Keith Worsley Keith Worsley

Slides:



Advertisements
Similar presentations
The General Linear Model (GLM)
Advertisements

SPM – introduction & orientation introduction to the SPM software and resources introduction to the SPM software and resources.
Statistical Inference
Overview of SPM p <0.05 Statistical parametric map (SPM)
The General Linear Model Christophe Phillips Cyclotron Research Centre University of Liège, Belgium SPM Short Course London, May 2011.
SPM Course Zurich, February 2012 Statistical Inference Guillaume Flandin Wellcome Trust Centre for Neuroimaging University College London.
SPM 2002 Experimental Design Daniel Glaser Institute of Cognitive Neuroscience, UCL Slides from: Rik Henson, Christian Buchel, Karl Friston, Chris Frith,
Realignment – Motion Correction (gif from FMRIB at Oxford)
SPM Software & Resources Wellcome Trust Centre for Neuroimaging University College London SPM Course London, May 2011.
SPM Software & Resources Wellcome Trust Centre for Neuroimaging University College London SPM Course London, October 2008.
SPM for EEG/MEG Guillaume Flandin
Event-related fMRI (er-fMRI)
Wellcome Centre for Neuroimaging at UCL
Group Analyses Guillaume Flandin SPM Course Zurich, February 2014
Group analysis Kherif Ferath Wellcome Trust Centre for Neuroimaging University College London SPM Course London, Oct 2010.
1st level analysis: basis functions, parametric modulation and correlated regressors. 1 st of February 2012 Sylvia Kreutzer Max-Philipp Stenner Methods.
Experimental design of fMRI studies SPM Course 2014 Sandra Iglesias Translational Neuromodeling Unit University of Zurich & ETH Zurich With many thanks.
Experimental design of fMRI studies Methods & models for fMRI data analysis in neuroeconomics April 2010 Klaas Enno Stephan Laboratory for Social and Neural.
Gordon Wright & Marie de Guzman 15 December 2010 Co-registration & Spatial Normalisation.
Experimental design of fMRI studies SPM Course 2012 Sandra Iglesias Translational Neuromodeling Unit University of Zurich & ETH Zurich With many thanks.
OverviewOverview Motion correction Smoothing kernel Spatial normalisation Standard template fMRI time-series Statistical Parametric Map General Linear.
Group analyses of fMRI data Methods & models for fMRI data analysis 28 April 2009 Klaas Enno Stephan Laboratory for Social and Neural Systems Research.
Multiple comparison correction Methods & models for fMRI data analysis 29 October 2008 Klaas Enno Stephan Branco Weiss Laboratory (BWL) Institute for Empirical.
Group analyses of fMRI data Methods & models for fMRI data analysis 26 November 2008 Klaas Enno Stephan Laboratory for Social and Neural Systems Research.
Preprocessing II: Between Subjects John Ashburner Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London, UK.
Voxel-Based Morphometry John Ashburner Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London, UK.
FMRI Preprocessing John Ashburner. Contents *Preliminaries *Rigid-Body and Affine Transformations *Optimisation and Objective Functions *Transformations.
Introduction to SPM SPM fMRI Course London, May 2012 Guillaume Flandin Wellcome Trust Centre for Neuroimaging University College London.
2nd Level Analysis Jennifer Marchant & Tessa Dekker
Introduction to SPM Batching
SPM Course Zurich, February 2015 Group Analyses Guillaume Flandin Wellcome Trust Centre for Neuroimaging University College London With many thanks to.
Coregistration and Spatial Normalisation
Methods & models for fMRI data analysis – HS 2013 David Cole Andrea Diaconescu Jakob Heinzle Sandra Iglesias Sudhir Shankar Raman Klaas Enno Stephan.
SPM Software & Resources Wellcome Trust Centre for Neuroimaging University College London SPM Course London, October 2008.
Methods for Dummies Second level Analysis (for fMRI) Chris Hardy, Alex Fellows Expert: Guillaume Flandin.
SPM Software & Resources Wellcome Trust Centre for Neuroimaging University College London SPM Course London, October 2009.
The General Linear Model
Mixture Models with Adaptive Spatial Priors Will Penny Karl Friston Acknowledgments: Stefan Kiebel and John Ashburner The Wellcome Department of Imaging.
Bayesian Inference in SPM2 Will Penny K. Friston, J. Ashburner, J.-B. Poline, R. Henson, S. Kiebel, D. Glaser Wellcome Department of Imaging Neuroscience,
Group Analyses Guillaume Flandin SPM Course London, October 2016
The General Linear Model (GLM)
Statistical Parametric Mapping for fMRI / MRI / VBM
Variational Bayesian Inference for fMRI time series
SPM Software & Resources
The general linear model and Statistical Parametric Mapping
The General Linear Model
2nd Level Analysis Methods for Dummies 2010/11 - 2nd Feb 2011
Wellcome Trust Centre for Neuroimaging University College London
Random Effects Analysis
fMRI Preprocessing John Ashburner
The General Linear Model (GLM)
Wellcome Dept. of Imaging Neuroscience University College London
The General Linear Model
From buttons to code Eamonn Walsh & Domenica Bueti
Statistical Parametric Mapping
The general linear model and Statistical Parametric Mapping
SPM2: Modelling and Inference
The General Linear Model
Hierarchical Models and
The General Linear Model (GLM)
Wellcome Dept. of Imaging Neuroscience University College London
Statistical Parametric Mapping
Anatomical Measures John Ashburner
Wellcome Centre for Neuroimaging at UCL
Bayesian Inference in SPM2
Wellcome Centre for Neuroimaging, UCL, UK.
The General Linear Model
Mixture Models with Adaptive Spatial Priors
The General Linear Model
The General Linear Model
Presentation transcript:

Keith Worsley 1951-2009

Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, Regression and Group Analysis Pipeline with Statistical Parametric Mapping SPM John Ashburner Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK.

Statistical Parametric Mapping (SPM) Image time-series Kernel Design matrix Statistical parametric map (SPM) Realignment Smoothing General linear model Gaussian field theory Statistical inference Normalisation p <0.05 Template Parameter estimates

SPM Interface and Batch mode

Pre-processing Overview Statistics or whatever fMRI time-series Template Anatomical MRI Smoothed Estimate Spatial Norm Motion Correct Smooth Coregister Spatially normalised Deformation

Batch Pre-processing

DARTEL Normalisation Simultaneous registration of GM to GM and WM to WM Template is an average shaped brain. Less bias in subsequent analysis. Iteratively created mean using DARTEL algorithm. Generative model of data. Multinomial noise model. Grey matter average of 471 subjects White matter average of 471 subjects

DARTEL Batch

Specify the Design for GLM Design matrix = + y X Parameter estimation

Batch 1st Level Analysis (Specify Design, Estimate, Result)

Group Analysis Of Summary Statistics First level Second level Data Design Matrix Contrast Images SPM(t) One-sample t-test @ 2nd level

2nd Level Analysis (Group Analysis)

SPM Resource http://www.fil.ion.ucl.ac.uk/spm “Human Brain Function” & “Statistical Parametric” Mapping books peer reviewed literature SPM email discussion list algorithm descriptions, code annotations, pseudo-code & SPM5/8 Manual

Feedback: Privacy Policy Feedback
Do Not Sell My Personal Information
About project: SlidePlayer Terms of Service

© 2024 SlidePlayer.com Inc. All rights reserved.