Joint representation of working memory and uncertainty in human cortex.
Hsin-Hung Li1, Thomas C Sprague2, Aspen H Yoo1
1Department of Psychology, New York University, New York, NY 10003, USA.
Neuron
|September 15, 2021
Summary
The brain represents visual working memory (VWM) content and uncertainty using probability distributions. This probabilistic neural code allows for simultaneous representation of memory details and associated confidence levels.
Area of Science:
- Cognitive Neuroscience
- Neuroimaging
- Computational Neuroscience
Background:
- Neural representations in visual working memory (VWM) are inherently noisy, leading to decision uncertainty.
- Mechanisms for simultaneously encoding memory content and uncertainty are not well understood.
Purpose of the Study:
- To test the hypothesis that the brain uses probability distributions to represent VWM content and uncertainty.
- To investigate if probabilistic population codes explain how the brain handles memory uncertainty.
Main Methods:
- Utilized functional magnetic resonance imaging (fMRI) to capture brain activity patterns.
- Developed a neural generative model to decode probability distributions from fMRI data.
- Analyzed activation patterns in retinotopic cortical areas and mid-dorsal stream regions.
Main Results:
- The mean of decoded probability distributions from retinotopic areas predicted memory reports.
- The spread of probability distributions in mid-dorsal stream areas correlated with subjective uncertainty.
- Evidence suggests joint representation of VWM content and uncertainty.
Conclusions:
- The human brain employs probabilistic neural codes to represent both the content and uncertainty of visual working memory.
- Findings support the theory of probabilistic population codes in explaining VWM mechanisms.
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