 | Martins J.C. Bioelectronic vision: retina models, evaluation metrics, and system design / J.C.Martins, L.A.Sousa. - Singapore; Hackensack: World Scientific, 2009. - xxiv, 246 p.: ill. (some col.). - (Series on bioengineering and biomedical engineering; Vol.3). - Bibliogr.: p.233-240. - Ind.: p.241-246. - ISBN-10 981-279-430-1; ISBN-13 978-981-279-430-7
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Preface ....................................................... vii
Acknowledgments ................................................ xi
List of Figures .............................................. xvii
List of Tables ................................................ xxi
List of Acronyms ............................................ xxiii
1 Introduction to Bioelectronic Vision ......................... 1
1.1 Main Causes of Blindness ................................ 2
1.2 Main Components of a Bioelectronic Vision System ........ 5
1.3 Classification of Visual Prostheses .................... 10
1.3.1 Retinal Neuroprosthesis ......................... 12
1.3.2 Cortical Visual Neuroprosthesis ................. 14
1.4 Conclusions and Further Reading ........................ 15
2 The Human Visual System ..................................... 21
2.1 Introduction ........................................... 21
2.2 The Neuron ............................................. 22
2.2.1 Neuron Anatomy .................................. 22
2.2.2 Neuron Dynamics ................................. 23
2.3 The Human Visual System ................................ 28
2.3.1 The Eye ......................................... 29
2.3.2 The Retina ...................................... 31
2.3.3 How the Retina Operates ......................... 37
2.3.4 The Visual Pathway .............................. 44
2.4 Modeling the Retina .................................... 49
2.4.1 The Retina Neural Code .......................... 49
2.4.2 Classification of Retina Models ................. 52
2.5 Conclusions and Further Reading ........................ 54
3 Characterization of the Neural Response ..................... 57
3.1 Introduction ........................................... 57
3.2 Spikes: The Essence of the Neural Code ................. 58
3.2.1 Retina Stimulation and Responses Recording ...... 60
3.2.2 Spike Trains and Firing Rates ................... 71
3.2.3 Spike Triggered Average ......................... 83
3.2.4 Spike Train Autocorrelation Function ............ 87
3.2.5 The Spike Triggered Covariance .................. 89
3.3 Stimulus and Response Statistics, and Firing
Probabilities .......................................... 90
3.3.1 Spike Train Statistics .......................... 92
3.3.2 Homogeneous Poisson Model of Spike Trains ....... 93
3.3.3 Inhomogeneous Poisson Model of Spike Trains .... 100
3.3.4 Spike-Count Statistics ......................... 102
3.4 Spiking Mechanisms .................................... 103
3.4.1 Generation of Poisson Spike Trains ............. 104
3.4.2 Integrate-and-Fire Spike Generation ............ 105
3.5 Conclusions and Further Reading ....................... 107
4 Retina Models .............................................. 113
4.1 Introduction .......................................... 113
4.2 Classification of Retina Models ....................... 113
4.3 Structural Models ..................................... 115
4.3.1 The Integrate and Fire Model ................... 115
4.3.2 The Leaky Integrate-and-Fire Model ............. 118
4.4 Functional Models ..................................... 123
4.4.1 Deterministic Models ........................... 124
4.4.2 Stochastic Models .............................. 129
4.4.3 White Noise based Models ....................... 138
4.5 Conclusions and Further Reading ....................... 145
5 Neural Activity Metrics and Models Assessment .............. 155
5.1 Introduction .......................................... 155
5.2 The Metric Definition ................................. 155
5.3 Firing Rate Metrics ................................... 156
5.3.1 Mean Squared Error ............................. 156
5.3.2 Normalized Mean Squared Error .................. 157
5.3.3 Percent Variance Accounted For ................. 158
5.3.4 Analysis of the Firing Rate Metrics ............ 159
5.4 Spike Train Metrics ................................... 160
5.4.1 Spike Time Metric .............................. 161
5.4.2 Interspike Interval Metric ..................... 166
5.4.3 Spike Train Distance Metric .................... 170
5.4.4 Spike Train Metrics Analysis ................... 174
5.5 Spike Events Metrics .................................. 177
5.5.1 Spike Events Metric Analysis ................... 187
5.6 Tuning and Assessment of Retina Models ................ 188
5.6.1 Deterministic Model ............................ 189
5.6.2 Stochastic Model ............................... 191
5.6.3 White* Noise Model ............................. 191
5.7 Conclusions and Further Reading ....................... 193
6 Design and Implementation of Bioelectronic Vision
Systems .................................................... 199
6.1 Retinal Prostheses .................................... 199
6.1.1 Epiretinal Implants ............................ 200
6.1.2 Subretinal Implants ............................ 202
6.2 Retinal Bioelectronic Vision System Design ............ 204
6.3 Cortical Visual Prostheses ............................ 208
6.4 Cortical Bioelectronic Vision System Design ........... 212
6.4.1 Early Layers ................................... 213
6.4.2 Neuromorphic Pulse Coding ...................... 217
6.4.3 Spike Multiplexing ............................. 218
6.4.4 Serial Communication Link ...................... 221
6.5 Vision Prosthesis Prototype ........................... 223
6.6 Conclusions and Further Reading ....................... 226
Bibliography .................................................. 233
Index ......................................................... 241
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