V. D. Tsukerman, O. V. Karimova, S. V. Kulakov, А. А. Sazykin

The spatial behavior of higher organisms and their navigation capabilities are controlled by the distributed control system. The most important component of that system is the entorhinal-hippocampal brain system. Last discoveries of specializing cells («grid cells», «place cells», «head direction cells») in this system grow up the numerous of theoretical and experimental studies. The wide interest to biological navigation problems closely related with the application aims as well as with an attempts to solve basic cognitive tasks such as episodic memory, encoding and memorizing of navigation pathways and many others. The conceptual model and computer simulations results of trajectory integration of space moving in free-scalable nonlinear oscillator neural networks with even cyclic inhibition (ECI-networks) are discussed in this paper. To estimate the phase shifting under input impact the ECI-networks contain two subsystems namely reference and information ones. The population of reference (nonencoding) oscillatory units has significant role in generation and stabilization of numerous time scales despite it don-t assist directly in the phase pattern encoding of input signals. In addition it serves to set up the basic theta rhythm. In these networks the relative phase of information units is determined and stabilized by the attractor dynamics that results in the formation of phase pattern of the encoded messages. Nonspecific input of network (common input for information units) mediately defines the linear velocity of spatial movement of the virtual object and particular inputs of information units define their angular velocity. Each layer (contour) of network information units has unique area of phase representations of high-frequency gamma burst in low-frequency theta-cycles i.e. it is shifted relatively to neighboring layers. External layer has the most high frequency and internal layers have the least ones because theta-frequency gradient is existed. The phase encoding of signals pattern with different temporal resolution from the maximal in external layer to the minimum in internal one is realized in ECI-network. Inside a single theta-cycle, the relative phase shift of information units reproduces ahead sequence of position on the trajectory of spatial movements, and the greater temporal shifts correspond to longer distances. The formation of a variety for steady-stated responses due to recurrent interactions in the network and shift mechanism that is guided by velocity inputs, arise the basis of the trajectory integration system. It was shown by computer modeling that network interactions architecture is one of the determining factors of inner (subjective) presentations of environment space. It determines dynamic formation of self-organized neural ensembles of different levels namely from phase cluster to oscillatory hyper-ensemble. Multifunctionality is the main characteristics of ensemble encoding of environment space because the same ensembles can encode (to present coherently) different events of environment space. It was experimentally shown that the high-precision frequency-phase mechanism in the frameworks of ensemble hypothesis can be used in navigation behavior.