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||<10%>__Software__ ||N/A || ||__Datasets__ ||N/A || ||__Suggested reading__ ||[[https://doi.org/10.1038/nrn.2016.167|Poldrack et al, NRN]] || ||__Suggested viewing__ ||N/A || |
||<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://youtu.be/kTVtc7kjVQg|Open Cognitive Neuroscience (will give this talk live on day)]] <<BR>> [[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__ ||[[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]] || |
||||||<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]] <<BR>> Subset of the CamCAN dataset (~3GB) https://www.cam-can.org/, please sign [[attachment:CamCAN Data User Agreement_COGNESTIC.docx|data user agreement]] if using || ||__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]] <<BR>> [[attachment:IntroductionToMRIPhysics.pdf|Slides]] || |
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||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI I'''+~ <<BR>> Marta Correia || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<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]] <<BR>> [[attachment:IntroductionToDiffusionMRI_I.pdf|Slides]] || |
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||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI II'''+~ <<BR>> Marta Correia || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<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]] <<BR>> [[attachment:IntroductionToDiffusionMRI_II.pdf|Slides]] || |
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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI I'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<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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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI II'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<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__ ||[[https://link.springer.com/article/10.1007/s11065-015-9294-9|Chen & Glover (2015), Functional Magnetic Resonance Imaging Methods]]<<BR>> [[https://mriquestions.com/uploads/3/4/5/7/34572113/ch2.pdf|Ashburner J & Friston KJ (2004), Rigid body registration]]<<BR>> [[https://doi.org/10.1002/mrm.24314|Maclaren et al. (2013), Prospective Motion Correction in Brain Imaging: A Review]]<<BR>> [[https://doi.org/10.1016/j.neuroimage.2011.06.078|Sladky et al. (2011), Slice-timing effects and their correction in functional MRI]]<<BR>> [[https://doi.org/10.1006/nimg.2000.0609|Friston et al. (2000), To Smooth or Not to Smooth?: Bias and Efficiency in fMRI Time-Series Analysis]]<<BR>> [[https://www.nature.com/articles/s41592-018-0235-4|Esteban et al., 2018, fMRIPrep: a robust preprocessing pipeline for functional MRI]] || ||__Suggested viewing__ ||[[https://youtu.be/7Kk_RsGycHs|fMRI Artifacts and Noise]] by Martin Lindquist and Tor Wager (11:57)<<BR>>[[https://youtu.be/Qc3rRaJWOc4|Pre-processing I]] by Martin Lindquist and Tor Wager (10:17)<<BR>>[[https://youtu.be/qamRGWSC-6g|Pre-processing II]] by Martin Lindquist and Tor Wager (7:42) || |
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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI III - Subject Level 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__ ||[[https://doi.org/10.1002/hbm.460020402|Friston et al. (1994), Statistical parametric maps in functional imaging: A general linear approach]]<<BR>>[[https://doi.org/10.1016/j.neuroimage.2012.01.133|Poline & Brett (2012), Poline, J. B., & Brett, M. (2012). The general linear model and fMRI: does love last forever?]]<<BR>>[[https://doi.org/10.3389/fnhum.2011.00028|Monti (2011), Statistical analysis of fMRI time-series: a critical review of the GLM approach]]<<BR>>[[https://doi.org/10.1191/0962280203sm341ra|Nichols & Hayasaka (2003), Controlling the familywise error rate in functional neuroimaging: a comparative review]]<<BR>>[[https://doi.org/10.1016/j.neuroimage.2008.05.021|Chumbley & Friston (2009), False discovery rate revisited: FDR and topological inference using Gaussian random fields]]<<BR>>[[https://doi.org/10.1016/j.neuroimage.2013.12.058|Woo et al. (2014), Cluster-extent based thresholding in fMRI analyses: Pitfalls and recommendations]]<<BR>>[[https://doi.org/10.1214/09-STS282|Lindquist (2008), The Statistical Analysis of fMRI Data]] || ||__Suggested viewing__ ||[[https://youtu.be/GDkLQuV4he4|The General Linear Model]] by Martin Lindquist and Tor Wager (12:24)<<BR>>[[https://www.youtube.com/watch?v=OyLKMb9FNhg|GLM applied to fMRI]] by Martin Lindquist and Tor Wager (11:21)<<BR>>[[https://www.youtube.com/watch?v=7MibM1ATai4|Model Building I – conditions and contrasts]] by Martin Lindquist and Tor Wager (11:48)<<BR>>[[https://www.youtube.com/watch?v=YfeMIcDWwko|Model Building II – temporal basis sets]] by Martin Lindquist and Tor Wager (11:08)<<BR>>[[https://www.youtube.com/watch?v=DEtwsFdFwYc|Model Building III- nuisance variables]] by Martin Lindquist and Tor Wager (13:58)<<BR>>[[https://www.youtube.com/watch?v=Ab-5AbJ8gAs|GLM Estimation]] by Martin Lindquist and Tor Wager (9:11)<<BR>>[[https://youtu.be/Mb9LDzvhecY|Noise Models- AR models]] by Martin Lindquist and Tor Wager (9:57)<<BR>>[[https://youtu.be/NRunOo7EKD8|Inference- Contrasts and t-tests]] by Martin Lindquist and Tor Wager (11:05)<<BR>>[[https://youtu.be/AalIM9-5-Pk|Multiple Comparisons]] by Martin Lindquist and Tor Wager (9:03)<<BR>>[[https://youtu.be/MxQeEdVNihg|FWER Correction]] by Martin Lindquist and Tor Wager (16:11)<<BR>>[[https://youtu.be/W9ogBO4GEzA|FDR Correction]] by Martin Lindquist and Tor Wager (5:25)<<BR>>[[https://youtu.be/N7Iittt8HrU|More about multiple comparisons]] by Martin Lindquist and Tor Wager (14:39) || |
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||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV'''+~ <<BR>> Dace Apšvalka || ||<10%>__Software__ || || ||__Datasets__ || || ||__Suggested reading__ || || ||__Suggested viewing__ || || |
||||||<tablewidth="100%"style="text-align:center">~+'''fMRI IV - Group Level Analysis & 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__ ||[[https://doi.org/10.1109/MEMB.2006.1607668|Mumford & Nichols (2006), Modeling and inference of multisubject fMRI data]]<<BR>>[[https://www.nature.com/articles/nn.4500|Nichols et al. (2017), Best practices in data analysis and sharing in neuroimaging using MRI]]<<BR>>[[https://doi.org/10.1016/j.neuroimage.2007.11.048|Poldrack et al. (2008), Guidelines for reporting an fMRI study]]<<BR>>[[https://doi.org/10.1016/j.neuroimage.2015.04.016|Gorgolewski et al. (2016), NeuroVault.org: A repository for sharing unthresholded statistical maps, parcellations, and atlases of the human brain]]<<BR>>[[https://doi.org/10.7554/eLife.71774|Markiewicz et al. (2021), The OpenNeuro resource for sharing of neuroscience data]] || ||__Suggested viewing__ ||[[https://youtu.be/__cOYPifDWk|Group-level Analysis I]] by Martin Lindquist and Tor Wager (7:05)<<BR>>[[https://youtu.be/-abMLQSjMSI|Group-level Analysis II]] by Martin Lindquist and Tor Wager (10:09)<<BR>>[[https://youtu.be/-yaHTygR9b8|Group-level Analysis III]] by Martin Lindquist and Tor Wager (14:01) || |
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||__Suggested viewing__ ||[[https://youtu.be/1VOKsWWLgjk|fMRI Functional Connectivity, including DCM]] || | ||__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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||<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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||<10%>__Software__ ||[[https://mne.tools/stable/index.html|MNE-Python]]neuro || | ||<10%>__Software__ ||[[https://mne.tools/stable/index.html|MNE-Python]] || |
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||__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 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]] <<BR>> [[attachment:General EEGMEG Literature.pdf|General EEG/MEG Literature]] || |
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||__Suggested reading__ ||[[https://pubmed.ncbi.nlm.nih.gov/35390459/|Linear source estimation and spatial resolution]] || | ||__Suggested reading__ ||[[https://pubmed.ncbi.nlm.nih.gov/35390459/|Linear source estimation and spatial resolution]]<<BR>> [[attachment:General EEGMEG Literature.pdf|General EEG/MEG Literature]] || |
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||__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 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]]<<BR>> [[attachment:General EEGMEG Literature.pdf|General EEG/MEG Literature]] || |
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||__Datasets__ || || | ||__Datasets__ || [[attachment:imagerydataset|Group-averged example data]] from [[https://www.nature.com/articles/srep20232|Mitchell & Cusack (2016) Semantic and emotional content of imagined representations in human occipitotemporal cortex]]|| |
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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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||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG'''+~ <<BR>> Rik Henson || | ||||||<tablewidth="100%"style="text-align:center">~+'''DCM for M/EEG'''+~ <<BR>> Pranay Yadav & Rik Henson || |
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||__Suggested viewing__ ||[[https://mediacentral.ucl.ac.uk/Play/63377|DCM for MEEG evoked responses]] <<BR>> [[https://youtu.be/6b35VvQpPDU|MEEG connectivity other than DCM (not demo'ed, and related to Hauk talks above)]] || | ||__Suggested viewing__ ||[[https://www.youtube.com/watch?v=HNaAvKmVCYo|Talk on DCM for M/EEG]] <<BR>> [[https://youtu.be/6b35VvQpPDU|MEEG connectivity other than DCM (not demo'ed, and related to Hauk talks above)]] || |
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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 |
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Websites |
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Suggested reading |
Munafo et al, 2017, problems in science |
|
Suggested viewing |
Open Cognitive Neuroscience (will give this talk live on day) |
Structural MRI - VBM and Surface-based Analysis |
||
Software |
||
Datasets |
Freesurfer tutorial data |
|
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 |
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Suggested viewing |
Diffusion MRI II - Tractography and Structural Connectivity |
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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 |
Chen & Glover (2015), Functional Magnetic Resonance Imaging Methods |
|
Suggested viewing |
fMRI Artifacts and Noise by Martin Lindquist and Tor Wager (11:57) |
fMRI IV - Group Level Analysis & Reporting |
||
Software |
||
Datasets |
||
Suggested reading |
Mumford & Nichols (2006), Modeling and inference of multisubject fMRI data |
|
Suggested viewing |
Group-level Analysis I by Martin Lindquist and Tor Wager (7:05) |
Connectivity for fMRI |
||
Software |
||
Datasets |
||
Suggested reading |
Resting-state functional Connectivity |
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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 |
||
Datasets |
Sample dataset in MNE-Python. Tutorials |
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Suggested reading |
Digitial Filtering |
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Suggested viewing |
EEG/MEG II – Source Estimation |
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Software |
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Datasets |
Sample dataset in MNE-Python. Tutorials |
|
Suggested reading |
Linear source estimation and spatial resolution |
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Suggested viewing |
EEG/MEG III – Time-Frequency and Functional Connectivity |
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Software |
||
Datasets |
Sample dataset in MNE-Python. Tutorials |
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Suggested reading |
Tutorial on Functional Connectivity |
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Suggested viewing |
Time-frequency and functional connectivity analysis |
Graph Theory |
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Software |
||
Datasets |
||
Suggested reading |
Complex brain networks: graph theoretical analysis of structural and functional systems |
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Suggested viewing |
MVPA/RSA I |
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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: |
Statistics in R |
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Software |
||
Datasets |
||
Suggested reading |
Statistical Methods for Psychology (Howell) |
|
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 |
|
Datasets |
||
Suggested reading |
Approaches to brain stimulation ; what can we infer from brain stimulation; using NIBS clinically ; focused ultrasound 1 and 2 |
|
Suggested viewing |
DCM for M/EEG |
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Software |
||
Datasets |
||
Suggested reading |
||
Suggested viewing |
Talk on DCM for M/EEG |