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||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||<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]] || |
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||||||<tablewidth="100%"style="text-align:center">~+'''Structural MRI'''+~ <<BR>> Marta Correia || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<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]] || |
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||<10%>__Software__ || || ||__Datasets__ || || |
||<10%>__Software__ ||[[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/|FSL]] [[https://www.mrtrix.org/|MRtrix3]] || ||__Datasets__ ||[[https://openneuro.org/datasets/ds001226/versions/00001|BTC_preop]] || |
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||<10%>__Software__ || || ||__Datasets__ || || |
||<10%>__Software__ ||[[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/|FSL]] [[https://www.mrtrix.org/|MRtrix3]] || ||__Datasets__ ||[[https://openneuro.org/datasets/ds001226/versions/00001|BTC_preop]] || |
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||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||<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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||__Datasets__ ||Sample dataset in MNE-Python. || | ||__Datasets__ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/preprocessing/index.html|Tutorials]] || |
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||__Suggested viewing__ ||[[https://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures?action=AttachFile&do=view&target=EEGMEG1.mp4|Preprocessing]] || | ||__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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||__Datasets__ ||Sample dataset in MNE-Python. || | ||__Datasets__ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/inverse/index.html|Tutorials]] || |
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||__Suggested viewing__ || || | ||__Suggested viewing__ ||[[https://mediacentral.ucl.ac.uk/Player/2917|M/EEG Source Analysis in SPM]] || |
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||__Datasets__ ||Sample dataset in MNE-Python. || ||__Suggested reading__ ||[[https://pubmed.ncbi.nlm.nih.gov/26778976/|Tutorial on Functional Connectivity]] || ||__Suggested viewing__ ||[[https://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures?action=AttachFile&do=view&target=EEGMEG3.mp4|Time-frequency and functional connectivity analysis]] || |
||__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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||<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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||<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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||<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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||__Suggested reading__ || || | ||__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]] || |
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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(dcmemeg2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG II'''+~ <<BR>> Rik Henson || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<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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Suggested reading |
Munafo et al, 2017, problems in science |
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Suggested viewing |
Statistical power in neuroimaging |
Structural MRI |
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Suggested reading |
Good et al, 2001, A VBM study of ageing |
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Suggested viewing |
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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Datasets |
The Decoding Toolbox example dataset |
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Suggested reading |
Mur et al. (2009) Revealing representational content with pattern-information fMRI--an introductory guide |
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Suggested viewing |
Excellent presentations from Martin Hebart's MVPA course, on: |
MVPA/RSA II |
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Software |
The RSA toolbox in Matlab |
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Datasets |
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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 |