Abstract
Abstract Recent neuroscience research provides evidence on how decision making systems can be implemented in cortical networks of human brains. In this paper we investigate the possibility of developing a biophysically-realistic decision making model based on the asynchronous recurrent network with attractors and binary neurons. Success of our approach suggests that decision making is a network phenomenon and biologically plausible performance of the model does not rely on neuron activation dynamics of the leaky integrate-and-fire neurons. Results presented here provide supplementary evidence that the postulates formulated by recent empirical research are indeed essential for the implementation of decision making system into neuronal networks.
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