Stochastic biomathematical models : with applications to neuronal modeling / Mostafa Bachar, Jerry Batzel, Susanne Ditlevsen, editors

Auteur secondaire : Bachar, Mostafa, Editeur scientifique • Batzel, Jerry, Editeur scientifique • Ditlevsen, Susanne, Editeur scientifiqueType de document : CongrèsCollection : Lecture notes in mathematics, 2058Langue : anglais.Pays: Allemagne.Éditeur : Berlin : Springer, cop. 2013Description : (1 vol. XVI-206 p.) : fig. ; 24 cmISBN: 9783642321566.ISSN: 0075-8434.Bibliographie : Bibliogr. en fin de contributions. Index.Sujet MSC : 92-06, Proceedings, conferences, collections, etc. pertaining to biology
92B05, Mathematical biology in general, General biology and biomathematics
92C20, Biology and other natural sciences, Physiological, cellular and medical topics, Neural biology
60J70, Probability theory and stochastic processes - Markov processes, Applications of Brownian motions and diffusion theory
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Item type Current library Call number Status Date due Barcode
 Congrès Congrès CMI
Salle 2
92-06 BAC (Browse shelf(Opens below)) Available 12188-01

Bibliogr. en fin de contributions. Index

Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and its
application in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression. (Source : Springer)

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