Dataset Information

Genetic and Neurophysiological Biomarkers of Neuroplasticity Inform Post-Stroke Language Recovery.

ABSTRACT:

Background

There is high variability in post-stroke aphasia severity and predicting recovery remains imprecise. Standard prognostics do not include neurophysiological indicators or genetic biomarkers of neuroplasticity, which may be critical sources of variability.

Objective

To evaluate whether a common polymorphism (Val⁶⁶Met) in the gene for brain-derived neurotrophic factor (BDNF) contributes to variability in post-stroke aphasia, and to assess whether BDNF polymorphism interacts with neurophysiological indicators of neuroplasticity (cortical excitability and stimulation-induced neuroplasticity) to improve estimates of aphasia severity.

Methods

Saliva samples and motor-evoked potentials (MEPs) were collected from participants with chronic aphasia subsequent to left-hemisphere stroke. MEPs were collected prior to continuous theta burst stimulation (cTBS; index for cortical excitability) and 10 minutes following cTBS (index for stimulation-induced neuroplasticity) to the right primary motor cortex. Analyses assessed the extent to which BDNF polymorphism interacted with cortical excitability and stimulation-induced neuroplasticity to predict aphasia severity beyond established predictors.

Results

Val⁶⁶Val carriers showed less aphasia severity than Val⁶⁶Met carriers, after controlling for lesion volume and time post-stroke. Furthermore, Val⁶⁶Val carriers showed expected effects of age on aphasia severity, and positive associations between severity and both cortical excitability and stimulation-induced neuroplasticity. In contrast, Val⁶⁶Met carriers showed weaker effects of age and negative associations between cortical excitability, stimulation-induced neuroplasticity and aphasia severity.

Conclusions

Neurophysiological indicators and genetic biomarkers of neuroplasticity improved aphasia severity predictions. Furthermore, BDNF polymorphism interacted with cortical excitability and stimulation-induced neuroplasticity to improve predictions. These findings provide novel insights into mechanisms of variability in stroke recovery and may improve aphasia prognostics.

SUBMITTER: Dresang HC

PROVIDER: S-EPMC9133188 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Genetic and Neurophysiological Biomarkers of Neuroplasticity Inform Post-Stroke Language Recovery.

Dresang Haley C HC Harvey Denise Y DY Xie Sharon X SX Shah-Basak Priyanka P PP DeLoretta Laura L Wurzman Rachel R Parchure Shreya Y SY Sacchetti Daniela D Faseyitan Olufunsho O Lohoff Falk W FW Hamilton Roy H RH

Neurorehabilitation and neural repair 20220415 6

<h4>Background</h4>There is high variability in post-stroke aphasia severity and predicting recovery remains imprecise. Standard prognostics do not include neurophysiological indicators or genetic biomarkers of neuroplasticity, which may be critical sources of variability.<h4>Objective</h4>To evaluate whether a common polymorphism (Val<sup>66</sup>Met) in the gene for brain-derived neurotrophic factor (BDNF) contributes to variability in post-stroke aphasia, and to assess whether BDNF polymorphi ...[more]

PMID: 35428413

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Project description:Identifying the neural changes that support recovery of cognitive functions after a brain lesion is important to advance our understanding of human neuroplasticity, which, in turn, forms the basis for the development of effective treatments. To date, the preponderance of neuroimaging studies has focused on localizing changes in average brain activity associated with functional recovery. Here, we took a novel approach by evaluating whether cognitive recovery in chronic stroke is related to increases in the differentiation of local neural response patterns. This approach is supported by research indicating that, in the intact brain, local neural representations become more differentiated (dissimilar) with learning (Glezer et al., 2015). We acquired fMRI data before and after 21 individuals received approximately 12 weeks of behavioral treatment for written language impairment due to a left-hemisphere stroke. We used Local-Heterogeneity Regression Analysis (Purcell and Rapp, 2018) to measure local neural response differentiation associated with written language processing, assuming that greater heterogeneity in the pattern of activity across adjacent neural areas indicates more well-differentiated neural representations. First, we observed pre to post-treatment increases in local neural differentiation (Local-Hreg) in the ventral occipital-temporal cortex of the left hemisphere. Second, we found that, in this region, higher local neural response differentiation prior to treatment was associated with less severe written language impairment, and that it also predicted greater future responsiveness to treatment. Third, we observed that changes in neural differentiation were systematically related to performance changes for trained and untrained items. Fourth, we did not observe these brain-behavior relationships for mean BOLD responses, only for Local-Hreg. Thus, this is the first investigation to quantify changes in local neural differentiation in the recovery of a cognitive function and the first to demonstrate the clear behavioral relevance of these changes. We conclude that the findings provide strong support for the novel hypothesis that the local re-differentiation of neural representations can play a significant role in functional recovery after brain lesion.

Dataset Information

Genetic and Neurophysiological Biomarkers of Neuroplasticity Inform Post-Stroke Language Recovery.

Background

Objective

Methods

Results

Conclusions

Publications

Genetic and Neurophysiological Biomarkers of Neuroplasticity Inform Post-Stroke Language Recovery.

Similar Datasets

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