Can sleep help us unlearn biases and make our memories more positive?
Implicit biases are unconscious stereotypes that influence our judgments and decisions - like assuming a particular gender for a specific job role. But what if we could change these biases?
In this episode, we explore how manipulations of sleep might help reshape our implicit attitudes. We speak with Professor Xiaoqing Hu, a leading researcher in the use of Targeted Memory Reactivation (TMR) during sleep to alter implicit bias and make memories more positive. Xiaoqing shares his journey of applying Implicit Association Tasks (IATs) to sleep research, and how conflict biases, congruent vs. incongruent data, and task design play a role in measuring and modifying bias.
We also dive into the nitty gritty of memory consolidation in sleep — examining how REM and NREM stages contribute to emotional memory consolidation, and how recency vs. saliency affects which memories get updated.
Prof. Hu discusses his groundbreaking study demonstrating the ability to update unwanted emotional memories during sleep, and we explore the potential for applying this research to clinical populations. We also consider how individual schemas might influence the effectiveness of TMR across different people.
If you would like to find out more about Prof. Hu's work, please see the lab website here. You can find relevant papers below:
Glossary
IAT - Implicit Association Task - a test used to measure the strength of automatic associations between our concepts that we may not be consciously aware of.
TMR - Targeted Memory Reactivation - A technique used to modify memory processing, through the use of presenting cues (audio or smell) that were associated with learning, whilst a person sleeps. These cues can modify select memories and in recent research is being used in emotional memory.
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Host Professor Penny Lewis
Produced by Sophie Smith
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