Predicting treatment outcomes for bilinguals with aphasia using computational modeling: Study protocol for the PROCoM...

Area of Science:

• Neuroscience
• Computational Linguistics
• Speech-Language Pathology

Background:

• Bilinguals with aphasia (BWA) exhibit variable language impairment and recovery.
• Identifying the optimal language for therapy is crucial for effective rehabilitation.
• The BiLex model accurately simulates bilingual lexical access and treatment response.

Purpose of the Study:

• To evaluate the BiLex model's ability to predict treatment outcomes in BWA.
• To compare treatment effectiveness in the model-recommended language versus the non-recommended language.
• To determine the optimal target language for aphasia rehabilitation in bilingual individuals.

Main Methods:

• A prospective, double-blind, randomized controlled trial with 48 Spanish-English BWA.
• 20 sessions of semantic treatment targeting lexical retrieval in one language.
• Assessment of treatment outcomes in both languages pre- and post-therapy.
• Statistical analysis using mixed-effect models and ANOVA to compare treatment effects.

Main Results:

• The BiLex model's predictions for treatment outcomes in treated and untreated languages will be analyzed.
• Treatment effects (effect size, percentage change) will be compared between the experimental and control groups.
• The study will determine if the model-recommended language yields superior outcomes.

Conclusions:

• The BiLex model shows promise in predicting optimal language treatment for BWA.
• Findings will inform clinical decisions regarding language selection for aphasia therapy.
• This research contributes to understanding bilingual language processing and recovery after brain injury.