scholarly journals Resting State fMRI Speech, Language, and Executive Function Network Connectivity in Children with and without Listening Difficulties

Author(s):  
Julia Catherine Hoyda ◽  
Hannah J Stewart ◽  
Jennifer Vannest ◽  
David R Moore

Listening Difficulties (LiD) are characterized by a child having reported issues with listening despite exhibiting normal hearing thresholds. LiD can often overlap with other developmental disorders, including speech and language disorders, and involve similar higher-order auditory processing. This study used resting-state functional MRI to examine functional brain networks associated with receptive and expressive speech and language and executive function in children with LiD and typically developing (TD) peers (average age of 10 years). We examined differences in region-of-interest (ROI)-to-ROI functional connectivity between: (1) the LiD group and the TD group and (2) within the LiD group, those participants who had seen a Speech-Language Pathologist and those who had not. The latter comparison was examined as a way of comparing children with and without speech and language disorders. Connections that differed between groups were analyzed for correlations with behavioral test data. The results showed functional connectivity differences between the LiD group and TD group in the executive function network and trends in the speech perception network. Differences were also found in the executive network between those LiD participants who had seen an SLP and those who had not. Several of these connectivity differences, particularly frontal-striatal connections, correlated with performance on behavioral tests: including tests that measure attention, executive function, and episodic memory, as well as speech, vocabulary, and sentence structure. The results of this study suggest that differences in functional connectivity in brain networks associated with speech perception and executive function may underlie and contribute to listening difficulties.

2006 ◽  
Vol 37 (S 1) ◽  
Author(s):  
T Clarke ◽  
B Bali ◽  
J Carvalho ◽  
S Foster ◽  
G Tremont ◽  
...  

2019 ◽  
Author(s):  
Aya Kabbara ◽  
Veronique Paban ◽  
Arnaud Weill ◽  
Julien Modolo ◽  
Mahmoud Hassan

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.


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