Stuttering as a trait or state – an ALE meta‐analysis of neuroimaging studies

Abstract

Stuttering is a speech disorder characterised by repetitions, prolongations and blocks that disrupt the forward movement of speech. An earlier meta-analysis of brain imaging studies of stuttering (Brown et al., 2005) revealed a general trend towards rightward lateralization of brain activations and hyperactivity in the larynx motor cortex bilaterally. The present study sought not only to update that meta-analysis with recent work but to introduce an important distinction not present in the first study, namely the difference between 'trait' and 'state' stuttering. The analysis of trait stuttering compares people who stutter (PWS) with people who do not stutter when behaviour is controlled for, i.e., when speech is fluent in both groups. In contrast, the analysis of state stuttering examines PWS during episodes of stuttered speech compared with episodes of fluent speech. Seventeen studies were analysed using activation likelihood estimation. Trait stuttering was characterised by the well-known rightward shift in lateralization for language and speech areas. State stuttering revealed a more diverse pattern. Abnormal activation of larynx and lip motor cortex was common to the two analyses. State stuttering was associated with overactivation in the right hemisphere larynx and lip motor cortex. Trait stuttering was associated with overactivation of lip motor cortex in the right hemisphere but underactivation of larynx motor cortex in the left hemisphere. These results support a large literature highlighting laryngeal and lip involvement in the symptomatology of stuttering, and disambiguate two possible sources of activation in neuroimaging studies of persistent developmental stuttering.

Stuttering as a trait or a state revisited: motor system involvement in persistent developmental stuttering

“…Briefly, the analysis used ALE to separately describe the neural correlates of having a propensity to stutter when speaking (i.e., the trait of being a person who stutters) and the behavior of stuttering (i.e., the state of currently exhibiting a stutter). Readers are referred to the original publication for methodological details (Belyk et al, 2015).…”

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This corrigendum reports an update to the meta-analysis reported in Belyk et al (2015). The publicly-available program GINGERALE contains the most widely adopted algorithm for meta-analyses by activation likelihood estimation (ALE) of functional magnetic resonance imaging (fMRI) experiments.

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“…These errors affected published ALE analyses using False-Discovery Rate (FDR) corrections for multiple comparisons prior to May 11, 2015 (GINGERALE versions prior to v.2.3.3) and cluster-wise Family-Wise Error (cFWE) corrections for multiple comparisons prior to April 26, 2016 (GINGERALE versions prior to v2.3.6). The implementation errors in these versions may have caused statistical thresholds in the resultant ALE analyses to be more liberal than intended by the researchers, including in our own analysis (Belyk et al, 2015).Furthermore, subsequent research has demonstrated that voxel-wise FDR correction in the context of ALE has the undesirable properties of being simultaneously low in sensitivity to true effects and highly susceptible to false positives (Eickhoff et al, 2016). This view is supported by a broader theoretical position that voxel-wise FDR may be inappropriate for spatially smooth data, such as the data represented in ALE analyses (Chumbley & Friston, 2009).…”

“…Briefly, the analysis used ALE to separately describe the neural correlates of having a propensity to stutter when speaking (i.e., the trait of being a person who stutters) and the behavior of stuttering (i.e., the state of currently exhibiting a stutter). Readers are referred to the original publication for methodological details (Belyk et al, 2015).Three changes were made from the original meta-analysis. First, we used the most recent version of the GINGERALE software in which major implementation errors have been corrected (v2.3.6, retrieved August 25, 2016).…”

“…These errors affected published ALE analyses using False-Discovery Rate (FDR) corrections for multiple comparisons prior to May 11, 2015 (GINGERALE versions prior to v.2.3.3) and cluster-wise Family-Wise Error (cFWE) corrections for multiple comparisons prior to April 26, 2016 (GINGERALE versions prior to v2.3.6). The implementation errors in these versions may have caused statistical thresholds in the resultant ALE analyses to be more liberal than intended by the researchers, including in our own analysis (Belyk et al, 2015).…”