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Course Material for COGNESTIC 2022

The Cognitive Neuroscience Skills Training In Cambridge (COGNESTIC) is a 2-week course that provides researchers with training in state-of-the-art methods for neuroimaging and neurostimulation. You can find more information on the COGNESTIC webpage.

Below you will find documents, videos and web links that will be used for the course or can be used for preparation.

Introduction and Open Science Rik Henson & Olaf Hauk
Websites	OSF UKRN BIDS
Suggested reading	Munafo et al, 2017, problems in science Button et al, 2013, power in neuroscience Poldrack et al, 2017, reproducible neuroimaging Marek et al, 2022, power in neuroimaging association studies
Suggested viewing	Statistical power in neuroimaging PayWall: open access Comedian's Perspective on science and media

Structural MRI Marta Correia
Software	FSL Freesurfer
Datasets	Freesurfer tutorial data
Suggested reading	Good et al, 2001, A VBM study of ageing Smith et al, 2004, Structural MRI analysis in FSL Dale et al, 1999, Cortical surface-based analysis I Fischl et al, 1999, Cortical surface-based analysis II
Suggested viewing	Using the command line Introduction to MRI Physics talk coming soon.

Diffusion MRI I Marta Correia
Software	FSL
Datasets	BTC_preop
Suggested reading	FSL Diffusion Toolbox Wiki Smith et al, 2006, Tract-based spatial statistics (TBSS)
Suggested viewing	Introduction to Diffusion MRI talk coming soon.

Diffusion MRI II Marta Correia
Software	MRtrix3
Datasets	BTC_preop
Suggested reading
Suggested viewing	Introduction to Diffusion MRI talk coming soon.

fMRI I - Data management, content, manipulation Dace Apšvalka
Software	HeudiConv, PyBIDS, NiBabel, Nilearn
Datasets	Wakeman Multimodal
Suggested reading	Gorgolewski et al, 2016, The brain imaging data structure (BIDS)
Suggested viewing	BIDS for MRI: Structure and Conversion by Taylor Salo (13:39) fMRI Data Structure & Terminology by Martin Lindquist and Tor Wager (6:47)

fMRI II - Quality control & Pre-processing Dace Apšvalka
Software
Datasets	Wakeman Multimodal
Suggested reading
Suggested viewing

fMRI III - Statistical Analysis Dace Apšvalka
Software
Datasets	Wakeman Multimodal
Suggested reading
Suggested viewing

fMRI IV - Reporting Dace Apšvalka
Software
Datasets	Wakeman Multimodal
Suggested reading
Suggested viewing

Connectivity for fMRI Rik Henson
Software	SPM12
Datasets	Wakeman Multimodal
Suggested reading	Resting-state functional Connectivity Simple Intro to DCM fMRI preprocessing in SPM12 (for demo) SPM12 manual (Chapter 36)
Suggested viewing	fMRI Functional Connectivity, including DCM Talk on Bayesian Model Comparison coming soon

Eye-tracking Edwin Dalmijer
Software
Datasets
Suggested reading
Suggested viewing

EEG/MEG I – Pre-processing Olaf Hauk
Software	MNE-Pythonneuro
Datasets	Sample dataset in MNE-Python. Tutorials
Suggested reading	Digitial Filtering Filtering How To Maxwell Filtering
Suggested viewing	Preprocessing What are we measuring with M/EEG?

EEG/MEG II – Source Estimation Olaf Hauk
Software	MNE-Python
Datasets	Sample dataset in MNE-Python. Tutorials
Suggested reading	Linear source estimation and spatial resolution
Suggested viewing	M/EEG Source Analysis in SPM

EEG/MEG III – Time-Frequency and Functional Connectivity Olaf Hauk
Software	MNE-Python
Datasets	Sample dataset in MNE-Python. Tutorials
Suggested reading	Tutorial on Functional Connectivity Analyzing Neural Time Series Data
Suggested viewing	Time-frequency and functional connectivity analysis Time-Frequency Analysis of EEG Time Series

Graph Theory Caroline Nettekoven
Software	Brain Connectivity Toolbox in Matlab
Datasets	Coding exercises Exercise solutions
Suggested reading	Complex brain networks: graph theoretical analysis of structural and functional systems
Suggested viewing	Slides

MVPA/RSA I Daniel Mitchell
Software	The Decoding Toolbox in Matlab
Datasets	The Decoding Toolbox example dataset (See toolbox webpage for a lower resolution alternative)
Suggested reading	Mur et al. (2009) Revealing representational content with pattern-information fMRI--an introductory guide Hebart et al. (2014) The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data
Suggested viewing	Excellent presentations from Martin Hebart's MVPA course, on: Introduction to MVPA Introduction to classification

MVPA/RSA II Daniel Mitchell
Software	The RSA toolbox in Matlab (Alternatively, https://git.fmrib.ox.ac.uk/hnili/rsa)
Datasets
Suggested reading	Kriegeskorte et al. (2008) Representational similarity analysis - connecting the branches of systems neuroscience Kriegeskorte & Kievit (2013) Representational geometry: integrating cognition, computation, and the brain Nili et al. (2014) A toolbox for representational similarity analysis
Suggested viewing	Martin Hebart's lecture on RSA

Statistics in R Peter Watson
Software	R
Datasets	Data&Code Readme
Suggested reading	Statistical Methods for Psychology (Howell) Introduction to R
Suggested viewing	CBU Statistics Lectures

Brain Stimulation Ajay Halai
Software
Datasets
Suggested reading
Suggested viewing

DCM for M/EEG Rik Henson
Software	SPM12
Datasets	Wakeman Multimodal
Suggested reading	Preprocessing M/EEG in SPM12 Simple Intro to DCM
Suggested viewing	Talk on DCM for M/EEG coming soon MEEG connectivity other than DCM (not demo'ed, and related to Hauk talks above)

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-Below you will find documents, videos and web links that will be used for the course or can be used for preparation. <<BR>><<BR>>
+Below you will find documents, videos and web links that will be used for the course or can be used for preparation. <<BR>><<BR>> <<Anchor(openscience)>>
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+||<10%>__Websites__ ||[[https://osf.io/|OSF]] <<BR>> [[https://www.ukrn.org/primers/|UKRN]] <<BR>> [[https://bids.neuroimaging.io/|BIDS]] ||
||__Suggested reading__ ||[[https://doi.org/10.1038/s41562-016-0021|Munafo et al, 2017, problems in science]] <<BR>> [[https://doi.org/10.1038/nrn3475|Button et al, 2013, power in neuroscience]] <<BR>> [[https://doi.org/10.1038/nrn.2016.167|Poldrack et al, 2017, reproducible neuroimaging]] <<BR>> [[https://doi.org/10.1038/s41586-022-04492-9|Marek et al, 2022, power in neuroimaging association studies]] ||
||__Suggested viewing__ ||[[https://www.youtube.com/watch?v=D0VKyjNGvrs|Statistical power in neuroimaging]] <<BR>> [[https://www.youtube.com/watch?v=zAzTR8eq20k|PayWall: open access]] <<BR>> [[https://www.facebook.com/LastWeekTonight/videos/896755337120143|Comedian's Perspective on science and media]] ||




<<BR>> <<Anchor(structuralmri)>>
||||||<tablewidth="100%"style="text-align:center">~+'''Structural MRI '''+~<<BR>> Marta Correia ||
||<10%>__Software__ ||[[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/|FSL]] [[https://surfer.nmr.mgh.harvard.edu/|Freesurfe]]r ||
||__Datasets__ ||[[https://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/Data|Freesurfer tutorial data]] ||
||__Suggested reading__ ||[[https://pubmed.ncbi.nlm.nih.gov/11525331/|Good et al, 2001, A VBM study of ageing]] <<BR>> [[https://pubmed.ncbi.nlm.nih.gov/15501092/|Smith et al, 2004, Structural MRI analysis in FSL]] <<BR>> [[https://pubmed.ncbi.nlm.nih.gov/9931268/|Dale et al, 1999, Cortical surface-based analysis I]] <<BR>> [[https://pubmed.ncbi.nlm.nih.gov/9931269/|Fischl et al, 1999, Cortical surface-based analysis II]] ||
||__Suggested viewing__ ||[[https://www.youtube.com/watch?v=6eJMxh7PlOY|Using the command line]] <<BR>> Introduction to MRI Physics talk coming soon. ||




<<BR>> <<Anchor(diffusionmri1)>>
||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI  I'''+~ <<BR>> Marta Correia ||
||<10%>__Software__ ||[[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/|FSL]] ||
||__Datasets__ ||[[https://openneuro.org/datasets/ds001226/versions/00001|BTC_preop]] ||
||__Suggested reading__ ||[[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FDT|FSL Diffusion Toolbox Wiki]] <<BR>> [[https://pubmed.ncbi.nlm.nih.gov/16624579/|Smith et al, 2006, Tract-based spatial statistics (TBSS)]] ||
||__Suggested viewing__ ||Introduction to Diffusion MRI talk coming soon. ||




<<BR>> <<Anchor(diffusionmri2)>>
||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI  II'''+~ <<BR>> Marta Correia ||
||<10%>__Software__ ||[[https://www.mrtrix.org/|MRtrix3]] ||
||__Datasets__ ||[[https://openneuro.org/datasets/ds001226/versions/00001|BTC_preop]] ||
||__Suggested reading__ || ||
||__Suggested viewing__ ||Introduction to Diffusion MRI talk coming soon. ||




<<BR>> <<Anchor(fmri1)>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI I - Data management, content, manipulation'''+~ <<BR>> Dace Apšvalka ||
||<10%>__Software__ ||[[https://heudiconv.readthedocs.io/en/latest/|HeudiConv]], [[https://bids-standard.github.io/pybids/|PyBIDS]], [[https://nipy.org/nibabel/|NiBabel]], [[https://nilearn.github.io/stable/index.html|Nilearn]]||
||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] ||
||__Suggested reading__ ||[[https://doi.org/10.1038/sdata.2016.44|Gorgolewski et al, 2016, The brain imaging data structure (BIDS)]] ||
||__Suggested viewing__ ||[[https://osf.io/fbj5u|BIDS for MRI: Structure and Conversion]] by Taylor Salo (13:39) <<BR>> [[https://youtu.be/OuRdQJMU5ro|fMRI Data Structure & Terminology]] by Martin Lindquist and Tor Wager (6:47) ||




<<BR>> <<Anchor(fmri2)>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI II - Quality control & Pre-processing'''+~ <<BR>> Dace Apšvalka ||
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-||__Datasets__ || ||
+||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] ||
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-<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''Structural MRI'''+~ <<BR>> Marta Correia ||
+<<BR>> <<Anchor(fmri3)>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III - Statistical Analysis'''+~ <<BR>> Dace Apšvalka ||
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-||__Datasets__ || ||
+||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] ||
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-<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI  I'''+~ <<BR>> Marta Correia ||
+<<BR>> <<Anchor(fmri4)>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV - Reporting'''+~ <<BR>> Dace Apšvalka ||
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-||__Datasets__ || ||
+||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] ||
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-<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI  II'''+~ <<BR>> Marta Correia ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+<<BR>> <<Anchor(connectivityfmri)>>
||||||<tablewidth="100%"style="text-align:center">~+'''Connectivity for fMRI'''+~ <<BR>> Rik Henson ||
||<10%>__Software__ ||[[https://www.fil.ion.ucl.ac.uk/spm/software/spm12/|SPM12]] ||
||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] ||
||__Suggested reading__ ||[[http://dx.doi.org/10.1016/j.tics.2013.09.016|Resting-state functional Connectivity]] <<BR>> [[https://doi.org/10.1016/j.neuroimage.2013.07.008|Simple Intro to DCM]] <<BR>>  [[https://www.frontiersin.org/articles/10.3389/fnins.2019.00300/full#supplementary-material|fMRI preprocessing in SPM12 (for demo)]]  <<BR>> [[https://www.fil.ion.ucl.ac.uk/spm/doc/spm12_manual.pdf|SPM12 manual (Chapter 36)]] ||
||__Suggested viewing__ ||[[https://youtu.be/1VOKsWWLgjk|fMRI Functional Connectivity, including DCM]] <<BR>> Talk on Bayesian Model Comparison coming soon ||
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-<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI I'''+~ <<BR>> Dace Apsvalka ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||




<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI II'''+~ <<BR>> Dace Apsvalka ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||




<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III'''+~ <<BR>> Dace Apsvalka ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||




<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV'''+~ <<BR>> Dace Apsvalka ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||




<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''Connectivity for fMRI'''+~ <<BR>> Rik Henson ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||




<<BR>>
+<<BR>> <<Anchor(eyetracking)>>
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+<<BR>> <<Anchor(eegmeg1)>>
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-||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+||<10%>__Software__ ||[[https://mne.tools/stable/index.html|MNE-Python]]neuro ||
||__Datasets__ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/preprocessing/index.html|Tutorials]] ||
||__Suggested reading__ ||[[https://pubmed.ncbi.nlm.nih.gov/25128257/|Digitial Filtering]] <<BR>>[[https://www.sciencedirect.com/science/article/pii/S0896627319301746|Filtering How To]] <<BR>> [[https://iopscience.iop.org/article/10.1088/0031-9155/51/7/008|Maxwell Filtering]] ||
||__Suggested viewing__ ||[[https://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures?action=AttachFile&do=view&target=EEGMEG1.mp4|Preprocessing]] <<BR>>[[https://mediacentral.ucl.ac.uk/Player/2909|What are we measuring with M/EEG]]? ||
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+<<BR>> <<Anchor(eegmeg2)>>
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-||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+||<10%>__Software__ ||[[https://mne.tools/stable/index.html|MNE-Python]] ||
||__Datasets__ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/inverse/index.html|Tutorials]] ||
||__Suggested reading__ ||[[https://pubmed.ncbi.nlm.nih.gov/35390459/|Linear source estimation and spatial resolution]] ||
||__Suggested viewing__ ||[[https://mediacentral.ucl.ac.uk/Player/2917|M/EEG Source Analysis in SPM]] ||
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-<<BR>>
+<<BR>> <<Anchor(eegmeg3)>>
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-||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+||<10%>__Software__ ||[[https://mne.tools/stable/index.html|MNE-Python]] ||
||__Datasets__ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/time-freq/index.html|Tutorials]] ||
||__Suggested reading__ ||[[https://pubmed.ncbi.nlm.nih.gov/26778976/|Tutorial on Functional Connectivity]]<<BR>> [[https://mitpress.mit.edu/books/analyzing-neural-time-series-data|Analyzing Neural Time Series Data]] ||
||__Suggested viewing__ ||[[https://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures?action=AttachFile&do=view&target=EEGMEG3.mp4|Time-frequency and functional connectivity analysis]] <<BR>> [[https://www.youtube.com/watch?v=wB417SAbdak|Time-Frequency Analysis of EEG Time Series]] ||
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-<<BR>>
+<<BR>> <<Anchor(graphtheory)>>
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-||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+||<10%>__Software__ ||[[https://sites.google.com/site/bctnet/|Brain Connectivity Toolbox]] in [[https://uk.mathworks.com/products/matlab.html|Matlab]] ||
||__Datasets__ ||[[https://www.caroline-nettekoven.com/slides/graph-theory-exercises/|Coding exercises]]<<BR>> [[https://www.caroline-nettekoven.com/slides/graph-theory-exercises-solutions/|Exercise solutions]] ||
||__Suggested reading__ ||[[https://www.nature.com/articles/nrn2575|Complex brain networks: graph theoretical analysis of structural and functional systems]] ||
||__Suggested viewing__ ||[[https://www.caroline-nettekoven.com/slides/graph-theory-lecture/|Slides]] ||
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-<<BR>>
+<<BR>> <<Anchor(rsa1)>>
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-||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+||<10%>__Software__ ||[[https://sites.google.com/site/tdtdecodingtoolbox/|The Decoding Toolbox]] in [[https://uk.mathworks.com/products/matlab.html|Matlab]] ||
||__Datasets__ ||[[https://www.bccn-berlin.de/tdt/downloads/sub01_firstlevel.zip|The Decoding Toolbox example dataset]] <<BR>> (See toolbox webpage for a lower resolution alternative) ||
||__Suggested reading__ ||[[https://academic.oup.com/scan/article/4/1/101/1613450|Mur et al. (2009) Revealing representational content with pattern-information fMRI--an introductory guide]]<<BR>>[[https://www.frontiersin.org/articles/10.3389/fninf.2014.00088/full|Hebart  et al. (2014) The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data]] ||
||__Suggested viewing__ ||Excellent presentations from Martin Hebart's MVPA course, on:<<BR>>[[https://fmrif.nimh.nih.gov/course/mvpa_course/2017/02_lecture1|Introduction to MVPA]]<<BR>>[[https://fmrif.nimh.nih.gov/course/mvpa_course/2017/03_lecture2|Introduction to classification]] ||
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+<<BR>> <<Anchor(rsa2)>>
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-||<10%>__Software__ || ||
+||<10%>__Software__ ||[[http://www.mrc-cbu.cam.ac.uk/methods-and-resources/toolboxes/license/|The RSA toolbox]] in [[https://uk.mathworks.com/products/matlab.html|Matlab]]<<BR>>(Alternatively, https://git.fmrib.ox.ac.uk/hnili/rsa) ||
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-||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+||__Suggested reading__ ||[[https://www.frontiersin.org/articles/10.3389/neuro.06.004.2008/full|Kriegeskorte et al. (2008) Representational similarity analysis - connecting the branches of systems neuroscience]]<<BR>>[[https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(13)00127-7|Kriegeskorte & Kievit (2013) Representational geometry: integrating cognition, computation, and the brain]] <<BR>>[[https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003553|Nili et al. (2014) A toolbox for representational similarity analysis]] ||
||__Suggested viewing__ ||[[https://fmrif.nimh.nih.gov/course/mvpa_course/2017/08_lecture6|Martin Hebart's lecture on RSA]] ||
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-<<BR>>
+<<BR>> <<Anchor(statistics)>>
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-||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+||<10%>__Software__ ||[[https://www.r-project.org/|R]] ||
||__Datasets__ ||[[attachment:PW SEPT 2022 R COURSE.zip|Data&Code]] [[attachment:README R COURSE.txt|Readme]] ||
||__Suggested reading__ ||[[https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjZrKTMs635AhWQUMAKHZfTA6gQFnoECAYQAQ&url=https://labs.la.utexas.edu/gilden/files/2016/05/Statistics-Text.pdf|Statistical Methods for Psychology (Howell)]] <<BR>> [[https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=&cad=rja&uact=8&ved=2ahUKEwjB1Pnxs635AhXOQkEAHfHvBqgQFnoECBQQAQ&url=https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf|Introduction to R]] ||
||__Suggested viewing__ ||[[https://imaging.mrc-cbu.cam.ac.uk/statswiki/StatsCourse2021/recordings|CBU Statistics Lectures]] ||
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+<<BR>> <<Anchor(brainstimulation)>>
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||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG I'''+~ <<BR>> Rik Henson ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
+<<BR>> <<Anchor(dcmemeg1)>>
||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG'''+~ <<BR>> Rik Henson ||
||<10%>__Software__ ||[[https://www.fil.ion.ucl.ac.uk/spm/software/spm12/|SPM12]] ||
||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] ||
||__Suggested reading__ ||[[https://doi.org/10.3389/fnins.2019.00300|Preprocessing M/EEG in SPM12]] <<BR>> [[https://doi.org/10.1016/j.neuroimage.2013.07.008|Simple Intro to DCM]] ||
||__Suggested viewing__ ||Talk on DCM for M/EEG coming soon <<BR>> [[https://youtu.be/6b35VvQpPDU|MEEG connectivity other than DCM (not demo'ed, and related to Hauk talks above)]] ||
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-<<BR>>
||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG II'''+~ <<BR>> Rik Henson ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||

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Course Material for COGNESTIC 2022