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Neural knowledge assembly in humans and neural networks.
Stephanie Nelli1, Lukas Braun2, Tsvetomira Dumbalska2
1Department of Cognitive Science, Occidental College, Los Angeles, CA 90041, USA; Department of Experimental Psychology, University of Oxford, Oxford OX2 6GC, UK.
Neuron
|March 10, 2023
Summary
New information can rapidly reshape human understanding by reorganizing neural codes for object relations. This study demonstrates rapid neural manifold rearrangement in the brain and a computational model, enabling flexible knowledge assembly.
Area of Science:
- Cognitive Neuroscience
- Computational Neuroscience
- Machine Learning
Background:
- Human understanding adapts flexibly to new information, a process termed knowledge assembly.
- Existing computational theories lack mechanisms for rapid reorganization of neural codes underlying this flexibility.
Purpose of the Study:
- To investigate the neural mechanisms of rapid knowledge assembly.
- To develop a computational model capable of similar knowledge reorganization.
Main Methods:
- Participants learned object orderings in distinct contexts, followed by new linking information.
- Blood-oxygen-level-dependent (BOLD) signals were measured during new information exposure.
- Online stochastic gradient descent was adapted for a neural network model.
Main Results:
- BOLD signals showed rapid and dramatic rearrangement of object representations on the neural manifold.
- The adapted neural network model demonstrated rapid knowledge assembly capabilities.
Conclusions:
- The dorsal frontoparietal cortex plays a key role in rapid knowledge assembly.
- Computational models can replicate the brain's ability to quickly reorganize knowledge representations.
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