Unsupervised Learning Facilitates Neural Coordination Across the Functional Clusters of the C. elegans Connectome

@article{Morales2020UnsupervisedLF,
  title={Unsupervised Learning Facilitates Neural Coordination Across the Functional Clusters of the C. elegans Connectome},
  author={Alejandro Morales and Tom Froese},
  journal={Frontiers in Robotics and AI},
  year={2020},
  volume={7}
}
Modeling of complex adaptive systems has revealed a still poorly understood benefit of unsupervised learning: when neural networks are enabled to form an associative memory of a large set of their own attractor configurations, they begin to reorganize their connectivity in a direction that minimizes the coordination constraints posed by the initial network architecture. This self-optimization process has been replicated in various neural network formalisms, but it is still unclear whether it… 
The distribution of inhibitory neurons in the C. elegans connectome facilitates self-optimization of coordinated neural activity
TLDR
An abstract simulation model of the C. elegans connectome is implemented that approximates the neurotransmitter identity of each neuron, and it is revealed that the biological distribution of inhibitory connections facilitates the self-optimization of coordinated neural activity compared with an arbitrary distribution of inhibitsory connections.

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