HIGHLIGHTS
SUMMARY
Since the connectome of the nematode C. elegans was obtained using electron microscopy methods in Bayesian reconstruction of memories stored in neural_networks from their connectivity 1986, methods for data acquisition and analysis have both been scaled up and improved significantly. The authors focus on local neural_networks that store information in their synaptic connectivity. A popular model for these networks are attractor neural_networks such as the Hopfield model and various generalisations, in which memories are stored as attractor states of the dynamics. One natural question to ask is then: given the knowledge of the synaptic . . .
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