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Published on: June 13, 2017
Basic mathematical rules are encoded by primate prefrontal cortex neurons.
Sylvia Bongard1, Andreas Nieder
1Animal Physiology, Institute of Neurobiology, University of Tübingen, 72076 Tübingen, Germany.
Summary
Scientists discovered that individual neurons in the prefrontal cortex (PFC) can represent abstract mathematical rules. This finding sheds light on how the brain processes numerical information and supports neural network models of cognition.
Area of Science:
- Neuroscience
- Cognitive Science
- Mathematics
Background:
- Mathematical principles involve abstract rules for numerical information processing.
- The neural basis for representing abstract mathematical rules in single neurons remains largely unknown.
Purpose of the Study:
- To investigate if single neurons in the prefrontal cortex (PFC) can represent abstract mathematical rules.
- To explore how the brain flexibly switches between different numerical rules.
Main Methods:
- Recorded activity of individual prefrontal cortex (PFC) neurons in rhesus monkeys.
- Monkeys performed tasks requiring flexible switching between 'greater than' and 'less than' rules with varying numerical quantities.
- Assessed generalization to novel set sizes to confirm abstract rule learning.
Main Results:
- The majority of recorded PFC neuronal activity reflected the abstract mathematical rules, not just sensory or memory information.
- Monkeys demonstrated abstract learning and generalized to previously unseen numerical quantities.
- Single PFC neurons showed capacity for flexible operations on abstract numerical quantities.
Conclusions:
- Single PFC neurons can represent abstract mathematical rules and operations.
- Findings support neural network models with 'rule-coding' units for information flow.
- These neuronal circuits may have evolved for syntactic processing in formalized mathematical systems.
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