Coverart for item
The Resource Emergent neural computational architectures based on neuroscience : towards neuroscience-inspired computing, Stefan Wermter, Jim Austin, David J. Willshaw, eds.

Emergent neural computational architectures based on neuroscience : towards neuroscience-inspired computing, Stefan Wermter, Jim Austin, David J. Willshaw, eds.

Label
Emergent neural computational architectures based on neuroscience : towards neuroscience-inspired computing
Title
Emergent neural computational architectures based on neuroscience
Title remainder
towards neuroscience-inspired computing
Statement of responsibility
Stefan Wermter, Jim Austin, David J. Willshaw, eds.
Contributor
Subject
Language
eng
Cataloging source
DLC
Index
index present
Language note
English
Literary form
non fiction
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Austin, Jim
  • Wermter, Stefan
  • Willshaw, David J
Series statement
Lecture notes in computer science. Lecture notes in artificial intelligence
Series volume
2036.
http://library.link/vocab/subjectName
  • Computer architecture
  • Neural computers
  • Neural networks (Computer science)
Label
Emergent neural computational architectures based on neuroscience : towards neuroscience-inspired computing, Stefan Wermter, Jim Austin, David J. Willshaw, eds.
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Contents
  • p. 1
  • Towards Novel, Neuroscience-Inspired Computing/
  • Stefan Wermter
  • Jim Austin
  • David Willshaw
  • Images of the Mind: Brain Images and Neural Networks/
  • John G. Taylor
  • p. 20
  • Stimulus-Independent Data Analysis for fMRI/
  • Silke Dodel
  • J. Michael Herrman
  • Theo Geisel
  • p. 39
  • Emergence of Modularity within One Sheet of Neurons: A Model Comparison/
  • Cornelius Weber
  • Klaus Obermayer
  • p. 53
  • Computational Investigation of Hemispheric Specialization and Interactions/
  • James A. Reggia
  • Yuri Shkuro
  • Natalia Shevtsova
  • p. 68
  • Explorations of the Interaction between Split Processing and Stimulus Types/
  • John Hicks
  • Padraic Monaghan
  • p. 83
  • Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization/
  • Joanna Bryson
  • Lynn Andrea Stein
  • p. 98
  • Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System/
  • Gustavo Deco
  • p. 114
  • Recurrent Long-Range Interactions in Early Vision/
  • Thorsten Hansen
  • Wolfgang Sepp
  • Heiko Neumann
  • p. 127
  • Neural Mechanisms for Representing Surface and Contour Features/
  • Thorsten Hansen
  • Heiko Neumann
  • p. 139
  • Representations of Neuronal Models Using Minimal and Bilinear Realisations/
  • Gary G. R. Green
  • Will Woods
  • S. Manchanda
  • p. 154
  • Collaborative Cell Assemblies: Building Blocks of Cortical Computation/
  • Ronan G. Reilly
  • p. 161
  • On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex/
  • Hauke Bartsch
  • Martin Stetter
  • Klaus Obermayer
  • p. 174
  • p. 188
  • Towards Computational Neural Systems through Developmental Evolution/
  • Alistair G. Rust
  • Rod Adams
  • Stella George
  • Complexity of the Brain: Structural, Functional, and Dynamic Modules/
  • Peter Erdi
  • Tamas Kiss
  • p. 203
  • Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission/
  • Simon R. Schultz
  • Huw D. R. Golledge
  • Stefano Panzeri
  • p. 212
  • Segmenting State into Entities and Its Implication for Learning/
  • James Henderson
  • p. 227
  • Temporal Structure of Neural Activity and Modelling of Information Processing in the Brain/
  • Roman Borisyuk
  • Galina Borisyuk
  • Yakov Kazanovich
  • p. 237
  • Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle/
  • Guido Bugmann
  • p. 255
  • Locust Olfaction (Synchronous Oscillations in Excitatory and Inhibitory Groups of Spiking Neurons)/
  • David C. Sterratt
  • p. 270
  • Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays/
  • David M. Halliday
  • p. 285
  • Role of Brain Chaos/
  • Peter Andras
  • p. 296
  • Neural Network Classification of Word Evoked Neuromagnetic Brain Activity/
  • Ramin Assadollahi
  • Friedemann Pulvermuller
  • p. 311
  • p. 320
  • Simulation Studies of the Speed of Recurrent Processing/
  • Stefano Panzeri
  • Edmund T. Rolls
  • Francesco P. Battaglia
  • Dynamics of Learning and Memory: Lessons from Neuroscience/
  • Michael J. Denham
  • p. 333
  • Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation/
  • Lokendra Shastri
  • p. 348
  • Plasticity and Nativism: Towards a Resolution of an Apparent Paradox/
  • Gary F. Marcus
  • p. 368
  • Cell Assemblies as an Intermediate Level Model of Cognition/
  • Christian R. Huyck
  • p. 383
  • Modelling Higher Cognitive Functions with Hebbian Cell Assemblies/
  • Marcin Chady
  • p. 398
  • Spiking Associative Memory and Scene Segmentation by Synchronization of Cortical Activity/
  • Andreas Knoblauch
  • Gunther Palm
  • p. 407
  • Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex/
  • Rafal Bogacz
  • Malcolm W. Brown
  • Christophe Giraud-Carrier
  • p. 428
  • Linguistic Computation with State Space Trajectories/
  • Hermann Moisl
  • p. 442
  • p. 461
  • Robust Stimulus Encoding in Olfactory Processing: Hyperacuity and Efficient Signal Transmission/
  • Tim Pearce
  • Paul Verschure
  • Joel White
  • Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?/
  • Mikel L. Forcada
  • Rafael C. Carrasco
  • p. 480
  • Investigation into the Role of Cortical Synaptic Depression in Auditory Processing/
  • Sue L. Denham
  • Michael J. Denham
  • p. 494
  • Role of Memory, Anxiety, and Hebbian Learning in Hippocampal Function: Novel Explorations in Computational Neuroscience and Robotics/
  • John F. Kazer
  • Amanda J. C. Sharkey
  • p. 507
  • Using a Time-Delay Actor-Critic Neural Architecture with Dopamine-Like Reinforcement Signal for Learning in Autonomous Robots/
  • Andres Perez-Uribe
  • p. 522
  • Connectionist Propositional Logic (A Simple Correlation Matrix Memory Based Reasoning System)/
  • Daniel Kustrin
  • Jim Austin
  • p. 534
  • Analysis and Synthesis of Agents That Learn from Distributed Dynami Data Sources/
  • Doina Caragea
  • Adrian Silvescu
  • Vasant Honavar
  • p. 547
  • Connectionist Neuroimaging/
  • Stephen Jose Hanson
  • Michiro Negishi
  • Catherine Hanson
  • p. 560
  • Author Index.
  • p. 577
Control code
13830016
Dimensions
24 cm.
Dimensions
unknown
Extent
x, 576 p.
Isbn
9783540423638
Lccn
20010384
Other physical details
ill.
Specific material designation
remote
Label
Emergent neural computational architectures based on neuroscience : towards neuroscience-inspired computing, Stefan Wermter, Jim Austin, David J. Willshaw, eds.
Publication
Bibliography note
Includes bibliographical references and index
Contents
  • p. 1
  • Towards Novel, Neuroscience-Inspired Computing/
  • Stefan Wermter
  • Jim Austin
  • David Willshaw
  • Images of the Mind: Brain Images and Neural Networks/
  • John G. Taylor
  • p. 20
  • Stimulus-Independent Data Analysis for fMRI/
  • Silke Dodel
  • J. Michael Herrman
  • Theo Geisel
  • p. 39
  • Emergence of Modularity within One Sheet of Neurons: A Model Comparison/
  • Cornelius Weber
  • Klaus Obermayer
  • p. 53
  • Computational Investigation of Hemispheric Specialization and Interactions/
  • James A. Reggia
  • Yuri Shkuro
  • Natalia Shevtsova
  • p. 68
  • Explorations of the Interaction between Split Processing and Stimulus Types/
  • John Hicks
  • Padraic Monaghan
  • p. 83
  • Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization/
  • Joanna Bryson
  • Lynn Andrea Stein
  • p. 98
  • Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System/
  • Gustavo Deco
  • p. 114
  • Recurrent Long-Range Interactions in Early Vision/
  • Thorsten Hansen
  • Wolfgang Sepp
  • Heiko Neumann
  • p. 127
  • Neural Mechanisms for Representing Surface and Contour Features/
  • Thorsten Hansen
  • Heiko Neumann
  • p. 139
  • Representations of Neuronal Models Using Minimal and Bilinear Realisations/
  • Gary G. R. Green
  • Will Woods
  • S. Manchanda
  • p. 154
  • Collaborative Cell Assemblies: Building Blocks of Cortical Computation/
  • Ronan G. Reilly
  • p. 161
  • On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex/
  • Hauke Bartsch
  • Martin Stetter
  • Klaus Obermayer
  • p. 174
  • p. 188
  • Towards Computational Neural Systems through Developmental Evolution/
  • Alistair G. Rust
  • Rod Adams
  • Stella George
  • Complexity of the Brain: Structural, Functional, and Dynamic Modules/
  • Peter Erdi
  • Tamas Kiss
  • p. 203
  • Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission/
  • Simon R. Schultz
  • Huw D. R. Golledge
  • Stefano Panzeri
  • p. 212
  • Segmenting State into Entities and Its Implication for Learning/
  • James Henderson
  • p. 227
  • Temporal Structure of Neural Activity and Modelling of Information Processing in the Brain/
  • Roman Borisyuk
  • Galina Borisyuk
  • Yakov Kazanovich
  • p. 237
  • Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle/
  • Guido Bugmann
  • p. 255
  • Locust Olfaction (Synchronous Oscillations in Excitatory and Inhibitory Groups of Spiking Neurons)/
  • David C. Sterratt
  • p. 270
  • Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays/
  • David M. Halliday
  • p. 285
  • Role of Brain Chaos/
  • Peter Andras
  • p. 296
  • Neural Network Classification of Word Evoked Neuromagnetic Brain Activity/
  • Ramin Assadollahi
  • Friedemann Pulvermuller
  • p. 311
  • p. 320
  • Simulation Studies of the Speed of Recurrent Processing/
  • Stefano Panzeri
  • Edmund T. Rolls
  • Francesco P. Battaglia
  • Dynamics of Learning and Memory: Lessons from Neuroscience/
  • Michael J. Denham
  • p. 333
  • Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation/
  • Lokendra Shastri
  • p. 348
  • Plasticity and Nativism: Towards a Resolution of an Apparent Paradox/
  • Gary F. Marcus
  • p. 368
  • Cell Assemblies as an Intermediate Level Model of Cognition/
  • Christian R. Huyck
  • p. 383
  • Modelling Higher Cognitive Functions with Hebbian Cell Assemblies/
  • Marcin Chady
  • p. 398
  • Spiking Associative Memory and Scene Segmentation by Synchronization of Cortical Activity/
  • Andreas Knoblauch
  • Gunther Palm
  • p. 407
  • Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex/
  • Rafal Bogacz
  • Malcolm W. Brown
  • Christophe Giraud-Carrier
  • p. 428
  • Linguistic Computation with State Space Trajectories/
  • Hermann Moisl
  • p. 442
  • p. 461
  • Robust Stimulus Encoding in Olfactory Processing: Hyperacuity and Efficient Signal Transmission/
  • Tim Pearce
  • Paul Verschure
  • Joel White
  • Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?/
  • Mikel L. Forcada
  • Rafael C. Carrasco
  • p. 480
  • Investigation into the Role of Cortical Synaptic Depression in Auditory Processing/
  • Sue L. Denham
  • Michael J. Denham
  • p. 494
  • Role of Memory, Anxiety, and Hebbian Learning in Hippocampal Function: Novel Explorations in Computational Neuroscience and Robotics/
  • John F. Kazer
  • Amanda J. C. Sharkey
  • p. 507
  • Using a Time-Delay Actor-Critic Neural Architecture with Dopamine-Like Reinforcement Signal for Learning in Autonomous Robots/
  • Andres Perez-Uribe
  • p. 522
  • Connectionist Propositional Logic (A Simple Correlation Matrix Memory Based Reasoning System)/
  • Daniel Kustrin
  • Jim Austin
  • p. 534
  • Analysis and Synthesis of Agents That Learn from Distributed Dynami Data Sources/
  • Doina Caragea
  • Adrian Silvescu
  • Vasant Honavar
  • p. 547
  • Connectionist Neuroimaging/
  • Stephen Jose Hanson
  • Michiro Negishi
  • Catherine Hanson
  • p. 560
  • Author Index.
  • p. 577
Control code
13830016
Dimensions
24 cm.
Dimensions
unknown
Extent
x, 576 p.
Isbn
9783540423638
Lccn
20010384
Other physical details
ill.
Specific material designation
remote

Library Locations

    • Harold Cohen LibraryBorrow it
      Ashton Street, Liverpool, L69 3DA, GB
      53.418074 -2.967913
Processing Feedback ...