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Neural control engineering : the emerging intersection between control theory and neuroscience / / Steven J. Schiff
| Neural control engineering : the emerging intersection between control theory and neuroscience / / Steven J. Schiff |
| Autore | Schiff Steven J |
| Pubbl/distr/stampa | Cambridge, MA, : MIT Press, c2012 |
| Descrizione fisica | 1 online resource (403 p.) |
| Disciplina | 612.8 |
| Collana | Computational neuroscience series |
| Soggetto topico |
Computational neuroscience
Nonlinear control theory Neural Networks (Computer) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-83468-5
0-262-31208-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; Chapter 1. Introduction; 1.1 Overview; 1.2 A Motivational Example; 1.3 Least Squares; 1.4 Expectation and Covariance; 1.5 Recursive Least Squares; 1.6 It's a Bayesian World; Exercises; Chapter 2. Kalman Filtering; 2.1 Linear Kalman Filtering; 2.2 Nonlinear Kalman Filtering; 2.3 Why Not Neuroscience?; Exercises; Chapter 3. The Hodgkin-Huxley Equations; 3.1 Pre-Hodgkin and Huxley; 3.2 Hodgkin and Huxley and Colleagues; 3.3 Hodgkin and Huxley; Exercises; Chapter 4. Simplified Neuronal Models; 4.1 The Van der Pol Equations; 4.2 Frequency Demultiplication
4.3 Bonhoeffer and the Passivation of Iron 4.4 Fitzhugh and Neural Dynamics; 4.5 Nagumo's Electrical Circuit; 4.6 Rinzel's Reduction; 4.7 Simplified Models and Control; Exercises; Chapter 5. Bridging from Kalman to Neuron; 5.1 Introduction; 5.2 Variables and Parameters; 5.3 Tracking the Lorenz System; 5.4 Parameter Tracking; 5.5 The Fitzhugh-Nagumo Equations; Exercises; Chapter 6. Spatiotemporal Cortical Dynamics-The Wilson Cowan Equations; 6.1 Before Wilson and Cowan; 6.2 Wilson and Cowan before 1973; 6.3 Wilson and Cowan during 1973; 6.4 Wilson and Cowan after 1973 6.5 Spirals, Rings, and Chaotic Waves in Brain 6.6 Wilson-Cowan in a Control Framework; Exercises; Chapter 7. Empirical Models; 7.1 Overview; 7.2 The Second Rehnquist Court; 7.3 The Geometry of Singular Value Decomposition; 7.4 Static Image Decomposition; 7.5 Dynamic Spatiotemporal Image Analysis; 7.6 Spatiotemporal Brain Dynamics; Exercises; Chapter 8. Model Inadequacy; 8.1 Introduction; 8.2 The Philosophy of Model Inadequacy; 8.3 The Mapping Paradigm-Initial Conditions; 8.4 The Transformation Paradigm; 8.5 Generalized Synchrony; 8.6 Data Assimilation as Synchronization of Truth and Model 8.7 The Consensus Set Exercises; Chapter 9. Brain-Machine Interfaces; 9.1 Overview; 9.2 The Brain; 9.3 In the Beginning; 9.4 After the Beginning; 9.5 Beyond Bins-Moving from Rates to Points in Time; 9.6 Back from the Future; 9.7 When Bad Models Happen to Good Monkeys; 9.8 Toward the Future; Chapter 10. Parkinson's Disease; 10.1 Overview; 10.2 The Networks of Parkinson's Disease; 10.3 The Thalamus-It's Not a Simple Relay Anymore; 10.4 The Contribution of China White; 10.5 Dynamics of Parkinson's Networks; 10.6 The Deep Brain Stimulation Paradox 10.7 Reductionist Cracking the Deep Brain Stimulation Paradox 10.8 A Cost Function for Deep Brain Stimulation; 10.9 Fusing Experimental GPi Recordings with DBS Models; 10.10 Toward a Control Framework for Parkinson's Disease; 10.11 Looking Forward; Chapter 11. Control Systems with Electrical Fields; 11.1 Introduction; 11.2 A Brief History of the Science of Electrical Fields and Neurons; 11.3 Applications of Electrical Fields in Vitro; 11.4 A Brief Affair with Chaos; 11.5 And a Fling with Ice Ages; 11.6 Feedback Control with Electrical Fields 11.7 Controlling Propagation-Speed Bumps for the Brain |
| Record Nr. | UNINA-9910462011603321 |
Schiff Steven J
|
||
| Cambridge, MA, : MIT Press, c2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Neural control engineering : the emerging intersection between control theory and neuroscience / / Steven J. Schiff
| Neural control engineering : the emerging intersection between control theory and neuroscience / / Steven J. Schiff |
| Autore | Schiff Steven J |
| Pubbl/distr/stampa | Cambridge, MA, : MIT Press, ©2012 |
| Descrizione fisica | 1 online resource (403 p.) |
| Disciplina | 612.8 |
| Collana | Computational neuroscience series |
| Soggetto topico |
Computational neuroscience
Nonlinear control theory |
| Soggetto non controllato | NEUROSCIENCE/General |
| ISBN |
1-283-83468-5
0-262-31208-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; Chapter 1. Introduction; 1.1 Overview; 1.2 A Motivational Example; 1.3 Least Squares; 1.4 Expectation and Covariance; 1.5 Recursive Least Squares; 1.6 It's a Bayesian World; Exercises; Chapter 2. Kalman Filtering; 2.1 Linear Kalman Filtering; 2.2 Nonlinear Kalman Filtering; 2.3 Why Not Neuroscience?; Exercises; Chapter 3. The Hodgkin-Huxley Equations; 3.1 Pre-Hodgkin and Huxley; 3.2 Hodgkin and Huxley and Colleagues; 3.3 Hodgkin and Huxley; Exercises; Chapter 4. Simplified Neuronal Models; 4.1 The Van der Pol Equations; 4.2 Frequency Demultiplication
4.3 Bonhoeffer and the Passivation of Iron 4.4 Fitzhugh and Neural Dynamics; 4.5 Nagumo's Electrical Circuit; 4.6 Rinzel's Reduction; 4.7 Simplified Models and Control; Exercises; Chapter 5. Bridging from Kalman to Neuron; 5.1 Introduction; 5.2 Variables and Parameters; 5.3 Tracking the Lorenz System; 5.4 Parameter Tracking; 5.5 The Fitzhugh-Nagumo Equations; Exercises; Chapter 6. Spatiotemporal Cortical Dynamics-The Wilson Cowan Equations; 6.1 Before Wilson and Cowan; 6.2 Wilson and Cowan before 1973; 6.3 Wilson and Cowan during 1973; 6.4 Wilson and Cowan after 1973 6.5 Spirals, Rings, and Chaotic Waves in Brain 6.6 Wilson-Cowan in a Control Framework; Exercises; Chapter 7. Empirical Models; 7.1 Overview; 7.2 The Second Rehnquist Court; 7.3 The Geometry of Singular Value Decomposition; 7.4 Static Image Decomposition; 7.5 Dynamic Spatiotemporal Image Analysis; 7.6 Spatiotemporal Brain Dynamics; Exercises; Chapter 8. Model Inadequacy; 8.1 Introduction; 8.2 The Philosophy of Model Inadequacy; 8.3 The Mapping Paradigm-Initial Conditions; 8.4 The Transformation Paradigm; 8.5 Generalized Synchrony; 8.6 Data Assimilation as Synchronization of Truth and Model 8.7 The Consensus Set Exercises; Chapter 9. Brain-Machine Interfaces; 9.1 Overview; 9.2 The Brain; 9.3 In the Beginning; 9.4 After the Beginning; 9.5 Beyond Bins-Moving from Rates to Points in Time; 9.6 Back from the Future; 9.7 When Bad Models Happen to Good Monkeys; 9.8 Toward the Future; Chapter 10. Parkinson's Disease; 10.1 Overview; 10.2 The Networks of Parkinson's Disease; 10.3 The Thalamus-It's Not a Simple Relay Anymore; 10.4 The Contribution of China White; 10.5 Dynamics of Parkinson's Networks; 10.6 The Deep Brain Stimulation Paradox 10.7 Reductionist Cracking the Deep Brain Stimulation Paradox 10.8 A Cost Function for Deep Brain Stimulation; 10.9 Fusing Experimental GPi Recordings with DBS Models; 10.10 Toward a Control Framework for Parkinson's Disease; 10.11 Looking Forward; Chapter 11. Control Systems with Electrical Fields; 11.1 Introduction; 11.2 A Brief History of the Science of Electrical Fields and Neurons; 11.3 Applications of Electrical Fields in Vitro; 11.4 A Brief Affair with Chaos; 11.5 And a Fling with Ice Ages; 11.6 Feedback Control with Electrical Fields 11.7 Controlling Propagation-Speed Bumps for the Brain |
| Record Nr. | UNINA-9910786339303321 |
|
Schiff Steven J
|
||
| Cambridge, MA, : MIT Press, ©2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Neural control engineering : the emerging intersection between control theory and neuroscience / / Steven J. Schiff
| Neural control engineering : the emerging intersection between control theory and neuroscience / / Steven J. Schiff |
| Autore | Schiff Steven J |
| Pubbl/distr/stampa | Cambridge, MA, : MIT Press, ©2012 |
| Descrizione fisica | 1 online resource (403 p.) |
| Disciplina | 612.8 |
| Collana | Computational neuroscience series |
| Soggetto topico |
Computational neuroscience
Nonlinear control theory |
| Soggetto non controllato | NEUROSCIENCE/General |
| ISBN |
1-283-83468-5
0-262-31208-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; Chapter 1. Introduction; 1.1 Overview; 1.2 A Motivational Example; 1.3 Least Squares; 1.4 Expectation and Covariance; 1.5 Recursive Least Squares; 1.6 It's a Bayesian World; Exercises; Chapter 2. Kalman Filtering; 2.1 Linear Kalman Filtering; 2.2 Nonlinear Kalman Filtering; 2.3 Why Not Neuroscience?; Exercises; Chapter 3. The Hodgkin-Huxley Equations; 3.1 Pre-Hodgkin and Huxley; 3.2 Hodgkin and Huxley and Colleagues; 3.3 Hodgkin and Huxley; Exercises; Chapter 4. Simplified Neuronal Models; 4.1 The Van der Pol Equations; 4.2 Frequency Demultiplication
4.3 Bonhoeffer and the Passivation of Iron 4.4 Fitzhugh and Neural Dynamics; 4.5 Nagumo's Electrical Circuit; 4.6 Rinzel's Reduction; 4.7 Simplified Models and Control; Exercises; Chapter 5. Bridging from Kalman to Neuron; 5.1 Introduction; 5.2 Variables and Parameters; 5.3 Tracking the Lorenz System; 5.4 Parameter Tracking; 5.5 The Fitzhugh-Nagumo Equations; Exercises; Chapter 6. Spatiotemporal Cortical Dynamics-The Wilson Cowan Equations; 6.1 Before Wilson and Cowan; 6.2 Wilson and Cowan before 1973; 6.3 Wilson and Cowan during 1973; 6.4 Wilson and Cowan after 1973 6.5 Spirals, Rings, and Chaotic Waves in Brain 6.6 Wilson-Cowan in a Control Framework; Exercises; Chapter 7. Empirical Models; 7.1 Overview; 7.2 The Second Rehnquist Court; 7.3 The Geometry of Singular Value Decomposition; 7.4 Static Image Decomposition; 7.5 Dynamic Spatiotemporal Image Analysis; 7.6 Spatiotemporal Brain Dynamics; Exercises; Chapter 8. Model Inadequacy; 8.1 Introduction; 8.2 The Philosophy of Model Inadequacy; 8.3 The Mapping Paradigm-Initial Conditions; 8.4 The Transformation Paradigm; 8.5 Generalized Synchrony; 8.6 Data Assimilation as Synchronization of Truth and Model 8.7 The Consensus Set Exercises; Chapter 9. Brain-Machine Interfaces; 9.1 Overview; 9.2 The Brain; 9.3 In the Beginning; 9.4 After the Beginning; 9.5 Beyond Bins-Moving from Rates to Points in Time; 9.6 Back from the Future; 9.7 When Bad Models Happen to Good Monkeys; 9.8 Toward the Future; Chapter 10. Parkinson's Disease; 10.1 Overview; 10.2 The Networks of Parkinson's Disease; 10.3 The Thalamus-It's Not a Simple Relay Anymore; 10.4 The Contribution of China White; 10.5 Dynamics of Parkinson's Networks; 10.6 The Deep Brain Stimulation Paradox 10.7 Reductionist Cracking the Deep Brain Stimulation Paradox 10.8 A Cost Function for Deep Brain Stimulation; 10.9 Fusing Experimental GPi Recordings with DBS Models; 10.10 Toward a Control Framework for Parkinson's Disease; 10.11 Looking Forward; Chapter 11. Control Systems with Electrical Fields; 11.1 Introduction; 11.2 A Brief History of the Science of Electrical Fields and Neurons; 11.3 Applications of Electrical Fields in Vitro; 11.4 A Brief Affair with Chaos; 11.5 And a Fling with Ice Ages; 11.6 Feedback Control with Electrical Fields 11.7 Controlling Propagation-Speed Bumps for the Brain |
| Record Nr. | UNINA-9910823685903321 |
|
Schiff Steven J
|
||
| Cambridge, MA, : MIT Press, ©2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||