V.V. Kolushov - Ph.D. (Eng.), Associate Professor, Department of «Нigher Mathematics», Ufa State Aviation Technical University (Ufa). E-mail: KVV@ufanet.ru A.V. Savelyev - Senior Research Scientist, Director of the Patent Agency «©Uniquely Honest Patenting» (Moscow). E-mail: gmkristo@rambler.ru

The analysis of the known methods of computer visualization and author bio-visualization results of designing algorithms qasi-visualization of mechanical behavior of biological tissue in view of its functional activity are presented. This allows you to play computer effects of animated images of real biological tissue \"revival\". In the neuroimaging field with the 1970s the considerable progress was made, with as the result today several basic neural-visualization methods are based on different physical principles are known and used [1]. However, it can be classified into two groups - the structural and functional neuroimaging, which usually exist separately and do not intersect. Our work is based on the conceptual approach that the problem of the structure and function solves by the dualism - with their combination by information technology. Dynamics of functional activity is not superimposed on a morphological static object, as in parallel in the same time slots is superimposed on playing dynamics of its forms variation [2]. We indicate this as the double overlay. On fig. 1 the EPSP visible transformation, deformation neuron in electrogenesis and antidromic return on the background of the refractory period. It-s received introduction of therapeutic practice in A.N. Bakulev-s CCHVS RAMS, in particular for the morpho-functional diagnostics of the spatial position of the sources of arrhythmia in myocardial tissue [3]. The methods were has developed and applied by the authors in the algorithms of the principle of superposition, allows to create effects of the \"revival\" of an individual cells, cells association to the department or area of the brain to detect the real neural physiological event and recreate a picture of the functioning of living tissue. This work was financially supported by RHSF in grant № 15-03-00519а «Post-non-classic paradigm of artificial intellect».

 

1. Lowe T. Improving image clarity using local feature dimension // IET Image Processing. 10 March 2015. DOI: 10.1049/iet-ipr.2014.0642.http://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2014.0642
2. Blue Brain Project Brain Waves Simulation.https://www.youtube.com/watch-v=2qTuZlMvFgY
3. Kajiya J.T., Kay T.L. Rendering fur with three dimensional textures // ACM Siggraph Computer Graphics. 1989. V. 23. № 3. P. 271-280.
4. Kolushov V.V., Savelev A.V. Spajjk-kollektivnoe nejjrokompjuternoe vizualizacionnoe konstruirovanie sverkhslozhnykh nejjronnykh sistem nejjrobiologii // Nejjrokompjutery: razrabotka, primenenie. 2013. № 8. S. 60-65. http://www.radiotec.ru/catalog.php-cat=jr7&art=13249