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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%>__Software__ ||MNE-Python || | ||<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/nrn.2016.167|Poldrack et al, 2017, reproducible neuroimaging]] <<BR>> [[https://doi.org/10.1038/nrn3475|Button et al, 2013, power in neuroscience]] <<BR>> [[https://doi.org/10.1038/s41586-022-04492-9|Marek et al, 2022, power in neuroimaging association studies]] || ||__Suggested viewing__ ||[[https://www.facebook.com/LastWeekTonight/videos/896755337120143|Comedian's Perspective on science and media]] <<BR>> [[https://www.youtube.com/watch?v=zAzTR8eq20k|PayWall: open access]] <<BR>> [[https://www.youtube.com/watch?v=syef3PPltG0|UKRN cartoon on preprints]] || <<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/|Freesurfer]] || |
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||__Suggested viewing__ || || | ||__Suggested viewing__ ||[[https://www.youtube.com/watch?v=6eJMxh7PlOY|Using the command line]] || |
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||||||<tablewidth="100%"style="text-align:center">~+'''Structural MRI'''+~ <<BR>> Marta Correia || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
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<<BR>> <<Anchor(diffusionmri1)>> | |
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<<BR>> <<Anchor(diffusionmri2)>> |
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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI I'''+~ <<BR>> Dace Apsvalka || | <<BR>> <<Anchor(fmri1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI I'''+~ <<BR>> Dace Apšvalka || |
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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI II'''+~ <<BR>> Dace Apsvalka || | <<BR>> <<Anchor(fmri2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI II'''+~ <<BR>> Dace Apšvalka || |
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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III'''+~ <<BR>> Dace Apsvalka || | <<BR>> <<Anchor(fmri3)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III'''+~ <<BR>> Dace Apšvalka || |
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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV'''+~ <<BR>> Dace Apsvalka || | <<BR>> <<Anchor(fmri4)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV'''+~ <<BR>> Dace Apšvalka || |
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<<BR>> ||||||<tablewidth="100%"style="text-align:center">~+'''Connectivity for fMRI'''+~ <<BR>> Rik Henson || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
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<<BR>> | <<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>> <<Anchor(eyetracking)>> |
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<<BR>> ||||||<tablewidth="100%"style="text-align:center">~+'''EEG/MEG I – Pre-processing'''+~ <<BR>> Olaf Hauk || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
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<<BR>> ||||||<tablewidth="100%"style="text-align:center">~+'''EEG/MEG II – Source Estimation'''+~ <<BR>> Olaf Hauk || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(eegmeg1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''EEG/MEG I – Pre-processing'''+~ <<BR>> Olaf Hauk || ||<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>> ||||||<tablewidth="100%"style="text-align:center">~+'''EEG/MEG III – Time-Frequency and Functional Connectivity'''+~ <<BR>> Olaf Hauk || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
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<<BR>> ||||||<tablewidth="100%"style="text-align:center">~+'''Graph Theory'''+~ <<BR>> Caroline Nettekoven || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(eegmeg2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''EEG/MEG II – Source Estimation'''+~ <<BR>> Olaf Hauk || ||<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>> ||||||<tablewidth="100%"style="text-align:center">~+'''MVPA/RSA I'''+~ <<BR>> Daniel Mitchell || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
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<<BR>> ||||||<tablewidth="100%"style="text-align:center">~+'''MVPA/RSA II'''+~ <<BR>> Daniel Mitchell || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(eegmeg3)>> ||||||<tablewidth="100%"style="text-align:center">~+'''EEG/MEG III – Time-Frequency and Functional Connectivity'''+~ <<BR>> Olaf Hauk || ||<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>> ||||||<tablewidth="100%"style="text-align:center">~+'''Statistics in R'''+~ <<BR>> Peter Watson || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
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<<BR>> | <<BR>> <<Anchor(graphtheory)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Graph Theory'''+~ <<BR>> Caroline Nettekoven || ||<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>> <<Anchor(rsa1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''MVPA/RSA I'''+~ <<BR>> Daniel Mitchell || ||<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]] || <<BR>> <<Anchor(rsa2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''MVPA/RSA II'''+~ <<BR>> Daniel Mitchell || ||<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) || ||__Datasets__ || || ||__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]] || <<BR>> <<Anchor(statistics)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Statistics in R'''+~ <<BR>> Peter Watson || ||<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]] || <<BR>> <<Anchor(brainstimulation)>> |
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<<BR>> ||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG I'''+~ <<BR>> Rik Henson || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
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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__ || || |
<<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)]] || |
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 |
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Munafo et al, 2017, problems in science |
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Comedian's Perspective on science and media |
Structural MRI |
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Diffusion MRI I |
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Diffusion MRI II |
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fMRI I |
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fMRI II |
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fMRI III |
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fMRI IV |
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Connectivity for fMRI |
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Resting-state functional Connectivity |
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fMRI Functional Connectivity, including DCM |
Eye-tracking |
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EEG/MEG I – Pre-processing |
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MNE-Pythonneuro |
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Sample dataset in MNE-Python. Tutorials |
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EEG/MEG II – Source Estimation |
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Sample dataset in MNE-Python. Tutorials |
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EEG/MEG III – Time-Frequency and Functional Connectivity |
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Sample dataset in MNE-Python. Tutorials |
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Tutorial on Functional Connectivity |
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Time-frequency and functional connectivity analysis |
Graph Theory |
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Complex brain networks: graph theoretical analysis of structural and functional systems |
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MVPA/RSA I |
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The Decoding Toolbox example dataset |
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Mur et al. (2009) Revealing representational content with pattern-information fMRI--an introductory guide |
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Excellent presentations from Martin Hebart's MVPA course, on: |
MVPA/RSA II |
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The RSA toolbox in Matlab |
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Kriegeskorte et al. (2008) Representational similarity analysis - connecting the branches of systems neuroscience |
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Statistics in R |
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Statistical Methods for Psychology (Howell) |
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Brain Stimulation |
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DCM for M/EEG |
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Talk on DCM for M/EEG coming soon |