Neuronal dynamics: from single neurons to networks and models of cognition
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2014
|
| Ausgabe: | first published |
| Schlagworte: | |
| Online-Zugang: | kostenfrei Inhaltsverzeichnis |
| Beschreibung: | Hier auch später erschienene, unveränderte Nachdrucke |
| Beschreibung: | xi, 577 Seiten Illustrationen, Diagramme |
| ISBN: | 9781107060838 9781107635197 |
Internformat
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Datensatz im Suchindex
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| adam_text |
NEURONAL DYNAMICS
From Single Neurons to Networks and Models of Cognition
WULFRAMGERSTNER
WERNERMKISTLER
RICHARDNAUD
LIAMPANINSKI
gil CAMBRIDGE
UNIVERSITY PRESS
Contents
Preface page ix
PART ONE FOUNDATIONS OF NEURONAL DYNAMICS 1
1 Introduction: neurons and mathematics 3
1 1 Elements of neuronal systems 3
1 2 Elements of neuronal dynamics 7
1 3 Integrate-and-fire models 10
1 4 Limitations of the leaky integrate-and-fire model 19
1 5 What can we expect from integrate-and-fire models? 23
1 6 Summary 25
2 Ion channels and the Hodgkin-Huxley model 28
2 1 Equilibrium potential 28
2 2 Hodgkin-Huxley model 31
2 3 The zoo of ion channels 42
2 4 Summary 56
3 Dendrites and synapses 58
3 1 Synapses 58
3 2 Spatial structure: the dendritic tree 64
3 3 Spatial structure: axons 72
3 4 Compartmental models 75
3 5 Summary \ 79
4 Dimensionality reduction and phase plane analysis 81
4 1 Threshold effects 81
4 2 Reduction to two dimensions 84
4 3 Phase plane analysis 91
4 4 Type I and type II neuron models 96
4 5 Threshold and excitability 103
4 6 Separation of time scales and reduction to one dimension 108
4 7 Summary 111
vi Contents
PART TWO GENERALIZED INTEGRATE-AND-F1 RE NEURONS 115
5 Nonlinear integrate-and-fire models 119
5 1 Thresholds in a nonlinear integrate-and-fire model 120
5 2 Exponential integrate-and-fire model 124
5 3 Quadratic integrate and fire 129
5 4 Summary 132
6 Adaptation and firing patterns 136
6 1 Adaptive exponential integrate-and-fire 136
6 2 Firing patterns 140
6 3 Biophysical origin of adaptation 149
6 4 Spike Response Model (SRM) 154
6 5 Summary 165
7 Variability of spike trains and neural codes 168
7 1 Spike-train variability 169
7 2 Mean firing rate 172
7 3 Interval distribution and coefficient of variation 178
7 4 Autocorrelation function and noise spectrum 179
7 5 Renewal statistics 181
7 6 The problem of neural coding 190
7 7 Summary 199
8 Noisy input models: barrage of spike arrivals 202
8 1 Noise input 202
8 2 Stochastic spike arrival 207
8 3 Subthreshold vs superthreshold regime 212
8 4 Diffusion limit and Fokker-Planck equation (*) 215
8 5 Summary 221
9 Noisy output: escape rate and soft threshold 224
9 1 Escape noise 224
9 2 Likelihood of a spike train 229
9 3 Renewal approximation of the Spike Response Model 232
9 4 From noisy inputs to escape noise v 235
9 5 Summary 241
10 Estimating parameters of probabilistic neuron models 243
10 1 Parameter optimization in linear and nonlinear models 244
10 2 Statistical formulation of encoding models 249
10 3 Evaluating goodness-of-fit 255
10 4 Closed-loop stimulus design 263
10 5 Summary 264
Contents
11 Encoding and decoding with stochastic neuron models
11 1 Encoding models for intracellular recordings
11 2 Encoding models in systems neuroscience
11 3 Decoding
11 4 Summary
PART THREE NETWORKS OF NEURONS AND
POPULATION ACTIVITY
12 Neuronal populations
12 1 Columnar organization
12 2 Identical neurons: a mathematical abstraction
12 3 Connectivity schemes
12 4 From microscopic to macroscopic
12 5 Summary
13 Continuity equation and the Fokker-Planck approach
13 1 Continuity equation
13 2 Stochastic spike arrival
13 3 Fokker-Planck equation
13 4 Networks of leaky integrate-and-fire neurons
13 5 Networks of nonlinear integrate-and-fire neurons
13 6 Neuronal adaptation and synaptic conductance
13 7 Summary
14 Quasi-renewal theory and the integral-equation approach
14 1 Population activity equations
14 2 Recurrent networks and interacting populations
14 3 Linear response to time-dependent input
14 4 Density equations vs integral equations
14 5 Adaptation in population equations
14 6 Heterogeneity and finite size
14 7 Summary
15 Fast transients and rate models
15 1 How fast are population responses?
15 2 Fast transients vs slow transients in models
15 3 Rate models
15 4 Summary
vii
viii Contents
PART FOUR DYNAMICS OF COGNITION
16 Competing populations and decision making
16 1 Perceptual decision making
16 2 Competition through common inhibition
16 3 Dynamics of decision making
16 4 Alternative decision models
16 5 Human decisions, determinism, and free will
16 6 Summary
17 Memory and attractor dynamics
17 1 Associations and memory
17 2 Hopfield model
17 3 Memory networks with spiking neurons
17 4 Summary
18 Cortical field models for perception
18 1 Spatial continuum model
18 2 Input-driven regime and sensory cortex models
18 3 Bump attractors and spontaneous pattern formation
18 4 Summary
19 • Synaptic plasticity and learning
19 1 Hebb rule and experiments
19 2 Models of Hebbian learning
19 3 Unsupervised learning
19 4 Reward-based learning
19 5 Summary
20 Outlook: dynamics in plastic networks
20 1 Reservoir computing
20 2 Oscillations: good or bad?
20 3 Helping patients
20 4 Summary
References ^
Index |
| any_adam_object | 1 |
| author | Gerstner, Wulfram 1963- Kistler, Werner M. 1969- Naud, Richard Paninski, Liam 1978- |
| author_GND | (DE-588)1089284381 (DE-588)1146395132 (DE-588)1257471570 (DE-588)1257472119 |
| author_facet | Gerstner, Wulfram 1963- Kistler, Werner M. 1969- Naud, Richard Paninski, Liam 1978- |
| author_role | aut aut aut aut |
| author_sort | Gerstner, Wulfram 1963- |
| author_variant | w g wg w m k wm wmk r n rn l p lp |
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| ctrlnum | (OCoLC)885437889 (DE-599)BVBBV041833142 |
| dewey-full | 612.8 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 612 - Human physiology |
| dewey-raw | 612.8 |
| dewey-search | 612.8 |
| dewey-sort | 3612.8 |
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| discipline | Biologie Informatik Medizin |
| edition | first published |
| format | Book |
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| language | English |
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| spelling | Gerstner, Wulfram 1963- (DE-588)1089284381 aut Neuronal dynamics from single neurons to networks and models of cognition Wulfram Gerstner ; Werner M. Kistler ; Richard Naud ; Liam Paninski first published Cambridge Cambridge University Press 2014 xi, 577 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Hier auch später erschienene, unveränderte Nachdrucke Neurobiology Neural networks (Neurobiology) Cognitive neuroscience Neurowissenschaften (DE-588)7555119-6 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Neuronales Netz (DE-588)4226127-2 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Künstliche Intelligenz (DE-588)4033447-8 s Neuronales Netz (DE-588)4226127-2 s Maschinelles Lernen (DE-588)4193754-5 s DE-604 Neurowissenschaften (DE-588)7555119-6 s Mathematisches Modell (DE-588)4114528-8 s Kistler, Werner M. 1969- (DE-588)1146395132 aut Naud, Richard (DE-588)1257471570 aut Paninski, Liam 1978- (DE-588)1257472119 aut Erscheint auch als Online-Ausgabe 978-1-107-44761-5 https://neuronaldynamics.epfl.ch/online/index.html kostenfrei Volltext HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027277980&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Gerstner, Wulfram 1963- Kistler, Werner M. 1969- Naud, Richard Paninski, Liam 1978- Neuronal dynamics from single neurons to networks and models of cognition Neurobiology Neural networks (Neurobiology) Cognitive neuroscience Neurowissenschaften (DE-588)7555119-6 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Neuronales Netz (DE-588)4226127-2 gnd Mathematisches Modell (DE-588)4114528-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)7555119-6 (DE-588)4033447-8 (DE-588)4226127-2 (DE-588)4114528-8 (DE-588)4193754-5 |
| title | Neuronal dynamics from single neurons to networks and models of cognition |
| title_auth | Neuronal dynamics from single neurons to networks and models of cognition |
| title_exact_search | Neuronal dynamics from single neurons to networks and models of cognition |
| title_full | Neuronal dynamics from single neurons to networks and models of cognition Wulfram Gerstner ; Werner M. Kistler ; Richard Naud ; Liam Paninski |
| title_fullStr | Neuronal dynamics from single neurons to networks and models of cognition Wulfram Gerstner ; Werner M. Kistler ; Richard Naud ; Liam Paninski |
| title_full_unstemmed | Neuronal dynamics from single neurons to networks and models of cognition Wulfram Gerstner ; Werner M. Kistler ; Richard Naud ; Liam Paninski |
| title_short | Neuronal dynamics |
| title_sort | neuronal dynamics from single neurons to networks and models of cognition |
| title_sub | from single neurons to networks and models of cognition |
| topic | Neurobiology Neural networks (Neurobiology) Cognitive neuroscience Neurowissenschaften (DE-588)7555119-6 gnd Künstliche Intelligenz (DE-588)4033447-8 gnd Neuronales Netz (DE-588)4226127-2 gnd Mathematisches Modell (DE-588)4114528-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Neurobiology Neural networks (Neurobiology) Cognitive neuroscience Neurowissenschaften Künstliche Intelligenz Neuronales Netz Mathematisches Modell Maschinelles Lernen |
| url | https://neuronaldynamics.epfl.ch/online/index.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027277980&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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