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| <<BR>> [[https://doi.org/10.1016/j.neuroimage.2013.07.008|Simple Intro to DCM]]|| | <<BR>> [[https://doi.org/10.1016/j.neuroimage.2013.07.008|Simple Intro to DCM]] || |
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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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Structural MRI |
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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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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 |
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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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MVPA/RSA II |
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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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||Suggested reading || Preprocessing M/EEG in SPM12
Simple Intro to DCM ||
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To-be-updated: Second part on functional Connectivity M/EEG |