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Stages of lexical impairments inform efficacy of transcranial magnetic stimulation on sustained aphasia treatment outcomes
Poster Session B, Friday, October 25, 10:00 - 11:30 am, Great Hall 3 and 4
Haley C Dresang1, Denise Y Harvey2, Leslie Vnenchak2, Peter Twigg2, Sam Cason2, Adelyn Brecher3, Lynn M Maher4, Roy H Hamilton2, H Branch Coslett2; 1University of Wisconsin-Madison, 2University of Pennsylvania, 3Moss Research Rehabilitation Institute, 4University of Houston
Introduction- A growing body of evidence has shown that transcranial magnetic stimulation (TMS) can enhance naming abilities in post-stroke aphasia. However, there is substantial variability in the efficacy of TMS, and it remains unclear which individuals are good candidates for TMS treatment approaches (Martin et al., 2009). One factor that may contribute to TMS treatment efficacy is the locus of aphasia impairment (Harvey et al., 2019). Computational models of word retrieval account for deficits occurring at two stages: the translation of meaning to word form (i.e., semantics), and the translation of the word to its sound form (i.e., phonology; Dell et al., 1997). This study investigated how semantic and phonological characteristics of baseline naming impairments may inform the efficacy of TMS on long-term naming improvements following language treatment in individuals with chronic aphasia. Methods- Thirty participants with aphasia underwent ten sessions of inhibitory TMS to right pars triangularis (rPTr) preceding modified constraint-induced language treatment. Nineteen participants were randomly assigned to active TMS and eleven were assigned to sham TMS. Participants completed the Philadelphia Naming Test (PNT; Roach et al., 1996) at baseline and at three- and six-months post-treatment. We coded PNT errors following established guidelines (Schwartz et al., 2006) and used the SP computational model (Foygel & Dell, 2000) to derive semantic and phonological parameters (i.e., s- and p-weights). We conducted two linear regression models, one for each parameter weight. The outcome measure was the proportional improvement in naming, calculated as pre-to-post treatment changes divided by the potential improvement from baseline. Fixed effects included two interactions: TMS x timepoint; TMS x parameter weight. Results- We found greater proportional naming improvements overall following both active (M=0.09, SD=0.28) and sham TMS (M=0.04, SD=0.30). Both models had significant main effects of TMS, such that active TMS was associated with greater naming improvements than sham. The s-weight model revealed significant interactions between TMS and time (χ2(1)= 5.78, p < 0.001), as well as between TMS and baseline s-weight (χ2(1)= 32.26, p < 0.001). The p-weight model also revealed significant interactions between TMS and time (χ2(1)= 6.13, p < 0.001), as well as between TMS and baseline p-weight (χ2(1)= 0.75, p= 0.003). Post-hoc analyses showed that individuals with greater s-weight showed greater naming improvement following active TMS than sham (β= 12.43, SE= 0.62, t= 20.06, p < 0.001), and improvements were greater at 6-months compared to 3-months for active TMS, while sham showed no difference across time (β= 0.10, SE= 0.01, t= 8.49, p < 0.001). In contrast, individuals with greater p-weight who received active TMS compared to sham showed greater naming improvement (β= 3.97, SE= 1.33, t= 2.99, p= 0.003) but only at 6-months post-treatment (β= 0.11, SE= 0.01, t= 8.54, p < 0.001). Conclusions- This study is among the first in a larger sample to demonstrate that baseline linguistic characteristics of individual aphasia patients contribute to variability in sustained TMS and aphasia treatment outcomes. These findings may have implications for clinical decision making as well as mechanistic accounts of brain stimulation for neurorehabilitation.
Topic Areas: Speech-Language Treatment, Disorders: Acquired