Stochastic transition and stochastic resonance as an enhancement technique for biomedicine: Using noise to defeat noise
Prasun Roy (National Brain Research Centre)
(February 5, 2003 2:30 PM - 3:30 AM)
Noise or fluctuations has traditionally been regarded as a nuisance, interfering with the signal or information processing, and so efforts have been made to minimize the noise. The recent discovery of the noise-induced activation or ordering shows that under certain circumstances, noise can in fact dramatically help the performance or processing in systems.. Two of the common types of noise-activated processes are delineated, namely stochastic resonance and stochastic transition (noise-induced transition). Research on this paradoxical phenomenon and its applications has become virtually an paradigm-setter in the mathematics, physics and neuroscience.
We develop an algorithm for analysing perturbation-induced stability-instability properties of systems and such a technique may be used to actuate a noise-induced activation in various biological/clinical systems. Stochastic enhancement in neural, immunological, chemical and radiological processes is shown. We describe the mathematical analysis and experimental findings of such activation in biological/neural processes and elucidate applications towards diagnosis and therapy, in neurology, radiology and oncology, with special applications for management to brain lesions. The associated phenomenon of non-equilibrial de-stabilization of a pathological system under artificially engineered perturbation, is analysed in terms of Prigogine-Glansdorff Stability Theorem and we explore a computational model of fluctuational transitions in complex systems in general.
- Belair, J, Glass, L, Heiden, U, Milton, J, (1997). Dynamical Disease: Mathematical analysis of human illness, American Institute of Physics, New York.
- Collins, J, Gregg, P. (1997). Noise-mediated enhancements and decrements in human sensation, Phys Rev E, 56, 923-26.
- Glass, L. (2002). Synchronization and rhythmic processes in physiology, Nature, 410, 277-84.
- Horsthemke, W., Lefever, R (1994). Noise induced transitions in physics and biology, Springer, Berlin-N.Y.
- Hahn, H, et al (1974). Threshold excitations and effect of noise in an enzyme system, PNAS, 71, 4067-71.
- Miller, J & Levin, R,. Stochastic resonance in neurone, Nature 380, 165-168, 1996.
- Paulsson, J, Berg, O, Ehrenberg, M. (2000). Stochastic Focussing: Fluctuation-enhanced sensitivity in cellular regulation, PNAS. 97(13), 7148-53.
- Roy, P, Kozma, R, et al (2002). >From Neurocomputation to Immunocomputation: A method and algorithm for fluctuation-induced instability in biological systems, IEEE Trans. Evolutionary Computing, 6(3), 1-14, 2002.
- Roy, P. et al (2000). Tumour Stability Analysis, Kybernetes: Intl J of Systems Science, 29, 896-926.
- Simonotto, E, et al, (1997). Visual perception of stochastic resonance, Phys Rev Lett 78:1186-88.