Neuroplasticity in Aphasia: A Proposed Framework of Language Recovery

Abstract

Purpose Despite a tremendous amount of research in this topic, the precise neural mechanisms underlying language recovery remain unclear. Much of the evidence suggests that activation of remaining left-hemisphere tissue, including perilesional areas, is linked to the best treatment outcomes, yet recruitment of the right hemisphere for various language tasks has also been linked to favorable behavioral outcomes. In this review article, we propose a framework of language recovery that incorporates a network-based view of the brain regions involved in recovery. Method We review evidence from the extant literature and work from our own laboratory to identify findings consistent with our proposed framework and identify gaps in our current knowledge. Results Expanding on Heiss and Thiel's (2006) hierarchy of language recovery, we identify 4 emerging themes: (a) Several bilateral regions constitute a network engaged in language recovery; (b) spared left-hemisphere regions are important components of the network engaged in language recovery; (c) as damage increases in the left hemisphere, activation expands to the right hemisphere and domain-general regions; and (d) patients with efficient, control-like network topology show greater improvement than patients with abnormal topology. We propose a mechanistic model of language recovery that accounts for individual differences in behavior, network topology, and treatment responsiveness. Conclusion Continued work in this topic will lead us to a better understanding of the mechanisms underlying language recovery, biomarkers that influence recovery, and, consequently, more personalized treatment options for individual patients. Presentation Video https://doi.org/10.23641/asha.10257590.

Figure 1.

Temporal course of neural reorganization in aphasia; data from Hillis and Heidler (2002) and Saur et al. (2006). The x-axis denotes time poststroke. The y-axes reflect degree of brain activation during language tasks (left) and percentage of recovery from aphasia (right). RH = right hemisphere; LH = left hemisphere.

Figure 2.

Brain regions associated with language processing, picture naming and/or semantic processing in patients with aphasia, as indicated by selected functional neuroimaging studies. ACC = anterior cingulate cortex; AG = angular gyrus; IFG = inferior frontal gyrus; INS = insula; IOG = inferior occipital gyrus; IPL = inferior parietal lobule; ITG = inferior temporal gyrus; medFG = medial frontal gyrus; MFG = middle frontal gyrus; MTG = middle temporal gyrus; PCC = posterior cingulate cortex; PCG = precentral gyrus; PCUN = precuneus; pSTS = posterior superior temporal sulcus; SFG = superior frontal gyrus; SMA = supplementary motor area; SMG = supramarginal gyrus; SPL = superior parietal lobule; STG = superior temporal gyrus; TP = temporal pole; T = treatment study.

Figure 3.

Steps involved in the analysis of graph theoretical data. ROIs = regions of interest; PWA = patients with aphasia; CSF = cerebrospinal fluid. The images in this figure were generated using MRICron (Rorden & Brett, 2000), the CONN toolbox (Whitfield-Gabrieli & Nieto-Castanon, 2012), and BRAPH (Mijalkov, Kakaei, Pereira, Westman, & Volpe, 2017).

Figure 4.

Proposed model of network connectivity, language functions, and treatment in patients with aphasia from onset through chronic recovery. Line trajectories reflect connectivity/network properties; line colors reflect severity of language deficits. Normal/optimal (i.e., healthy control) levels of connectivity and language function are represented by a dashed green line at the top of the figure. In the acute stage poststroke, behavioral deficits coincide with abnormal functional connectivity (FC) and network topology (i.e., the network becomes unlike that of healthy controls, as indicated by the descending line in the acute stage). In the following months, gradual restoration of connectivity and network topology coincide with a degree of behavioral recovery (as indicated by the ascending red-to-yellow line in the subacute stage). However, when patients reach the chronic stage (i.e., 6–12 months postonset), abnormal connectivity and network topology persist. When treatment is administered, patients whose network properties are already higher (and, per our recent preliminary work, more like those of healthy controls) have a favorable behavioral response and further network normalization (as indicated by the ascending yellow-to-blue line). Those whose networks were more abnormal at the start of treatment have poorer behavioral outcomes and less substantial changes in network measures (as indicated by the orange line). Critically, likely responders can be distinguished from likely nonresponders prior to treatment due to differences in network properties; that is, pretreatment network differences (indicated by the black two-way arrow) are potentially meaningful predictors of treatment outcome and may be representative of different patterns of neural reorganization from the acute through chronic stages of recovery.