1.

Record Nr.

UNISA996466481003316

Titolo

Stochastic Biomathematical Models [[electronic resource] ] : with Applications to Neuronal Modeling / / edited by Mostafa Bachar, Jerry J. Batzel, Susanne Ditlevsen

Pubbl/distr/stampa

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013

ISBN

3-642-32157-7

Edizione

[1st ed. 2013.]

Descrizione fisica

1 online resource (XVI, 206 p. 34 illus., 13 illus. in color.)

Collana

Mathematical Biosciences Subseries, , 2524-6771 ; ; 2058

Disciplina

612.8/1046015118

Soggetti

Probabilities

Mathematical models

StatisticsĀ 

Neurobiology

Probability Theory and Stochastic Processes

Mathematical Modeling and Industrial Mathematics

Statistics for Life Sciences, Medicine, Health Sciences

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

1 Introduction to stochastic models in biology -- 2 One-dimensional homogeneous diffusions -- 3 A brief introduction to large deviations theory -- 4 Some numerical methods for rare events simulation and analysis -- 5 Stochastic Integrate and Fire models: a review on mathematical methods and their applications -- 6 Stochastic partial differential equations in Neurobiology: linear and nonlinear models for spiking neurons -- 7 Deterministic and stochastic FitzHugh-Nagumo systems -- 8 Stochastic modeling of spreading cortical depression.

Sommario/riassunto

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.