The danger of systematic bias in group-level FMRI-lag-based causality estimation.

The danger of systematic bias in group-level FMRI-lag-based causality estimation.

Pokaż inne wersje (1)

Schippers, Renken and Keysers (NeuroImage, 2011) present a simulation of multi-subject lag-based causality estimation. We fully agree that single-subject evaluations (e.g., Smith et al., 2011) need to be revisited in the context of multi-subject studies, and Schippers' paper is a good example,...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy:	Smith, S, Bandettini, P, Miller, K, Behrens, T, Friston, K, David, O, Liu, T, Woolrich, M, Nichols, T
Format:	Journal article
Język:	English
Wydane:	2012

Podobne zapisy

The danger of systematic bias in group-level FMRI-lag-based causality estimation
od: Smith, S, i wsp.
Wydane: (2011)

Meaningful design and contrast estimability in FMRI.
od: Smith, S, i wsp.
Wydane: (2007)

Multilevel linear modelling for FMRI group analysis using Bayesian inference.
od: Woolrich, M, i wsp.
Wydane: (2004)

Statistical analysis of fMRI data
od: Woolrich, M, i wsp.
Wydane: (2009)

Network modelling methods for FMRI.
od: Smith, S, i wsp.
Wydane: (2011)

Nonparametric estimation of temporal autocorrelation in FMRI
od: Woolrich, M, i wsp.
Wydane: (2000)

Variance decomposition for single-subject task-based fMRI activity estimates across many sessions
od: Gonzalez-Castillo, J, i wsp.
Wydane: (2016)

Mixture models with adaptive spatial regularization for segmentation with an application to FMRI data.
od: Woolrich, M, i wsp.
Wydane: (2005)

On bias in the estimation of autocorrelations for fMRI voxel time-series analysis.
od: Marchini, J, i wsp.
Wydane: (2003)

Functional connectomics from resting-state fMRI
od: Smith, S, i wsp.
Wydane: (2013)

Comparing dynamic causal models of neurovascular coupling with fMRI and EEG/MEG
od: Jafarian, A, i wsp.
Wydane: (2020)

Missing Data Estimation in FMRI Dynamic Causal Modeling
od: Shaza eZaghlool, i wsp.
Wydane: (2014-07-01)

Evaluation of Directed Causality Measures and Lag Estimations in Multivariate Time-Series
od: Jolan Heyse, i wsp.
Wydane: (2021-10-01)

Evidence for a vascular contribution to diffusion FMRI at high b value.
od: Miller, K, i wsp.
Wydane: (2007)

Bayesian inference in FMRI.
od: Woolrich, M
Wydane: (2012)

Bayesian inference in FMRI
od: Woolrich, M
Wydane: (2012)

Negativity Bias in Dangerous Drivers.
od: Jing Chai, i wsp.
Wydane: (2016-01-01)

Ethnicity, minority status, and inter-group bias: A systematic meta-analysis on fMRI studies
od: Aino Saarinen, i wsp.
Wydane: (2023-01-01)

Group-PCA for very large fMRI datasets.
od: Smith, S, i wsp.
Wydane: (2014)

The Bias of Standard Methods in Estimating Causal Effect
Wydane: (2017-06-01)

Functional connectomics from resting-state fMRI.
od: Smith, S, i wsp.
Wydane: (2013)

Group-PCA for very large fMRI datasets
od: Smith, S, i wsp.
Wydane: (2014)

Estimating biases during detection of leads and lags between climate elements across Dansgaard–Oeschger events
od: J. Slattery, i wsp.
Wydane: (2024-11-01)

Time lag bias in publishing clinical trials.
od: Clarke, M, i wsp.
Wydane: (1998)

Heirarchical fully Bayesian spatio-temporal analysis of FMRI data
od: Woolrich, M, i wsp.
Wydane: (2001)

Correction: Increasing fMRI Sampling Rate Improves Granger Causality Estimates
Wydane: (2014-01-01)

Correction: Increasing fMRI Sampling Rate Improves Granger Causality Estimates.
Wydane: (2014-01-01)

A group analysis using the Multiregression Dynamic Models for fMRI networked time series
od: Costa, L, i wsp.
Wydane: (2018)

Optimising network modelling methods for fMRI
od: Pervaiz, U, i wsp.
Wydane: (2020)

Fully Bayesian spatio-temporal modeling of FMRI data.
od: Woolrich, M, i wsp.
Wydane: (2004)

Temporal autocorrelation in univariate linear modeling of FMRI data.
od: Woolrich, M, i wsp.
Wydane: (2001)

Variational Bayesian Causal Connectivity Analysis for fMRI
od: Martin eLuessi, i wsp.
Wydane: (2014-05-01)

Origin of the Time Lag Phenomenon and the Global Signal in Resting-State fMRI
od: Shiori Amemiya, i wsp.
Wydane: (2020-10-01)

Omitted variable bias: A threat to estimating causal relationships
od: R. Wilms, i wsp.
Wydane: (2021-12-01)

INTERGROUP ATTRIBUTIONS FOR SUCCESS AND FAILURE - GROUP-SERVING BIAS AND GROUP-SERVING CAUSAL SCHEMATA
od: Hewstone, M, i wsp.
Wydane: (1990)

A Strategy to Reduce Bias of Entropy Estimates in Resting-State fMRI Signals
od: Albert C. Yang, i wsp.
Wydane: (2018-06-01)

Optimising network modelling methods for fMRI
od: Usama Pervaiz, i wsp.
Wydane: (2020-05-01)

Self-regulation learning as active inference: dynamic causal modeling of an fMRI neurofeedback task
od: Gabriela Vargas, i wsp.
Wydane: (2023-08-01)

Bayesian deconvolution of [corrected] fMRI data using bilinear dynamical systems.
od: Makni, S, i wsp.
Wydane: (2008)

Behavioural relevance of spontaneous, transient brain network interactions in fMRI
od: Vidaurre, D, i wsp.
Wydane: (2021)