Compensatory and Serial Processing Models for Relating Electrophysiology, Speech Understanding, and Cognition

用于关联电生理、语音理解和认知的补偿和串行处理模型

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Abstract

OBJECTIVES: The objective of this study was to develop a framework for investigating the roles of neural coding and cognition in speech perception. DESIGN: N1 and P3 auditory evoked potentials, QuickSIN speech understanding scores, and the Digit Symbol Coding cognitive test results were used to test the accuracy of either a compensatory processing model or serial processing model. RESULTS: The current dataset demonstrated that neither the compensatory nor the serial processing model were well supported. An additive processing model may best represent the relationships in these data. CONCLUSIONS: With the outcome measures used in this study, it is apparent that an additive processing model, where exogenous neural coding and higher order cognition contribute independently, best describes the effects of neural coding and cognition on speech perception. Further testing with additional outcome measures and a larger number of subjects is needed to confirm and further clarify the relationships between these processing domains.

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