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fMRI Methods Lecture1 - Introduction

FMRI Methods Lecture1 - Introduction. [email protected]

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Page 1: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

fMRI Methods

Lecture1 - Introduction

Page 2: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

http://www.weizmann.ac.il/neurobiology/labs/malach/ilan

[email protected]

Leonesco Bldg. room 208

Page 3: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Go over syllabus

Weekly exercises, final project (grades)

Office hours

Groups

Scanning (safety, Helsinki)

Matlab (experience, licenses)

Huettel et. al.

Course overview

Page 4: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Imaging

Contrast

Resolution(spatial, temporal)

Page 5: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Resolution scales

Page 6: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

MRI scanner

What is the measurement in this image?

Page 7: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Hydrogen atoms

Page 8: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Physics

Sta

tic m

agne

tic fi

eld

dire

ctio

n

Page 9: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Physics

Page 10: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

The voxel

Page 11: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

First anatomical MRI

106 voxels took 4 hours to scan!

Damadian et. al. 1977

Page 12: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Anatomy

1T 2T

Page 13: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Anatomical measures

Gray/White matter Cortical thickness

Page 14: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Diffusion tensor imaging (DTI)

Page 15: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Tractography

Blue: up-down Green: fwd-bwd Yellow: right-left

Page 16: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Tractography

Page 17: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

So far we didn’t care about temporal resolution.

Page 18: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Neurovascular coupling

Heeger et. al. 2002

Page 19: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Hemodynamics

Page 20: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Hemodynamic changes

Heeger et. al. 2002

Time

Page 21: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Hemodynamic response

Page 22: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Experiment

Page 23: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Experiment

Page 24: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

scan/volume fMRI

R L

Front

Back

24 slices every 1.5 seconds

Page 25: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

fMRI activation maps

Motor system

Page 26: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

fMRI activation maps

Motor system

Visualsystem

Page 27: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

fMRI activation maps

Motor system

Visualsystem

Obsession with localization!

Page 28: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

With fMRI we care about temporal resolution.

Temporal sampling rate.

Limited by Hemodynamics

Page 29: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Break

Page 30: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

A tool for manipulating vectors and matrices.

Matlab offers an immense number of functions with which one can do these manipulations quickly.

Generally we will assume that our data (neural and hemodynamic responses) are generated by a linear

system.

What does it mean to be linear?

Matlab

Page 31: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

A linear system is one that satisfies the following two conditions:

1. Additivity/Superposition – f(x+y) = f(x) + f(y)

2. Homogeneity – f(ax) = af(x)

What does this mean?

Linearity

Page 32: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

a*x + b*y + c*z

scaling/weighting

Example of a linear system

X

Y

Stimulus and neural response:

X (stimulus) = a*Y (neural response)

Page 33: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

The response of a single neuron at any given time is non-linear.

It’s an all or nothing response with a certain threshold – a spike.

A linear system has to output “graded” responses of consistently increasing/decreasing amplitudes.

However, the summed response of a neuron across time windows of a given length (i.e. compute its firing rate) may be linear….

Example of a non-linear system

Page 34: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

The response of a single neuron at any given time is non-linear.

It’s an all or nothing response with a certain threshold – a spike.

A linear system has to output “graded” responses of consistently increasing/decreasing amplitudes.

However, the summed response of a neuron across time windows of a given length (i.e. compute its firing rate) may be linear….

Example of a non-linear system

Page 35: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Are incredibly useful ways of representing data...

Vectors and matrices

For example images of the brain

Page 36: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Are incredibly useful ways of representing data...

Vectors and matrices

Or sound – voltage changes over time

Page 37: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

And for manipulating the data...

Vectors and matrices

How would you increase the volume of this sound segment?

Page 38: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Go over handout

Open Matlab getting started section

“Geometric” linear algebra

Page 39: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Open a folder for your code on the local computer. Try to keep the path name simple (e.g. “C:\Your_name”).

Download code and MRI data from:http://www.weizmann.ac.il/neurobiology/labs/malach/ilan/lecture_notes.html

Save Lab1.zip in the folder you’ve created and unzip.

Open Matlab. Change the “current directory” to the directory you’ve created.

Open: “Lab1_VisualizingBrain.m”When done open: “Lab1_CreatingStimuli.m”

Matlab Tutorials

Page 40: FMRI Methods Lecture1 - Introduction.  ilan.dinstein@weizmann.ac.il

Read Chapters 1 & 2 of Huettel et. al. (available in library)

Review Geometric linear algebra handout

Matlab exercise: email me the report as a word document. The report should include answers, figures, and the actual Matlab code used to generate them (copy it into word).

This week, don’t forget to also send me the movie you’ve created.

Homework!