Vladyslav V. Shaposhnyk

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We present a framework for modelling and analyzing emerging neural activity from multiple interconnected modules, where each module is formed by a neural network. The neural network simulator operates a 2D lattice tissue of leaky integrate-and-fire neurons with genetic, ontogenetic and epigenetic features. The Java Agent DEvelopment (JADE) environment(More)
Complex neural modules with embedded neural development and synaptic plasticity features have been connected to form a hierarchical recurrent circuit. Virtual electrodes have been used to record a “neural” generated signal, called electrochipogram EChG, from each module. The EChG are processed by frequency domain methods to determine the modifications in(More)
Modular architecture is a hallmark of many brain circuits. Particularly, in the cerebral cortex it has been observed that reciprocal connections are often present between functionally interconnected areas that are hierarchically organized. Evolutionary development is another distinctive characteristic of living species, even the simplest viruses are capable(More)
Modular architecture is a hallmark of many brain circuits. In the cerebral cortex, in particular, it has been observed that reciprocal connections are often present between functionally interconnected areas that are hierarchically organized. We investigate the effect of reciprocal connections in a network of modules of simulated spiking neurons. The neural(More)
The robust regression analysis works on data affected by deviations from a general assumption of normality. Currently the field of robust linear regression analysis is well developed and there are number of stable and verified by time methods. In contrast the robust structural modeling and high-order model parameter estimation are still under active(More)
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