Evidence for planning and motor subtypes of stuttering based on resting state functional connectivity.

We tested the hypothesis, generated from the Gradient Order Directions Into Velocities of Articulators (GODIVA) model, that adults who stutter (AWS) may comprise subtypes based on differing connectivity within the cortico-basal ganglia planning or motor loop. Resting state functional connectivity from 91 AWS and 79 controls was measured for all GODIVA model connections. Based on a principal components analysis, two connections accounted for most of the connectivity variability in AWS: left thalamus - left posterior inferior frontal sulcus (planning loop component) and left supplementary motor area - left ventral premotor cortex (motor loop component). A k-means clustering algorithm using the two connections revealed three clusters of AWS. Cluster 1 was significantly different from controls in both connections; Cluster 2 was significantly different in only the planning loop; and Cluster 3 was significantly different in only the motor loop. These findings suggest the presence of planning and motor subtypes of stuttering.

Brain activity during the preparation and production of spontaneous speech in children with persistent stuttering.

Speech production forms the basis for human verbal communication. Though fluent speech production is effortless and automatic for most people, it is disrupted in speakers who stutter, who experience difficulties especially during spontaneous speech and at utterance onsets. Brain areas comprising the basal ganglia thalamocortical (BGTC) motor loop have been a focus of interest in the context of stuttering, given this circuit's critical role in initiating and sequencing connected speech. Despite the importance of better understanding the role of the BGTC motor loop in supporting overt, spontaneous speech production, capturing brain activity during speech has been challenging to date, due to fMRI artifacts associated with severe head motions during speech production. Here, using an advanced technique that removes speech-related artifacts from fMRI signals, we examined brain activity occurring immediately before, and during, overt spontaneous speech production in 22 children with persistent stuttering (CWS) and 18 children who do not stutter (controls) in the 5-to-12-year age range. Brain activity during speech production was compared in two conditions: spontaneous speech (i.e., requiring language formulation) and automatic speech (i.e., overlearned word sequences). Compared to controls, CWS exhibited significantly reduced left premotor activation during spontaneous speech production but not during automatic speech. Moreover, CWS showed an age-related reduction in left putamen and thalamus activation during speech preparation. These results provide further evidence that stuttering is associated with functional deficits in the BGTC motor loop, which are exacerbated during spontaneous speech production.

Brain developmental trajectories associated with childhood stuttering persistence and recovery.

Stuttering is a neurodevelopmental disorder affecting 5-8 % of preschool-age children, continuing into adulthood in 1 % of the population. The neural mechanisms underlying persistence and recovery from stuttering remain unclear and little information exists on neurodevelopmental anomalies in children who stutter (CWS) during preschool age, when stuttering symptoms typically first emerge. Here we present findings from the largest longitudinal study of childhood stuttering to date, comparing children with persistent stuttering (pCWS) and those who later recovered from stuttering (rCWS) with age-matched fluent peers, to examine the developmental trajectories of both gray matter volume (GMV) and white matter volume (WMV) using voxel-based morphometry. A total of 470 MRI scans were analyzed from 95 CWS (72 pCWS and 23 rCWS) and 95 fluent peers between 3 and 12 years of age. We examined overall group and group by age interactions in GMV and WMV in preschool age (3-5 years old) and school age (6-12 years old) CWS and controls, controlling for sex, IQ, intracranial volume, and socioeconomic status. The results provide broad support for a possible basal ganglia-thalamocortical (BGTC) network deficit starting in the earliest phases of the disorder and point to normalization or compensation of earlier occurring structural changes associated with stuttering recovery.

Auditory rhythm discrimination in adults who stutter: An fMRI study.

Rhythm perception deficits have been linked to neurodevelopmental disorders affecting speech and language. Children who stutter have shown poorer rhythm discrimination and attenuated functional connectivity in rhythm-related brain areas, which may negatively impact timing control required for speech. It is unclear whether adults who stutter (AWS), who are likely to have acquired compensatory adaptations in response to rhythm processing/timing deficits, are similarly affected. We compared rhythm discrimination in AWS and controls (total n = 36) during fMRI in two matched conditions: simple rhythms that consistently reinforced a periodic beat, and complex rhythms that did not (requiring greater reliance on internal timing). Consistent with an internal beat deficit hypothesis, behavioral results showed poorer complex rhythm discrimination for AWS than controls. In AWS, greater stuttering severity was associated with poorer rhythm discrimination. AWS showed increased activity within beat-based timing regions and increased functional connectivity between putamen and cerebellum (supporting interval-based timing) for simple rhythms.

Neural activity during solo and choral reading: A functional magnetic resonance imaging study of overt continuous speech production in adults who stutter.

Previous neuroimaging investigations of overt speech production in adults who stutter (AWS) found increased motor and decreased auditory activity compared to controls. Activity in the auditory cortex is heightened, however, under fluency-inducing conditions in which AWS temporarily become fluent while synchronizing their speech with an external rhythm, such as a metronome or another speaker. These findings suggest that stuttering is associated with disrupted auditory motor integration. Technical challenges in acquiring neuroimaging data during continuous overt speech production have limited experimental paradigms to short or covert speech tasks. Such paradigms are not ideal, as stuttering primarily occurs during longer speaking tasks. To address this gap, we used a validated spatial ICA technique designed to address speech movement artifacts during functional magnetic resonance imaging (fMRI) scanning. We compared brain activity and functional connectivity of the left auditory cortex during continuous speech production in two conditions: solo (stutter-prone) and choral (fluency-inducing) reading tasks. Overall, brain activity differences in AWS relative to controls in the two conditions were similar, showing expected patterns of hyperactivity in premotor/motor regions but underactivity in auditory regions. Functional connectivity of the left auditory cortex (STG) showed that within the AWS group there was increased correlated activity with the right insula and inferior frontal area during choral speech. The AWS also exhibited heightened connectivity between left STG and key regions of the default mode network (DMN) during solo speech. These findings indicate possible interference by the DMN during natural, stuttering-prone speech in AWS, and that enhanced coordination between auditory and motor regions may support fluent speech.

Neuroanatomical anomalies associated with rare AP4E1 mutations in people who stutter.

Developmental stuttering is a common speech disorder with strong genetic underpinnings. Recently, stuttering has been associated with mutations in genes involved in lysosomal enzyme trafficking. However, how these mutations affect the brains of people who stutter remains largely unknown. In this study, we compared grey matter volume and white matter fractional anisotropy between a unique group of seven subjects who stutter and carry the same rare heterozygous AP4E1 coding mutations and seven unrelated controls without such variants. The carriers of the AP4E1 mutations are members of a large Cameroonian family in which the association between AP4E1 and persistent stuttering was previously identified. Compared to controls, mutation carriers showed reduced grey matter volume in the thalamus, visual areas and the posterior cingulate cortex. Moreover, reduced fractional anisotropy was observed in the corpus callosum, consistent with the results of previous neuroimaging studies of people who stutter with unknown genetic backgrounds. Analysis of gene expression data showed that these structural differences appeared at the locations in which expression of AP4E1 is relatively high. Moreover, the pattern of grey matter volume differences was significantly associated with AP4E1 expression across the left supratentorial regions. This spatial congruency further supports the connection between AP4E1 mutations and the observed structural differences.

Developmental Factors That Predict Head Movement During Resting-State Functional Magnetic Resonance Imaging in 3-7-Year-Old Stuttering and Non-stuttering Children.

Early childhood marks a period of dynamic neurocognitive development. Preschool-age coincides with the onset of many childhood disorders and is a developmental period that is frequently studied to determine markers of neurodevelopmental disorders. Magnetic resonance imaging (MRI) is often used to explore typical brain development and the neural bases of neurodevelopmental disorders. However, acquiring high-quality MRI data in young children is challenging. The enclosed space and loud sounds can trigger unease and cause excessive head movement. A better understanding of potential factors that predict successful MRI acquisition would increase chances of collecting useable data in children with and without neurodevelopmental disorders. We investigated whether age, sex, stuttering status, and childhood temperament as measured using the Child Behavioral Questionnaire, could predict movement extent during resting-state functional MRI (rs-fMRI) in 76 children aged 3-7 years, including 42 children who stutter (CWS). We found that age, sex, and temperament factors could predict motion during rs-fMRI scans. The CWS were not found to differ significantly from controls in temperament or head movement during scanning. Sex and age were significant predictors of movement. However, age was no longer a significant predictor when temperament, specifically effortful control, was considered. Controlling for age, boys with higher effortful control scores moved less during rs-fMRI procedures. Additionally, boys who showed higher negative affectivity showed a trend for greater movement. Considering temperament factors in addition to age and sex may help predict the success of acquiring useable rs-fMRI (and likely general brain MRI) data in young children in MR neuroimaging.

Association Between Gray Matter Volume Variations and Energy Utilization in the Brain: Implications for Developmental Stuttering.

Purpose The biological mechanisms underlying developmental stuttering remain unclear. In a previous investigation, we showed that there is significant spatial correspondence between regional gray matter structural anomalies and the expression of genes linked to energy metabolism. In the current study, we sought to further examine the relationship between structural anomalies in the brain in children with persistent stuttering and brain regional energy metabolism. Method High-resolution structural MRI scans were acquired from 26 persistent stuttering and 44 typically developing children. Voxel-based morphometry was used to quantify the between-group gray matter volume (GMV) differences across the whole brain. Group differences in GMV were then compared with published values for the pattern of glucose metabolism measured via F18 fluorodeoxyglucose uptake in the brains of 29 healthy volunteers using positron emission tomography. Results A significant positive correlation between GMV differences and F18 fluorodeoxyglucose uptake was found in the left hemisphere (ρ = .36, p < .01), where speech-motor and language processing are typically localized. No such correlation was observed in the right hemisphere (ρ = .05, p = .70). Conclusions Corroborating our previous gene expression studies, the results of the current study suggest a potential connection between energy metabolism and stuttering. Brain regions with high energy utilization may be particularly vulnerable to anatomical changes associated with stuttering. Such changes may be further exacerbated when there are sharp increases in brain energy utilization, which coincides with the developmental period of rapid speech/language acquisition and the onset of stuttering during childhood. Supplemental Material https://doi.org/10.23641/asha.14110454.

Linking Lysosomal Enzyme Targeting Genes and Energy Metabolism with Altered Gray Matter Volume in Children with Persistent Stuttering.

Developmental stuttering is a childhood onset neurodevelopmental disorder with an unclear etiology. Subtle changes in brain structure and function are present in both children and adults who stutter. It is a highly heritable disorder, and 12-20% of stuttering cases may carry a mutation in one of four genes involved in intracellular trafficking. To better understand the relationship between genetics and neuroanatomical changes, we used gene expression data from the Allen Institute for Brain Science and voxel-based morphometry to investigate the spatial correspondence between gene expression patterns and differences in gray matter volume between children with persistent stuttering (n = 26, and 87 scans) and their fluent peers (n = 44, and 139 scans). We found that the expression patterns of two stuttering-related genes (GNPTG and NAGPA) from the Allen Institute data exhibited a strong positive spatial correlation with the magnitude of between-group gray matter volume differences. Additional gene set enrichment analyses revealed that genes whose expression was highly correlated with the gray matter volume differences were enriched for glycolysis and oxidative metabolism in mitochondria. Because our current study did not examine the participants' genomes, these results cannot establish the direct association between genetic mutations and gray matter volume differences in stuttering. However, our results support further study of the involvement of lysosomal enzyme targeting genes, as well as energy metabolism in stuttering. Future studies assessing variations of these genes in the participants' genomes may lead to increased understanding of the biological mechanisms of the observed spatial relationship between gene expression and gray matter volume.

Neurofilament-lysosomal genetic intersections in the cortical network of stuttering.

The neurobiological underpinnings of stuttering, a speech disorder characterized by disrupted speech fluency, remain unclear. While recent developments in the field have afforded researchers the ability to pinpoint several genetic profiles associated with stuttering, how these specific genetic backgrounds impact neuronal circuits and how they generate or facilitate the emergence of stuttered speech remains unknown. In this study, we identified the large-scale cortical network that characterizes stuttering using functional connectivity MRI and graph theory. We performed a spatial similarity analysis that examines whether the topology of the stuttering cortical network intersects with genetic expression levels of previously reported genes for stuttering from the protein-coding transcriptome data of the Allen Human Brain Atlas. We found that GNPTG - a gene involved in the mannose-6-phosphate lysosomal targeting pathways - was significantly co-localized with the stuttering cortical network. An enrichment analysis demonstrated that the genes identified with the stuttering cortical network shared a significantly overrepresented biological functionality of Neurofilament Cytoskeleton Organization (NEFH, NEFL and INA). The relationship between lysosomal pathways, cytoskeleton organization, and stuttering, was investigated by comparing the genetic interactome between GNPTG and the neurofilament genes implicated in the current study. We found that genes of the interactome network, including CDK5, SNCA, and ACTB, act as functional links between lysosomal and neurofilament genes. These findings support the notion that stuttering is due to a lysosomal dysfunction, which has deleterious effects on the neurofilament organization of the speech neuronal circuits. They help to elucidate the intriguing, unsolved link between lysosomal mutations and the presence of stuttering.

Stuttering Severity Modulates Effects of Non-invasive Brain Stimulation in Adults Who Stutter.

Stuttering is a neurodevelopmental disorder that manifests as frequent disruptions in the flow of speech, affecting 1% of adults. Treatments are limited to behavioral interventions with variable success and high relapse rates, particularly in adults. However, even in severe cases, fluency can be temporarily induced during conditions in which the speaker synchronizes his speech with external rhythmic cues, such as when reading in unison (choral speech) or with a metronome. Non-invasive neuromodulation techniques such as transcranial direct current stimulation (tDCS) have shown promise in augmenting the effects of behavioral treatment during motor and speech/language rehabilitation, but only one study to date has examined behavioral modulatory effects of tDCS in the context of stuttering. Using high-definition (HD)-tDCS electrodes, which improves focality of stimulation relative to conventional tDCS, we investigated the effects of tDCS on speech fluency and brain activation in 14 adults who stutter (AWS). Either anodal or sham stimulation was delivered on separate days over left supplementary motor area (SMA). During stimulation, participants read aloud in sync with a metronome. Measures of speech fluency and brain activity functional magnetic resonance imaging (fMRI) were collected before and after stimulation. No significant differences in brain activity or speech fluency were found when comparing active and sham stimulation. However, stuttering severity significantly modulated the effect of stimulation: active stimulation attenuated the atypically strong association between stuttering severity and right thalamocortical network activity, especially in more severe speakers. These preliminary results warrant additional research into potential application of HD-tDCS to modulate speech motor networks to enhance fluency in stuttering.

Neuroanatomical Correlates of Childhood Stuttering: MRI Indices of White and Gray Matter Development That Differentiate Persistence Versus Recovery.

Purpose We review two recent neuroanatomical studies of children who stutter (CWS), one that examines white matter integrity and the other that focuses on cortical gray matter morphology. In both studies, we sought to examine differences between children whose stuttering persists ("persistent"), children who recovered from stuttering ("recovered"), and their nonstuttering peers ("controls"). Method Both of the reviewed studies use data from a large pediatric sample spanning preschool- to school-age children (3-10 years old at initial testing). Study 1 focused on surface-based measures of cortical size (thickness) and shape (gyrification) using structural magnetic resonance imaging, whereas Study 2 utilized diffusion tensor imaging to examine white matter integrity. Results In both studies, the main difference that emerged between CWS and fluent peers encompassed left hemisphere speech motor areas that are interconnected via the arcuate fasciculus. In the case of white matter integrity, the temporoparietal junction and posterior superior temporal gyrus, both connected via the left arcuate fasciculus, and regions along the corpus callosum that contain fibers connecting bilateral motor regions were significantly decreased in white matter integrity in CWS compared to controls. In the morphometric study, children who would go on to have persistent stuttering specifically had lower cortical thickness in ventral motor and premotor areas of the left hemisphere. Conclusion These results point to aberrant development of cortical areas involved in integrating sensory feedback with speech movements in CWS and differences in interhemispheric connectivity between the two motor cortices. Furthermore, developmental trajectories in these areas seem to diverge between persistent and recovered cases.

Reproducibility of axonal water fraction derived from the spherical mean diffusion weighted signal.

Recent years have seen growing interest in measuring axonal water fraction (AWF) using the spherical mean diffusion weighted signal, but information about the reproducibility of this method is needed before applying it in large-scale studies. The current study aims to evaluate the reproducibility of AWF derived from the spherical mean signal method. This retrospective study analyzed the Human Connectome Project (HCP) test-retest diffusion data of ten healthy adults. The diffusion scan was performed two times for each subject. Diffusion tensor imaging-based fractional anisotropy (FA) was calculated with b = 1000 s/mm2. AWF was calculated with b = 3000 s/mm2 using the spherical mean signal method. Gradient nonlinearities were corrected in both methods. Reproducibility was assessed using the reproducibility error, which is the percent absolute change relative to the mean. The mean reproducibility error of fractional anisotropy (FA) is 9.7 ±â€¯1.0% in white matter and 18.0 ±â€¯2.0% in gray matter. The mean reproducibility error of AWF is 4.6 ±â€¯0.6% in white matter and 7.0 ±â€¯1.5% in gray matter. Spherical mean signal-based AWF is more reproducible than FA for the HCP high resolution, low signal-to-noise ratio diffusion data.

Functional and Neuroanatomical Bases of Developmental Stuttering: Current Insights.

Affecting 5% of all preschool-aged children and 1% of the general population, developmental stuttering-also called childhood-onset fluency disorder-is a complex, multifactorial neurodevelopmental disorder characterized by frequent disruption of the fluent flow of speech. Over the past two decades, neuroimaging studies of both children and adults who stutter have begun to provide significant insights into the neurobiological bases of stuttering. This review highlights convergent findings from this body of literature with a focus on functional and structural neuroimaging results that are supported by theoretically driven neurocomputational models of speech production. Updated views on possible mechanisms of stuttering onset and persistence, and perspectives on promising areas for future research into the mechanisms of stuttering, are discussed.

Comparison of NODDI and spherical mean signal for measuring intra-neurite volume fraction.

PURPOSE: Neurite orientation dispersion and density imaging (NODDI) is a clinically feasible approach to measure intra-neurite volume fraction (fin). However, the sophisticated fitting procedure takes several hours. And the NODDI model relied on several questionable assumptions. Recent analytical work demonstrated that fin could be simply calculated from the spherical mean signal (MEANS) averaged over all gradient directions with a more solid theoretical foundation. The current study aims to compare NODDI and MEANS for measuring fin in human brain and investigate the potential of MEANS as a fast approach in clinics. METHODS: NODDI fin and MEANS fin were measured and compared on the same dataset. NODDI fin was obtained using the NODDI MATLAB Toolbox. MEANS fin is the product of the spherical mean signal and 2bD/π, where D is the intra-neurite intrinsic diffusivity. RESULTS: NODDI fin and MEANS fin maps are similar. The voxel-by-voxel correlation suggests that NODDI fin and MEANS fin are approximately equivalent to each other. CONCLUSION: MEANS may have potential to serve a fast and simple approach to estimate fin in clinics.

Linking spherical mean diffusion weighted signal with intra-axonal volume fraction.

Diffusion MRI has been widely used to assess brain tissue microstructure. However, the conventional diffusion tensor imaging (DTI) is inadequate for characterizing fiber direction or fiber density in voxels with crossing fibers in brain white matter. The constrained spherical deconvolution (CSD) technique has been proposed to measure the complex fiber orientation distribution (FOD) using a single high b-value (b ≥ 3000 s/mm2) to derive the intra-axonal volume fraction (Vin) from the calculated FOD. Recently, the spherical mean technique (SMT) was developed to fit Vin directly from a multi-compartment model with multi-shell b-values. Although different numbers of b-values are needed in the two techniques, both methods have been suggested to be related to the spherical mean diffusion weighted signal (S¯). The current study compared the two techniques on the same high-quality Human Connectome Project diffusion data and investigated the relation between S¯ and Vin systematically. At high b-values (b ≥ 3000 s/mm2), S¯ is linearly related to Vin, and S¯ provides similar contrast with Vin in white matter. At low b-values (b ~ 1000 s/mm2), the linear relation between S¯ and Vin is sensitive to the variations of intrinsic diffusivity. These results demonstrate that S¯ measured with the typical b-value of 1000 s/mm2 is not an indicator of Vin, and previous DTI studies acquired with b = 1000 s/mm2 cannot be re-analyzed to provide Vin-weighted contrast.

Minimal number of gradient directions for robust measurement of spherical mean diffusion weighted signal.

PURPOSE: Determination of the minimum number of gradient directions (Nmin) for robust measurement of spherical mean diffusion weighted signal (S¯). METHODS: Computer simulations were employed to characterize the relative standard deviation (RSD) of the measured spherical mean signal as a function of the number of gradient directions (N). The effects of diffusion weighting b-value and signal-to-noise ratio (SNR) were investigated. Multi-shell high angular resolution Human Connectome Project diffusion data were analyzed to support the simulation results. RESULTS: RSD decreases with increasing N, and the minimum number of N needed for RSD ≤ 5% is referred to as Nmin. At high SNRs, Nmin increases with increasing b-value to achieve sufficient sampling. Simulations showed that Nmin is linearly dependent on the b-value. At low SNRs, Nmin increases with increasing b-value to reduce the noise. RSD can be estimated as σS¯N, where σ = 1/SNR is the noise level. The experimental results were in good agreement with the simulation results. The spherical mean signal can be measured accurately with a subset of gradient directions. CONCLUSION: As Nmin is affected by b-value and SNR, we recommend using 10 × b / b1 (b1 = 1 ms/µm2) uniformly distributed gradient directions for typical human diffusion studies with SNR ~ 20 for robust spherical mean signal measurement.

Anomalous morphology in left hemisphere motor and premotor cortex of children who stutter.

Stuttering is a neurodevelopmental disorder that affects the smooth flow of speech production. Stuttering onset occurs during a dynamic period of development when children first start learning to formulate sentences. Although most children grow out of stuttering naturally, ∼1% of all children develop persistent stuttering that can lead to significant psychosocial consequences throughout one's life. To date, few studies have examined neural bases of stuttering in children who stutter, and even fewer have examined the basis for natural recovery versus persistence of stuttering. Here we report the first study to conduct surface-based analysis of the brain morphometric measures in children who stutter. We used FreeSurfer to extract cortical size and shape measures from structural MRI scans collected from the initial year of a longitudinal study involving 70 children (36 stuttering, 34 controls) in the 3-10-year range. The stuttering group was further divided into two groups: persistent and recovered, based on their later longitudinal visits that allowed determination of their eventual clinical outcome. A region of interest analysis that focused on the left hemisphere speech network and a whole-brain exploratory analysis were conducted to examine group differences and group × age interaction effects. We found that the persistent group could be differentiated from the control and recovered groups by reduced cortical thickness in left motor and lateral premotor cortical regions. The recovered group showed an age-related decrease in local gyrification in the left medial premotor cortex (supplementary motor area and and pre-supplementary motor area). These results provide strong evidence of a primary deficit in the left hemisphere speech network, specifically involving lateral premotor cortex and primary motor cortex, in persistent developmental stuttering. Results further point to a possible compensatory mechanism involving left medial premotor cortex in those who recover from childhood stuttering.

A systematic literature review of sex differences in childhood language and brain development.

The extent of sex differences in childhood language development is unclear. We conducted a systematic literature review synthesizing results from studies examining sex differences in brain structure and function relevant to language development during childhood. We searched PubMed and Scopus databases, and this returned a total of 46 published studies meeting criteria for inclusion that directly examined sex differences in brain development relevant to language function in children. The results indicate that: (a) sex differences in brain structure or function do not necessarily lead to differences in language task performance; (b) evidence for sex differences in brain and language development are limited; (c) when present, sex differences often interact with a variety of factors such as age and task. Overall, the magnitude of sexual dimorphism of brain developmental trajectories associated with language is not as significant as previously thought. Sex differences were found, however, in studies employing tighter age ranges. This suggests that sex differences may be more prominent during certain developmental stages but are negligible in other stages, likely due to different rates of maturation between the sexes. More research is needed to improve our understanding of how sex differences may arise due to the influence of sex hormones and developmental stages, and how these differences may lead to differences in various language task performance. These studies are expected to provide normative information that may be used in studies examining neurodevelopmental disorders that frequently affect more males than females, and also often affect language development.

Anomalous network architecture of the resting brain in children who stutter.

PURPOSE: We combined a large longitudinal neuroimaging dataset that includes children who do and do not stutter and a whole-brain network analysis in order to examine the intra- and inter-network connectivity changes associated with stuttering. Additionally, we asked whether whole brain connectivity patterns observed at the initial year of scanning could predict persistent stuttering in later years. METHODS: A total of 224 high-quality resting state fMRI scans collected from 84 children (42 stuttering, 42 controls) were entered into an independent component analysis (ICA), yielding a number of distinct network connectivity maps ("components") as well as expression scores for each component that quantified the degree to which it is expressed for each child. These expression scores were compared between stuttering and control groups' first scans. In a second analysis, we examined whether the components that were most predictive of stuttering status also predicted persistence in stuttering. RESULTS: Stuttering status, as well as stuttering persistence, were associated with aberrant network connectivity involving the default mode network and its connectivity with attention, somatomotor, and frontoparietal networks. The results suggest developmental alterations in the balance of integration and segregation of large-scale neural networks that support proficient task performance including fluent speech motor control. CONCLUSIONS: This study supports the view that stuttering is a complex neurodevelopmental disorder and provides comprehensive brain network maps that substantiate past theories emphasizing the importance of considering situational, emotional, attentional and linguistic factors in explaining the basis for stuttering onset, persistence, and recovery.