Stefan Wermter, Jim Austin, David J. Willshaw (Eds.):
Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing.
Lecture Notes in Computer Science 2036 Springer 2001, ISBN 3-540-42363-X
Modular Organisation and Robustness
John G. Taylor
: Images of the Mind: Brain Images and Neural Networks.
: Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System.
Ronan G. Reilly
: Collaborative Cell Assemblies: Building Blocks of Cortical Computation.
, Tamás Kiss
: The Complexity of the Brain: Structural, Functional, and Dynamic Modules.
Timing and Synchronisation
: Segmenting State into Entities and Its Implication for Learning.
: Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle.
David M. Halliday
: Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays.
Learning and Memory Storag
Michael J. Denham
: The Dynamics of Learning and Memory: Lessons from Neuroscience.
: Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation.
Gary F. Marcus
: Plasticity and Nativism: Towards a Resolution of an Apparent Paradox.
: Modelling Higher Cognitive Functions with Hebbian Cell Assemblies.
: Linguistic Computation with State Space Trajectories.
John F. Kazer
, Amanda J. C. Sharkey
: The Role of Memory, Anxiety, and Hebbian Learning in Hippocampal Function: Novel Explorations in Computational Neuroscience and Robotics.
: Using a Time-Delay Actor-Critic Neural Architecture with Dopamine-Like Reinforcement Signal for Learning in Autonomous Robots.