|
Size: 1513
Comment:
|
Size: 24837
Comment: only temporary
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 4: | Line 4: |
| 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''' Rik Henson & Olaf Hauk || ||Software || || |
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)>> ||||||<tablewidth="734px" tableheight="248px"style="text-align:center">~+'''Introduction and Open Science'''+~ <<BR>> Rik Henson & Olaf Hauk || ||<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]] || ||__Tutorial slides and scripts__ ||[[attachment:COGNESTIC_OpenCogNeuro.pdf|Open Science Talk Slides]] || <<BR>> <<Anchor(pythonprimer)>> ||||||<tablewidth="734px" tableheight="248px"style="text-align:center">~+'''Primer on Python'''+~ <<BR>> Edwin Dalmijer || ||<10%>__Websites__ ||[[https://www.python.org/|Python]], [[https://numpy.org/|NumPy]], [[https://scipy.org/|SciPy]], [[https://matplotlib.org/|Matplotlib]], [[https://psychopy.org/|PsychoPy]] || ||__Suggested reading__ ||None || ||__Suggested viewing__ ||[[https://www.youtube.com/watch?v=H8Du3llCa6w|saliency-mapping of Taylor Swift music videos]] || ||__Tutorial slides and scripts__ ||None || <<BR>> <<Anchor(structuralmri)>> ||||||<tablewidth="100%"style="text-align:center">'''Structural MRI I - Voxel-based morphometry'''~+''' '''+~<<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]] || ||__Tutorial slides and scripts__ ||[[attachment:COGNESTIC_FSLVBM.pdf|FSLVBM slides]] <<BR>> [[attachment:FSLVBM_tutorials.docx|FSLVBM tutorial]] <<BR>> [[attachment:FSLVBM_cognestic_all.sh|FSLVBM bash script]] <<BR>> <<BR>> [[attachment:COGNESTIC_FS_CorticalThickness.pdf|FreeSurfer Cortical Thickness slides]] <<BR>> [[attachment:FreeSurfer_tutorials.docx|Freesurfer tutorials]] <<BR>> [[attachment:FS_check_location.sh|FS check location script]] <<BR>> [[attachment:FS_visualising_output.sh|FS visualising the output script]]<<BR>> [[attachment:FS_group_analysis.sh|FS group analysis script]] <<BR>> [[attachment:FS_ROI_analysis.sh|FS ROI analysis script]] || <<BR>> <<Anchor(structuralmri2)>> ||||||<tablewidth="100%"style="text-align:center">'''Structural MRI II - Surface-based analyses'''~+''' '''+~<<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__ || || ||__Suggested viewing__ || || ||__Tutorial slides and scripts__ || || <<BR>> <<Anchor(diffusionmri1)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI I - The Diffusion Tensor Model'''+~ <<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]] || ||__Tutorial slides and scripts__ ||[[attachment:COGNESTIC_FSL_DTI&TBSS.pdf|FSL DTI and TBSS slides]] <<BR>> [[attachment:FSL_FDT_DTI_tutorials.docx|DTI and group analysis in TBSS tutorial]]<<BR>> [[attachment:FDT_DTI_pipeline.sh|FSL DTI pipeline script]] <<BR>> [[attachment:FDT_DTI_TBSS.sh|FSL TBSS script]]<<BR>> [[attachment:FDT_DTI_group_QC.sh|FSL Group QC script]] || <<BR>> <<Anchor(diffusionmri2)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Diffusion MRI II - Tractography and the Anatomical Connectome'''+~ <<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]] || ||__Tutorial slides and scripts__ ||[[attachment:COGNESTIC_MRtrix_tractography.pdf|MRtrix Tractography slides]] <<BR>> [[attachment:MRtrix_dMRI_tutorials.docx|MRtrix Tractography tutorials]] <<BR>> [[attachment:MRTrix_dMRI_preprocessing.sh|MRtrix preprocessing script]] <<BR>> [[attachment:MRTrix_dMRI_CSD_tractography.sh|MRtrix CSD Tractography script]] <<BR>> [[attachment:MRTrix_dMRI_connectome.sh|MRtrix connectome script]] || <<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) || ||Slides and scripts__ __ ||https://github.com/dcdace/COGNESTIC-fMRI || <<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__ __ ||[[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) || ||Slides and scripts ||https://github.com/dcdace/COGNESTIC-fMRI || <<BR>> <<Anchor(fmri3)>> ||||||<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) || ||Slides and scripts__ __ ||https://github.com/dcdace/COGNESTIC-fMRI || <<BR>> <<Anchor(fmri4)>> ||||||<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) || ||Slides and scripts ||https://github.com/dcdace/COGNESTIC-fMRI || <<BR>> <<Anchor(connectivityfmri)>> ||||||<tablewidth="734px" tableheight="239px"style="text-align:center">~+'''fMRI Connectivity'''+~ <<BR>> Petar Raykov || ||<10%>__Software__ ||[[https://carpentries-incubator.github.io/SDC-BIDS-fMRI/aio/index.html|Nilearn Python]] || ||__Datasets__ ||[[https://nilearn.github.io/dev/modules/generated/nilearn.datasets.fetch_development_fmri.html|movie dataset]] || ||__Suggested reading__ ||[[http://dx.doi.org/10.1016/j.tics.2013.09.016|Resting-state functional Connectivity]] || ||__Suggested viewing__ ||[[https://www.youtube.com/watch?v=1VOKsWWLgjk|fMRI Functional and Effective Connectivity in fMRI]] || ||__Tutorial slides and scripts__ ||[[attachment:Multimodal_DCM_cognestic_tutorial_fMRI.pdf|DCM tutorial in SPM (not covered in-person)]] || <<BR>> <<Anchor(networks)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Brain Network Analysis'''+~ <<BR>> Lena Dorfschmidt || ||<10%>Software__ __ ||[[https://pypi.org/project/bctpy/|Brain connectivity toolbox in python]] || ||Datasets__ __ || || ||Suggested reading__ __ ||Bullmore, E., Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. ''Nat Rev Neurosci'' '''10''', 186–198 (2009). [[https://doi.org/10.1038/nrn2575|https://doi.org/10.1038/nrn2575]] <<BR>> Fornito, Alex, Andrew Zalesky, and Edward Bullmore. ''Fundamentals of brain network analysis''. Academic press, 2016. || ||Suggested viewing__ __ ||[[https://www.youtube.com/watch?v=HjSGqwAFRcc|Understanding your brain as a network and as art]] || ||Slides and scripts || || <<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]]<<BR>> [[attachment:MNE_Installation_Instructions.pdf|MNE Installation for Cognestic]] || ||__Datasets__ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/preprocessing/index.html|Tutorials]]<<BR>> [[attachment:MNE_Installation_Instructions.pdf|MNE Installation for Cognestic]] || ||__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]] || ||__Suggested viewing__ ||[[https://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures?action=AttachFile&do=view&target=EEGMEG1.mp4|Introduction to EEG/MEG Preprocessing]] <<BR>>[[https://mediacentral.ucl.ac.uk/Player/2909|What are we measuring with M/EEG]]? || ||Slides and scripts__ __ ||[[attachment:EEGMEG1-preprocessing.zip|Notebooks and Slides]] || <<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]]<<BR>> [[attachment:MNE_Installation_Instructions.pdf|MNE Installation for Cognestic]] || ||Datasets__ __ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/inverse/index.html|Tutorials]]<<BR>> [[attachment:MNE_Installation_Instructions.pdf|MNE Installation for Cognestic]] || ||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]] || ||Suggested viewing__ __ ||[[https://imaging.mrc-cbu.cam.ac.uk/methods/IntroductionNeuroimagingLectures?action=AttachFile&do=view&target=EEGMEG2_SourceEstimation.mp4|Introduction to EEG/MEG Source Estimation]] [[https://mediacentral.ucl.ac.uk/Player/2917|M/EEG Source Analysis in SPM]] || ||Slides and scripts ||[[attachment:EEGMEG2-sourceestimation.zip|Notebooks and Slides]] || <<BR>> <<Anchor(eegmeg4)>> ||||||<tablewidth="100%"style="text-align:center">~+'''EEG/MEG VI – Priors and Multimodal Imaging'''+~ <<BR>> Olaf Hauk || ||<10%>__Software__ ||[[https://mne.tools/stable/index.html|MNE-Python]]<<BR>> [[attachment:MNE_Installation_Instructions.pdf|MNE Installation for Cognestic]] || ||__Datasets__ ||Sample dataset in MNE-Python. [[https://mne.tools/stable/auto_tutorials/time-freq/index.html|Tutorials]]<<BR>> [[attachment:MNE_Installation_Instructions.pdf|MNE Installation for Cognestic]] || ||__Suggested reading__ || || ||__Suggested viewing__ || || ||Slides and scripts__ __ || || <<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]]. (This might not be accessible from the CBU internet connection, so please download it in advance or use a difffernt wifi connection) || ||__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]]. (I've suggested these two, but the others are worth a look too.) || ||Slides and scripts__ __ ||[[attachment:COGNESTIC22_MVPA_djm_Part1.pptx|Slides for morning session - MVPA]]<<BR>> [[attachment:TDTdemoFunctions.zip|These functions should be saved in a subfolder of the Decoding Toolbox demos folder]]<<BR>> [[attachment:FunctionsToGoInTopFolder.zip|These functions should be saved in the top-level folder]] <<BR>>(Please see the 3rd slide for an overview of the file structure expected by the demo scripts) || <<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>>For the demos, please download this alternative version: https://git.fmrib.ox.ac.uk/hnili/rsa <<BR>>(Note that the toolbox development has recently switched to Python. We will not be demoing this version, but you can find it here: [[https://github.com/rsagroup/rsatoolbox|Version 3.0]]) || ||Datasets__ __ ||[[attachment:imageryexp.zip|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]] || ||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]]<<BR>> <<BR>>EEG/MEG: <<BR>> [[https://pubmed.ncbi.nlm.nih.gov/27779910/%20|Tutorial on EEG/MEG decoding]]<<BR>> [[https://pubmed.ncbi.nlm.nih.gov/27779910|Temporal Generalization]] || ||Suggested viewing__ __ ||[[https://fmrif.nimh.nih.gov/course/mvpa_course/2017/08_lecture6|Martin Hebart's lecture on RSA]] || ||Slides and scripts ||[[attachment:COGNESTIC22_MVPA_djm_Part2.pptx|Slides for afternoon session - RSA]] <<BR>>[[attachment:FunctionsToGoInRsa-MasterDemos.zip|These functions should be saved in rsa-master/Demos]]<<BR>> [[attachment:EEGMEG4-decoding.zip|EEGMEG Notebooks and Slides]] || <<BR>> <<Anchor(brainstimulation)>> ||||||<tablewidth="100%"style="text-align:center">~+'''Brain Stimulation, Plethysmography, Electromyography'''+~ <<BR>> Ajay Halai, Alexis Deighton MacIntyre, Hristo Dimitrov || ||<10%>Software ||Plethysmography: https://github.com/alexisdmacintyre/SpeechBreathingToolbox || |
| Line 8: | Line 193: |
| ||Suggested reading || || ||<tablewidth="100%" tablestyle="border-color:#000000; "11% style="text-align:center; ">'''Introduction and Open Science''' Rik Henson & Olaf Hauk ||<11% style="text-align:center; ">'''Diffusion MRI I''' Marta Correia ||<11% style="text-align:center; ">'''fMRI I''' Dace Ap''š''valka ||<11% style="text-align:center; ">'''fMRI III''' Dace Ap''š''valka ||<11% style="text-align:center; ">'''Connectivity for fMRI''' Rik Henson ||<11% style="text-align:center; ">'''Lab visits''' (fMRI, EEG/MEG, TMS) || ||<11% style="text-align:center;">'''Structural MRI''' Marta Correia ||<11% style="text-align:center;">'''Diffusion MRI II''' Marta Correia ||<11% style="text-align:center;">'''fMRI II''' Dace Ap''š''valka ||<11% style="text-align:center;">'''fMRI IV''' Dace Ap''š''valka ||<11% style="text-align:center;">'''Eye-tracking''' Edwin Dalmijer ||<11% style="text-align:center;"> || |
||Suggested reading__ __ ||Brain Stimulation: <<BR>> [[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]] <<BR>><<BR>> Plethysmography: <<BR>>Heck, D. H., McAfee, S. S., Liu, Y., Babajani-Feremi, A., Rezaie, R., Freeman, W. J., ... & Kozma, R. (2017). Breathing as a fundamental rhythm of brain function. Frontiers in neural circuits, 10, 115. https://doi.org/10.3389/fncir.2016.00115 <<BR>> Varga, S., & Heck, D. H. (2017). Rhythms of the body, rhythms of the brain: Respiration, neural oscillations, and embodied cognition. Consciousness and Cognition, 56, 77-90. https://doi.org/10.1016/j.concog.2017.09.008 <<BR>>Allen, M., Varga, S., & Heck, D. H. (2022). Respiratory rhythms of the predictive mind. Psychological Review. https://doi.org/10.1037/rev0000391 || ||Suggested viewing__ __ ||Brain Stimulation: [[attachment:AH_slides.pptx|slides]] || ||Slides and scripts || || ---- ---- |
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 |
Open Cognitive Neuroscience (will give this talk live on day) |
|
Tutorial slides and scripts |
||
Primer on Python |
||
Websites |
||
Suggested reading |
None |
|
Suggested viewing |
||
Tutorial slides and scripts |
None |
|
Structural MRI I - Voxel-based morphometry |
||
Software |
||
Datasets |
Freesurfer tutorial data |
|
Suggested reading |
Introduction to GLM for structural MRI analysis |
|
Suggested viewing |
Using the command line |
|
Tutorial slides and scripts |
FSLVBM slides |
|
Structural MRI II - Surface-based analyses |
||
Software |
||
Datasets |
Freesurfer tutorial data |
|
Suggested reading |
|
|
Suggested viewing |
|
|
Tutorial slides and scripts |
|
|
Diffusion MRI I - The Diffusion Tensor Model |
||
Software |
||
Datasets |
||
Suggested reading |
FSL Diffusion Toolbox Wiki |
|
Suggested viewing |
||
Tutorial slides and scripts |
FSL DTI and TBSS slides |
|
Diffusion MRI II - Tractography and the Anatomical Connectome |
||
Software |
||
Datasets |
||
Suggested reading |
||
Suggested viewing |
||
Tutorial slides and scripts |
MRtrix Tractography slides |
|
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) |
|
Slides and scripts |
||
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) |
|
Slides and scripts |
||
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) |
|
Slides and scripts |
||
fMRI Connectivity |
||
Software |
||
Datasets |
||
Suggested reading |
||
Suggested viewing |
||
Tutorial slides and scripts |
||
Brain Network Analysis |
||
Software |
||
Datasets |
|
|
Suggested reading |
Bullmore, E., Sporns, O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10, 186–198 (2009). https://doi.org/10.1038/nrn2575 |
|
Suggested viewing |
||
Slides and scripts |
|
|
EEG/MEG I – Pre-processing |
||
Software |
||
Datasets |
Sample dataset in MNE-Python. Tutorials |
|
Suggested reading |
Digitial Filtering |
|
Suggested viewing |
Introduction to EEG/MEG Preprocessing |
|
Slides and scripts |
||
EEG/MEG II – Source Estimation |
||
Software |
||
Datasets |
Sample dataset in MNE-Python. Tutorials |
|
Suggested reading |
Linear source estimation and spatial resolution |
|
Suggested viewing |
Introduction to EEG/MEG Source Estimation M/EEG Source Analysis in SPM |
|
Slides and scripts |
||
EEG/MEG VI – Priors and Multimodal Imaging |
||
Software |
||
Datasets |
Sample dataset in MNE-Python. Tutorials |
|
Suggested reading |
|
|
Suggested viewing |
|
|
Slides and scripts |
|
|
MVPA/RSA I |
||
Software |
The Decoding Toolbox in Matlab. (This might not be accessible from the CBU internet connection, so please download it in advance or use a difffernt wifi connection) |
|
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: |
|
Slides and scripts |
Slides for morning session - MVPA |
|
MVPA/RSA II |
||
Software |
The RSA toolbox in Matlab |
|
Datasets |
Group-averged example data from Mitchell & Cusack (2016) Semantic and emotional content of imagined representations in human occipitotemporal cortex |
|
Suggested reading |
Kriegeskorte et al. (2008) Representational similarity analysis - connecting the branches of systems neuroscience |
|
Suggested viewing |
||
Slides and scripts |
Slides for afternoon session - RSA |
|
Brain Stimulation, Plethysmography, Electromyography |
||
Software |
Plethysmography: https://github.com/alexisdmacintyre/SpeechBreathingToolbox |
|
Datasets |
|
|
Suggested reading |
Brain Stimulation: |
|
Suggested viewing |
Brain Stimulation: slides |
|
Slides and scripts |
|
|