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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>> <<Anchor(openscience)>> |
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__ || || ||__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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<<BR>> <<Anchor(structuralmri)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Structural MRI'''+~ <<BR>> Marta Correia || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(structuralmri)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Structural MRI - VBM and Surface-based Analysis '''+~<<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__ ||[[attachment:IntroductionToGLM.pdf|Introduction to GLM for structural MRI analysis]] <<BR>> [[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>> [[https://youtu.be/Psh-GovQLiI|Introduction to MRI Physics and image contrast]] || |
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<<BR>> <<Anchor(diffusionmri1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI I'''+~ <<BR>> Marta Correia || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(diffusionmri1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI I - DTI Model Fitting and Group Analysis'''+~ <<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://doi.org/10.1371/journal.pbio.1002203|Le Bihan et al, 2015, What water tells us about biological tissues]] <<BR>> [[https://doi.org/10.3389/fnins.2013.00031|Soares et al, 2013, A short guide to Diffusion Tensor Imaging]] <<BR>> [[https://pubmed.ncbi.nlm.nih.gov/16624579/|Smith et al, 2006, Tract-based spatial statistics (TBSS)]] || ||__Suggested viewing__ ||[[https://youtu.be/stpmlzO7b6c|Introduction to Diffusion MRI - Part I]] || |
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<<BR>> <<Anchor(diffusionmri2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI II'''+~ <<BR>> Marta Correia || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(diffusionmri2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI II - Tractography and Structural Connectivity'''+~ <<BR>> Marta Correia || ||<10%>__Software__ ||[[https://www.mrtrix.org/|MRtrix3]] || ||__Datasets__ ||[[https://openneuro.org/datasets/ds001226/versions/00001|BTC_preop]] || ||__Suggested reading__ ||[[https://mrtrix.readthedocs.io/en/latest/|MRtrix3 documentation]] <<BR>> [[https://www.sciencedirect.com/science/article/pii/B9780123964601000196|MR Diffusion Tractography]] || ||__Suggested viewing__ ||[[https://youtu.be/QDJJ6G2ZouA|Introduction to Diffusion MRI - Part II]] || |
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<<BR>> <<Anchor(fmri1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI I'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(fmri1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI I - Data management, structure, 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) || |
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<<BR>> <<Anchor(fmri2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI II'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(fmri2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI II - Quality control & Pre-processing'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ ||[[https://mriqc.readthedocs.io/en/latest/|MRIQC]], [[https://fmriprep.org/en/stable/|fMRIprep]], [[https://nipype.readthedocs.io/en/latest/|Nipype]] || ||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] || ||__Suggested reading__ ||...coming soon... || ||__Suggested viewing__ ||...coming soon... || |
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<<BR>> <<Anchor(fmri3)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(fmri3)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III - Statistical Analysis'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ ||[[http://nipype.readthedocs.io/en/latest/|Nipype]], [[http://nilearn.github.io/stable/index.html|Nilearn]], [[http://www.fil.ion.ucl.ac.uk/spm/software/spm12/|SPM12]] || ||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] || ||__Suggested reading__ ||...coming soon... || ||__Suggested viewing__ ||...coming soon... || |
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<<BR>> <<Anchor(fmri4)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
<<BR>> <<Anchor(fmri4)>> ||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV - Reporting'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ ||[[http://nilearn.github.io/stable/index.html|Nilearn]], [[https://pysurfer.github.io/|PySurfer]], [[http://www.fil.ion.ucl.ac.uk/spm/software/spm12/|SPM12]] || ||__Datasets__ ||[[https://openneuro.org/datasets/ds000117/versions/1.0.5|Wakeman Multimodal]] || ||__Suggested reading__ ||...coming soon... || ||__Suggested viewing__ ||...coming soon... || |
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<<BR>> <<Anchor(connectivityfmri)>> |
<<BR>> <<Anchor(connectivityfmri)>> |
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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>> [[https://youtu.be/1cbEmn_Qgkc|Bayesian Model Comparison (for DCM for fMRI/MEEG)]] || |
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<<BR>> <<Anchor(eyetracking)>> |
<<BR>> <<Anchor(eyetracking)>> |
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||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||<10%>__Software__ ||Python NumPy, [[https://scipy.org/|SciPy]], [[https://matplotlib.org/|Matplotlib]] || ||__Datasets__ ||EyeLink EDF examples (to be provided) || ||__Suggested reading__ ||https://doi.org/10.3758/s13428-021-01762-8 Paper on eye-tracking reporting standards (great for beginners and experts alike) || ||__Suggested viewing__ ||https://www.youtube.com/watch?v=F5eBln42VyM Talk at the MRC CBU on how to hack pupillometry studies || |
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<<BR>> <<Anchor(eegmeg1)>> |
<<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)>> |
<<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>> <<Anchor(eegmeg3)>> |
<<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>> <<Anchor(graphtheory)>> |
<<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>> <<Anchor(rsa1)>> |
<<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)>> |
<<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>> <<Anchor(statistics)>> |
<<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)>> |
<<BR>> <<Anchor(brainstimulation)>> |
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||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||<10%>__Software__ ||[[https://simnibs.github.io/simnibs/build/html/index.html|SIMNIBS]] (also requires access to Matlab, FSL and Freesurfer to run certain functions, see SIMNIBS installation guide) and [[http://www.k-wave.org/|k-wave]] || ||__Datasets__ ||[[https://simnibs.github.io/simnibs/build/html/dataset.html|tutorial_data]] || ||__Suggested reading__ ||[[https://www.sciencedirect.com/science/article/pii/S1053811916001191?via=ihub|Approaches to brain stimulation]] ; [[https://direct.mit.edu/jocn/article/33/2/195/95534/Inferring-Causality-from-Noninvasive-Brain|what can we infer from brain stimulation]]; [[https://www.nature.com/articles/nrneurol.2010.30.pdf|using NIBS clinically]] ; focused ultrasound [[https://www.nature.com/articles/srep34026.pdf|1]] and [[https://www.nature.com/articles/s41598-018-28320-1.pdf|2]] || ||__Suggested viewing__ ||[[attachment:COGNESTIC_slides|slides]] || |
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<<BR>> <<Anchor(dcmemeg1)>> ||||||<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>> <<Anchor(dcmemeg2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG II'''+~ <<BR>> Rik Henson || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
---- ---- |
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 |
||
Websites |
||
Suggested reading |
Munafo et al, 2017, problems in science |
|
Suggested viewing |
Statistical power in neuroimaging |
Structural MRI - VBM and Surface-based Analysis |
||
Software |
||
Datasets |
||
Suggested reading |
Introduction to GLM for structural MRI analysis |
|
Suggested viewing |
Using the command line |
Diffusion MRI I - DTI Model Fitting and Group Analysis |
||
Software |
||
Datasets |
||
Suggested reading |
FSL Diffusion Toolbox Wiki |
|
Suggested viewing |
Diffusion MRI II - Tractography and Structural Connectivity |
||
Software |
||
Datasets |
||
Suggested reading |
||
Suggested viewing |
fMRI I - Data management, structure, manipulation |
||
Software |
||
Datasets |
||
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 II - Quality control & Pre-processing |
||
Software |
||
Datasets |
||
Suggested reading |
...coming soon... |
|
Suggested viewing |
...coming soon... |
fMRI III - Statistical Analysis |
||
Software |
||
Datasets |
||
Suggested reading |
...coming soon... |
|
Suggested viewing |
...coming soon... |
fMRI IV - Reporting |
||
Software |
||
Datasets |
||
Suggested reading |
...coming soon... |
|
Suggested viewing |
...coming soon... |
Connectivity for fMRI |
||
Software |
||
Datasets |
||
Suggested reading |
Resting-state functional Connectivity |
|
Suggested viewing |
fMRI Functional Connectivity, including DCM |
Eye-tracking |
||
Software |
Python NumPy, SciPy, Matplotlib |
|
Datasets |
EyeLink EDF examples (to be provided) |
|
Suggested reading |
https://doi.org/10.3758/s13428-021-01762-8 Paper on eye-tracking reporting standards (great for beginners and experts alike) |
|
Suggested viewing |
https://www.youtube.com/watch?v=F5eBln42VyM Talk at the MRC CBU on how to hack pupillometry studies |
EEG/MEG I – Pre-processing |
||
Software |
MNE-Pythonneuro |
|
Datasets |
Sample dataset in MNE-Python. Tutorials |
|
Suggested reading |
||
Suggested viewing |
EEG/MEG II – Source Estimation |
||
Software |
||
Datasets |
Sample dataset in MNE-Python. Tutorials |
|
Suggested reading |
||
Suggested viewing |
EEG/MEG III – Time-Frequency and Functional Connectivity |
||
Software |
||
Datasets |
Sample dataset in MNE-Python. Tutorials |
|
Suggested reading |
Tutorial on Functional Connectivity |
|
Suggested viewing |
Time-frequency and functional connectivity analysis |
Graph Theory |
||
Software |
||
Datasets |
||
Suggested reading |
Complex brain networks: graph theoretical analysis of structural and functional systems |
|
Suggested viewing |
MVPA/RSA I |
||
Software |
||
Datasets |
The Decoding Toolbox example dataset |
|
Suggested reading |
Mur et al. (2009) Revealing representational content with pattern-information fMRI--an introductory guide |
|
Suggested viewing |
Excellent presentations from Martin Hebart's MVPA course, on: |
MVPA/RSA II |
||
Software |
The RSA toolbox in Matlab |
|
Datasets |
|
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Suggested reading |
Kriegeskorte et al. (2008) Representational similarity analysis - connecting the branches of systems neuroscience |
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Suggested viewing |
Statistics in R |
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Software |
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Datasets |
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Suggested reading |
Statistical Methods for Psychology (Howell) |
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Suggested viewing |
Brain Stimulation |
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Software |
SIMNIBS (also requires access to Matlab, FSL and Freesurfer to run certain functions, see SIMNIBS installation guide) and k-wave |
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Datasets |
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Suggested reading |
Approaches to brain stimulation ; what can we infer from brain stimulation; using NIBS clinically ; focused ultrasound 1 and 2 |
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Suggested viewing |
DCM for M/EEG |
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Software |
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Datasets |
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Suggested reading |
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Suggested viewing |
Talk on DCM for M/EEG coming soon |