Machine Learning and Interpretation in Neuroimaging (Record no. 39901)

000 -LEADER
fixed length control field 06372nam a22006015i 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783642347139
-- 978-3-642-34713-9
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.6
245 10 - TITLE STATEMENT
Title Machine Learning and Interpretation in Neuroimaging
Sub 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.
260 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Berlin, Heidelberg :
Name of publisher Springer Berlin Heidelberg :
-- Imprint: Springer,
Year of publication 2012.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIV, 266 p. 83 illus.
Other physical details online resource.
490 1# - SERIES STATEMENT
Series statement Lecture Notes in Computer Science,
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-Based Brain 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 Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Data mining.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer vision.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Optical pattern recognition.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer Imaging, Vision, Pattern Recognition and Graphics.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Pattern Recognition.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Probability and Statistics in Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Image Processing and Computer Vision.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Computer Applications.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Langs, Georg.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Rish, Irina.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Grosse-Wentrup, Moritz.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Murphy, Brian.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-642-34713-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type E-BOOKS
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2012.
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 0302-9743 ;
Holdings
Withdrawn status Lost status Damaged status Not for loan Current library Accession Number Uniform Resource Identifier Koha item type
        IMSc Library EBK10607 http://dx.doi.org/10.1007/978-3-642-34713-9 E-BOOKS
The Institute of Mathematical Sciences, Chennai, India

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