Exploration of Cortical Function

1. Introduction.- 2. Neurons and Neuronal Signal.- 1 Overview.- 2 The Resting Potential.- 3 Passive Signal Propagation in Dendrites.- 4 Active Propagation of Spikes.- 5 Synaptic Transmission and Plasticity.- 3 The Early Visual System of Macaque Monkeys.- 1 Anatomy of the Early Visual Pathway.- 2 Physiology of the Early Visual Pathway.- 4 Optical Imaging of Brain Activity.- 1 Principles of Optical Imaging.- 2 Monte-Carlo Simulation of Optical Imaging.- 3 Results for Simulated Video Imaging.- 4 Simulated Scanning Laser Optical Imaging.- 5 Optical Imaging as Source Separation Problem.- 1 Formulation of the Source Separation Task.- 2 Heuristic Methods for Source Separation.- 6 Regression Methods for Source Separation.- 1 General Linear Models.- 2 Nonlinear Parametric Models.- 7 Projection Methods for Source Separation.- 1 Principle.- 2 Principal Component Analysis.- 3 Independent Component Analysis.- 4 Second Order Decorrelation Methods.- 5 Examples and Benchmarks.- 8 Real World Applications of Source Separation Techniques.- 1 Nonlinear Model-Analysis of Calcium Imaging Signals.- 2 PCA for Optical Imaging of Intrinsic Signals.- 3 ESD for Optical Imaging Data.- 4 Concluding Remarks.- 9 Computational Models of Early Vision.- 1 Why Computational Models?.- 2 Statistics of Natural Images.- 3 Compact Coding.- 4 Factorial Codes.- 5 Sparse Distributed Coding.- 10 Mean-Field Modeling of Cortical Function.- 1 Iceberg-Model of Orientation Selectivity.- 2 Mean-Field Model of Neuronal Population Activity.- 3 Modeling Orientation Selectivity with two Cell Types.- 4 Modeling Contrast Saturation with two Cell Types.- 5 Hypercolumns with Multiple Populations.- 6 Mean-Field Modeling of Contextual Effects.- 7 Concluding Remarks.- References.