= 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 [[https://www.mrc-cbu.cam.ac.uk/conferences/cognestic2022/|COGNESTIC webpage]].
Below you will find documents, videos and web links that will be used for the course or can be used for preparation. <
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||||||~+'''Introduction and Open Science'''+~ <
> Rik Henson & Olaf Hauk ||
||<10%>__Websites__ || [[https://osf.io/|OSF]] <
> [[https://www.ukrn.org/primers/|UKRN]]||
||__Suggested reading__ ||[[https://doi.org/10.1038/nrn.2016.167|Poldrack et al, 2017, NRN]] <
> [[https://www.ukrn.org/primers/]] <
> [[https://doi.org/10.1038/s41562-016-0021|Munafo et al, 2017, NHB]] ||
||__Suggested viewing__ ||[[https://www.facebook.com/LastWeekTonight/videos/896755337120143|Comedian's Perspective]] <
> [[https://www.youtube.com/watch?v=zAzTR8eq20k|PayWall]] ||
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||||||~+'''Structural MRI'''+~ <
> Marta Correia ||
||<10%>__Software__ ||[[https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/|FSL]] [[https://surfer.nmr.mgh.harvard.edu/|Freesurfer]] ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ ||[[https://www.youtube.com/watch?v=6eJMxh7PlOY|Using the command line]] ||
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||||||~+'''Diffusion MRI I'''+~ <
> Marta Correia ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
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<
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||||||~+'''Diffusion MRI II'''+~ <
> Marta Correia ||
||<10%>__Software__ || ||
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||||||~+'''fMRI I'''+~ <
> Dace Apšvalka ||
||<10%>__Software__ || ||
||__Datasets__ || ||
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<
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||||||~+'''fMRI II'''+~ <
> Dace Apšvalka ||
||<10%>__Software__ || ||
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<
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||||||~+'''fMRI III'''+~ <
> Dace Apšvalka ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
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<
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||||||~+'''fMRI IV'''+~ <
> Dace Apšvalka ||
||<10%>__Software__ || ||
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||__Suggested reading__ || ||
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<
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||||||~+'''Connectivity for fMRI'''+~ <
> 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]] <
> [[https://doi.org/10.1016/j.neuroimage.2013.07.008|Simple Intro to DCM]] <
> [[https://www.frontiersin.org/articles/10.3389/fnins.2019.00300/full#supplementary-material|fMRI preprocessing in SPM12 (for demo)]] <
> [[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]] ||
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||||||~+'''Eye-tracking'''+~ <
> Edwin Dalmijer ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
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<
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||||||~+'''EEG/MEG I – Pre-processing'''+~ <
> 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]] <
>[[https://www.sciencedirect.com/science/article/pii/S0896627319301746|Filtering How To]] <
> [[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]] <
>[[https://mediacentral.ucl.ac.uk/Player/2909|What are we measuring with M/EEG]]? ||
<
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||||||~+'''EEG/MEG II – Source Estimation'''+~ <
> 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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||||||~+'''EEG/MEG III – Time-Frequency and Functional Connectivity'''+~ <
> 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]]<
> [[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]] <
> [[https://www.youtube.com/watch?v=wB417SAbdak|Time-Frequency Analysis of EEG Time Series]] ||
<
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||||||~+'''Graph Theory'''+~ <
> 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]]<
> [[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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||||||~+'''MVPA/RSA I'''+~ <
> 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]] <
> (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]]<
>[[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:<
>[[https://fmrif.nimh.nih.gov/course/mvpa_course/2017/02_lecture1|Introduction to MVPA]]<
>[[https://fmrif.nimh.nih.gov/course/mvpa_course/2017/03_lecture2|Introduction to classification]] ||
<
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||||||~+'''MVPA/RSA II'''+~ <
> 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]]<
>(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]]<
>[[https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(13)00127-7|Kriegeskorte & Kievit (2013) Representational geometry: integrating cognition, computation, and the brain]] <
>[[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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||||||~+'''Statistics in R'''+~ <
> 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)]] <
> [[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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||||||~+'''Brain Stimulation'''+~ <
> Ajay Halai ||
||<10%>__Software__ || ||
||__Datasets__ || ||
||__Suggested reading__ || ||
||__Suggested viewing__ || ||
<
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||||||~+'''DCM for M/EEG'''+~ <
> 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]] <
> [[https://doi.org/10.1016/j.neuroimage.2013.07.008|Simple Intro to DCM]] ||
||__Suggested viewing__ ||[[https://mediacentral.ucl.ac.uk/Play/63377|DCM for MEEG evoked responses]] <
> [[https://youtu.be/6b35VvQpPDU|MEEG connectivity other than DCM (not demo'ed, and related to Hauk talks above)]] ||