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Related Experiment Video

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A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

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Not-so-working Memory: Drift in Functional Magnetic Resonance Imaging Pattern Representations during Maintenance

Phui Cheng Lim¹, Emily J Ward², Timothy J Vickery³

¹University of Nebraska-Lincoln.

Journal of Cognitive Neuroscience

|May 22, 2019

Summary

This summary is machine-generated.

Working memory representations drift over time due to neural noise, leading to errors. This study quantifies this "representational drift" using neuroimaging and links it to recognition task performance.

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Area of Science:

Cognitive Neuroscience
Neuroimaging

Background:

Working memory (WM) is essential for cognition but prone to errors.
Limited fidelity of WM representations, even for single features, remains unexplained.
Neural noise may cause representations to drift rather than simply decay.

Purpose of the Study:

To test the hypothesis that neural representations in working memory drift over time.
To develop and apply a novel neuroimaging-based index of representational drift.
To link representational drift to performance in a working memory recognition task.

Main Methods:

Functional magnetic resonance imaging (fMRI) during a match/nonmatch orientation recognition task.
Development of a pattern-based index to quantify representational drift in brain activity.
Correlation of representational drift with behavioral accuracy in the WM task.

Main Results:

A novel "representational drift" index successfully predicted task performance.
Drift away from the target stimulus increased false nonmatch reports.
Drift toward incorrect stimuli increased false match reports.

Conclusions:

Neural noise contributes to working memory errors by causing representational drift.
Representational drift pushes WM representations toward incorrect configurations, not just random decay.
Neuroimaging can index behaviorally relevant drift in neural representation space.