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020 _z9780123748829
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_bElsevier Science & Technology
_nhttp://www.sciencedirect.com
050 4 _aQP356
_b.G22 2010
060 4 _a2010 J-281
060 4 _aQU 26.5
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082 0 4 _a612.8
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049 _aMAIN
100 1 _aGabbiani, Fabrizio.
_9248965
245 1 0 _aMathematics for neuroscientists /
_cFabrizio Gabbiani, Steven J. Cox.
250 _a1st ed.
260 _aAmsterdam ;
_aBoston :
_bElsevier Academic Press,
_c2010.
300 _a1 online resource (xi, 486 pages) :
_billustrations (some color)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
490 1 _aElsevier science & technology books
520 _aThis book provides a grounded introduction to the fundamental concepts of mathematics, neuroscience and their combined use, thus providing the reader with a springboard to cutting-edge research topics and fostering a tighter integration of mathematics and neuroscience for future generations of students. The book alternates between mathematical chapters, introducing important concepts and numerical methods, and neurobiological chapters, applying these concepts and methods to specific topics. It covers topics ranging from classical cellular biophysics and proceeding up to systems level neuroscience. Starting at an introductory mathematical level, presuming no more than calculus through elementary differential equations, the level will build up as increasingly complex techniques are introduced and combined with earlier ones. Each chapter includes a comprehensive series of exercises with solutions, taken from the set developed by the authors in their course lectures. MATLAB code is included for each computational figure, to allow the reader to reproduce them. Biographical notes referring the reader to more specialized literature and additional mathematical material that may be needed either to deepen the reader's understanding or to introduce basic concepts for less mathematically inclined readers completes each chapter. A very didactic and systematic introduction to mathematical concepts of importance for the analysis of data and the formulation of concepts based on experimental data in neuroscience Provides introductions to linear algebra, ordinary and partial differential equations, Fourier transforms, probabilities and stochastic processes Introduces numerical methods used to implement algorithms related to each mathematical concept Illustrates numerical methods by applying them to specific topics in neuroscience, including Hodgkin-Huxley equations, probabilities to describe stochastic release, stochastic processes to describe noise in neurons, Fourier transforms to describe the receptive fields of visual neurons Provides implementation examples in MATLAB code, also included for download on the accompanying support website (which will be updated with additional code and in line with major MATLAB releases) Allows the mathematical novice to analyze their results in more sophisticated ways, and consider them in a broader theoretical framework.
504 _aIncludes bibliographical references (pages 473-482) and index.
505 0 _aPassive isopotential cell -- Differential equations -- Active isopotential cell -- Quasi-active isopotential cell -- Passive cable -- Fourier series and transforms -- Passive dendritic tree -- Active dendritic tree -- Reduced single neuron models -- Probability and random variables -- Synaptic transmission and quantal release -- Neuronal calcium signaling -- Singular value decomposition and applications -- Quantification of spike train variability -- Stochastic processes -- Membrane noise -- Power and cross spectra -- Natural light signals and phototransduction -- Firing rate codes and early vision -- Models of simple and complex cells -- Stochastic estimation theory -- Reverse-correlation and spike train decoding -- Signal detection theory -- Relating neuronal responses and psychophysics -- Population codes -- Neuronal networks -- Solutions to selected exercises.
588 0 _aPrint version record.
590 _aeBooks on EBSCOhost
_bEBSCO eBook Subscription Academic Collection - Worldwide
650 0 _aComputational neuroscience.
_9235746
650 0 _aComputational biology.
_9152481
650 0 _aNeurosciences.
_92788
650 0 _aNeural circuitry.
_9145982
650 0 _aNeural transmission.
_9176563
650 1 2 _aComputational Biology
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_9926974
650 2 2 _aMathematical Concepts
_91011411
650 2 2 _aModels, Neurological
_9699392
650 2 2 _aNerve Net
_9437585
650 2 2 _aNeurons
_xphysiology
_9315827
650 2 2 _aNeurosciences
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_9924091
650 2 2 _aSynaptic Transmission
_9903876
650 2 _aComputational Biology
_9152481
650 2 _aNeurosciences
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650 6 _aNeurosciences informatiques.
_9913933
650 6 _aBio-informatique.
_9888926
650 6 _aNeurosciences.
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650 6 _aRéseaux nerveux.
_9894511
650 6 _aTransmission nerveuse.
_9903879
650 7 _aMEDICAL
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650 7 _aPSYCHOLOGY
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650 7 _aComputational biology.
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650 7 _aComputational neuroscience.
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650 7 _aNeurosciences.
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650 7 _aNeurosciences
_xInformatique.
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650 7 _aNeurosciences
_xModèles mathématiques.
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655 4 _aElectronic books.
700 1 _aCox, Steven J.
_q(Steven James),
_d1960-
_91489642
776 0 8 _iPrint version:
_aGabbiani, Fabrizio.
_tMathematics for neuroscientists.
_b1st ed.
_dAmsterdam ; Boston : Elsevier Academic Press, 2010
_z9780123748829
_w(OCoLC)441761565
830 0 _aElsevier science & technology books.
_9331189
856 4 0 _uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=342483
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