In this paper, a new model of formal neuron, analog mechanisms of neuron training, and a new model of biological feedback are proposed. The statement is supported by the neurobiological data published by other authors and through our experiments in silicon. Key qualitative and quantitative differences of the proposed neural network model from the concept accepted today are discussed. A new concept reflects the mechanisms of memory formation. The model bridges the gap between the micro-level of the molecular processes in a neuron and the macro-level of information processing and storage in brain. Thus, an opportunity appears of modeling the processes occurring in brain, as well as developing the artificial neural networks, which are trained in a real-time mode, and are not limited in their structure and complexity of connections. The proposed model is easily implemented, both as virtual emulation and by means of digital and analog artificial neural networks.