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008			220426s2022 sz | o |||| 0|eng d
020			_a9783030894399
024	7		_a10.1007/978-3-030-89439-9 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQP376 _b2022 EB
245	0	0	_aComputational Modelling of the Brain : _bModelling Approaches to Cells, Circuits and Networks _cedited by Michele Giugliano, Mario Negrello, Daniele Linaro
250			_a1st edition 2022
264		1	_aCham _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XII, 359 páginas) _b115 ilustraciones, 94 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aCellular Neuroscience Neural Circuits and Systems Neuroscience _x2524-6585 _v1359
505	0		_aPART I. Cellular Scale -- Chapter 1. Modelling Neurons in 3D at the Nanoscale -- Chapter 2. Modelling Dendrites and Spatially-Distributed Neuronal Membrane Properties -- Chapter 3. A User's Guide to Generalized Integrate-and-Fire Models -- Chapter 4. Neuron-glia Interactions and Brain Circuits -- Chapter 5. Short-term Synaptic Plasticity: Microscopic Modelling and (some) Computational Implications -- PART II. Molecular Scale -- Chapter 6. The Mean Field Approach for Populations of Spiking Neurons -- Chapter 7. Multidimensional Dynamical Systems with Noise -- Chapter 8. Computing Extracellular Electric Potentials from Neuronal Simulations -- Chapter 9. Bringing Anatomical Information into Neuronal Network Models -- PART III. Network Scale -- Chapter 10. Computational Concepts for Reconstructing and Simulating Brain Tissue -- Chapter 11. Reconstruction of the Hippocampus -- Chapter 12. Challenges for Place and Grid Cell Models -- Chapter 13. Whole-Brain Modelling: Past, Present, and Future.
520			_aThis volume offers an up-to-date overview of essential concepts and modern approaches to computational modelling, including the use of experimental techniques related to or directly inspired by them. The book introduces, at increasing levels of complexity and with the non-specialist in mind, state-of-the-art topics ranging from single-cell and molecular descriptions to circuits and networks. Four major themes are covered, including subcellular modelling of ion channels and signalling pathways at the molecular level, single-cell modelling at different levels of spatial complexity, network modelling from local microcircuits to large-scale simulations of entire brain areas and practical examples. Each chapter presents a systematic overview of a specific topic and provides the reader with the fundamental tools needed to understand the computational modelling of neural dynamics. This book is aimed at experimenters and graduate students with little or no prior knowledge of modelling who are interested in learning about computational models from the single molecule to the inter-areal communication of brain structures. The book will appeal to computational neuroscientists, engineers, physicists and mathematicians interested in contributing to the field of neuroscience. Chapters 6, 10 and 11 are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. .
988			_aSpringer_BiomedLife_2022
650		7	_2embne _9139532 _aCerebro
650		7	_2embne _9481390 _aNeurociencia computacional
700	1		_aGiugliano, Michele. _eeditor literario
700	1		_aNegrello, Mario. _eeditor literario
700	1		_aLinaro, Daniele. _eeditor literario _0(orcid)0000-0001-8751-0350 _1https://orcid.org/0000-0001-8751-0350
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783030894382
776	0	8	_iPrinted edition: _z9783030894405
776	0	8	_iPrinted edition: _z9783030894412
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-89439-9 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b09/2022 _dz _eb _zSI