Reference health

Fast Gaussian Naïve Bayes for searchlight classification analysis

https://doi.org/10.1016/j.neuroimage.2017.09.001
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31/31 checkable references clean · checked 2026-07-22

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

7 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 31 checked references that resolve
resolves10.1016/j.neuroimage.2013.11.043
Searchlight-based multi-voxel pattern analysis of fMRI by cross-validated MANOVA
resolves10.1016/j.neuroimage.2016.07.040
Valid population inference for information-based imaging: From the second-level t -test to prevalence inference
resolves10.1016/j.neuroimage.2008.05.021
False discovery rate revisited: FDR and topological inference using Gaussian random fields
resolves10.3758/s13415-013-0186-2
Distinguishing multi-voxel patterns and mean activation: Why, how, and what does it tell us?
resolves10.2307/1932409
Measures of the Amount of Ecologic Association Between Species
resolves10.3389/fninf.2014.00024
BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs
resolves10.1016/j.neuroimage.2015.10.022
Decoding the direction of imagined visual motion using 7 T ultra-high field fMRI
resolves10.1016/j.neuroimage.2013.03.041
Searchlight analysis: Promise, pitfalls, and potential
resolves10.1093/cercor/bhr357
Higher Level Visual Cortex Represents Retinotopic, Not Spatiotopic, Object Location
resolves10.1016/S0042-6989(01)00073-6
The lateral occipital complex and its role in object recognition
resolves10.1016/j.neuroimage.2003.08.003
Validating cluster size inference: random field and permutation methods
resolves10.1016/j.neuron.2015.05.025
A Primer on Pattern-Based Approaches to fMRI: Principles, Pitfalls, and Perspectives
resolves10.1002/hbm.23140
Classification based hypothesis testing in neuroscience: Below‐chance level classification rates and overlooked statistical properties of linear parametric classifiers
resolves10.1016/j.neuropsychologia.2011.11.007
Analyses of regional-average activation and multivoxel pattern information tell complementary stories
resolves10.1073/pnas.0600244103
Information-based functional brain mapping
resolves10.1016/j.mri.2008.02.016
Comparison of pattern recognition methods in classifying high-resolution BOLD signals obtained at high magnetic field in monkeys
resolves10.1016/j.neuroimage.2012.08.043
Joint neuronal tuning for object form and position in the human lateral occipital complex
resolves10.1016/j.neuroimage.2010.05.051
Comparison of multivariate classifiers and response normalizations for pattern-information fMRI
resolves10.1002/hbm.1058
Nonparametric permutation tests for functional neuroimaging: A primer with examples
resolves10.1016/j.nicl.2014.04.004
Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions
resolves10.1016/j.neuroimage.2010.04.270
A comparison of volume-based and surface-based multi-voxel pattern analysis
resolves10.3389/fninf.2016.00027
CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave
resolves10.1016/j.neuroimage.2010.05.026
Information mapping with pattern classifiers: A comparative study
resolves10.1016/j.neuroimage.2008.11.007
Machine learning classifiers and fMRI: A tutorial overview
resolves10.1371/journal.pone.0069566
Smoothness without Smoothing: Why Gaussian Naive Bayes Is Not Naive for Multi-Subject Searchlight Studies
resolves10.1016/j.neuroimage.2005.12.062
Divide and conquer: A defense of functional localizers
resolves10.1016/j.neuroimage.2008.03.061
Threshold-free cluster enhancement: Addressing problems of smoothing, threshold dependence and localisation in cluster inference
resolves10.1037/0278-7393.6.2.174
A standardized set of 260 pictures: Norms for name agreement, image agreement, familiarity, and visual complexity.
resolves10.1002/hbm.20169
Location and spatial profile of category‐specific regions in human extrastriate cortex
resolves10.1016/j.neuroimage.2012.09.063
Statistical inference and multiple testing correction in classification-based multi-voxel pattern analysis (MVPA): Random permutations and cluster size control
resolves10.1002/hbm.22318
Multivariate linear regression of high‐dimensional fMRI data with multiple target variables
The 7 references without a DOI — listed, not checked
no DOI — not checked10.1016/j.neuroimage.2017.09.001_bib3
no DOI — not checkedLIBSVM: a library for support vector machines
no DOI — not checkedThe Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data
no DOI — not checked10.1016/j.neuroimage.2017.09.001_bib19
no DOI — not checkedPermutation tests for studying classifier performance
no DOI — not checkedTraining fMRI classifiers to discriminate cognitive state across multiple human subjects
no DOI — not checkedPotential for false positive results from multi-voxel pattern analysis on functional imaging data
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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