We will also stream this seminar via Zoom.
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Different Hemispheric Network Dynamics during Auditory Language Comprehension and its clinical implications regarding Resting State fMRI
With growing interest in modeling neurobehavior, there is increased interest in understanding patterns of functional connectivity (FC) during language processing. Previous research has suggested that static resting-state and task-based fMRI may be interchangeable in determining FC in language-related regions of interest. For these reasons, authors have argued for the elimination of using task-based fMRI assessments in preoperative clinical work up of language mapping. However, given that language exhibits not only 3D spatial attributes but also temporal components, understanding the temporal dynamics of these two modalities is essential in developing adaptive computational models. Thus, the stability of language neural networks during resting-state and task-based fMRI during auditory comprehension was examined in healthy participants.
There was more correlation variability over time FC in only specific common networks in the left hemisphere during task-based fMRI while large scale neural networks in the right hemisphere did not show this variability over time.
Our finding suggests that the temporal dynamics of identical neuronal networks during resting-state and task-based fMRI are markedly different especially within the left hemisphere but not in the right hemisphere. This may be an important computational model feature that may improve model prediction of clinical outcome following central nervous system injury and can be used to confirm language laterality in cases where standard fMRI neuroactivation studies are equivocal.
A pizza lunch will be served. Please bring your own beverage.
This is a joint seminar with Penn’s Integrated Language Sciences and Technology (ILST) initiative.