The quantitative evaluation of functional neuroimaging experiments: the NPAIRS data analysis framework.
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Neuroanatomical correlates of Klinefelter syndrome studied in relation to the neuropsychological profileDetecting stable distributed patterns of brain activation using Gini contrastPredicting IQ change from brain structure: a cross-validation studyQuantifying functional connectivity in multi-subject fMRI data using component modelsMachine learning classifiers and fMRI: a tutorial overviewMultivariate strategies in functional magnetic resonance imagingInteracting with the National Database for Autism Research (NDAR) via the LONI Pipeline workflow environmentAn open science resource for establishing reliability and reproducibility in functional connectomicsConnectomics and new approaches for analyzing human brain functional connectivityA review of feature reduction techniques in neuroimagingCircular analysis in systems neuroscience: the dangers of double dippingProgress toward openness, transparency, and reproducibility in cognitive neuroscienceAn improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity dataSeven topics in functional magnetic resonance imaging.Sex differences in brain activity during aversive visceral stimulation and its expectation in patients with chronic abdominal pain: a network analysisWhat's new in neuroimaging methods?Clinically useful brain imaging for neuropsychiatry: How can we get there?The support feature machine: classification with the least number of features and application to neuroimaging data.Eyes-open/eyes-closed dataset sharing for reproducibility evaluation of resting state fMRI data analysis methods.GLMdenoise: a fast, automated technique for denoising task-based fMRI data.A method for multitask fMRI data fusion applied to schizophrenia.Optimizing preprocessing and analysis pipelines for single-subject fMRI: 2. Interactions with ICA, PCA, task contrast and inter-subject heterogeneity.Analyzing for information, not activation, to exploit high-resolution fMRI.Theoretical, statistical, and practical perspectives on pattern-based classification approaches to the analysis of functional neuroimaging data.Evaluation and comparison of GLM- and CVA-based fMRI processing pipelines with Java-based fMRI processing pipeline evaluation system.Revealing representational content with pattern-information fMRI--an introductory guide.Validation of coevolving residue algorithms via pipeline sensitivity analysis: ELSC and OMES and ZNMI, oh my!A mutual information-based metric for evaluation of fMRI data-processing approaches.Dimensionality estimation for optimal detection of functional networks in BOLD fMRI data.Data-driven optimization and evaluation of 2D EPI and 3D PRESTO for BOLD fMRI at 7 Tesla: I. Focal coverage.Dissociation of Down syndrome and Alzheimer's disease effects with imaging.Complex and magnitude-only preprocessing of 2D and 3D BOLD fMRI data at 7 T.Neurocognitive phenotypes and genetic dissection of disorders of brain and behavior.Evaluation of the channelized Hotelling observer with an internal-noise model in a train-test paradigm for cardiac SPECT defect detectionMultishot versus single-shot pulse sequences in very high field fMRI: a comparison using retinotopic mapping.Common component classification: what can we learn from machine learning?Linking brain-wide multivoxel activation patterns to behaviour: Examples from language and math.Multivariate lesion-symptom mapping using support vector regression.Neurocognitive endophenotypes of obsessive-compulsive disorder.Sparse network-based models for patient classification using fMRI.
P2860
P800
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P2860
The quantitative evaluation of functional neuroimaging experiments: the NPAIRS data analysis framework.
description
2002 nî lūn-bûn
@nan
2002 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2002 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2002年の論文
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2002年学术文章
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2002年学术文章
@zh-cn
2002年学术文章
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2002年学术文章
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2002年学术文章
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2002年學術文章
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name
The quantitative evaluation of ...... PAIRS data analysis framework.
@ast
The quantitative evaluation of ...... PAIRS data analysis framework.
@en
type
label
The quantitative evaluation of ...... PAIRS data analysis framework.
@ast
The quantitative evaluation of ...... PAIRS data analysis framework.
@en
prefLabel
The quantitative evaluation of ...... PAIRS data analysis framework.
@ast
The quantitative evaluation of ...... PAIRS data analysis framework.
@en
P2093
P50
P921
P356
P1433
P1476
The quantitative evaluation of ...... PAIRS data analysis framework.
@en
P2093
Jon Anderson
Rafal Kustra
Stephen LaConte
Suraj Muley
P304
P356
10.1006/NIMG.2001.1034
P407
P50
P577
2002-04-01T00:00:00Z