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Gerstner W., Kistler W.M. — Spiking Neuron Models
Gerstner W., Kistler W.M. — Spiking Neuron Models

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Название: Spiking Neuron Models

Авторы: Gerstner W., Kistler W.M.

Аннотация:

This introduction to spiking neurons can be used in advanced-level courses in computational neuroscience, theoretical biology, neural modeling, biophysics, or neural networks. It focuses on phenomenological approaches rather than detailed models in order to provide the reader with a conceptual framework. The authors formulate the theoretical concepts clearly without many mathematical details. While the book contains standard material for courses in computational neuroscience, neural modeling, or neural networks, it also provides an entry to current research. No prior knowledge beyond undergraduate mathematics is required.


Язык: en

Рубрика: Биология/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 2002

Количество страниц: 504

Добавлена в каталог: 21.12.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Action potential      13 47
Adaptation      19 59
Afterpotential      15
Alpha function      110
AMPA receptor      62 387
Analog neuron      204
Arborization function      409
Arrhenius Current model      199
Arrhenius formula      199
Asynchronous firing      240
Asynchronous firing stability      294
Attractor length      319
Auditory system      450
Autocorrelation function      169
Axon      12
Back propagating action potential      378
Balanced excitation and inhibition      187 248 317
Barn owl, auditory system      450
BCM rule      370
Bifurcation      86
Bifurcation Hopf      86
Bifurcation saddle-node      89
Binary neuron      313
Blobs of activity      331
Cable equation      64
Calcium current      55 60
Calcium dynamics      60
Calcium second messenger      387
Cluster states      296 308
Coding, neuronal      23
Coding, neuronal, correlation code      31 151 442
Coding, neuronal, phase code      31 149 450 453
Coding, neuronal, pulse code      29 149
Coding, neuronal, rate code      24 25 34 35 204
Coding, neuronal, signal transmission      257 441 450
Coding, neuronal, spike code      29 149 442 450
Coefficient of variation      196
Coincidence detector      450 453
Coincidence rate      128
Compartmental model      71
Competition      402
Complex cells      406
Conditioning      432
Conductance-based neuron model      45 124
Connectivity, mexican hat      324 329
Connectivity, sparse random      246
Continuity equation      220
Correlation code      31 151
Correlation function      414
Correlation matrix      396
Correlation, input-output      281 284
Correlation, reverse      32 286
Correlation, spario-temporal      418
Correlation, spike-spike      415
Cortical map      410
Covariance matrix      396
Covariance rule      369
Delay lines      442 446 455
Dendrite      12 63
Dendrite compartmental model      71
Density equation      217
Density equation for membrane potential      219
Density equation for phase variable      229
Density equation for refractory variable      225
Diffusion model      188 220
Electric fish      445
entropy      320
Epsilon kernel definition      110
Epsilon kernel interpretation      112
Escape model      174
Escape model for population      223
Escape rate      174
Eta kernel definition      110
Eta kernel for Hodgkin — Huxley model      126
Eta kernel interpretation      111
Excitable system      91
Field equation      254 325
Field equation blob/bump solution      331
Field equation for hypercolumn      335
Field equation for several populations      338
Field equation for spiking neurons      343
Field equation homogeneous solution      325
Firing intensity      174
Firing rate      24 25 34 169
Firing rate instantaneous      414
Firing rate joint      414
First passage time      192
First principal component      397 399
Fish, electric      445
Fitzhugh — Nagumo model      79 89
FitzHugh — Nagumo model impulse response      114
FitzHugh — Nagumo model nulldines      86
Fixed point      83
Flow field      82
Flux across threshold      218
Flux drift      219
Flux jump      219
Flux refractory      224
Fokker — Planck equation      189 221 425
Frozen noise      312
Gain function      25
Gain function and population activity      243
Gain function of Hodkgin — Huxley model      48
Gain function of integrate-and-fire model noise-free      104
Gain function of integrate-and-fire model with noise      223
Gain function of neocortical neuron model      55
Gain function type I      90
Gain function type II      90
Gating variable      45
Green's function      67
Hazard      164
Hazard model      174
Hebb's postulate      361
Hodgkin — Huxley model      44
Hodgkin — Huxley model eta kernel      126
Hodgkin — Huxley model gain function      48
Hodgkin — Huxley model kappa kernel      126
Hodgkin — Huxley model reduction to SRM      125
Hodgkin — Huxley model reduction to two dimensions      77
Hopf bifurcation      86
Hopf bifurcation subcritical      88
Hopf bifurcation supercritical      88
Hypercolumn      334
Impulse response      112
Impulse response FitzHugh — Nagumo model      114
Inferior olive      310
Information theory      320
Inhibition shunting      21
Inhibitory rebound      19 48 55
Integrate-and-fire model      101
Integrate-and-fire model gain function      104
Integrate-and-fire model noisy      184
Integrate-and-fire model relation to detailed model      133
Integrate-and-fire model relation to SRM      116
Integrate-and-fire model, leaky      102
Integrate-and-fire model, multi-compartment      142
Integrate-and-fire model, multi-compartment, relation to $\textrm{SRM}_0$      144
Integrate-and-fire model, multi-compartment, relation to SRM      146
Integrate-and-fire model, nonlinear      105 133
Integrate-and-fire model, quadratic      106
Integrate-and-fire model, two-compartment      145
Interneuron model reduction to nonlinear i&f      133
Interneuron model reduction to SRM      137
Interval distribution      164
Interval distribution for escape rate models      178
Interval distribution for inhomogeneous Poisson process      180
Interval distribution for periodic input      181
Interval distribution input-dependent      163
Interval distribution interspike      162
Ion channel      44 51
Ion channel, A-current      54
Ion channel, potassium      53
Ion channel, sodium      51
Ion current, calcium      55
Kappa kernel definition      110
Kappa kernel for Hodgkin — Huxley model      126
Kappa kernel interpretation      112
Kramers — Moyal expansion      189
Langevin equation      184 190
Lateral geniculate nucleus (LGN)      406
Learning equation      395
Learning rule, Oja's      405
Learning window      366 373
Limit cycle      85 319
Locking      300
Locking noise-flee      300
Locking theorem      301 303
Locking with noise      306
Long-term potentiation      see “LTP”
Low-connectivity network      246
LTP      362
LTP heterosynaptic      369
LTP homosynaptic      369
Markov process      189
Master equation      425
McCulloch — Pitts neuron      314
Mean field dynamics      314
Membrane potential      14
Membrane potential density      188 192 217
Membrane potential stationary distribution      221
Morris — Lecar model      78 90
Nernst potential      41
neuron      11
Neuron bursting      19
Neuron postsynaptic      12
Neuron presynaptic      12
Neurotransmitter      14
NMDA receptor      62 383 387
NMDA receptor coincidence detector      387
Noise      157
Noise channel      160
Noise model, diffusive noise      184
Noise model, noisy integration      184
Noise model, noisy reset      183
Noise model, noisy threshold      174
Noise model, random connectivity      246
Noise model, stochastic spike arrival      184
Noise spectrum      170
Noise, escape      174
Noise, Gaussian white      184
Noise, Johnson      159
Noise, slow      182
Noise, synaptic      160 320
Noise, thermal      159
Nulldines      82
Oja's rule      370
Orientation selectivity      406
Orientation selectivity map      410
Orientation selectivity, model of      334
Ornstein — Uhlenbeck process      184 190
Oscillation      293
Oscillation as an instability      294
Oscillation of spatial network      338
Oscillation, cluster states      296 308
Oscillation, synchronous irregular      310
Oscillation, synchronous locked      300
OWL      450
Pairing experiment      365
Phase code      31 149
Phase plane analysis      82
Phase portrait      82
Place cells      431
Point process      161
Poisson neuron      172
Poisson neuron with absolute refractoriness      167 173
Poisson neuron, linear      415
Poisson process      172
Poisson process, homogeneous      165
Poisson process, inhomogeneous      180 203 206
Population      28
Population activity      28
Population activity as a flux      218
Population activity asynchronous firing      240
Population activity continuum model      250
Population activity definition      28 213
Population activity density equation      217
Population activity field equation      254 325
Population activity integral equation      232
Population activity linearized equation      258 263
Population activity noise-flee equation      259
Population activity oscillations      293
Population activity transients      269
Population activity Wilson — Cowan equation      208 235 238
Population activity, blobs/bumps of      331
Population rate model      207
Population vector      29
Population, coupled      207 250
Population, fully connected      214
Population, homogeneous      214
Population, inhomogeneous      183
Postsynaptic potential      14 112
Postsynaptic potential, excitatory      20
Postsynaptic potential, inhibtory      20
Power spectrum      170
Prediction      429
Primary visual cortex (V1)      406
Principal component analysis      395
Principal components      396
PSTH, peri-stimulus time histogram      27 281
Pulse code      29; see “Coding”
Quasi steady state      78
Random connectivity      246
Random walk      187
Rate      24 25
Rate code      25 204
Rate, mean firing rate      24 25
Rate, population activity      28
Rate, spike density      27
Rebound, inhibitory      19 48 55
Receptive field      406
Receptive field development      406
Receptive fields, asymmetric      406
Receptive fields, center-surround      406
Reconstruction kernel      32
Refractoriness      113
Refractory density      223
Refractory period      13
Refractory period, absolute      13
Refractory period, Hodgkin — Huxley model      47 50
Renewal hypothesis      167
Renewal process      161
Response kernel      111
Reverberating loop      310
Reversal potential      21 43
Reverse correlation      32 286
Saddle point      83
Self-averaging      401
Separation of time scales      94
Sequences      441
Short-term memory      320
Signal transmission      257 433 441 450
Signal-to-noise ratio      170 201 280
Simple cells      406
Soma      12
Sparse network      312
Spike packets      351
Spike response model      110
Spike response model definition      110
Spike response model relation to Hodgkin — Huxley model      125
Spike response model relation to integrate-and-fire      116
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