Cerebral Cortex

Inhaltsverzeichnis

• 1 Modeling Cortical Circuitry: A History and Prospectus.
• 1. Introduction.
• 2. Lorente de Nó through Dynamical Systems Models.
• 3. Hodgkin and Huxley through Network Models.
• 4. Prospectus.
• 5. References.
• 2 Interpretations of Data and Mechanisms for Hippocampal Pyramidal Cell Models.
• 2. The Database for Single-Neuron Models.
• 3. Strategies for Single-Neuron Models.
• 4. Anatomy and the Model: Data and Methods.
• 5. The Linear Model: Data and Methods.
• 6. Phenomenological Templates.
• 7. Review of Hippocampal Models.
• 8. Channel Models.
• 9. Ionic Concentration Dynamics.
• 10. Nonsynaptic Channels of Hippocampal Pyramidal Cells.
• 11. HPC Sodium Channels.
• 12. HPC Calcium Channels.
• 13. HPC Potassium Channels.
• 14. Nonspecific Cation and Chloride Currents.
• 15. Simulations of HPC Properties with the Working Model.
• 16. References.
• 3 Functional Implications of Active Currents in the Dendrites of Pyramidal Neurons.
• 2. Historical Perspective.
• 3. Amplification of Synaptic Inputs.
• 4. Compartment Model Simulations of Amplification.
• 5. Effects of Dendritic Active Currents on EPSP Shape.
• 6. The Effect of Dendritic Active Currents in Shaping the Intrinsic Firing Properties of Pyramidal Cells.
• 7. Effects of Potassium Currents.
• 8. Linking Firing of the Soma to Depolarization at Distal Synapses and the Implementation of Hebb’s Hypothesis.
• 9. Apologies.
• 10. Concluding Observations.
• 11. References.
• 4 Comparing Different Modeling Approaches of Visual Cortical Cell Characteristics.
• 2. Foundations.
• 3. Models of Cortical Orientation Specificity.
• 4. Concluding Remarks.
• 5. Appendix.
• 6. References.
• 5 The Role of Recurrent Excitation in Neocortical Circuits.
• 2. Wiring Neocortical Circuits.
• 3. CanonicalMicrocircuits.
• 4. Units of Construction of the Basic Cortical Circuit.
• 5. The Neuronal Components of Layer 4.
• 6. Computation of Orientation.
• 7. Noise and Restoration.
• 8. References.
• 6 Neural Mechanisms Underlying the Analysis of Moving Visual Stimuli.
• 2. A Primer of Basic Concepts.
• 3. Neural Mechanisms: Mammals.
• 4. Neural Mechanisms: Turtles.
• 5. Conclusions and Future Directions.
• 7 Linearity and Gain Control in VI Simple Cells.
• 2. The Linear Model of Simple Cells.
• 3. Some Linear Properties of Simple Cells.
• 4. Biophysics of the Linear Model.
• 5. Some Nonlinear Properties of Simple Cells.
• 6. The Normalization Model of Simple Cells.
• 7. Testing the Normalization Model.
• 8. Biophysical Plausibility of the Normalization Model.
• 9. Conclusions.
• 10. References.
• 8 Non-Fourier Cortical Processes in Texture, Form, and Motion Perception.
• 2. Analysis of Texture Boundaries by Non-Fourier Mechanisms.
• 3. Area V4 Neurons and Form Vision.
• 4. Two-Dimensional Motion.
• 5. Discussion.
• 9 Modeling Thalamocortical Oscillations.
• 1. Slow Thalamic Rhythms.
• 2. Thalamus as Magnet for Modeling—Dynamics and Neural Systems.
• 3. Early Modeling Predicted a Role for Inhibitory Phasing.
• 4. Modeling the T Channel.
• 5. Modeling the Low-Threshold Spike.
• 6. The Basic Two-Neuron Network.
• 7. The Search for Origins: Whence Spindling?.
• 8. Synchrony and Spread of Network Activity.
• 9. Summary and Conclusions.
• 10 Realistic Network Models of Synchronized Oscillations in Visual Cortex.
• 2. Model Structure.
• 3. Model Results.
• 4. Conclusion.
• 11 Modeling the Piriform Cortex.
• 2. Summary of Data Being Modeled.
• 3. Modeling ofPhysiological Data.
• 4. Modeling of Functional Hypotheses.
• 5. Summary and Future Directions.