Functional neural circuits that underlie developmental stuttering

Qiao, Jianping; Wang, Zhishun; Zhao, Guizhe; Huo, Yuankai; Herder, Carl; Sikora, Chamonix O.; Peterson, Bradley S.

doi:10.1371/journal.pone.0179255

Cited by 30 publications

(23 citation statements)

References 69 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Secondly, we applied the ICA with HPM-ICA, which we proposed and published previously ( Wang et al, 2011 ; Qiao et al, 2015 , 2017 ), to the preprocessed fMRI data to estimate the brain FC networks. In this method, we used ICA to generate N ICs for each participant and then used partner matching to match these components across the participants, yielding clusters of components that matched across participants.…”

Section: Methodsmentioning

confidence: 99%

Aberrant Functional Network Connectivity as a Biomarker of Generalized Anxiety Disorder

Qiao

Cao

et al. 2017

Front. Hum. Neurosci.

Self Cite

View full text Add to dashboard Cite

Neural disruptions during emotion regulation are common of generalized anxiety disorder (GAD). Identifying distinct functional and effective connectivity patterns in GAD may provide biomarkers for their diagnoses. This study aims to investigate the differences of features of brain network connectivity between GAD patients and healthy controls (HC), and to assess whether those differences can serve as biomarkers to distinguish GAD from controls. Independent component analysis (ICA) with hierarchical partner matching (HPM-ICA) was conducted on resting-state functional magnetic resonance imaging data collected from 20 GAD patients with medicine-free and 20 matched HC, identifying nine highly reproducible and significantly different functional brain connectivity patterns across diagnostic groups. We then utilized Granger causality (GC) to study the effective connectivity between the regions that identified by HPM-ICA. The linear discriminant analysis was finally used to distinguish GAD from controls with these measures of neural connectivity. The GAD patients showed stronger functional connectivity in amygdala, insula, putamen, thalamus, and posterior cingulate cortex, but weaker in frontal and temporal cortex compared with controls. Besides, the effective connectivity in GAD was decreased from the cortex to amygdala and basal ganglia. Applying the ICA and GC features to the classifier led to a classification accuracy of 87.5%, with a sensitivity of 90.0% and a specificity of 85.0%. These findings suggest that the presence of emotion dysregulation circuits may contribute to the pathophysiology of GAD, and these aberrant brain features may serve as robust brain biomarkers for GAD.

show abstract

Section: Methodsmentioning

confidence: 99%

Aberrant Functional Network Connectivity as a Biomarker of Generalized Anxiety Disorder

Qiao

Cao

et al. 2017

Front. Hum. Neurosci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…To associate the spatial distribution of the task-based functional networks identified by ICA with resting-state networks, we derived Tanimoto Indices (also known as Jaccard Indices) by comparing each task-based network to all restingstate networks (Wang and Peterson, 2008;Qiao et al, 2017). Overlaps of the top five task-related networks for each group (all participants, AC, AWS) with resting-state networks are presented in Supplementary Tables S1-S3.…”

Section: Independent Component Analysis (Ica)mentioning

confidence: 99%

Neural Correlates of Vocal Pitch Compensation in Individuals Who Stutter

Sares

Deroche

Ohashi

et al. 2020

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Stuttering is a disorder that impacts the smooth flow of speech production and is associated with a deficit in sensorimotor integration. In a previous experiment, individuals who stutter were able to vocally compensate for pitch shifts in their auditory feedback, but they exhibited more variability in the timing of their corrective responses. In the current study, we focused on the neural correlates of the task using functional MRI. Participants produced a vowel sound in the scanner while hearing their own voice in real time through headphones. On some trials, the audio was shifted up or down in pitch, eliciting a corrective vocal response. Contrasting pitch-shifted vs. unshifted trials revealed bilateral superior temporal activation over all the participants. However, the groups differed in the activation of middle temporal gyrus and superior frontal gyrus [Brodmann area 10 (BA 10)], with individuals who stutter displaying deactivation while controls displayed activation. In addition to the standard univariate general linear modeling approach, we employed a data-driven technique (independent component analysis, or ICA) to separate task activity into functional networks. Among the networks most correlated with the experimental time course, there was a combined auditory-motor network in controls, but the two networks remained separable for individuals who stuttered. The decoupling of these networks may account for temporal variability in pitch compensation reported in our previous work, and supports the idea that neural network coherence is disturbed in the stuttering brain.

show abstract

“…Salmelin et al found that rather than the typical pattern of activity starting in L-IFG, advancing to left lateral central sulcus, and then to the dorsal premotor cortex, AWS had activity first arising in motor cortex prior to L-IFG thus indicating attempts to initiate the motor programs prior to the construction of the articulatory plan. In addition, the front aslant tract (i.e., between Broca's and SMA) has been implicated as a neural correlate of stuttering (Kronfeld-Duenias, Amir, Ezrati-Vinacour, Civier, & Ben-Shachar, 2016;Misaghi, Zhang, Gracco, Luc, & Beal, 2018;Qiao et al, 2017), highlighting the possible dysfunction between planning/execution areas in stuttering speakers. Taken together with previous results from the literature, our findings confirm the importance of the L-IFG for our understanding of stuttering and indicate involvement of neural processes underlying speech-motor planning in the disorder.…”

Section: Neural Correlates Of Planning In Adults Who Stuttermentioning

confidence: 99%

A fNIRS Investigation of Speech Planning and Execution in Adults Who Stutter

Jackson¹,

Wijeakumar

Beal

et al. 2019

Neuroscience

View full text Add to dashboard Cite

Our study aimed to determine the neural correlates of speech planning and execution in adults who stutter (AWS). Fifteen AWS and 15 controls (CON) completed two tasks that either manipulated speech planning or execution processing loads.Functional near-infrared spectroscopy (fNIRS) was used to measure changes in blood flow concentrations during each task, thus providing an indirect measure of neural activity. An image-based reconstruction technique was used to analyze the results and facilitate their interpretation in the context of previous functional neuroimaging studies of AWS that used positron emission tomography (PET) or functional magnetic resonance imaging (fMRI). For planning, we compared neural activity associated with high versus low planning load in AWS and CON. For execution, we compared the neural activity associated with overt versus covert naming in AWS and CON. Broadly, group level effects corroborate previous PET/fMRI findings including under-activation in lefthemisphere perisylvian speech-language networks and over-activation in righthemisphere homologues. Increased planning load revealed atypical left-hemisphere activation in AWS, whereas increased execution load yielded atypical right frontotemporo-parietal and bilateral motor activation in AWS. Our results add to the limited literature differentiating speech planning versus execution processes in AWS. Highlights1. This report includes the largest sample of AWS to undergo fNIRS to date.2. AWS showed atypical activation in left speech-language regions for planning and right hemisphere homologues for execution.3. Atypical right hemisphere activation comprises a known inhibitory network 4. Group main effects were generally in line with previous PET/fMRI studies of AWS.

show abstract

Functional neural circuits that underlie developmental stuttering

Cited by 30 publications

References 69 publications

Aberrant Functional Network Connectivity as a Biomarker of Generalized Anxiety Disorder

Aberrant Functional Network Connectivity as a Biomarker of Generalized Anxiety Disorder

Neural Correlates of Vocal Pitch Compensation in Individuals Who Stutter

A fNIRS Investigation of Speech Planning and Execution in Adults Who Stutter

Contact Info

Product

Resources

About