Multilevel development of cognitive abilities in an artificial neural network
Abstract
Multiple biological mechanisms support the unique ability of the brain to develop complex cognitive abilities. Nevertheless, it remains unclear which mechanisms are necessary and sufficient. We propose a neurocomputational model of the developing brain spanning sensorimotor, cognitive, and conscious levels. The model solves three tasks of increasing complexity: from visual recognition to cognitive manipulation and maintenance of conscious percepts. Results highlight two fundamental mechanisms for the multilevel development of cognitive abilities in biological neural networks: 1) synaptic epigenesis, with Hebbian learning at the local scale and reinforcement learning at the global scale; and 2) self-organized dynamics, through spontaneous activity and balanced excitatory/inhibitory ratio of neurons. We emphasize how these core features of human intelligence could guide future development in artificial intelligence.
- Publication:
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Proceedings of the National Academy of Science
- Pub Date:
- September 2022
- DOI:
- 10.1073/pnas.2201304119
- Bibcode:
- 2022PNAS..11901304V