arXiv subjects

Fail M. Gafarov

Publications and source records attributed to Fail M. Gafarov.

3 recordsLinked to original sources

arXiv2007

Relaxational Singularities of Human Motor System at Aging Due to Short-Range and Long-Range Time Correlations

In this paper we study the relaxation singularities of human motor system at aging. Our purpose is to examine the structure of force output variability as a function of human aging in the time and frequency domains. For analysis of experimental data we have developed here the statistical theory of relaxation of force output fluctuation with taking into account the effects of two relaxation channels. The first of them contains the contribution of short-range correlation whereas other relaxation component reflects the effect of long-range correlation. The analysis of experimental data shows, that the general behavior of relaxation processes at human aging is determined by a complicated combination and nonlinear interactions two above stated relaxation processes as a whole.

physics.data-an↗

arXiv2006

Activity-dependent self-wiring is a basis of structural plastisity in neural networks

Dynamical wiring and rewiring in neural networks are carried out by activity-dependent growth and retraction of axons and dendrites, guided by gudance molecules, released by target cells. Experience-dependent structural changes in cortical microcurcuts lead to changes in activity, i.e. to changes in information encoded. Specific pattens of external stimulation can lead to creation of new synaptical connections between neurons. Calcium influxes controlled by neuronal activity regulates processes of neurotrophic factors release by neurons, growth cones movement and synapse differentiation in developing neural system, therefore activity-dependent self-wiring can serve as a basis of structural plasticity in cortical networks and can be considered as a form of learning.

q-bio.NC↗

arXiv2006

Self-wiring in neural nets of point-like cortical neurons fails to reproduce cytoarchitectural differences

We propose a model for description of activity-dependent evolution and self-wiring between binary neurons. Specifically, this model can be used for investigation of growth of neuronal connectivity in the developing neocortex. By using computational simulations with appropriate training pattern sequences, we show that long-term memory can be encoded in neuronal connectivity and that the external stimulations form part of the functioning neocortical circuit. It is proposed that such binary neuron representations of point-like cortical neurons fail to reproduce cytoarchitectural differences of the neocortical organization, which has implications for inadequacies of compartmental models.

q-bio.NC↗