Statistical Learning in Aphasia: Preliminary Results from an Artificial Grammar Learning Task

Abstract

Statistical learning, i.e., the discovery of structure based on statistical properties of stimuli, is considered an implicit process that plays an important role in nonlinguistic and linguistic tasks, including speech segmentation and grammar learning (Aslin & Newport, 2012; Saffran, 2002; Saffran et al., 1996). Moreover, individual differences in statistical learning ability have been shown to be associated with natural language processing (Misyak & Christiansen, 2012; Misyak et al., 2010). Yet little is known about this type of learning in individuals with aphasia, who must relearn linguistic skills after brain damage. To date, studies of implicit learning processes in aphasia have provided mixed results, including evidence of limited or absent implicit learning for a visual artificial grammar (Christiansen et al., 2010; Zimmerer et al., 2014), as well as evidence of relatively intact implicit learning in Serial Reaction Time tasks (Goschke et al., 2001; Schuchard & Thompson, 2013). The purpose of the present study was to test statistical learning and overnight consolidation of an artificial phrase structure grammar under implicit conditions in individuals with agrammatic aphasia and healthy age-matched adults