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The Relevance of the Time Domain to Neural Network Models (Record no. 17424)

000 -LEADER
fixed length control field 03851nam a22004455i 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20140310150235.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 110914s2012 xxu| s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781461407249
978-1-4614-0724-9
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number RC321-580
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 612.8
Edition number 23
264 #1 -
-- Boston, MA :
-- Springer US,
-- 2012.
912 ## -
-- ZDB-2-SBL
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Rao, A. Ravishankar.
Relator term editor.
245 14 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title The Relevance of the Time Domain to Neural Network Models
Medium [electronic resource] /
Statement of responsibility, etc edited by A. Ravishankar Rao, Guillermo A. Cecchi.
300 ## - PHYSICAL DESCRIPTION
Extent XVIII, 226 p.
Other physical details online resource.
440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Springer Series in Cognitive and Neural Systems ;
Volume number/sequential designation 3
520 ## - SUMMARY, ETC.
Summary, etc A significant amount of effort in neural modeling is directed towards understanding the representation of external objects in the brain. There is also a rapidly growing interest in modeling the intrinsically-generated activity in the brain, as represented by the default mode network hypothesis, and the emergent behavior that gives rise to critical phenomena such as neural avalanches. Time plays a critical role in these intended modeling domains, from the exquisite discriminations in the mammalian auditory system to the precise timing involved in high-end activities such as competitive sports or professional music performance. The growth in experimental high-throughput neuroscience techniques has allowed the multi-scale acquisition of neural signals, from individual electrode recordings to whole-brain functional magnetic resonance imaging activity, including the ability to manipulate neural signals with optogenetic approaches. This has created a deluge of experimental data, spanning multiple spatial and temporal scales, and posing the enormous challenge of its interpretation in terms of a predictive theory of brain function. In addition, there has been a massive growth in availability of computational power through parallel computing. The Relevance of the Time Domain to Neural Network Models aims to develop a unified view of how the time domain can be effectively employed in neural network models. The book proposes that conceptual models of neural interaction are required in order to understand the data being collected. Simultaneously, these proposed models can be used to form hypotheses of neural interaction and system behavior that can be neuroscientifically tested. The book concentrates on a crucial aspect of brain modeling: the nature and functional relevance of temporal interactions in neural systems. This book will appeal to a wide audience consisting of computer scientists and electrical engineers interested in brain-like computational mechanisms, computer architects exploring the development of high-performance computing systems to support these computations, neuroscientists probing the neural code and signaling mechanisms, mathematicians and physicists interested in modeling complex biological phenomena, and graduate students in all these disciplines who are searching for challenging research questions.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Medicine.
Topical term or geographic name as entry element Neurosciences.
Topical term or geographic name as entry element Computer science.
Topical term or geographic name as entry element Artificial intelligence.
Topical term or geographic name as entry element Biomedicine.
Topical term or geographic name as entry element Neurosciences.
Topical term or geographic name as entry element Computation by Abstract Devices.
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Cecchi, Guillermo A.
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9781461407232
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-1-4614-0724-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type E-Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Damaged status Lost status Withdrawn status Current location Full call number
2014-04-04AUM Main Library2014-04-04 2014-04-04 E-Book   AUM Main Library612.8