Stroke induced reorganization of the neural networks for sentence comprehension, and relationship to perilesional dysfunction revealed by MEG and ASL
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1
Baycrest Hospital, Canada
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2
University of Toronto, Canada
Introduction: Considerable changes in the cortical representation of language processing can occur following stroke. Both left and right hemisphere regions are thought to support language recovery; however the relative contributions of each hemisphere and neural mechanisms mediating this process are not well understood (Meltzer et al., 2013; Price & Crinion, 2005; Saur et al., 2006; Thompson, 2000; 2010). It is generally thought that recovery of function in perilesional areas offers the best prognosis for clinical improvement (Heiss, 2003; Heiss & Thiel, 2006). Therefore, assessing the functionality of these areas is essential to targeting interventions. One potential biomarker of perilesional function and dysfunction relates to abnormalities in spontaneous neural activity (Meinzer et al., 2007; Poza et al., 2007). Perilesional tissue produces a large amount of high amplitude slow-wave activity, which can be quantified using algorithms that examine frequency spectra or complexity (e.g. multiscale entropy: MSE). This slowed spontaneous activity is a marker of subtle neural damage associated with the long-term effects of stroke beyond the primary infarct zone, and may be an indicator of “functional lesion” extent. Many questions remain unanswered regarding its potential associations with 1) cognitive dysfunction, 2) anatomical damage such as white matter disconnection, and 3) decreased blood flow (hypoperfusion).
Method: In the present study we used magnetoencephalography (MEG) to clarify the roles of dorsal and ventral language pathways in processing of semantic and syntactic information in healthy adults and participants with stroke-induced aphasia. In addition, we used functional and structural imaging to understand the roles of perilesional and contralesional activity in recovery from post-stroke aphasia, and to explore the potential of right hemisphere activity to support recovery. Using resting MEG and ASL, we developed a paradigm to identify perilesional cortex that is structurally intact, but not functioning optimally. We mapped the distribution of spontaneous slow-wave activity, its relationship to task-related activation during language comprehension, and decreased blood flow (hypoperfusion) in a group of stroke participants.
Results: We found that in healthy controls, activation of a temporo-frontal “ventral network” was involved in semantic processing, and a fronto-parietal “dorsal network” was associated with syntax (Figure 1A). Patients with aphasia activated homologous RH areas and dorsal LH regions; however they failed to activate ventral cortex adjacent to the lesion (Figure 1B). In addition, these perilesional regions consistently produced slow-wave activity, indicating that they are dysfunctional even though the tissue was not infarcted (Figure 1 C and D). Furthermore, abnormalities in spontaneous neural activity were associated with less task-related activation, and hypoperfusion in the affected regions
These results suggest that the reduced task-related responses in perilesional tissue and the degree of RH recruitment during language processing, are related to abnormal slowing of neural activity, and to reduced blood flow (hypoperfusion). Reversal of such abnormalities may be a fruitful target for interventions such as noninvasive brain stimulation.
Conclusion: Our results provide a basis for identifying a relationship between functional, structural and vascular markers of intact/impaired language function and recovery in patients with post-stroke aphasia.
References
Heiss, W. D., & Thiel, A. (2006).A proposed regional hierarchy in recovery of post- stroke aphasia. Brain and Language, 98, 118–123.
Heiss, W. D., et al. (2003).Disturbance and recovery of language function: Correlates in PET activation studies. NeuroImage, 20, S42–49.
Meinzer, M., et al. (2007). Functional re-recruitment of dysfunctional brain areas predicts language recovery in chronic aphasia. NeuroImage, 39, 2038-2046.
Meltzer, J. A., et al. (2013). Adaptive significance of right hemisphere activation in aphasic language comprehension. Neuropsychologia, 51, 1248-1259.
Poza, J., et al. (2007). Extraction of spectral based measures from MEG background oscillations in Alzheimer’s disease. Medical Engineering & Physics, 29, 1073-1083.
Price, C. J., & Crinion, J. (2005).The latest on functional imaging studies of aphasic stroke. Current Opinion in Neurology, 18, 429–434.
Saur, D., et al. (2006). Dynamics of language reorganization after stroke. Brain, 129, 1371-1384.
Thompson, C. K. (2000). Neuroplasticity: evidence form aphasia. Journal of Communication disorders, 33, 357-366.
Thompson, C. K. (2010).Neuralplasticity and treatment-induced recovery of sentence processing in agrammatism. Neuropsychologia, 48, 3211–3227.
Keywords:
Stroke,
Aphasia,
Language comprehension,
resting-state MEG,
language processing
Conference:
Academy of Aphasia -- 52nd Annual Meeting, Miami, FL, United States, 5 Oct - 7 Oct, 2014.
Presentation Type:
Poster presentation ONLY
Topic:
Not student
Citation:
Kielar
A,
Chu
RK,
Panamsky
L,
Khatamian
YB,
Chen
JJ and
Meltzer
JA
(2014). Stroke induced reorganization of the neural networks for sentence comprehension, and relationship to perilesional dysfunction revealed by MEG and ASL.
Front. Psychol.
Conference Abstract:
Academy of Aphasia -- 52nd Annual Meeting.
doi: 10.3389/conf.fpsyg.2014.64.00015
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Received:
14 Apr 2014;
Published Online:
04 Aug 2014.
*
Correspondence:
Dr. Aneta Kielar, Baycrest Hospital, Toronto, Canada, akielar@email.arizona.edu