1 Single-Unit Analysis Versus Population Response Analysis.- 2 Outline of this Book.- 1 Information Coding.- 1.1 Information Coding and Transmission by Single Cells and Cell Populations.- Box A. Information Theory.- 1.
2 Cooperative Effects and Ensemble Coding.- 2 Spontaneous Activity.- 2.1 Noise or Information Carrier?.- 2.2 Quantification and Representation.- Box B, Distribution Functions.- 2.
3 The Auditory System.- 2.4 The Visual System.- 2.5 Other Brain Areas.- 2.6 Synthesis of Spontaneous Activity Phenomenology.- 3 Receptive Fields.
- 3.1 Receptotopic and Nonreceptotopic Receptive Fields.- Box C. Conformal Mapping.- 3.2 Center-Surround Structure.- 3.3 Receptive Field Changes in Central Neurons: Feature Detectors?.
- 3.4 Temporal Properties of the Receptive Field.- 4 Single-Neuron Models.- 4.1 Diffusion Models.- Box D. Renewal Theory.- Box E.
Master Equation.- 4.2 Discrete Input Models.- 4.3 Neural Interaction -- Black Box -- Models.- Box E Laplace Transforms.- 5 Neural Network Models.- 5.
1 Neurons as Logical Switching Elements.- 5.2 Little-Neurons as Network Elements: Introduction of Probability.- 5.3 Statistical Theories of Memory.- Box G. Statistical Mechanics and the Ising Model.- 5.
4 Statistical Neuromechanics.- 5.5 Neural Field Theories.- 5.6 Interaction in Neural Nets.- 6 Multiple Separate Recordings from Neural Nets.- 6.1 Recording from Multiple Sites in the Brain.
- 6.2 Separating Multiple-Unit Spike Trains.- 6.2.1 Separation on the Basis of Waveform Parameters.- 6.2.2 Spike Separation on the Basis of the Entire Waveform: Template Matching.
- 6.2.3 Optimal Filter Procedures.- 6.2.4 Procedures Based on Cluster Analysis in Signal Space.- Box K Principal Component Analysis.- 6.
2.5 Detection and Classification Procedures.- 6.2.6 The Performance of Spike Separation Procedures.- Box L Classification Theory.- 6.2.
7 Difficulties Encountered with Spike Separation Procedures.- 7 Representation and Detection of Correlated Neural Activity.- 7.1 Representation of Multiple-Site Recorded Continuous Neural Activity.- Box 1 Stationarity of Random Processes.- 7.2 Representation of Multiunit Spike Trains.- 7.
3 Cross-Correlation.- 7.4 Joint Peri-Stimulus-Time Scattergrams.- 7.5 A Hierarchy of Multiunit Representations.- 7.6 Correlation Analysis of Larger Numbers of Neural Units.- 7.
7 Are Higher-Order Correlation Analyses Necessary?.- 7.8 Correcting Cross-Correlations for Effects of Stimulus Coupling 142.- 8 Correlated Neuronal Activity Observed in the Vertebrate Brain.- 8.1 The Visual System.- 8.1.
1 The Retinal Ganglion Cells.- 8.1.2 From Ganglion Cell to Lateral Geniculate Nucleus.- 8.1.3 Inside the Lateral Geniculate Nucleus.- 8.
1.4 The Striate Cortex.- 8.1.5 Geniculo-Striate Connections.- 8.2 The Auditory System.- 8.
2.1 The Auditory Nerve.- 8.2.2 The Dorsal Cochlear Nucleus.- 8.2.3 The Auditory Midbrain.
- 8.2.4 The Medial Geniculate Body.- 8.2.5 The Geniculocortical Projection.- 8.2.
6 The Primary Auditory Cortex.- 8.3 The Somatosensory System.- 8.4 Simultaneous Versus Sequential Single-Unit Recording.- 8.5 The Motor System.- 8.
5.1 The Motor Cortex.- 8.5.2 Respiratory Areas in the Brainstem.- 8.5.3 Intercostal Motoneurons and Skeletal Motoneurons.
- 8.6 Comparison Between the Sensory and Motor Systems.- 8.7 Correlated Neural Activity and the State of the Animal.- 8.8 Correlated Neural Activity and Cognition.- 9 System Identification from Neural Correlation.- 9.
1 Identification on the Basis of Continuous Input and Output Signals.- 9.2 Identification on the Basis of Continuous Input and Discrete Output.- 9.3 Identification Based upon Discrete Input and Discrete Output.- 9.3.1 Linear System Analysis.
- 9.3.2 Nonlinear Systems Analysis.- 9.4 Identification Based upon Discrete Input and Continuous Output.- 9.5 When Systems Identification Does Not Work.- 10 Plasticity -- The Capacity to Change.
- 10.1 The Developing Brain.- 10.1.1 Physiological Signs of Plasticity.- 10.1.2 Morphological Substrates of Plasticity.
- 10.2 The Adult Brain.- 10.2.1 Physiological Signs of Plasticity.- 10.2.1.
1 Local Changes.- Box K, Classical and Operant Conditioning.- 10.2.1.2 Global Changes.- 10.2.
2 Morphological Changes in Adult Brains.- 10.3 Mechanisms and Models for Modifiable Synapses.- 10.3.1 General Considerations.- 10.3.
2 Formal Models for Modifiable Synapses.- 10.3.3 Stability Considerations for Modifiable Elements.- 10.3.4 Associative Recall and Learning.- 11 Learning -- The Cerebellum.
- Box L, Anatomy, Physiology and Pharmacology of the Cerebellum.- 11.1 The Cerebellum as a Timing Device.- 11.2 The Cerebellum as a Perceptron.- 11.2.1 Theoretical Considerations.
- 11.2.2 Experimental Evidence.- 11.3 The Cerebellum as a Space-Time Metric.- Box M. Vectors and Tensors in Oblique Frames of Reference.- 12 Learning -- The Hippocampus.
- 12.1 Types of Memory.- 12.2 Brain Structures Involved in Memory.- Box N. The Hippocampus.- 12.3 A Mechanism of Memory Formation in the Hippocampus.
- 12.4 Formal Models of Memory Formation.- 12.5 A Model for the Role of the Hippocampus in Memory.- 13 Learning -- The Neocortex.- 13.1 The Neocortex: Pinnacle or Way-Station?.- Box Q The Neocortex.
- 13.2 Development Aspects of Neocortical Organizations.- 13.3 The Neocortex as a Self-Organizing System.- 13.3.1 General Considerations.- 13.
3.2 Theoretical Descriptions.- Box P Neural Assemblies.- 13.3.3 Relation Between Structural Organization and Assembly Formation.- 13.4 Does the Brain Learn by Selection?.
- 14 The Correlative Brain.- 14.1 Correlation, the Basic Mechanism of the Brain?.- 14.1.1 Correlation Is Used in the Formation of Topographic Maps.- 14.1.
2 Correlation Is Used and Necessary to Detect Events in the Outside World.- 14.1.3 Correlation Is the Basis of Learning, Association, Pattern Recognition, Novelty Detection, and Memory Recall.- 14.1.4 Correlation, Motor Coordination, and Context- Dependent Behavior.- 14.
2 Topographic and Functional Brain Maps.- 14.3 Top-Down and Bottom-Up Approaches to Brain Function.- 14.3.1 An "Integrated Circuit" Approach to Brain Function.- References.