LEADER 01261nam0-22003851i-450- 001 990003970590403321 005 20100105115341.0 010 $a0-08-034315-5 035 $a000397059 035 $aFED01000397059 035 $a(Aleph)000397059FED01 035 $a000397059 100 $a20100105d1988----km-y0itay50------ba 101 0 $aeng 102 $aGB 105 $aa-------001yy 200 1 $aAdvances in solar energy technology$eproceedings of the Biennal Congress of the International Solar Energy Society, Hamburg, Federal Republic of Germany, 13-18 September 1987$fedited by W.H. Bloss and F. Pfisterer 210 $aOxford$cPergamon Press$d1988 215 $a4 v.$cill.$d24 cm 610 0 $aEnergia solare 676 $a621.47 702 1$aBloss,$bWerner H.$f<1930- > 702 1$aPfisterer,$bF. 710 02$aInternational Solar Energy Society$0304508 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990003970590403321 952 $a00 I1182$b2312$fDETEC 952 $a00 F1458(1/4)$b869$fDETEC 952 $a00 F1458(3/4)$b869$fDETEC 952 $a00 F1458(4/4)$b869$fDETEC 952 $a00 F1458(2/4)$b869$fDETEC 959 $aDETEC 996 $aAdvances in solar energy technology$9512418 997 $aUNINA LEADER 05452nam 2200685 a 450 001 9910791474803321 005 20200520144314.0 010 $a1-282-76902-2 010 $a9786612769023 010 $a0-08-089049-0 035 $a(CKB)2560000000015252 035 $a(EBL)582009 035 $a(OCoLC)700688819 035 $a(SSID)ssj0000422821 035 $a(PQKBManifestationID)12156846 035 $a(PQKBTitleCode)TC0000422821 035 $a(PQKBWorkID)10432772 035 $a(PQKB)10287898 035 $a(MiAaPQ)EBC582009 035 $a(Au-PeEL)EBL582009 035 $a(CaPaEBR)ebr10415281 035 $a(CaONFJC)MIL276902 035 $a(PPN)17024878X 035 $a(EXLCZ)992560000000015252 100 $a20101013d2010 uy 0 101 0 $aeng 135 $aurcn||||||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMathematics for neuroscientists$b[electronic resource] /$fFabrizio Gabbiani, Steven J. Cox 205 $a1st ed. 210 $aAmsterdam ;$aBoston $cElsevier$d2010 215 $a1 online resource (505 p.) 225 0 $aElsevier science & technology books 300 $aDescription based upon print version of record. 311 $a0-12-374882-8 320 $aIncludes bibliographical references (p. 473-482) and index. 327 $aFront cover; Mathematics for Neuroscientists; Copyright page; Full Contents; Preface; Chapter 1. Introduction; 1.1. How to Use This Book; 1.2. Brain Facts Brief; 1.3. Mathematical Preliminaries; 1.4. Units; 1.5. Sources; Chapter 2. The Passive Isopotential Cell; 2.1. Introduction; 2.2. The Nernst Potential; 2.3. Membrane Conductance; 2.4. Membrane Capacitance and Current Balance; 2.5. Synaptic Conductance; 2.6. Summary and Sources; 2.7. Exercises; Chapter 3. Differential Equations; 3.1. Exact Solution; 3.2. Moment Methods*; 3.3. The Laplace Transform*; 3.4. Numerical Methods 327 $a3.5. Synaptic Input 3.6. Summary and Sources; 3.7. Exercises; Chapter 4. The Active Isopotential Cell; 4.1. The Delayed Rectifier Potassium Channel; 4.2. The Sodium Channel; 4.3. The Hodgkin-Huxley Equations; 4.4. The Transient Potassium Channel*; 4.5. Summary and Sources; 4.6. Exercises; Chapter 5. The Quasi-Active Isopotential Cell; 5.1. The Quasi-Active Model; 5.2. Numerical Methods; 5.3. Exact Solution via Eigenvector Expansion; 5.4. A Persistent Sodium Current*; 5.5. A Nonspecific Cation Current that is Activated by Hyperpolarization*; 5.6. Summary and Sources; 5.7. Exercises 327 $aChapter 6. The Passive Cable 6.1. The Discrete Passive Cable Equation; 6.2. Exact Solution Via Eigenvector Expansion; 6.3. Numerical Methods; 6.4. The Passive Cable Equation; 6.5. Synaptic Input; 6.6. Summary and Sources; 6.7. Exercises; Chapter 7. Fourier Series and Transforms; 7.1. Fourier Series; 7.2. The Discrete Fourier Transform; 7.3. The Continuous Fourier Transform; 7.4. Reconciling the Discrete and Continuous Fourier Transforms; 7.5. Summary and Sources; 7.6. Exercises; Chapter 8. The Passive Dendritic Tree; 8.1. The Discrete Passive Tree; 8.2. Eigenvector Expansion 327 $a8.3. Numerical Methods 8.4. The Passive Dendrite Equation; 8.5. The Equivalent Cylinder*; 8.6. Branched Eigenfunctions*; 8.7. Summary and Sources; 8.8. Exercises; Chapter 9. The Active Dendritic Tree; 9.1. The Active Uniform Cable; 9.2. On the Interaction of Active Uniform Cables*; 9.3. The Active Nonuniform Cable; 9.4. The Quasi-Active Cable*; 9.5. The Active Dendritic Tree; 9.6. Summary and Sources; 9.7. Exercises; Chapter 10. Reduced Single Neuron Models; 10.1. The Leaky Integrate-and-Fire Neuron; 10.2. Bursting Neurons; 10.3. Simplified Models of Bursting Neurons; 10.4. Summary and Sources 327 $a10.5. Exercises Chapter 11. Probability and Random Variables; 11.1. Events and Random Variables; 11.2. Binomial Random Variables; 11.3. Poisson Random Variables; 11.4. Gaussian Random Variables; 11.5. Cumulative Distribution Functions; 11.6. Conditional Probabilities*; 11.7. Sum of Independent Random Variables*; 11.8. Transformation of Random Variables*; 11.9. Random Vectors*; 11.10. Exponential and Gamma Distributed Random Variables; 11.11. The Homogeneous Poisson Process; 11.12. Summary and Sources; 11.13. Exercises; Chapter 12. Synaptic Transmission and Quantal Release 327 $a12.1. Basic Synaptic Structure and Physiology 330 $aVirtually all scientific problems in neuroscience require mathematical analysis, and all neuroscientists are increasingly required to have a significant understanding of mathematical methods. There is currently no comprehensive, integrated introductory book on the use of mathematics in neuroscience; existing books either concentrate solely on theoretical modeling or discuss mathematical concepts for the treatment of very specific problems. 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