Abstract
Originary neurogenic, non-syndromatic stuttering has been linked to a dysfunctional sensorimotor system. Studies have demonstrated that adults who stutter (AWS) perform poorly at speech and finger motor tasks and learning (e.g., Smits-Bandstra et al., 2006b; Namasivayam and van Lieshout, 2008). The high relapse rate after stuttering treatment could be a further hint for deficient motor learning and, in particular, for the limited generalization of the learned technique in daily communication. In this study, we tested generalization of finger sequence skills in AWS using an effector-dependent transfer task after a 24-h retention period. Additionally, we wanted to corroborate previous motor learning results in AWS for practice and retention: 16 AWS and 16 age-, sex-, and education-matched controls performed the task during four test sessions. Our results indicate that generalization performance in AWS was not inferior to that of fluent controls. In addition, we found, contrary to previous results, that AWS showed a steeper learning progress after practice and consolidation compared with controls. We suggest that with sufficient practice and a 24-h consolidation phase, AWS are able to retain the learned performance of tapping a five-item finger sequence as well as fluent controls in terms of speed and accuracy.
Highlights
Originary neurogenic, non-syndromic stuttering is a speech fluency disorder characterized by involuntary speech fluency disruptions (Neumann et al, 2016)
The finger tapping task that we used in the current study might reveal general limitations in motor sequence learning in adults who stutter (AWS) (Bauerly and De Nil, 2015)
One AWS and one ANS did not perform the effector-dependent Transfer task but applied an extrinsic, effector-independent transformation by typing 14231 instead of 41324. Another AWS typed all sequences during the first Transfer block as 41234 instead of 41324
Summary
Non-syndromic stuttering is a speech fluency disorder characterized by involuntary speech fluency disruptions (Neumann et al, 2016). The finger tapping transfer task was conducted on the same day as the original motor sequence task and consisted of a new sequence For both modalities, speech and finger tapping, ANS transferred the improvements in reaction time of the practiced movements faster than AWS (Smits-Bandstra et al, 2006b). Speech and finger tapping, ANS transferred the improvements in reaction time of the practiced movements faster than AWS (Smits-Bandstra et al, 2006b) These results suggest that AWS might have difficulties in speech as well as non-speech motor sequence learning. The finger tapping task that we used in the current study might reveal general limitations in motor sequence learning in AWS (Bauerly and De Nil, 2015). With an additional analysis of error type, we expect (3) that AWS will show more TE within a sequence, indicating greater variability of sequence execution than ANS (Albouy et al, 2012)
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