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||<rowstyle="mso-height-source:userset"height="40px" class="xl72" style="border-top:none;text-align:right">10:00 ||<class="xl75" style="border-top:none;border-left:none"> ||<width="145px" class="xl85" style="border-top:none;text-align:center" |2>'''[[attachment:MRPhysicsI_2018.pdf|MRI Physics I]]''' <<BR>> Marta Correia <<BR>> ~-This talk will cover the basic principles of MRI physics for beginners, including excitation and relaxation mechanisms, slice selective gradients, frequency and phase encoding, image formation and k-space.-~ ||<width="145px" class="xl85" style="border-top:none;text-align:center" |2>'''[[attachment:DiffusionMRI_2018.pdf|Introduction to Diffusion MRI]]''' <<BR>> Marta Correia <<BR>> ~-This workshop will cover the basic principles of diffusion MRI acquisition and data analysis.-~ ||<width="145px" class="xl82" style="border-top:none;text-align:center" |2>'''fMRI Analysis I - Pre-Processing''' <<BR>> Johan Carlin<<BR>> ~-Functional MRI data requires extensive pre-processing before it can be analysed. We will review how this is implemented in SPM. The workshop demonstrates pre-processing using Automatic Analysis (AA).-~ ||<width="145px" class="xl82" style="border-top:none;text-align:center" |2>'''fMRI Analysis III - Group Analysis and Statistical Inference'''<<BR>> Johan Carlin<<BR>>~-In fMRI, most statistical inferences are made at the group level. We will cover how SPM implements random-effects group (ie, second-level) analysis. We will also discuss multiple comparisons correction in SPM, and non-parametric alternatives. The workshop demonstrates how to run a group-level analysis in SPM, and how to threshold statistical maps in the results user interface.-~ ||<width="145px" class="xl80" style="border-top:none;text-align:center" |2>'''Graph Theory''' <<BR>> Sarah Morgan<<BR>> ~-An introduction to graph theoretical analysis of brain networks, aimed at beginners. We will discuss the motivation for graph theoretical approaches, learn how to calculate some simple graph theory metrics, compare the results to null models and signpost some novel, more complex graph theoretical techniques.~- || ||<rowstyle="mso-height-source:userset"height="40px" class="xl72" style="border-top:none;text-align:right">10:00 ||<class="xl75" style="border-top:none;border-left:none"> ||<width="145px" class="xl85" style="border-top:none;text-align:center" |2>'''[[attachment:MRPhysicsI_2018.pdf|MRI Physics I]]''' <<BR>> Marta Correia <<BR>> ~-This talk will cover the basic principles of MRI physics for beginners, including excitation and relaxation mechanisms, slice selective gradients, frequency and phase encoding, image formation and k-space.-~ ||<width="145px" class="xl85" style="border-top:none;text-align:center" |2>'''[[attachment:DiffusionMRI_2018.pdf|Introduction to Diffusion MRI]]''' <<BR>> Marta Correia <<BR>> ~-This workshop will cover the basic principles of diffusion MRI acquisition and data analysis.-~ ||<width="145px" class="xl82" style="border-top:none;text-align:center" |2>'''fMRI Analysis I - Pre-Processing''' <<BR>> Johan Carlin<<BR>> ~-Functional MRI data requires extensive pre-processing before it can be analysed. We will review how this is implemented in SPM. The workshop demonstrates pre-processing using Automatic Analysis (AA).-~ ||<width="145px" class="xl82" style="border-top:none;text-align:center" |2>'''fMRI Analysis III - Group Analysis and Statistical Inference'''<<BR>> Johan Carlin<<BR>>~-In fMRI, most statistical inferences are made at the group level. We will cover how SPM implements random-effects group (ie, second-level) analysis. We will also discuss multiple comparisons correction in SPM, and non-parametric alternatives. The workshop demonstrates how to run a group-level analysis in SPM, and how to threshold statistical maps in the results user interface.-~ ||<width="145px" class="xl80" style="border-top:none;text-align:center" |2>'''Graph Theory''' <<BR>> Sarah Morgan<<BR>> ~-An introduction to graph theoretical analysis of brain networks, aimed at beginners. We will discuss the motivation for graph theoretical approaches, learn how to calculate some simple graph theory metrics, compare the results to null models and signpost some novel, more complex graph theoretical techniques.-~ ||

Introduction to Neuroimaging Methods

Lectures and Workshops

Lectures and workshops will take place in January and February 2018 in the CBU West Wing Seminar Room (unless stated otherwise, please check below). They are structured in three blocks: MRI (Jan 15-17), fMRI and Connectivity (Feb 13-15), as well as EEG/MEG and Multimodal Imaging (Feb 19-23). Workshops usually take about 2 hours, lectures may be shorter.

Details will be announced before individual events via this mailing list: http://lists.mrc-cbu.cam.ac.uk/mailman/listinfo/skillstraining (Non-CBU people can subscribe by sending an e-mail to skillstraining-subscribe (at) mrc-cbu (dot) cam (dot) ac (dot) uk).

We expect attendees to have basic skills in scientific computing and programming, e.g. at the level taught in our previous workshops. It might help to refresh your memories a little bit.

Look here for other training opportunities in and around Cambridge.

Please contact OlafHauk with questions and feedback.


BrainComputer.jpg


(f)MRI and Connectivity

Jan 15
(Mon)

Jan 16
(Tue)

Jan 17
(Wed)

Feb 13
(Tue)

Feb 14
(Wed)

Feb 15
(Thu)

10:00

MRI Physics I
Marta Correia
This talk will cover the basic principles of MRI physics for beginners, including excitation and relaxation mechanisms, slice selective gradients, frequency and phase encoding, image formation and k-space.

Introduction to Diffusion MRI
Marta Correia
This workshop will cover the basic principles of diffusion MRI acquisition and data analysis.

fMRI Analysis I - Pre-Processing
Johan Carlin
Functional MRI data requires extensive pre-processing before it can be analysed. We will review how this is implemented in SPM. The workshop demonstrates pre-processing using Automatic Analysis (AA).

fMRI Analysis III - Group Analysis and Statistical Inference
Johan Carlin
In fMRI, most statistical inferences are made at the group level. We will cover how SPM implements random-effects group (ie, second-level) analysis. We will also discuss multiple comparisons correction in SPM, and non-parametric alternatives. The workshop demonstrates how to run a group-level analysis in SPM, and how to threshold statistical maps in the results user interface.

Graph Theory
Sarah Morgan
An introduction to graph theoretical analysis of brain networks, aimed at beginners. We will discuss the motivation for graph theoretical approaches, learn how to calculate some simple graph theory metrics, compare the results to null models and signpost some novel, more complex graph theoretical techniques.

11:00

Some Physics You Might Find Useful
Olaf Hauk Demonstration of basic physical concepts needed for the interpretation of EEG/MEG and fMRI data, including some experimental demos.

13:30

MRI Physics II
Marta Correia
This talk is aimed at fMRI beginners. Firstly, I will talk about the basic mechanisms behind BOLD contrast. In the second half of the talk, I will discuss common image artefacts and ways to work around them.

Lab tour and demo
Marta Correia, Marius Mada

fMRI Analysis II - GLM and Experimental Design
Johan Carlin
The single-participant (ie, first-level) general linear model is at the heart of SPM's fMRI implementation. After going over its features, we will discuss what the SPM GLM implies about which experimental designs are likely to work well (ie, are efficient). The workshop is an interactive exploration of the efficiency of different fMRI designs.

fMRI/EEG/MEG Connectivity
Rik Henson

14:30


EEG/MEG and Multimodal Imaging

Feb 19
(Mon)

Feb 20
(Tue)

Feb 21
(Wed)

Feb 22
(Thu)

Feb 23
(Fri)

10:00:00

EEG/MEG 1 - pre-processing
Olaf Hauk

EEG/MEG 2 - Source Estimation
Olaf Hauk

Brain Stimulation
Benedikt Zoefel

EEG/MEG Analysis in SPM
Jason Taylor and Rik Henson

Source Estimation And Statistics in SPM
Jason Taylor and Rik Henson

11:00:00

13:30:00

MEG lab visit and demo
Clare Cook and Olaf Hauk

EEG/MEG 3 - time-frequency and functional connectivity
Olaf Hauk

Multimodal Imaging
Rik Henson

Multimodal Imaging In SPM
Jason Taylor and Rik Henson

14:30:00



PREVIOUS schedule (with materials attached)

April 26

14.30

Multivariate fMRI Analysis I PDF

Marieke Mur

Lecture + Workshop

This workshop introduces linear classification, one of the most popular forms of multivoxel pattern analysis. We will give an overview of the most commonly used linear classifiers, and list the steps that are needed to implement a classification analysis. The workshop will include a hands-on matlab session, during which we'll go through example code that performs linear classification on an fMRI data set.

May 3

14.30

Multivariate fMRI Analysis II PDF

Marieke Mur

Lecture + Workshop

This workshop introduces representational similarity analysis (RSA), a more recent form of multivoxel pattern analysis which has gained popularity over the last few years. We will give an overview of the origin of RSA and how it relates to linear classification, and list the steps that are needed to implement RSA. The workshop will include a hands-on matlab session, during which we'll analyse the same fMRI data as last week, but this time using RSA.

May 10

14.00

Multimodal Imaging

Rik Henson

Lecture

This lecture will describe possible generative models that can be used to integrate data from EEG, MEG and fMRI

May 16 (Tuesday !!!)

13.00

Connectivity with EEG/MEG and fMRI

Rik Henson

Lecture

This lecture will introduce concepts of functional and effective connectivity, briefly describe effective connectivity in fMRI (eg dynamic causal modelling) and then expand on the larger range of methods available for measuring connectivity with EEG/MEG.

May 24

14.30

Diffusion MRI I

Marta Correia

Lecture + Workshop

This workshop will cover the basic principles of diffusion MRI acquisition and data analysis. It will include a practical component covering pre-processing of diffusion MRI data, model fitting, group analysis of diffusion parameters and tractography.

May 31

14.30

Diffusion MRI II

Marta Correia

Lecture + Workshop

In this week’s workshop we will continue the hands on session for pre-processing of diffusion MRI data and introduce methods for group analyses. We will also cover more advanced diffusion MRI methods, including tractography and probabilistic modelling.

July 26/27

fMRI and EEG/MEG Analysis in SPM - from raw data to multimodal images

WWSR

Wed, July 26

10.00-12.00

Introduction to EEG/MEG analysis in SPM

Jason Taylor

Lecture+Demo

Introduction and overview of EEG/MEG analysis in SPM.

14.00-16.00

fMRI analysis in SPM

Jason Taylor & Rik Henson

Lecture+Demo

Demo of standard fMRI analysis in SPM12.

Thu, July 27

10.00-12.00

Source estimation and statistics in SPM

Jason Taylor & Rik Henson

Lecture+Demo

Demo of source estimation and statistics in SPM12.

14.00-16.00

Multimodal imaging workshop and Q&A

Jason Taylor, Rik Henson, Hunar Abdulrahman

Workshop

Participants can analyse a multi-modal data set under supervision, following chapter 42 of the SPM12 manual


Previous Lent Term

Date

Time

Title

Presenter(s)

Type

Comments

Jan 18

14.30

A Field Day: Some Physics You May Find Useful

Olaf Hauk

Lecture (~ 1h)

Basic physical concepts needed for the interpretation of EEG/MEG and fMRI data. Electric potential, fields, atoms and spins...

Jan 25

14.30

MRI Physics 1: Introduction to MRI Physics

Marta Correia

Lecture (~1.5h)

This talk will cover the basic principles of MRI physics for beginners, including nuclear spins and net magnetization, excitation and relaxation mechanisms, slice selective gradients, frequency and phase encoding, image formation and k-space.

Jan 30 (Monday!!)

12.30

MRI Physics 2:The BOLD Signal and Common Artefacts

Marta Correia

Lecture

This talk is aimed at fMRI beginners and will be divided into two parts. Firstly, I will talk about the biophysics of fMRI and the basic mechanism behind BOLD contrast. In the second half, I will discuss common image artefacts and ways to work around them.

Feb 8

14.30

fMRI Analysis 1: fMRI Pre-Processing (workshop materials)

Johan Carlin

Lecture + Workshop

We will cover basic preprocessing of fMRI data, and some useful diagnostic visualisations to help spot problems.

Feb 15

14.30

fMRI Analysis 2: Single subject analysis using GLM (workshop materials)

Johan Carlin

Lecture + Workshop

This workshop covers the basic principles of single-subject design focusing on how it is implemented in SPM. We will also discuss how to design efficient fMRI experiments.

Feb 22

14.30

fMRI Analysis 3: Group analysis and statistical inference (workshop materials)

Johan Carlin

Lecture + Workshop

After a short recap of the GLM, which also is the basis of group analysis, we will review some example designs. We will focus especially on statistical inference and multiple comparisons correction.

Mar 1

14.30

Brain stimulation PDF

Benedikt Zöfel

Lecture (45 min approx.)

This talk will provide an introduction to brain stimulation methods, with a focus on transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES). I will cover the principles of these techniques, the physiological basis of the effects, the different protocols used, and examples of how brain stimulation can be used as an experimental and therapeutic tool.

Mar 8

14.30

EEG/MEG 1: Pre-processing and Data Reviewing PDF

Olaf Hauk

Lecture + Workshop

Signal generation, Maxfilter, Common artefacts, ICA, Averaging, MEG-MRI Coregistration

Mar 14 (!!!) Tuesday

14.30

EEG/MEG 2: Head Models and Source Estimation PDF

Olaf Hauk

Lecture+Workshop

We will look at structural MRI data and reconstructed cortical surfaces, co-register MRI and MEG coordinate systems, talk about the basis theory of source estimation, and try some linear source estimation ourselves. We will then compare different methods as well as EEG and MEG with respect to spatial resolution using the concepts of point-spread and cross-talk.

April 5 (postponed from March 22nd)

14.30

EEG/MEG 3: Time-frequency and Functional Connectivity Analysis PDF

Olaf Hauk

Lecture+Workshop

Basics of Fourier and Wavelet analysis; source estimation at single-trial level; spatial resolution: point- and field-spread; spectral connectivity: coherence and phase-locking; possibly more…

None: IntroductionNeuroimagingLectures (last edited 2024-02-19 09:44:51 by OlafHauk)