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Neural codes and distributed representations : foundations of neural computation /

Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computations collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Abbott, L. F., Sejnowski, Terrence J. (Terrence Joseph)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, Mass. : MIT Press, ©1999.
©1999
Colección:Computational neuroscience.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Neural codes and distributed representations :  |b foundations of neural computation /  |c edited by Laurence Abbott and Terrence J. Sejnowski. 
260 |a Cambridge, Mass. :  |b MIT Press,  |c ©1999. 
264 4 |c ©1999 
300 |a 1 online resource (xxiii, 345 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
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490 1 |a Computational neuroscience 
500 |a "A Bradford book." 
504 |a Includes bibliographical references and index. 
505 0 0 |t Introduction --  |g 1.  |t Deciphering the Brain's Codes /  |r Masakazu Konishi --  |g 2.  |t A Neural Network for Coding of Trajectories by Time Series of Neuronal Population Vectors /  |r Alexander V. Lukashin and Apostolos P. Georgopoulos --  |g 3.  |t Self-Organization of Firing Activities in Monkey's Motor Cortex: Trajectory Computation from Spike Signals /  |r Siming Lin, Jennie Si and A.B. Schwartz --  |g 4.  |t Theoretical Considerations for the Analysis of Population Coding in Motor Cortex /  |r Terrence D. Sanger --  |g 5.  |t Statistically Efficient Estimation Using Population Coding /  |r Alexandre Pouget, Kechen Zhang, Sophie Deneve and Peter E. Latham --  |g 6.  |t Parameter Extraction from Population Codes: A Critical Assessment /  |r Herman P. Snippe --  |g 7.  |t Energy Efficient Neural Codes /  |r William B. Levy and Robert A. Baxter --  |g 8.  |t Seeing Beyond the Nyquist Limit /  |r Daniel L. Ruderman and William Bialek --  |g 9.  |t A Model of Spatial Map Formation in the Hippocampus of the Rat /  |r Kenneth I. Blum and L.F. Abbott --  |g 10.  |t Probabilistic Interpretation of Population Codes /  |r Richard S. Zemel, Peter Dayan and Alexandre Pouget --  |g 11.  |t Cortical Cells Should Fire Regularly, But Do Not /  |r William R. Softky and Christof Koch --  |g 12.  |t Role of Temporal Integration and Fluctuation Detection in the Highly Irregular Firing of a Leaky Integrator Neuron Model with Partial Reset /  |r Guido Bugmann, Chris Christodoulou and John G. Taylor --  |g 13.  |t Physiological Gain Leads to High ISI Variability in a Simple Model of a Cortical Regular Spiking Cell /  |r Todd W. Troyer and Kenneth D. Miller --  |g 14.  |t Coding of Time-Varying Signals in Spike Trains of Integrate-and-Fire Neurons with Random Threshold /  |r Fabrizio Gabbiani and Christof Koch --  |g 15.  |t Temporal Precision of Spike Trains in Extrastriate Cortex of the Behaving Macaque Monkey /  |r Wyeth Bair and Christof Koch --  |g 16.  |t Conversion of Temporal Correlations Between Stimuli to Spatial Correlations Between Attractors /  |r M. Griniasty, M.V. Tsodyks and Daniel J. Amit --  |g 17.  |t Neural Network Model of the Cerebellum: Temporal Discrimination and the Timing of Motor Responses /  |r Dean V. Buonomano and Michael D. Mauk --  |g 18.  |t Gamma Oscillation Model Predicts Intensity Coding by Phase Rather than Frequency /  |r Roger D. Traub, Miles A. Whittington and John G.R. Jefferys --  |g 19.  |t Effects of Input Synchrony on the Firing Rate of a Three-Conductance Cortical Neuron Model /  |r Venkatesh N. Murthy and Eberhard E. Fetz --  |g 20.  |t NMDA-Based Pattern Discrimination in a Modeled Cortical Neuron /  |r Bartlett W. Mel --  |g 21.  |t The Impact of Parallel Fiber Background Activity on the Cable Properties of Cerebellar Purkinje Cells /  |r Moshe Rappe, Yosef Yarom and Idan Segev --  |t Index. 
588 0 |a Print version record. 
520 8 |a Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computations collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems. 
546 |a English. 
590 |a eBooks on EBSCOhost  |b EBSCO eBook Subscription Academic Collection - Worldwide 
650 0 |a Neural networks (Neurobiology) 
650 0 |a Coding theory. 
650 0 |a Neural conduction. 
650 0 |a Neural networks (Computer science) 
650 0 |a Neural transmission. 
650 2 |a Neural Conduction 
650 2 |a Neural Networks, Computer 
650 2 |a Synaptic Transmission 
650 6 |a Réseaux neuronaux (Neurobiologie) 
650 6 |a Conduction nerveuse. 
650 6 |a Réseaux neuronaux (Informatique) 
650 6 |a Transmission nerveuse. 
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650 7 |a Neural networks (Computer science)  |2 fast  |0 (OCoLC)fst01036260 
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650 7 |a Neural networks (Neurobiology)  |2 fast  |0 (OCoLC)fst01036271 
650 1 7 |a Neurofysiologie.  |2 gtt 
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700 1 |a Abbott, L. F. 
700 1 |a Sejnowski, Terrence J.  |q (Terrence Joseph) 
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830 0 |a Computational neuroscience. 
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