Sequence learning on motor and non-motor tasks in people who stutter

Abstract

The purpose of this study was to investigate the differences in sequence learning in people who stutter (PWS) and people who are typically fluent (PWTF) using both implicit and explicit sequence learning paradigms while controlling for motor performance. Persistent developmental stuttering (PDS) is a complex neurodevelopmental disorder that impacts 1% of the adult population. It is characterized by the presence of involuntary, audible, or silent prolongations or syllable repetitions most often at the beginning of a word. PWS are thought to have underlying neural differences that impact motor skill learning with further influence on motor sequence learning. In this study, we employed sequence-based learning paradigms to determine the impact of motor output demands on implicit and explicit sequence learning. A total of 28 participants (PWTF = 19; PWS = 9) were recruited for this study. Participants completed a serial reaction time task (SRTT) which measured their ability to learn a 10-item sequence with manual motoroutput in both implicit and explicit contexts in which the presence of a sequence was either concealed or disclosed, respectively. Participants also engaged in a visual statistical learning (VSL) task to measure implicit sequence learning when motor output was not required. Our hypothesis was largely influenced by differences in striatal learning mechanisms in PWS. We hypothesized that PWS would demonstrate less motor learning on implicit tasks when compared to PWTF while no significant differences would be expected on explicit tasks. Second, we hypothesized no significant differences in performance on the non-motor implicit tasks between PWS and PWTF indicating that when motor demands are not a factor, learning is the same. In brief, statistical analysis of our current data set found no significant group differences across all three tasks. Further investigation is necessary to explore the impact of manual motor output on sequence learning using explicit and implicit paradigms.