The computational resources of a neuromorphic network model introduced earlier were investigated in the first paper of this series. It was argued that a form of ubiquitous spontaneous local convolution enabled logical gate-like neural motifs to form into hierarchical feed-forward structures of the Hubel-Wiesel type. Here we investigate concomitant data-like structures and their dynamic rôle in memory formation, retrieval, and replay.
View Article and Find Full Text PDFJ Comput Neurosci
February 2024
The computational resources of a neuromorphic network model introduced earlier are investigated in the context of such hierarchical systems as the mammalian visual cortex. It is argued that a form of ubiquitous spontaneous local convolution, driven by spontaneously arising wave-like activity-which itself promotes local Hebbian modulation-enables logical gate-like neural motifs to form into hierarchical feed-forward structures of the Hubel-Wiesel type. Extra-synaptic effects are shown to play a significant rôle in these processes.
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