Emergent Neural Computational Architectures Based on Neuroscience Towards Neuroscience-Inspired Computing /
It is generally understood that the present approachs to computing do not have the performance, flexibility, and reliability of biological information processing systems. Although there is a comprehensive body of knowledge regarding how information processing occurs in the brain and central nervous...
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| Other Authors: | , , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2001.
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| Edition: | 1st ed. 2001. |
| Series: | Lecture Notes in Artificial Intelligence ;
2036 |
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of Contents:
- Towards Novel Neuroscience-Inspired Computing
- Towards Novel Neuroscience-Inspired Computing
- Modular Organisation and Robustness
- Images of the Mind: Brain Images and Neural Networks
- Stimulus-Independent Data Analysis for fMRI
- Emergence of Modularity within One Sheet of Neurons: A Model Comparison
- Computational Investigation of Hemispheric Specialization and Interactions
- Explorations of the Interaction between Split Processing and Stimulus Types
- Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization
- Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System
- Recurrent Long-Range Interactions in Early Vision
- Neural Mechanisms for Representing Surface and Contour Features
- Representations of Neuronal Models Using Minimal and Bilinear Realisations
- Collaborative Cell Assemblies: Building Blocks of Cortical Computation
- On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex
- Towards Computational Neural Systems through Developmental Evolution
- The Complexity of the Brain: Structural, Functional, and Dynamic Modules
- Timing and Synchronisation
- Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission
- Segmenting State into Entities and Its Implication for Learning
- Temporal Structure of Neural Activity and Modelling of Information Processing in the Brain
- Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle
- Locust Olfaction
- Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays
- The Role of Brain Chaos
- Neural Network Classification of Word Evoked Neuromagnetic Brain Activity
- Simulation Studies of the Speed of Recurrent Processing
- Learning and Memory Storage
- The Dynamics of Learning and Memory: Lessons from Neuroscience
- Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation
- Plasticity and Nativism: Towards a Resolution of an Apparent Paradox
- Cell Assemblies as an Intermediate Level Model of Cognition
- Modelling Higher Cognitive Functions with Hebbian Cell Assemblies
- Spiking Associative Memory and Scene Segmentation by Synchronization of Cortical Activity
- A Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex
- Linguistic Computation with State Space Trajectories
- Robust Stimulus Encoding in Olfactory Processing: Hyperacuity and Efficient Signal Transmission
- Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?
- An Investigation into the Role of Cortical Synaptic Depression in Auditory Processing
- 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
- Connectionist Propositional Logic A Simple Correlation Matrix Memory Based Reasoning System
- Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
- Connectionist Neuroimaging.
