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Related Experiment Video

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Brain Imaging Investigation of the Neural Correlates of Emotional Autobiographical Recollection

Brain Imaging Investigation of the Neural Correlates of Emotional Autobiographical Recollection

Published on: August 26, 2011

Interactive alignment: Priming or memory retrieval?

Michael Kaschak¹, Arthur Glenberg

¹Department of Psychology, Florida State University, Tallahassee, FL 32310 kaschak@psy.fsu.edu.

The Behavioral and Brain Sciences

|February 5, 2008

Summary

This study suggests memory retrieval, not automatic priming, better explains how speakers align during conversation. Data supports a memory-based perspective for understanding conversational alignment.

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Area of Science:

Cognitive Psychology
Psycholinguistics
Computational Linguistics

Background:

The interactive alignment model by Pickering & Garrod (2000) posits automatic priming as the mechanism for speaker alignment.
Conversational alignment is crucial for effective communication and shared understanding.
Existing models primarily focus on implicit, automatic processes.

Purpose of the Study:

To propose and evaluate memory retrieval as an alternative mechanism for explaining speaker alignment.
To challenge the primacy of automatic priming in current alignment models.
To provide empirical evidence favoring a memory-based account of alignment.

Main Methods:

Theoretical discussion contrasting priming and memory retrieval mechanisms.
Presentation of empirical data (details not specified in abstract).
Analysis of how memory retrieval can replicate priming effects.

Main Results:

Memory retrieval processes can account for phenomena attributed to automatic priming.
Empirical data presented supports the memory-based view over the priming-based view.
The proposed memory-based model offers a viable alternative to the interactive alignment model.

Conclusions:

Speaker alignment in conversation is better explained by memory retrieval processes.
The automatic priming mechanism may not be the sole or primary driver of alignment.
Future research should explore memory-based models for understanding linguistic interaction.