Churchland P.S., Sejnowski T.J. — The computational brain :: Электронная библиотека попечительского совета мехмата МГУ

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Churchland P.S., Sejnowski T.J. — The computational brain

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Название: The computational brain

Авторы: Churchland P.S., Sejnowski T.J.

Аннотация:

The Computational Brain is the first unified and broadly accessible book to bring together computational concepts and behavioral data within a neurobiological framework. Churchland and Sejnowski address the foundational ideas of the emerging field of computational neuroscience, examine a diverse range of neural network models, and consider future directions of the field.

Язык:

Рубрика: Биология/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1992

Количество страниц: 544

Добавлена в каталог: 04.12.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

Pyramidal cells computer models of      402—403
Pyramidal cells in microcircuit      39f
Pyramidal cells network of      40f
Pyramidal cells rhythmic inhibition of      267
Pyramidal cells simulation of      404—405
Quantitative model      5—6
Quantum physics      2
Quisqualate receptors      260
Radial basis function      127—128
Radial basis function advantage of      128
Ramachandran's stereo pairs      218 219f
Random-dot stereograms      see also “Dot stereograms” 194f
Random-dot stereograms activation pattern in      203
Random-dot stereograms fusion of      211—213 214f
Random-dot stereograms learning to solve      246—248
Random-dot stereograms ten-level, gray-scale      205f
Raphe nucleus, projecting neurons originating in      57
Reaction time (RT), measurement of      24—25
Real space coordinate transformation between motor space and      336f
Real space metrically deformed topographic map of      336f
Real world depth cues and      216—221
Real world inputs      125
Real world modeling of interactions in      415
Real-worldliness and network models      125—130
Real-worldliness principal aspects of      125
Reality, achieving model that does justice to      416
Receptive fields      53—57
Receptive fields center-surround, in retina      54
Receptive fields dynamic nature of      56—57
Receptive fields in fingertips      54
Receptive fields of input unit      184
Receptors, genetics of proteins of      4
Reciprocal connections      317
Reciprocal innervation law      361
Recognition deficits      319—323
Recognition deficits and network organization      321
Recognition memory      286
Recognition of man-made objects      323
Recognition of subcategories      321—323
Recognition of unique individuals      321—323
Recurrent network      77f 115—125
Recurrent network input-output structure of      303f
Recurrent network model of      120f
Recurrent network output of      122f
Reduction, definition of      415
Redundancy      163
Redundancy reasons for usefulness of      165
Referee network      129—130
Referee network in system of mini-nets      130f
Reflex arc, concept of      29
Regional blood flow monitoring      435
Rehearsal      284 301
Relaxation      83—84 90
Relaxation labeling      96
Relaxation nets, solution of global problems by      93
REM sleep, theta waves during      264—265
Repeatable patterns, generation of      381—383
Representations abstract vs modality-specific      321
Representations and need to survive      147—148
Representations current vs stored      142
Representations definition of      316—317
Representations distribution and redistribution of      171
Representations explicit vs. implicit      168
Representations in visual system of brain      157—163
Representations indexical      422
Representations neurobiology of      142—237
Representations occurrent/abeyant distinction for      165—167
Representations operations on      62
Research co-evolution of      10—11
Research on cognitive and psychophysical level      12
Research on network level      12—13
Response latency      138—139
Response selective processing      302f
Retina comparison of images on to varying planes of fixation      197—199
Retina detecting movement on      369
Retina ganglion cells of      54
Retina optics of      224—225
Retina photoreceptors in      223
Retina projections from      150f
Retina slip on      354 357 366—367
Retina spots of light falling on      227f
Retina studies of      160
Retina synaptic organization of in vertebrates      149f
Retina three-dimensional information carried to      171
Retina types of cells in      42—43
Retinal ganglion cells pathways of      148—149
Retinotopy      155
Retraining holus-bolus      127—128
Retrograde tracing technique      442
Reversible figures      145f
Rhythmic behavior      381—382
Rhythmic behavior afferent control of      385
Rhythmic behavior brain stem in      409
Rhythmic behavior in Grillner model      409
Rhythmic behavior NMDA receptors in timing of      403
Rhythmic behavior representation of      169—170
Rhythmic behavior variety of      381—382
Rhythmic patterns, generation of      381—382
Rhythmicity, slow and high-frequency      398
Robots (cont.) six-legged      424f
Robots construction of      422—423
Rod photoreceptors      148 223
Rod photoreceptors recording response from      144f
Saccade-movement information      359
Saccades      188 195
Saccades effects on amplitude and direction of      236
Saccadic-burst neurons      358
Scalability, improvement of      125—127
Scalar encoding      164
Scaling problem      112
Scientific advances      1
Screen-door problem averaging method in      237
Screen-door problem improved performance in      212—213
Screen-door problem solution of      211—212
Second-messenger, activation of      48
Segmental ganglion, of leech      339f 340f
Segmental oscillators change in frequency of      396
Segmental oscillators connecting pairs of cells in      392—394
Segmental oscillators coupling of      392—395 397
Segmental oscillators time in      337—338
Segmental swimming oscillator      388—399
Segregation task      93
Self-organizing systems      97—98
Selverston, Allen      4
Sensorimotor coordination nature of problem of      332—335 337—338
Sensorimotor integration      15 331—411
Sensorimotor integration dynamics of      177
Sensorimotor integration in LeechNet      341—353
Sensorimotor integration modeling neuron in      399—411
Sensorimotor integration spinal cord circuits in      382
Sensorimotor integration strategy for      338—339
Sensorimotor integration time in      379—388
Sensory information guiding body movements      331
Sensory information processing of      23
Sensory input, categorization of      418—422
Sensory neurons, high-level place-coded      155—157
Sensory processing hierarchy      23—25
Sensory receptors, types of in vertebrates      143f
Sensory representation, power and versatility of population coding in      233—234
Sensory space, position in      334f
Sensory system hierarchical organization of      23—24
Sensory system topographic maps of      31—34
Sensory transducers      142—143
Sensory-motor device      416
Shape-from-shading model      183—188
Sharp brain waves      264 265
Sharp brain waves hierarchical organization of cell population burst with      268f
Sharp brain waves in humans      270
Sherrington's reciprocal innervation law      361
Short-term memory and hippocampus      281

Short-term memory circulating      301—303
Short-term memory creation of with short recurrent connections      122—123
Short-term memory neuronal implementation of      301—304
Short-term memory vs. long-term memory      297—299
Short-term processes, and synaptic efficacy      305f
Signal integration      143—144
Signal processing      143—144
Signal semantics      286
Signal/noise ratio      228
Similarity space      169
Simulations paradigm      413—414
Simulations parameters of      413—416
Simulations vs. synthetic brain function      415—416
Single-unit recording      440—442
Size constancy of      188
Size gradient      189
Size perception of      196f
Sleep, brain waves during      265
Slide rule      71f
Smeary images      366—367
Smooth pursuit      367
Smooth pursuit basic oculomotor circuits used for      368
Smooth pursuit eye tracking system in      370f
Smooth pursuit integration of with VOR      354 368—369
Smooth pursuit system      358
Smooth pursuit system for visual tracking      29
Snout, of mouse      38f
Sodium channels controlling voltage across      401
Sodium channels fast      399
Sodium channels simulation in pyramidal neuron      404—405f
Sodium current, during action potential in squid giant axon      400f
Sodium mapping      432—434
Solar system model      136
Somatosensory cortex multiple representations of body surface in      32—33
Somatosensory cortex studies of      160
Somatosensory system size of receptive field of      53—54
Somatosensory system topographic mapping of      32—34 155
Sonar signals discriminating      112—115
Sonar signals typical spectral envelopes of      116—117f
Sonar target recognition network, preprocessing for      114f
Sound recognition      320
Sound source, precise location of      155
Space-time diagram      175f
Spatial learning, and long-term potentiation      259
Spatial vision coarse coding in      225—226
Spatial vision hyperacuity in      225
Specialization      318
Specialization at behavioral level      325
Specialization by substructures      130
Specialization in regions of nervous system      50—51 50f
Speech recognition network, testing new voice on      127
Spin glass system      85—87
Spin glass system local energy minima in      88
Spin glass system thermodynamics of      88—89
Spinal cord basic rhythm of segments of      410
Spinal cord complexity of      388
Spinal cord in sensorimotor integration      339
Spinal cord intersegmental influence in      410
Spinal cord intra- and intersegmental connections of      384f
Spinal cord lamprey      392
Spinal cord lamprey activity of      395f
Spinal cord neuron models in lamprey      403
Spinal cord oscillating circuits in      382—388 390f
Spinal cord pharmacology of      388
Spinal cord posterior view of      383f
Spinal cord stretch receptor input to      409
Spinal cord structure of      382
Split-brain studies      429
Squashing functions      111—112 124 137
Squashing functions matrix plus      168
Squashing functions nonlinear      109—111
Squid giant axon, action potentials in      399—402
SSL (some small lies) constraint      402
Stable limit cycle      123
State space      64—65 155 163
State space and color perception      223—224
State space and color variation      225f
State space characterizing rhythmic movement      170f
State space conceptual fecundity of      167—174
State space increasing number of dimensions of      105
State transitions      67
Stellate cells      36f
Stepping movements, of cockroach and cat      387f
Stereo invariants, unsupervised learning of      215—216
Stereo vision      188
Stereo vision and object recognition      193
Stereo vision computational models of      199—221
Stereo vision cooperative algorithm in      210—215
Stereo vision depth cues in and real world      216—221
Stereo vision false      195
Stereo vision neurophysiology and anatomy of      197—199
Stereo vision psychological parameters of      189—195
Stereo vision study of in spiny lobster      4—5
Stereo vision unsupervised learning of stereo invariants in      215—216
Stereoacuity, falling off of      226
Stereopsis      192
Stereopsis as powerful depth cue      218—220
Stereopsis coarse      202—209
Stereopsis modules for      220
Stereopsis visual processing of      218
Stereotypy      339
Stimulus-guided modifiability      381
Stomatogastric ganglion circuit in      5f
Stonehenge      66—67
Stretch receptors, input to spinal cord by      409
Stretch reflex, pathways for      32f
Striate cortex, cell bodies of      35f
Striatum radiatum, EEG recording from      264f
String galvanometer      437—438
Submodalities, talking across      326
Subnetworks, clustering related information in      128—129
Substantia nigra, projecting neurons originating in      57
Superconducting magnetometers      440
Superior colliculus, vector-averaging in      234 235f
Superstructure concepts      1
Surface principal curvatures of      183—186
Surface principal orientation of      185—186
Swimming central pattern generator for      349
Swimming characteristics of      389f
Swimming in lamprey      388—399
Swimming model of      15
Swimming oscillator, segmental      388—399
Sympathetic gangion cell, bullfrog      401
Synapses (cont.) conditions for induction of plasticity in      254f
Synapses and function of neuron      17
Synapses anti-Hebbian      252—253
Synapses change in strength of as function of postsynaptic activity      295f
Synapses decreasing strength of      289—295
Synapses diagram of on dendritic spine      46f
Synapses dynamic functioning of      179
Synapses excitatory and inhibitory signals by      43f
Synapses function of      44
Synapses induction of long-term potentiation at      221
Synapses main biochemical mechanisms of      49f
Synapses modification of      220
Synapses modification of non-Hebbian      253—254
Synapses modification of pseudo-Hebbian      252—253
Synapses modification of signs of      293—295
Synapses modification of strengthening in human nervous system      51
Synapses modification of strengthening number of in cortex      51
Synapses modification of strengthening presynaptic connection      263
Synapses plasticity of      136 250—254
Synapses short-term processes affecting efficacy of      305f
Synapses tree diagram of forms of Hebbian change of      253f
Synapses types of      52f
Synapses use-dependent changes in      290f
Synaptic weight change theory      253—254
Synchronous bursts      220—221
Systematic mapping      65
Systems concepts      29—31

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