Information processing in the brain is the most important brain function and it is given by the simultaneous activity of billions of neurons each connected by synaptic contacts with thousands of other neurons. The activity of synapses on a single neuron contribute to the neural code formation (spike sequences) which contribute to the activity of neural networks. Since from the most elementary structures which transfer information in the brain, the synapses, the complexity of the mechanisms supporting their functionality represents a limitation to the complete understanding by using only experimental approaches. The transfer, integration and elaboration of the informationamong these structures require the synergy of experimental, modeling, computational and theoretical approaches, with different levels of complexity, to be fully understood.

The aim of this section is then to publish original papers, reports, reviews and collections of articles reporting results of biologically inspired theoretical and computational models ranging from synaptic transmission to neural network activity. Papers which compare experimental and theoretical results will be particularly welcome. Articles welcome will be (but not restricted to) in the following fields:

• Synaptic modeling
• Synaptic integration and neuronal modeling
• Dendritic synaptic computing
• Single neuron modeling
• Neuronal integration
• Neuronal coding
• Neuronal networks
• Biologically inspired Neuronal modeling in Artificial Intelligence
• Biologically inspired Neuronal networks in Artificial Intelligence
• Theoretical neurosciences

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