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A framework to account for demand-based functional reorganisation in post-stroke aphasia
Poster Session B, Friday, October 25, 10:00 - 11:30 am, Great Hall 3 and 4
Ajay Halai1, Niklas Wiemers1,2, Matt Lambon Ralph1; 1MRC Cognition and Brain Sciences Unit, University of Cambridge, UK, 2Department of Neurology, University of Leipzig Medical Center, Germany
Background: Understanding how language recovers in post stroke aphasia (PSA) is challenging, particularly in terms of neural mechanisms driving recovery (Stefaniak et al., 2020). Our current theories of recovery suggest different systems that are recruited such as residual language systems (Saur et al., 2006), right hemisphere homologue (Stockert et al., 2020) or multiple-demand network (MDN) (Brownsett et al., 2014) - but crucially not why or how. PSA patients have heterogenous lesions, in terms of site and size, which place differential demands on the underlying residual system and its’ capabilities for reorganisation - resulting in multiple patterns of recovery that are based on the demand and resources available. Theoretical framework: Our proposed framework considers four factors in combination. Computational models have shown that residual left language regions can compensate a mild ‘lesion’; whereas moderate/severe lesions increase contralateral regions. Next, language has modular features in the brain (Hickok & Poeppel, 2007) and studies have shown lesion site specific deficits (Stockert et al., 2020 frontal vs temporo-parietal). A third consideration is how multiple networks interact to support language, where demand and spare capacity will determine how these are weighted. For example, domain-specific network changes have been demonstrated by Ueno et al., (2011) who showed damage to the dorsal pathway led to some recovery driven by ventral stream reorganisation. Conversely, domain-general networks such as MDN is recruited during stroke aphasia recovery (Geranmayeh et al., 2017). Finally, language is multi-dimensional meaning that core underlying features of language can be disrupted independently depending on lesion site/size (Ueno et al., 2011) and have unequal recovery trajectories that relate to (de-)activation in the brain (Stefaniak et al., 2022). Investigation: We addressed how the combination of these factors impact recovery by focusing on the role of the MDN and right language homologue hypothesis in recovery, where we hypothesise that involvement of either system will be demand dependent. Chronic post-stroke aphasia patients (n=57) were assessed with an extensive behavioural battery, structural and resting-state fMRI. First, we found that peri-lesional functional connectivity (FC) decreased, while FC between peri-lesional and domain-specific networks in both hemispheres and peri-lesional and MDN increased with greater damage to core language clusters. Next, we used mediation analysis to determine if lesion load to a critical functional cluster mediated the relationship between FC-behaviour. The relationship between FC and phonology performance remained unchanged after including lesion load to a phonology ROI, whereas FC and fluency were significantly mediated by lesion load to a fluency ROI. Lastly, we built prediction models using lesion size, lesion load, functional connectivity, and combinations of these (plus interactions) to predict behavioural outcome. We were able to predict phonology and fluency but failed to predict semantics and executive cognition and adding functional connectivity improved performance for phonology only. Together, we demonstrated demand-dependent reorganisation within/between multiple language-relevant networks that individually relate to language dimensions.
Topic Areas: Disorders: Acquired, Methods