Event Abstract

Back to Event

A computationally implemented mechanistic account of post-stroke aphasia recovery

YA-NING CHANG1* and Matthew Lambon Ralph1
  • 1 MRC Cognition and Brain Sciences Unit, University of Cambridge, United Kingdom

Numerous neuroimaging studies have demonstrated right hemisphere activation in post-stroke aphasia recovery (e.g., Turkeltaub et al., 2012). Within a regional hierarchy framework, right hemisphere activation in recovery could be an indication of suboptimal performance because optimal language recovery is often associated with the preserved left hemisphere activation (Heiss et al., 2006). However, evidence in support for this notion primarily comes from aphasic patients with mild left hemisphere lesions (e.g., Saur et al., 2006) and thus with more perilesional left hemisphere regions intact. It remains unclear whether the observation is confounded with lesion severity. Moreover, a growing number of neuroimaging studies in healthy participants have demonstrated leftward asymmetric but bilateral activation during language tasks (e.g., Poeppel, 2014 for a review), suggesting that right hemisphere contributes to language activity in healthy participants. Hence, the critical questions relevant to aphasia recovery are how do the left hemisphere and right hemisphere work together to contribute to language processing; why left hemisphere lesions are more likely to cause impaired language performance than right hemisphere lesions; what are the influences of lesion severity on aphasia recovery, particularly in association with a shift of activation between the two hemisphere? To address these issues computationally and provide a mechanic account of aphasia recovery, we constructed a bilateral model of spoken word production based on neural network modelling. Specifically, we implemented the model concerning hemispheric structural asymmetry to investigate if leftward asymmetric but bilateral activation in healthy participants could result from greater computational resources available for language processing in the left hemisphere than in the right. We then investigated whether damage to language regions in the left hemisphere would be more likely to result in impaired language performance because of the removal of major language processing resources. Lastly, we examined whether the dynamic changes in activation patterns between the two hemispheres in aphasia recovery could be related to lesion severity. The simulation results demonstrated a link between differential computational resources with asymmetric but bilateral activation during a repetition task. Importantly, damage to the model with different levels of severity reproduced the changes in brain activation patterns observed in post-stroke aphasia recovery as reported in Saur et al. (2006). The resulting patterns suggest the relationship between brain activation and recovery performance is correlated rather than causal. The simulations provide insights into neural machinery underlying hemispheric language processing and its shift of activation in aphasia recovery.

Acknowledgements

The research was supported by an ERC Advanced grant to MALR (GAP: 670428).

References

Heiss, W. D., & Thiel, A. (2006). A proposed regional hierarchy in recovery of post-stroke aphasia. Brain Lang, 98(1), 118-123. Poeppel, D. (2014). The neuroanatomic and neurophysiological infrastructure for speech and language. Current Opinion in Neurobiology, 28, 142-149. Saur, D., Lange, R., Baumgaertner, A., Schraknepper, V., Willmes, K., Rijntjes, M., & Weiller, C. (2006). Dynamics of language reorganization after stroke. Brain, 129 (Pt 6), 1371-1384. Turkeltaub, P. E., Coslett, H. B., Thomas, A. L., Faseyitan, O., Benson, J., Norise, C., & Hamilton, R. H. (2012). The right hemisphere is not unitary in its role in aphasia recovery. Cortex, 48(9), 1179-1186.

Keywords: Language recovery, spoken word repetition, Hemisphere activity, computational modeling, Aphasia after stroke

Conference: Academy of Aphasia 57th Annual Meeting, Macau, Macao, SAR China, 27 Oct - 29 Oct, 2019.

Presentation Type: Platform presentation

Topic: Not eligible for student award

Citation: CHANG Y and Lambon Ralph M (2019). A computationally implemented mechanistic account of post-stroke aphasia recovery. Front. Hum. Neurosci. Conference Abstract: Academy of Aphasia 57th Annual Meeting. doi: 10.3389/conf.fnhum.2019.01.00081

Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.

The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.

Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.

For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.

Received: 03 May 2019; Published Online: 09 Oct 2019.

* Correspondence: Mx. YA-NING CHANG, MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom, yaningchang@gmail.com