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2007 3rd International IEEE/EMBS Conference on Neural Engineering : Kohala Coast, Hawaii, 2-5 May 2007
| 2007 3rd International IEEE/EMBS Conference on Neural Engineering : Kohala Coast, Hawaii, 2-5 May 2007 |
| Pubbl/distr/stampa | IEEE |
| Disciplina | 612.8 |
| Soggetto topico |
Neural networks (Neurobiology)
Neural networks (Computer science) Computational neuroscience |
| ISBN | 1-5090-8668-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
2007 3rd International IEEE/EMBS Conference on Neural Engineering
Computer Design |
| Record Nr. | UNISA-996280947903316 |
| IEEE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
2007 3rd International IEEE/EMBS Conference on Neural Engineering : Kohala Coast, Hawaii, 2-5 May 2007
| 2007 3rd International IEEE/EMBS Conference on Neural Engineering : Kohala Coast, Hawaii, 2-5 May 2007 |
| Pubbl/distr/stampa | IEEE |
| Disciplina | 612.8 |
| Soggetto topico |
Neural networks (Neurobiology)
Neural networks (Computer science) Computational neuroscience |
| ISBN | 1-5090-8668-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
2007 3rd International IEEE/EMBS Conference on Neural Engineering
Computer Design |
| Record Nr. | UNINA-9910143014003321 |
| IEEE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Neural Computation, Machine Learning, and Cognitive Research VI : Selected Papers from the XXIV International Conference on Neuroinformatics, October 17-21, 2022, Moscow, Russia / / edited by Boris Kryzhanovsky, Witali Dunin-Barkowski, Vladimir Redko, Yury Tiumentsev
| Advances in Neural Computation, Machine Learning, and Cognitive Research VI : Selected Papers from the XXIV International Conference on Neuroinformatics, October 17-21, 2022, Moscow, Russia / / edited by Boris Kryzhanovsky, Witali Dunin-Barkowski, Vladimir Redko, Yury Tiumentsev |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (585 pages) |
| Disciplina |
745.05
006.32 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Machine learning Computational neuroscience Computational Intelligence Machine Learning Computational Neuroscience |
| ISBN | 3-031-19032-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I: Neuroinformatics and Artificial Intelligence -- Tree Inventory with LiDAR Data -- Towards Reliable Solar Atmospheric Parameters Neural-Based Inference -- Addressing Task Prioritization in Model-based Reinforcement Learning -- Automatic Generation of Conversational Skills from Dialog Datasets -- Part II: Neural Networks and Cognitive Sciences. Adaptive Behavior and Evolutionary Simulation -- Individual Topology Structure of Eye Movement Trajectories -- Neural Network Providing the Involvement of Voluntary Attention into the Processing and Conscious Perception of Sensory Information -- Alpha Rhythm Dynamics During Spoken Word Recognition -- Robotic Devices Control Based on Neuromorphic Classifiers of Imaginary Motor Commands -- A Software System for Training Motor Imagery in Virtual Reality -- On the Importance of Diversity -- “MYO-chat” – A New Computer Control System for People with Disabilities -- Low-bit Quantization of Transformer for Audio Speech Recognition -- A Model of Predicting and Using Regularities by an Autonomous Agent -- A Review of One-Shot Neural Architecture Search Methods -- Does a Recurrent Neural Network Use Reflection During a Reflexive Game? -- A Gender Genetic Algorithm and its Comparison with Conventional Genetic Algorithm -- Associations of Morphometric Changes of the Brain with the Levels of IGF1, a Multifunctional Growth Factor, and with Systemic Immune Parameters Reflect the Disturbances of Neuroimmune Interactions in Patients with Schizophrenia -- Part III: Modern Methods and Technologies in Neurobiology -- Dynamics of Background and Evoked Activity of Neurons in the Auditory Cortex of the Unanaesthetized Cat -- Search for Markers of Moderate Cognitive Disorders through Phase Synchronization between Rhythmic Photostimulus and EEG Pattern -- Astrocytes Enhance Image Representation Encoded in Spiking Neural Network -- Classification of Neuron Type Based on Average Activity -- Comparative Analysis of Statistical and Neural Network Classification Methods on the Example of Synthesized Data in the Stimulus-Independent Brain-Computer Interface Paradigm -- Shunting Effect of Synaptic Channels Located on Presynaptic Terminal -- Analysis of Appearances, Formation and Evolution of Biological Functional Systems -- The Reinforcement Learning Theory, Value Function, and the Nature of Value Function Calculation by the Insular Cortex -- To the Role of Inferior Olives in Cerebellar Neuromechanics -- Individual Differences in Mismatch-Induced c-Fos Expression in the Retrosplenial Cortex in Rats: Shift in Activity is Layer-Specific -- Sleep of Poor and Good Nappers under the Afternoon Exposure to Weak 2-Hz/8-Hz Electromagnetic Fields -- Part IV: Applications of Neural Networks -- Classification of Light Microscopy Image Using Probabilistic Bayesian Neural Network -- SPICE Model of Analog Content-Addressable Memory Based on 2G FeFET Crossbar -- IQ-GAN: Instance Quantized Image Synthesis -- Specifics of Crossbar Resistor Arrays -- Recurrent and Graph Neural Networks for Particle Tracking at the BM@N Experiment -- Modeling of a Neural Network Algorithm for Suppressing Non-Stationary Interference in an Adaptive Antenna Array -- Learning Various Locomotion Skills from Scratch with Deep Reinforcement Learning -- Center3dAugNet: Effect of Rotation Representation on One-Stage Joint Car Detection and 6D-Pose Estimation -- Global memory transformer for processing long documents -- Development of the Convolutional Neural Network for Defining the Renal Pathology Using Computed Tomography Images -- Possibility of Using Various Architectures of Convolutional Neural Networks in the Problem of Determining the Type of Rhythm -- DeepPavlov Topics: Topic Classification Dataset for Conversational Domain in English -- Multi-Input Convolutional Neural Networks in Real-Time Semantic Segmentation Tasks -- Integration of Data and Algorithms in Solving Inverse Problems of Spectroscopy of Solutions by Machine Learning Methods -- Investigation of Pareto Front of Neural Network Approximation of Solution of Laplace Equation in Two Statements: with Discontinuous Initial Conditions or with Measurement Data? -- Multitask learning for extensive object description to improve scene understanding on monocular video -- Use of Classification Algorithms to Predict the Grade of Geomagnetic Disturbance -- Information processing in spiking neuron-astrocyte network in ageing -- Multilingual Case-insensitive Named Entity Recognition -- Multi-level Pipeline for Data Mining with Similar Structure -- Creating a Brief Review of Judicial Practice Using Clustering Methods -- Part V: Neural Network Theory, Concepts and Architectures -- "Gas” instead of “Liquid”: which Liquid State Machine is Better? -- Using a Resistor Array to Tackle Optimization Problems -- Generative Adversarial Networks as an Approach to Unsupervised Link Prediction Problem -- DGAC: Dialog Graph AutoConstruction up on Data with a Regular Structure -- Relay System of Differential Equations with Delay as a Perceptron Model -- Analysis of Predictive Capabilities of Adaptive Multilayer Models with Physics-Based Architecture for Duffing Oscillator? -- An Attempt to Formalize the Formulation of the Network Architecture Search Problem for Convolutional Neural Networks -- Use of Conditional Variational Autoencoders and Partial Least Squares in Solving an Inverse Problem of Spectroscopy -- On the Similarities between Denoising Diffusion Models and Autoencoders. |
| Record Nr. | UNINA-9910627241903321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Basal ganglia [[electronic resource] ] : physiological, behavioral, and computational studies / / topic editors: Ahmed A. Moustafa, Alon Korngreen, Izhar Bar-Gad and Hagai Bergman
| Basal ganglia [[electronic resource] ] : physiological, behavioral, and computational studies / / topic editors: Ahmed A. Moustafa, Alon Korngreen, Izhar Bar-Gad and Hagai Bergman |
| Autore | Ahmed A. Moustafa |
| Pubbl/distr/stampa | Frontiers Media SA, 2015 |
| Descrizione fisica | 1 online resource (494 pages) : illustrations; digital, PDF file(s) |
| Collana |
Frontiers Research Topics
Frontiers in Computational Neuroscience Frontiers in Systems Neuroscience |
| Soggetto topico |
Basal ganglia
Basal ganglia - Physiology Basal ganglia - Research Computational neuroscience Neurobiology - Mathematical models Basal Ganglia - physiopathology |
| Soggetto genere / forma | Congress. |
| Soggetto non controllato |
Subthalamic Nucleus
dopaime Parkinson's disease (PD) human imagine studies animal studies Basal Ganglia computational modeling |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910137217403321 |
Ahmed A. Moustafa
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| Frontiers Media SA, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Bayesian Filter Design for Computational Medicine : A State-Space Estimation Framework / / by Dilranjan S. Wickramasuriya, Rose T. Faghih
| Bayesian Filter Design for Computational Medicine : A State-Space Estimation Framework / / by Dilranjan S. Wickramasuriya, Rose T. Faghih |
| Autore | Wickramasuriya Dilranjan S |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (235 pages) |
| Disciplina |
612.8
570.285 |
| Altri autori (Persone) | FaghihRose T |
| Soggetto topico |
Computational neuroscience
Neurotechnology (Bioengineering) Biomedical engineering Signal processing Biophysics Cell interaction Computational Neuroscience Neuroengineering Biomedical Engineering and Bioengineering Digital and Analog Signal Processing Mechanobiological Cell Signaling |
| ISBN | 3-031-47104-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Some Useful Statistical Results -- State-space Model with One Binary Observation -- State-space Model with One Binary and One Continuous Observation -- State-space Model with One Binary and Two Continuous Observations -- State-space Model with One Binary, Two Continuous and a Spiking-type Observation -- State-space Model with One Marked Point Process (MPP) Observation -- Additional Models and Derivations -- MATLAB Code Examples -- List of Supplementary MATLAB Functions. |
| Record Nr. | UNINA-9910845077403321 |
|
Wickramasuriya Dilranjan S
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Biophysics of computation [[electronic resource] ] : information processing in single neurons / / Christof Koch
| Biophysics of computation [[electronic resource] ] : information processing in single neurons / / Christof Koch |
| Autore | Koch Christof <1956-> |
| Pubbl/distr/stampa | New York, : Oxford University Press, 1999 |
| Descrizione fisica | 1 online resource (587 p.) |
| Disciplina | 573.8/536 |
| Collana | Computational neuroscience |
| Soggetto topico |
Computational neuroscience
Neurons Neural networks (Neurobiology) Action potentials (Electrophysiology) Neural conduction |
| Soggetto genere / forma | Electronic books. |
| ISBN |
0-19-756233-7
1-280-59509-4 9786613624925 0-19-976055-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Preface; List of Symbols; Introduction; 1 The Membrane Equation; 1.1 Structure of the Passive Neuronal Membrane; 1.1.1 Resting Potential; 1.1.2 Membrane Capacity; 1.1.3 Membrane Resistance; 1.2 A Simple RC Circuit; 1.3 RC Circuits as Linear Systems; 1.3.1 Filtering by RC Circuits; 1.4 Synaptic Input; 1.5 Synaptic Input Is Nonlinear; 1.5.1 Synaptic Input, Saturation, and the Membrane Time Constant; 1.5.2 Synaptic Interactions among Excitation and Shunting Inhibition; 1.5.3 Gain Normalization in Visual Cortex and Synaptic Input; 1.6 Recapitulation; 2 Linear Cable Theory
2.1 Basic Assumptions Underlying One-Dimensional Cable Theory2.1.1 Linear Cable Equation; 2.2 Steady-State Solutions; 2.2.1 Infinite Cable; 2.2.2 Finite Cable; 2.3 Time-Dependent Solutions; 2.3.1 Infinite Cable; 2.3.2 Finite Cable; 2.4 Neuronal Delays and Propagation Velocity; 2.5 Recapitulation; 3 Passive Dendritic Trees; 3.1 Branched Cables; 3.1.1 What Happens at Branch Points?; 3.2 Equivalent Cylinder; 3.3 Solving the Linear Cable Equation for Branched Structures; 3.3.1 Exact Methods; 3.3.2 Compartmental Modeling; 3.4 Transfer Resistances; 3.4.1 General Definition; 3.4.2 An Example 3.4.3 Properties of K[sub(ij)]3.4.4 Transfer Resistances in a Pyramidal Cell; 3.5 Measures of Synaptic Efficiency; 3.5.1 Electrotonic Distance; 3.5.2 Voltage Attenuation; 3.5.3 Charge Attenuation; 3.5.4 Graphical Morphoelectrotonic Transforms; 3.6 Signal Delays in Dendritic Trees; 3.6.1 Experimental Determination of T[sub(m)]; 3.6.2 Local and Propagation Delays in Dendritic Trees; 3.6.3 Dependence of Fast Synaptic Inputs on Cable Parameters; 3.7 Recapitulation; 4 Synaptic Input; 4.1 Neuronal and Synaptic Packing Densities; 4.2 Synaptic Transmission Is Stochastic 4.2.1 Probability of Synaptic Release p4.2.2 What Is the Synaptic Weight?; 4.3 Neurotransmitters; 4.4 Synaptic Receptors; 4.5 Synaptic Input as Conductance Change; 4.5.1 Synaptic Reversal Potential in Series with an Increase in Conductance; 4.5.2 Conductance Decreasing Synapses; 4.6 Excitatory NMDA and Non-NMDA Synaptic Input; 4.7 Inhibitory GABAergic Synaptic Input; 4.8 Postsynaptic Potential; 4.8.1 Stationary Synaptic Input; 4.8.2 Transient Synaptic Input; 4.8.3 Infinitely Fast Synaptic Input; 4.9 Visibility of Synaptic Inputs; 4.9.1 Input Impedance in the Presence of Synaptic Input 4.10 Electrical Gap Junctions4.11 Recapitulation; 5 Synaptic Interactions in a Passive Dendritic Tree; 5.1 Nonlinear Interaction among Excitation and Inhibition; 5.1.1 Absolute versus Relative Suppression; 5.1.2 General Analysis of Synaptic Interaction in a Passive Tree; 5.1.3 Location of the Inhibitory Synapse; 5.1.4 Shunting Inhibition Implements a ""Dirty"" Multiplication; 5.1.5 Hyperpolarizing Inhibition Acts Like a Linear Subtraction; 5.1.6 Functional Interpretation of the Synaptic Architecture and Dendritic Morphology: AND-NOT Gates 5.1.7 Retinal Directional Selectivity and Synaptic Logic |
| Record Nr. | UNINA-9910457836903321 |
|
Koch Christof <1956->
|
||
| New York, : Oxford University Press, 1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Biophysics of computation [[electronic resource] ] : information processing in single neurons / / Christof Koch
| Biophysics of computation [[electronic resource] ] : information processing in single neurons / / Christof Koch |
| Autore | Koch Christof <1956-> |
| Pubbl/distr/stampa | New York, : Oxford University Press, 1999 |
| Descrizione fisica | 1 online resource (587 p.) |
| Disciplina | 573.8/536 |
| Collana | Computational neuroscience |
| Soggetto topico |
Computational neuroscience
Neurons Neural networks (Neurobiology) Action potentials (Electrophysiology) Neural conduction |
| ISBN |
0-19-029285-7
0-19-756233-7 1-280-59509-4 9786613624925 0-19-976055-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Preface; List of Symbols; Introduction; 1 The Membrane Equation; 1.1 Structure of the Passive Neuronal Membrane; 1.1.1 Resting Potential; 1.1.2 Membrane Capacity; 1.1.3 Membrane Resistance; 1.2 A Simple RC Circuit; 1.3 RC Circuits as Linear Systems; 1.3.1 Filtering by RC Circuits; 1.4 Synaptic Input; 1.5 Synaptic Input Is Nonlinear; 1.5.1 Synaptic Input, Saturation, and the Membrane Time Constant; 1.5.2 Synaptic Interactions among Excitation and Shunting Inhibition; 1.5.3 Gain Normalization in Visual Cortex and Synaptic Input; 1.6 Recapitulation; 2 Linear Cable Theory
2.1 Basic Assumptions Underlying One-Dimensional Cable Theory2.1.1 Linear Cable Equation; 2.2 Steady-State Solutions; 2.2.1 Infinite Cable; 2.2.2 Finite Cable; 2.3 Time-Dependent Solutions; 2.3.1 Infinite Cable; 2.3.2 Finite Cable; 2.4 Neuronal Delays and Propagation Velocity; 2.5 Recapitulation; 3 Passive Dendritic Trees; 3.1 Branched Cables; 3.1.1 What Happens at Branch Points?; 3.2 Equivalent Cylinder; 3.3 Solving the Linear Cable Equation for Branched Structures; 3.3.1 Exact Methods; 3.3.2 Compartmental Modeling; 3.4 Transfer Resistances; 3.4.1 General Definition; 3.4.2 An Example 3.4.3 Properties of K[sub(ij)]3.4.4 Transfer Resistances in a Pyramidal Cell; 3.5 Measures of Synaptic Efficiency; 3.5.1 Electrotonic Distance; 3.5.2 Voltage Attenuation; 3.5.3 Charge Attenuation; 3.5.4 Graphical Morphoelectrotonic Transforms; 3.6 Signal Delays in Dendritic Trees; 3.6.1 Experimental Determination of T[sub(m)]; 3.6.2 Local and Propagation Delays in Dendritic Trees; 3.6.3 Dependence of Fast Synaptic Inputs on Cable Parameters; 3.7 Recapitulation; 4 Synaptic Input; 4.1 Neuronal and Synaptic Packing Densities; 4.2 Synaptic Transmission Is Stochastic 4.2.1 Probability of Synaptic Release p4.2.2 What Is the Synaptic Weight?; 4.3 Neurotransmitters; 4.4 Synaptic Receptors; 4.5 Synaptic Input as Conductance Change; 4.5.1 Synaptic Reversal Potential in Series with an Increase in Conductance; 4.5.2 Conductance Decreasing Synapses; 4.6 Excitatory NMDA and Non-NMDA Synaptic Input; 4.7 Inhibitory GABAergic Synaptic Input; 4.8 Postsynaptic Potential; 4.8.1 Stationary Synaptic Input; 4.8.2 Transient Synaptic Input; 4.8.3 Infinitely Fast Synaptic Input; 4.9 Visibility of Synaptic Inputs; 4.9.1 Input Impedance in the Presence of Synaptic Input 4.10 Electrical Gap Junctions4.11 Recapitulation; 5 Synaptic Interactions in a Passive Dendritic Tree; 5.1 Nonlinear Interaction among Excitation and Inhibition; 5.1.1 Absolute versus Relative Suppression; 5.1.2 General Analysis of Synaptic Interaction in a Passive Tree; 5.1.3 Location of the Inhibitory Synapse; 5.1.4 Shunting Inhibition Implements a ""Dirty"" Multiplication; 5.1.5 Hyperpolarizing Inhibition Acts Like a Linear Subtraction; 5.1.6 Functional Interpretation of the Synaptic Architecture and Dendritic Morphology: AND-NOT Gates 5.1.7 Retinal Directional Selectivity and Synaptic Logic |
| Record Nr. | UNINA-9910779059703321 |
|
Koch Christof <1956->
|
||
| New York, : Oxford University Press, 1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Biophysics of computation : information processing in single neurons / / Christof Koch
| Biophysics of computation : information processing in single neurons / / Christof Koch |
| Autore | Koch Christof <1956-> |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York, : Oxford University Press, 1999 |
| Descrizione fisica | 1 online resource (587 p.) |
| Disciplina |
573.8/536
573.8536 |
| Collana | Computational neuroscience |
| Soggetto topico |
Computational neuroscience
Neurons Neural networks (Neurobiology) Action potentials (Electrophysiology) Neural conduction |
| ISBN |
0-19-029285-7
0-19-756233-7 1-280-59509-4 9786613624925 0-19-976055-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Contents; Preface; List of Symbols; Introduction; 1 The Membrane Equation; 1.1 Structure of the Passive Neuronal Membrane; 1.1.1 Resting Potential; 1.1.2 Membrane Capacity; 1.1.3 Membrane Resistance; 1.2 A Simple RC Circuit; 1.3 RC Circuits as Linear Systems; 1.3.1 Filtering by RC Circuits; 1.4 Synaptic Input; 1.5 Synaptic Input Is Nonlinear; 1.5.1 Synaptic Input, Saturation, and the Membrane Time Constant; 1.5.2 Synaptic Interactions among Excitation and Shunting Inhibition; 1.5.3 Gain Normalization in Visual Cortex and Synaptic Input; 1.6 Recapitulation; 2 Linear Cable Theory
2.1 Basic Assumptions Underlying One-Dimensional Cable Theory2.1.1 Linear Cable Equation; 2.2 Steady-State Solutions; 2.2.1 Infinite Cable; 2.2.2 Finite Cable; 2.3 Time-Dependent Solutions; 2.3.1 Infinite Cable; 2.3.2 Finite Cable; 2.4 Neuronal Delays and Propagation Velocity; 2.5 Recapitulation; 3 Passive Dendritic Trees; 3.1 Branched Cables; 3.1.1 What Happens at Branch Points?; 3.2 Equivalent Cylinder; 3.3 Solving the Linear Cable Equation for Branched Structures; 3.3.1 Exact Methods; 3.3.2 Compartmental Modeling; 3.4 Transfer Resistances; 3.4.1 General Definition; 3.4.2 An Example 3.4.3 Properties of K[sub(ij)]3.4.4 Transfer Resistances in a Pyramidal Cell; 3.5 Measures of Synaptic Efficiency; 3.5.1 Electrotonic Distance; 3.5.2 Voltage Attenuation; 3.5.3 Charge Attenuation; 3.5.4 Graphical Morphoelectrotonic Transforms; 3.6 Signal Delays in Dendritic Trees; 3.6.1 Experimental Determination of T[sub(m)]; 3.6.2 Local and Propagation Delays in Dendritic Trees; 3.6.3 Dependence of Fast Synaptic Inputs on Cable Parameters; 3.7 Recapitulation; 4 Synaptic Input; 4.1 Neuronal and Synaptic Packing Densities; 4.2 Synaptic Transmission Is Stochastic 4.2.1 Probability of Synaptic Release p4.2.2 What Is the Synaptic Weight?; 4.3 Neurotransmitters; 4.4 Synaptic Receptors; 4.5 Synaptic Input as Conductance Change; 4.5.1 Synaptic Reversal Potential in Series with an Increase in Conductance; 4.5.2 Conductance Decreasing Synapses; 4.6 Excitatory NMDA and Non-NMDA Synaptic Input; 4.7 Inhibitory GABAergic Synaptic Input; 4.8 Postsynaptic Potential; 4.8.1 Stationary Synaptic Input; 4.8.2 Transient Synaptic Input; 4.8.3 Infinitely Fast Synaptic Input; 4.9 Visibility of Synaptic Inputs; 4.9.1 Input Impedance in the Presence of Synaptic Input 4.10 Electrical Gap Junctions4.11 Recapitulation; 5 Synaptic Interactions in a Passive Dendritic Tree; 5.1 Nonlinear Interaction among Excitation and Inhibition; 5.1.1 Absolute versus Relative Suppression; 5.1.2 General Analysis of Synaptic Interaction in a Passive Tree; 5.1.3 Location of the Inhibitory Synapse; 5.1.4 Shunting Inhibition Implements a ""Dirty"" Multiplication; 5.1.5 Hyperpolarizing Inhibition Acts Like a Linear Subtraction; 5.1.6 Functional Interpretation of the Synaptic Architecture and Dendritic Morphology: AND-NOT Gates 5.1.7 Retinal Directional Selectivity and Synaptic Logic |
| Record Nr. | UNINA-9910825116003321 |
|
Koch Christof <1956->
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| New York, : Oxford University Press, 1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Brain computation as hierarchical abstraction / / Dana H. Ballard
| Brain computation as hierarchical abstraction / / Dana H. Ballard |
| Autore | Ballard Dana H (Dana Harry), <1946-> |
| Pubbl/distr/stampa | Cambridge, Massachusetts : , : The MIT Press, , [2015] |
| Descrizione fisica | 1 online resource (xiv, 440 pages) : illustrations (black and white, and colour) |
| Disciplina | 612.8/23343 |
| Collana | Computational neuroscience |
| Soggetto topico |
Computational neuroscience
Neurobiology |
| Soggetto non controllato | NEUROSCIENCE/General |
| ISBN |
0-262-32382-6
0-262-53412-6 0-262-32381-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910463718403321 |
|
Ballard Dana H (Dana Harry), <1946->
|
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| Cambridge, Massachusetts : , : The MIT Press, , [2015] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Brain computation as hierarchical abstraction / / Dana H. Ballard
| Brain computation as hierarchical abstraction / / Dana H. Ballard |
| Autore | Ballard Dana H (Dana Harry), <1946-> |
| Pubbl/distr/stampa | Cambridge, Massachusetts : , : The MIT Press, , [2015] |
| Descrizione fisica | 1 online resource (xiv, 440 pages) : illustrations (black and white, and colour) |
| Disciplina | 612.8/23343 |
| Collana | Computational neuroscience |
| Soggetto topico |
Computational neuroscience
Neurobiology |
| Soggetto non controllato | NEUROSCIENCE/General |
| ISBN |
0-262-32382-6
0-262-53412-6 0-262-32381-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910788171203321 |
|
Ballard Dana H (Dana Harry), <1946->
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| Cambridge, Massachusetts : , : The MIT Press, , [2015] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
