Spike Based Learning Rules And Stabilization Of Persistent Neural Activity
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Spiking Neuron Models
Author | : Wulfram Gerstner |
Publisher | : Cambridge University Press |
Total Pages | : 498 |
Release | : 2002-08-15 |
Genre | : Computers |
ISBN | : 9780521890793 |
Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.
Correlative Learning
Author | : Zhe Chen |
Publisher | : John Wiley & Sons |
Total Pages | : 480 |
Release | : 2008-01-07 |
Genre | : Science |
ISBN | : 0470171448 |
Correlative Learning: A Basis for Brain and Adaptive Systems provides a bridge between three disciplines: computational neuroscience, neural networks, and signal processing. First, the authors lay down the preliminary neuroscience background for engineers. The book also presents an overview of the role of correlation in the human brain as well as in the adaptive signal processing world; unifies many well-established synaptic adaptations (learning) rules within the correlation-based learning framework, focusing on a particular correlative learning paradigm, ALOPEX; and presents case studies that illustrate how to use different computational tools and ALOPEX to help readers understand certain brain functions or fit specific engineering applications.
Advances in Neural Information Processing Systems 12
Author | : Sara A. Solla |
Publisher | : MIT Press |
Total Pages | : 1124 |
Release | : 2000 |
Genre | : Computers |
ISBN | : 9780262194501 |
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.
Neural Information Processing
Author | : Derong Liu |
Publisher | : Springer |
Total Pages | : 941 |
Release | : 2017-11-07 |
Genre | : Computers |
ISBN | : 3319700960 |
The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constituts the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions. The 6 volumes are organized in topical sections on Machine Learning, Reinforcement Learning, Big Data Analysis, Deep Learning, Brain-Computer Interface, Computational Finance, Computer Vision, Neurodynamics, Sensory Perception and Decision Making, Computational Intelligence, Neural Data Analysis, Biomedical Engineering, Emotion and Bayesian Networks, Data Mining, Time-Series Analysis, Social Networks, Bioinformatics, Information Security and Social Cognition, Robotics and Control, Pattern Recognition, Neuromorphic Hardware and Speech Processing.
Cognitive NeuroIntelligence
Author | : Jia Liu |
Publisher | : Frontiers Media SA |
Total Pages | : 172 |
Release | : 2021-09-23 |
Genre | : Science |
ISBN | : 2889713407 |
Deep Learning in Science
Author | : Pierre Baldi |
Publisher | : Cambridge University Press |
Total Pages | : 387 |
Release | : 2021-07 |
Genre | : Computers |
ISBN | : 1108845355 |
Rigorous treatment of the theory of deep learning from first principles, with applications to beautiful problems in the natural sciences.
Artificial Neural Networks as Models of Neural Information Processing
Author | : Marcel van Gerven |
Publisher | : Frontiers Media SA |
Total Pages | : 220 |
Release | : 2018-02-01 |
Genre | : |
ISBN | : 2889454010 |
Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.
Advances in Neural Networks - ISNN 2017
Author | : Fengyu Cong |
Publisher | : Springer |
Total Pages | : 601 |
Release | : 2017-06-12 |
Genre | : Computers |
ISBN | : 3319590723 |
This book constitutes the refereed proceedings of the 14th International Symposium on Neural Networks, ISNN 2017, held in Sapporo, Hakodate, and Muroran, Hokkaido, Japan, in June 2017. The 135 revised full papers presented in this two-volume set were carefully reviewed and selected from 259 submissions. The papers cover topics like perception, emotion and development, action and motor control, attractor and associative memory, neurodynamics, complex systems, and chaos.
Spike-timing dependent plasticity
Author | : Henry Markram |
Publisher | : Frontiers E-books |
Total Pages | : 575 |
Release | : |
Genre | : |
ISBN | : 2889190439 |
Hebb's postulate provided a crucial framework to understand synaptic alterations underlying learning and memory. Hebb's theory proposed that neurons that fire together, also wire together, which provided the logical framework for the strengthening of synapses. Weakening of synapses was however addressed by "not being strengthened", and it was only later that the active decrease of synaptic strength was introduced through the discovery of long-term depression caused by low frequency stimulation of the presynaptic neuron. In 1994, it was found that the precise relative timing of pre and postynaptic spikes determined not only the magnitude, but also the direction of synaptic alterations when two neurons are active together. Neurons that fire together may therefore not necessarily wire together if the precise timing of the spikes involved are not tighly correlated. In the subsequent 15 years, Spike Timing Dependent Plasticity (STDP) has been found in multiple brain brain regions and in many different species. The size and shape of the time windows in which positive and negative changes can be made vary for different brain regions, but the core principle of spike timing dependent changes remain. A large number of theoretical studies have also been conducted during this period that explore the computational function of this driving principle and STDP algorithms have become the main learning algorithm when modeling neural networks. This Research Topic will bring together all the key experimental and theoretical research on STDP.