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Research Articles

An electrophysiological and behavioral investigation of feedback-based learning in aphasia

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Pages 1195-1221 | Received 29 Mar 2023, Accepted 02 Oct 2023, Published online: 22 Oct 2023
 

ABSTRACT

Introduction

Feedback is a fundamental aspect of aphasia treatments. However, learning from feedback is a cognitively demanding process. At the most basic level, individuals must detect feedback and extract outcome-related information (i.e., feedback processing). Neuroanatomical and neuropsychological differences associated with post-stroke aphasia may influence feedback processing and potentially how people with aphasia (PWA) respond to feedback-based treatments. To better understand how post-stroke aphasia affects feedback-based learning, the current study leverages event-related potentials (ERPs) to (1) characterize the relationship between feedback processing and learning, (2) identify cognitive skills that are associated with feedback processing, and (3) identify behavioural correlates of feedback-based learning in PWA.

Methods

Seventeen PWA completed a feedback-based novel word learning task. Feedback processing was measured using the feedback-related negativity (FRN), an ERP hypothesized to reflect the detection and evaluation of outcomes communicated via feedback. Individuals also completed neuropsychological assessments of language (phonological processing, verbal short-term memory) and executive functioning.

Results

PWA elicited an FRN that was sensitive to feedback valence. The magnitude of the FRN was not associated with novel word learning but was strongly correlated with performance on another feedback-based task, the Berg Card Sort. Cognitive variables (information updating, selective attention) but not language variables were associated with novel word learning.

Discussion & Conclusion

For PWA, feedback processing may be associated with learning in some but not all feedback-based contexts. These findings may inform future research in determining which variables moderate the relationship between feedback processing and learning with the long-term goal of identifying how feedback can be modified to support successful learning during aphasia rehabilitation.

Acknowledgments

Thank you, Asiya Gul, for your support with EEG data processing; Kesi Cania, for assistance with behavioural data processing and double scoring; and Victoria Tilton-Bolowsky for your feedback on this manuscript. Thank you to the individuals with aphasia who participated in this research.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Declaration of interest statement

The authors have no relevant financial or nonfinancial conflicts of interest to disclose.

Notes

1 To verify that this participant did not have a response preference, we calculated the percent of responses that were for the target on the left and the right. The participant chose the item on the left 48% of the time and the item on the right 52% of the time indicating no response bias secondary to a history of visual inattention.

2 To ensure that latency correction did not impact findings, analyses were run with both the latency and non-latency corrected data. Significant findings were the same across data sets. Latency corrected data is presented here for visual clarity of figures.

Additional information

Funding

This work was supported by the National Institute on Deafness and Other Communication Disorders of the National Institute of Health awarded to Sofia Vallila-Rohter [R21 DC019203] and Yael Arbel [R15 DC016438]. A portion of Kristen Nunn’s time was also supported by the Department of Veterans Affairs Office of Academic Affiliations, Advanced Fellowship in Geriatrics of the Veterans Affairs Pittsburgh Health Care System and the Department of Veterans Affairs Pittsburgh Geriatric Research, Education, and Clinical Center (GRECC). The content is solely the responsibility of the authors and does not represent the views of the National Institute of Health, VA, or United States Government.

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