Multiscale Analysis and Nonlinear Dynamics: From Genes to the BrainMisha Meyer Pesenson John Wiley & Sons, 13.09.2013 - 328 Seiten Since modeling multiscale phenomena in systems biology and neuroscience is a highly interdisciplinary task, the editor of the book invited experts in bio-engineering, chemistry, cardiology, neuroscience, computer science, and applied mathematics, to provide their perspectives. Each chapter is a window into the current state of the art in the areas of research discussed and the book is intended for advanced researchers interested in recent developments in these fields. While multiscale analysis is the major integrating theme of the book, its subtitle does not call for bridging the scales from genes to behavior, but rather stresses the unifying perspective offered by the concepts referred to in the title. It is believed that the interdisciplinary approach adopted here will be beneficial for all the above mentioned fields. |
Inhalt
Modeling Across ScalesDiscrete Geometric | |
2Model 10 3 Results | |
Structures in Homogenization and Inverse Homogenization | |
Synthetic Biochemical Dynamic Circuits | |
Nonlinear Dynamics the Brain | |
Adaptive | |
Computational Functionof Neuronal Synchronization 11 1 Introduction 11 2 SomeBasic | |
Chapter | |
Neuronal | |
Linking NonlinearNeural DynamicstoSingle Trial Human Behavior | |
MultiscaleNonlinear | |
Multiresolution Riemannian Manifolds Analysis on Compact | |
Nonlinear Dynamics Genelets | |
Andere Ausgaben - Alle anzeigen
Multiscale Analysis and Nonlinear Dynamics: From Genes to the Brain Misha Meyer Pesenson Keine Leseprobe verfügbar - 2013 |
Häufige Begriffe und Wortgruppen
Acad action potential activity analysis approximation axons bandlimited behavior Biol boundary brain dynamics brain networks Bullmore canbe cerebral cortex chemical systems circuits cognitive complex Comput conductivity convex convex functions correlations cortex cortical coupling defined Delaunay triangulation discrete divergencefree electrical impedance tomography electroencephalography equation example experimental feedback Figure fMRI frequency functional connectivity gamma genelet global harmonic coordinates homogenization human brain input interactions interpolation inthe inverse isotropic largescale linear manifolds mathematical matrix mechanism methods modularity modules molecular multiple multiresolution multiresolution analysis multiscale Natl neocortex neocortical neural Neuroimage neuronal Neurosci nodes nonlinear observed ofthe operator optimization organization oscillations oscillatory parameterization parameters phase Phys potentials problem Proc processes properties receptive fields Riemannian manifolds scales signal simulations smallworld SMNI solution space spatial specific spike trains stochastic structure switch synaptic synchronization synthetic Systems Biology temporal Theorem topological tothe transcriptional variable vector vitro wavelet waves weighted Delaunay triangulations