A geometric phase transition produces crystalline hippocampal coding in food-caching birds that yields over 100-fold higher location memory capacity than the mist-like coding in non-caching birds.
Neural networks and physical systems with emergent collective computational abilities
2 Pith papers cite this work. Polarity classification is still indexing.
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Self-organising memristive networks exhibit collective nonlinear dynamics that can support physical learning with parallels to biological plasticity and potential for energy-efficient edge intelligence.
citing papers explorer
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Geometric Phase Transition Enables Extreme Hippocampal Memory Capacity
A geometric phase transition produces crystalline hippocampal coding in food-caching birds that yields over 100-fold higher location memory capacity than the mist-like coding in non-caching birds.
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Self-Organising Memristive Networks as Physical Learning Systems
Self-organising memristive networks exhibit collective nonlinear dynamics that can support physical learning with parallels to biological plasticity and potential for energy-efficient edge intelligence.