| The LNCS series reports state-of-the-art results in computer science research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R&D community, with numerous individuals, as well as with prestigious organizations and societies, LNCS has grown into the most comprehensive computer science resarch forum available. The scope of LNCS, including its subseries LNAI, spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields. The type of material publised traditionally includes. -proceedings(published in time for the respective conference) -post-proceedings(consisting of thoroughly revised final full papers) -research monographs(which may be basde on outstanding PhD work, research projects, technical reports, etc.) |
| Neurobiological Modeling and Analysis How Reward Can Induce Reverse Replay of Behavioral Sequences in the Hippocampus Analysis of Early Hypoxia EEG Based on a Novel Chaotic Neural Network BCM-Type Synaptic Plasticity Model Using a Linear Summation of Calcium Elevations as a Sliding Threshold A New Method for Multiple Spike Train Analysis Based on Information Discrepancy Self-organizing Rhythmic Patterns with Spatio-temporal Spikes in Class I and Class II Neural Networks Self-organization Through Spike-Timing Dependent Plasticity Using Localized Synfire-Chain Patterns Comparison of Spike-Train Responses of a Pair of Coupled Neurons Under the External Stimulus Fatigue-Induced Reversed Hemispheric Plasticity During Motor Repetitions: A Brain Electrophysiological Study Functional Differences Between the Spatio-temporal Learnin Rule (STLR) and Hebb Type (HEBB) in Single Pyramidal Cells in the Hippocampal CA1 Area Ratio of Average Inhibitory to Excitatory Conductance Modulates the Response of Simple Cell Cognitive Processing Sequence Disambiguation by Functionally Divided Hippocampal CA3 Model A Time-Dependent Model of Information Capacity of Visual Attention Learning with Incrementality Lability of Reactivated Human Declarative Memory A Neuropsychologically-Inspired Computational Approach to the Generalization of Cerebellar Learning A Neural Model for Stereo Transparency with the Population of the Disparity Energy Models Functional Connectivity in the Resting Brain: An Analysis Based on ICA Semantic Addressable Encoding Top-Down Attention Guided Object Detection …… Learning Algorithms Support Vector Machines Self-Organizing Map Independet Component Analysis and Blind Source Separation Author Index |
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