A developing neural network is a dynamic, self-modifying system. A feedback loop exists between the development of neuronal shape, type and distribution of ionic channels, and connectivity on one hand, and electrical neuronal and network activity on the other hand.
In this context the following problems have been studied:
The BrainArt Gallery - Evian GordonComparative Mammalian Brain Collections
Neurogenetik - online
Kapitel 34, Lehrbuch der Genetik, von Seyffert, Wilhelm. Gustav Fischer Verlag 1998.Development of the mammalian central nervous system
(Pasko Rakic, Section of Neurobiology at Yale University School of Medicine, New Haven CTIntroduction to Neurobiology Fall 2000
Developmental Biology - online, by Scott F. Gilbert, Sinauer Associates, 2000.
Neuronal Morphogenesis
Hilary G.E. Hentschel, Emory University, Department of Physics, Atlanta GATheoretical Neurobiology: Modelling the Development of the Nervous System
Jaap van Pelt, Netherlands Institute for Brain Research, Amsterdam, The NetherlandsSynaptic integration and information processing in neuronal dendrites
Michael Häusser, University College London, UK
Theoretical aspects of pattern formation and neuronal development
Alfred Gierer, Hans Meinhardt, Max-Planck-Institut für Entwicklungsbiologie, TübingenCortical Map Development / Axon Guidance - Mathematical modeling and in vitro experiments
Geoffrey J. Goodhill, Computational Neuroscience Laboratory, Department of Neuroscience, Georgetown University Medical Center, Washington DC, USAEvolutionary Artificial Neural Networks
Alistair Rust, European Bioinformatics Institute, Hinxton, Cambridge, UKFrom Neurons to Brain: Adaptive Self-Wiring of Neural Networks
Ronen Segev, Tel Aviv University, IsraelBiological Modeling and Visualization
Przemyslaw Prusinkiewicz, Department of Computer Science, University of Calgary, Calgary, Alberta, CanadaSelf-organization and electrophysiological dynamics of mammalian networks in cell culture
Center for Network Neuroscience, University of North Texas, Denton TX
Complex spatio-temporal patterns of discharge in the central nervous system
- simultaneous electrophysiological recordings of the activity of several single neurons
- higher-order EEG analysis
- spontaneous network activity in large-scale neural networks
- non-linear dynamics of patterned activity in simulated and real spike trains
Dendritica - Software tools for studying dendritic signallingBLISS/SYNOD - Simulation environment for neural systems
Spiking Neural Networks -SPINN SoC
Signal Processing Techniques for Spike Train Analysis using Matlab - Gabbiani / Koch
Neuronal assemblies: Multi-electrode recording, spike train analysis, theoretical and simulation studies
George Gerstein, U. of Pennsylvania, NeuroscienceNeural Ensemble Physiology
Miguel A.L. Nicolelis, Department of Neurobiology, Duke UniversityNEOSIM - Neural Open Simulation - Software tools for large scale systems modelling of the
nervous systemSNNAP - Simulator for Neural Networks and Action Potentials
Neuronal Pattern Analysis Beckman Institute, University of Illinois at Urbana Champaign, Urbana IL
New Neuroscience Technologies for Studying Learning in Vitro
Steve M. Potter, Caltech Division of Biology, Pasadena CAmulti-electrode array culture dishes 2-photon time-lapse microscopy high-speed imaging of neural activity neurally-controlled computer-simulated animals
MEA-Tools - MATLAB Tools for the analysis of multi-neuronal data recorded with multi-electrode arraysMulti-electrode Recording - Links
Confocal Microscopy_- Related Links
Innovationslolleg "Komplexe und zelluläre Sensorsysteme"-Universität Rostock
Computational Neuroscience: Realistic Modeling for Experimentalists, edited by E.De Schutter, CRC Press 2000