threshold mechanisms); and (3) discuss why the notion of anticipation is relevant to current hypotheses of stuttering.
