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Scott A. — Neuroscience: a mathematical primer
Scott A. — Neuroscience: a mathematical primer



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Название: Neuroscience: a mathematical primer

Автор: Scott A.

Аннотация:

This is an introductory text of mathematical neuroscience intended for anyone who wants to appreciate the role that mathematics and mathematical modeling and analysis can do to aid an understanding of how the brain works and the nature of the mind. In particular, the book will be of interest to established neuroscientists and neuroscience students who wish to know what roles mathematical formulations can play in attempting to comprehend the dynamics of a human brain. It is expected that this text will be interesting for mathematics faculty teaching in neuroscience programs. It also aims to serve as a general introduction to neuromathematics in neuroscience programs at both undergraduate and graduate levels. Physical scientists and bioengineers who plan to extend their research activities into the realms of cognitive science will find this an ideal guide, as will philosophers and social scientists who wish to understand the degree to which dynamics of a brain can be reduced to mathematical formulations. Mathematical formulations in neuroscience are of five sorts: (i) Exact descriptions of well understood dynamic processes, like the Hodgkin — Huxley theory of the nerve impulse. (ii) Metaphorical descriptions of more complex phenomena, like the stationary states of a Hopfield model. (iii) Information theory for dealing with the storage and transmission of data. (iv) Logical calculus (Boolean algebra) for the analysis of information processing systems. (v) Number theory for counting large numbers of possibilities. (vi) Statistical tools for organizing and evaluating data.


Язык: en

Рубрика: Математика/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2002

Количество страниц: 352

Добавлена в каталог: 10.12.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Synapses chemical      35—39
Synapses electrical      39—40
Synaptic cleft      35 36 37
Synaptic cleft delay      37 42 235 266 271
Tapered fibers      199—201
Tasaki, Ichiji      142 148 150 151 155 156 157
Temperature control      13 14
Temperature parameter      124 125
Temporal lobes      307
Tetraethylammonium (TEA)      62
Tetrakaidekahedron      51
Tetrodotoxin (TTX)      61
Thermal equilibrium      58 59
Thompson, D’Arcy Wentworth      49 206 311
Thought process      17 258—259 308
Threshold      6 249 267 268 287 306
Threshold charge      33 110 112
Threshold for cell assembly      267 268 280
Threshold for cell assembly M-P model      9 41 42
Threshold for cell assembly sodium ion current      97 100 143
Threshold for cell assemblysquid axon      84 110
Threshold impulse      84 106—107
Threshold logic unit (TLU)      42—43
Tien, Ti      52
Time, nature of      31 45 129 301 310
Train of thought      see Phase sequence
Training algorithm      237
Training algorithm theorem      240
Translation mode      135 327 329
Transmembrane ionic current      31—32 55—59 96—97
Transmembrane ionic current calcium      62—63 210
Transmembrane ionic current potassium      62 69 70—73
Transmembrane ionic current sodium      61 69 70—73
Transmembrane voltage      31 54
Tsien, R.W.      199
Tuckwell, H.C.      199
Turing patterns      5 250 251
Turing, Alan      5 251 302
Unstable traveling wave      86 106—107
Unstable traveling wave H-H system      84 85 86
Unstable traveling wave in F-N model      125 126
Unstable traveling wave M-C model      121
Utah electrode array (UEA)      18
Vacuum permittivity      55
Varicosity (local enlargement)      33 199 201
Verhulst function      see Logistic equation
Verhulst, Pierre Francois      15
Vesicle(s)      35 36 37
Vesicle(s) release probability      38
Volta, Alessandro      1
Voltage clamping      67 68—69 91
Voltage clamping sensitive dyes      18
Voltage clamping source, ideal      68
Voorhees, Burt      309
Watt, James      13
Wave equation      317 318
Wave equation front      4 95—112 130—132
Wave equation of activity      2 3 10 251
Wave equation of activity information      248—252 270
Waxman, Steven      10 43 46 222
Weinberg, A.      103
Weinberg, Steven      296
Wescott, William      52
Widening at branchings      87 202 204
Wiener, Norbert      13 299
Wilson — Cowan equations      250—251
Wilson, Hugh      76 77 207 249 251
Wilson, M.A.      287
Wu, J.Y.      284
Yajima, S.      243
Yanagida, E.      136
Yoshizawa, S.      123
Young, C.      103
Young, John Zachary      3 6
Zeldovich, Yakov      4 102 108 324
“Causal-power actuality principle”      303—304
“Coney Island for rats”      264
“Neural Darwinism”      18
“Three dimensional fish-net”      18 259 282 308
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