The E%-WTA model lets neural assembly sizes emerge from network dynamics via percentage-based selection and E/I inhibition, yielding higher stimulus recovery rates than the original Assembly Calculus k-WTA model.
A second func- tion of gamma frequency oscillations: An e%-max winner- take-all mechanism selects which cells fire
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Formation of Artificial Neural Assemblies by Biologically Plausible Inhibition Mechanisms
The E%-WTA model lets neural assembly sizes emerge from network dynamics via percentage-based selection and E/I inhibition, yielding higher stimulus recovery rates than the original Assembly Calculus k-WTA model.