Machine Learning and Interpretation in Neuroimaging (Record no. 183683)

MARC details
000 -LEADER
fixed length control field 06808nam a22006735i 4500
001 - CONTROL NUMBER
control field 978-3-642-34713-9
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125955.0
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 121116s2012 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642347139
-- 978-3-642-34713-9
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-642-34713-9
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1501-1820
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA1634
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYT
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM016000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYT
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006
Edition number 23
245 10 - TITLE STATEMENT
Title Machine Learning and Interpretation in Neuroimaging
Medium [electronic resource] :
Remainder of title International Workshop, MLINI 2011, Held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised Selected and Invited Contributions /
Statement of responsibility, etc edited by Georg Langs, Irina Rish, Moritz Grosse-Wentrup, Brian Murphy.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2012.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2012.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 266 p. 83 illus.
Other physical details online resource.
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-- computer
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-- online resource
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490 1# - SERIES STATEMENT
Series statement Lecture Notes in Artificial Intelligence,
International Standard Serial Number 2945-9141 ;
Volume number/sequential designation 7263
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note A Comparative Study of Algorithms for Intra- and Inter-subjects fMRI Decoding -- Beyond Brain Reading: Randomized Sparsity and Clustering to Simultaneously Predict and Identify -- Searchlight Based Feature Extraction -- Looking Outside the Searchlight -- Population Codes Representing Musical Timbre for High-Level fMRI Categorization of Music Genres -- Induction in Neuroscience with Classification: Issues and Solutions -- A New Feature Selection Method Based on Stability Theory – Exploring Parameters Space to Evaluate Classification Accuracy in Neuroimaging Data -- Identification of OCD-Relevant Brain Areas through Multivariate Feature Selection -- Deformation-Invariant Sparse Coding for Modeling Spatial Variability of Functional Patterns in the Brain -- Decoding Complex Cognitive States Online by Manifold Regularization in Real-Time fMRI -- Modality Neutral Techniques for Brain Image Understanding -- How Does the Brain Represent Visual Scenes? A Neuromagnetic Scene Categorization Study -- Finding Consistencies in MEG Responses to Repeated Natural Speech -- Categorized EEG Neurofeedback Performance Unveils Simultaneous fMRI Deep Brain Activation -- Predicting Clinically Definite Multiple Sclerosis from Onset Using SVM -- MKL-Based Sample Enrichment and Customized Outcomes Enable Smaller AD Clinical Trials -- Pairwise Analysis for Longitudinal fMRI Studies -- Non-separable Spatiotemporal Brain Hemodynamics Contain Neural Information -- The Dynamic Beamformer -- Covert Attention as a Paradigm for Subject-Independent Brain-Computer Interfacing -- The Neural Dynamics of Visual Processing in Monkey Extrastriate Cortex: A Comparison between Univariate and Multivariate Techniques -- Statistical Learning for Resting-State fMRI: Successes and Challenges -- Relating Brain Functional Connectivity to Anatomical Connections: Model Selection -- Information-Theoretic Connectivity-Based Cortex Parcellation -- Inferring Brain Networks through Graphical Models with Hidden Variables -- Pitfalls in EEG-BasedBrain Effective Connectivity Analysis -- Data-Driven Modeling of BOLD Drug Response Curves Using Gaussian Process Learning -- Variational Bayesian Learning of Sparse Representations and Its Application in Functional Neuroimaging -- Identification of Functional Clusters in the Striatum Using Infinite Relational Modeling -- A Latent Feature Analysis of the Neural Representation of Conceptual Knowledge -- Real-Time Functional MRI Classification of Brain States Using Markov-SVM Hybrid Models: Peering Inside the rt-fMRI Black Box -- Restoring the Generalizability of SVM Based Decoding in High Dimensional Neuroimage Data.
520 ## - SUMMARY, ETC.
Summary, etc Brain imaging brings together the technology, methodology, research questions and approaches of a wide range of scientific fields including physics, statistics, computer science, neuroscience, biology, and engineering. Thus, methodological and technological advances that enable us to obtain measurements, examine relationships across observations, and link these data to neuroscientific hypotheses happen in a highly interdisciplinary environment. The dynamic field of machine learning with its modern approach to data mining provides many relevant approaches for neuroscience and enables the exploration of open questions. This state-of-the-art survey offers a collection of papers from the Workshop on Machine Learning and Interpretation in Neuroimaging, MLINI 2011, held at the 25th Annual Conference on Neural Information Processing, NIPS 2011, in the Sierra Nevada, Spain, in December 2011. Additionally, invited speakers agreed to contribute reviews on various aspects of the field, adding breadth and perspective to the volume. The 32 revised papers were carefully selected from 48 submissions. At the interface between machine learning and neuroimaging the papers aim at shedding some light on the state of the art in this interdisciplinary field. They are organized in topical sections on coding and decoding, neuroscience, dynamcis, connectivity, and probabilistic models and machine learning.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Image processing
General subdivision Digital techniques.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer vision.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Pattern recognition systems.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science
General subdivision Mathematics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Mathematical statistics.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Application software.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Imaging, Vision, Pattern Recognition and Graphics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Automated Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Probability and Statistics in Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Vision.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer and Information Systems Applications.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Langs, Georg.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Rish, Irina.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Grosse-Wentrup, Moritz.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Murphy, Brian.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642347122
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783642347146
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Artificial Intelligence,
-- 2945-9141 ;
Volume number/sequential designation 7263
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-642-34713-9">https://doi.org/10.1007/978-3-642-34713-9</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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