SlideShare a Scribd company logo
1 of 45
Download to read offline
Hi, kids! My name
                                           is Vickie Voxel. I’m
                                             going to tell you
              ●   ●
                                           about fMRI, HRF &
                                                  BOLD.



                  Intro to fMRI
                            Part I: HRF & BOLD
Dr. Russell James, Texas Tech University
An fMRI picture of the
           brain is made up of
        thousands of boxes, called
           voxels, just like me!
●   ●
We voxels
are small –
  usually
 about the
size of one   ●   ●




peppercorn
Inside each
           of us
         voxels are
         thousands
        of neurons
●   ●
When a lot of
        these neurons
         start to fire,
           the body
           rushes in
●   ●   oxygen to help
This rush of
        oxygen comes
         through the
          blood and
          makes me
●   ●      start to
         change color
As my blood
           oxygen
        increases, I
         get redder

●   ●
And redder



●   ●
If this keeps
        going, I will be
          totally red
        from all of the
         oxygen in my
●   ●        blood
But then, if
          the neurons
           don’t keep
           firing, the
         body will stop
●   ●   rushing oxygen
              to me
And my color
        will start to
         return to
           normal

●   ●
I can get a bit
        blue at the end
         if my oxygen
        drops too low,
        right before it
●   ●      returns to
             normal
In 20 seconds
           after the
        neurons fired,
        I will be back
         to my normal
●   ●     color again
This whole
        color change
         process is
          called my
        hemodynamic
●   ●     response
“Hemo” means
                                                                             blood. “Dynamic”
                                                                             means change.
                                             ●   ●
                                                                             So, hemodynamic
                                                                             response is my
                                                                             “blood-change”
Blood Oxygen Level




                                     ●   ●           ●   ●



                                                                             response.
                             ●   ●                           ●   ●




                     ●   ●                                           ●   ●           ●   ●   ●   ●   ●   ●



                                                                             ●   ●




                         0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                             SECONDS after neurons fire  
When we model
                                                                              this change with
                                                                             math, we call it a
                                             ●   ●
                                                                               hemodynamic
                                                                             response function
Blood Oxygen Level




                                     ●   ●           ●   ●




                             ●   ●                           ●   ●




                     ●   ●                                           ●   ●           ●   ●   ●   ●   ●   ●



                                                                             ●   ●




                         0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                             SECONDS after neurons fire  
But, saying
                                                                                  “hemodynamic
                                                                                     response
                                             ●   ●
                                                                                 function” takes
                                                                                 too long, so we
                                                                                 will just call it
Blood Oxygen Level




                                     ●   ●           ●   ●



                                                                                     the HRF
                             ●   ●                           ●   ●




                     ●   ●                                           ●   ●           ●   ●   ●   ●   ●   ●



                                                                             ●   ●




                         0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                             SECONDS after neurons fire  
●   ●                                       The HRF
Blood Oxygen Level




                                     ●   ●           ●   ●




                             ●   ●                           ●   ●




                     ●   ●                                           ●   ●           ●   ●   ●   ●   ●   ●



                                                                             ●   ●




                         0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                             SECONDS after neurons fire  
The fMRI machine can see my color
        change because blood with a lot of
        oxygen (red) is less attracted to
        magnets than blood without much
        oxygen (pink or blue).


●   ●




●   ●
But, instead of showing pictures
in red, pinks, and blues, the fMRI
creates black and white pictures.



                                  Differences in
                                  magnetism are
                                  shown as shades of
                                  light and dark.
 ●   ●                ●       ●




 ●   ●
                  ●       ●
The fMRI machine is measuring a BOLD
signal because the color is
                            Blood
                            Oxygen
                            Level
                            Dependent



 ●   ●              ●       ●   High blood oxygen



                                Low blood oxygen
 ●   ●
                ●       ●
So, instead of an
                                                                             HRF looking like
                                                                                   this…
                                             ●   ●
Blood Oxygen Level




                                     ●   ●           ●   ●




                             ●   ●                           ●   ●




                     ●   ●                                           ●   ●           ●   ●   ●   ●   ●   ●



                                                                             ●   ●




                         0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                             SECONDS after neurons fire  
The fMRI shows
                                                                             an HRF that looks
                                                                                 like this…
                                             ●   ●
Blood Oxygen Level




                                     ●   ●           ●   ●




                             ●   ●                           ●   ●




                     ●   ●                                           ●   ●           ●   ●   ●   ●   ●   ●



                                                                             ●   ●




                         0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                             SECONDS after neurons fire  
Because the color
                                                                             tells us the blood
                                                                              oxygen level, we
                                             ●   ●
                                                                             really don’t need
                                                                              a vertical axis…
Blood Oxygen Level




                                     ●   ●           ●   ●




                             ●   ●                           ●   ●




                     ●   ●                                           ●   ●           ●   ●   ●   ●   ●   ●



                                                                             ●   ●




                         0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                             SECONDS after neurons fire  
We can just use
                                                           one line




●   ●       ●   ●       ●   ●       ●   ●       ●   ●       ●   ●   ●   ●   ●   ●   ●   ●




0       1   2       3   4       5   6       7   8       9   10 11 12 13 14 15 16
                        SECONDS after neurons fire  
And, if we always
                                                  take a picture
                                                 every 2 seconds,
                                                then we don’t even
                                                 need the seconds
                                                  on the bottom


●   ●       ●   ●       ●   ●       ●   ●       ●   ●       ●   ●   ●   ●   ●   ●   ●   ●




0       1   2       3   4       5   6       7   8       9   10 11 12 13 14 15 16
                        SECONDS after neurons fire  
So, all of our HRF
                                      information is
                                       shown on the
Neuron                                timeline below
firing
starts



 ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●   ●
But, instead of a
Neuron
firing
                                                 series of colors,
starts                                              the fMRI
                                                 machine gives us
                                                     numbers

 180     200         250       305        249         201       182       172         180

 ●   ●   ●   ●      ●   ●     ●   ●      ●   ●      ●   ●     ●   ●     ●   ●       ●   ●
The fMRI records a
Neuron                          number for the
firing                      magnetism of each voxel
starts                           at each time



 180     200         250       305        249         201       182       172         180

 ●   ●   ●   ●      ●   ●     ●   ●      ●   ●     ●   ●      ●   ●     ●   ●       ●   ●
If we take a picture every 3
seconds for 7 minutes, we get 140
     numbers for each voxel
And we might have 100,000 or so
   voxels in the whole brain
20 images per minute X 7 minutes
X 100,000 voxels X 20 people =
280 million data points
            We can’t track it by hand!
So we have to ask
 the computer to
analyze the data
But the computer
  needs to know
WHAT to look for
and WHEN to look
      for it
So WHAT are we
  looking for?
We are looking for changes in the
                         signal that look like this
                                              ●   ●
Blood Oxygen Level




                                      ●   ●           ●   ●




                              ●   ●                           ●   ●




                      ●   ●                                           ●   ●             ●   ●   ●   ●   ●   ●



                                                                                ●   ●




                          0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                                                              SECONDS
We are looking for changes in the
                         signal that look like this
                                              ●   ●
Blood Oxygen Level




                                      ●   ●           ●   ●




                              ●   ●                           ●   ●




                      ●   ●                                           ●   ●             ●   ●   ●   ●   ●   ●



                                                                                ●   ●




                          0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
                                                                              SECONDS
We are looking for changes in the
       signal that look like this…
        because this looks like an HRF,
        meaning it was caused by a large
            group of neurons firing

180       200         250       305        249         201       182       172         180

●   ●     ●   ●      ●   ●     ●   ●      ●   ●     ●   ●      ●   ●     ●   ●       ●   ●
We are looking for changes in the
       signal that look like this…
        because this looks like an HRF,
        meaning it was caused by a large
            group of neurons firing

180       200         250       305        249         201       182       172         180

●   ●     ●   ●      ●   ●     ●   ●      ●   ●     ●   ●      ●   ●     ●   ●       ●   ●
WHEN are we
looking for this
HRF-like signal?
We are interested in the HRF-like
signals that happen right after the
  subject experiences something

+     +      +            +      +
Then we can estimate the
likelihood that a voxel, or group of
    voxels, is responding to the
               stimulus
This simple concept can be
difficult in practice because:
1. The signal change is small
2. The brain is noisy
This simple concept can be
difficult in practice because:
1. The signal change is small
2. The brain is noisy

Overcoming these barriers
requires:
          Good study design
                  +
          Good data analysis
Bye for now!
                                            Next time we will
                                              look at how to
                                           create a good study
              ●   ●


                                                  design.



                  Intro to fMRI
                            Part I: HRF & BOLD
Dr. Russell James, Texas Tech University

More Related Content

What's hot

EEG Artifact and How to Resolve
EEG Artifact and How to ResolveEEG Artifact and How to Resolve
EEG Artifact and How to ResolveLalit Bansal
 
Event Related Potentials
Event Related PotentialsEvent Related Potentials
Event Related PotentialsRahul Jain
 
NEUROIMAGING IN PSYCHIATRY
NEUROIMAGING IN PSYCHIATRYNEUROIMAGING IN PSYCHIATRY
NEUROIMAGING IN PSYCHIATRYSubrata Naskar
 
Brain Stimulation & Neuromodulation September 2016 - BH Summit
Brain Stimulation & Neuromodulation September 2016 - BH SummitBrain Stimulation & Neuromodulation September 2016 - BH Summit
Brain Stimulation & Neuromodulation September 2016 - BH SummitJay Yeomans
 
The Human Connectome Project multimodal cortical parcellation: new avenues fo...
The Human Connectome Project multimodal cortical parcellation: new avenues fo...The Human Connectome Project multimodal cortical parcellation: new avenues fo...
The Human Connectome Project multimodal cortical parcellation: new avenues fo...Emma Robinson
 
Diffusion MRI, Tractography,and Connectivity: what machine learning can do?
Diffusion MRI, Tractography,and Connectivity: what machine learning can do?Diffusion MRI, Tractography,and Connectivity: what machine learning can do?
Diffusion MRI, Tractography,and Connectivity: what machine learning can do?Ting-Shuo Yo
 
Introduction to resting state fMRI preprocessing and analysis
Introduction to resting state fMRI preprocessing and analysisIntroduction to resting state fMRI preprocessing and analysis
Introduction to resting state fMRI preprocessing and analysisCameron Craddock
 
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...BharathSrinivasG
 
Brain Research Methods Copy
Brain Research Methods CopyBrain Research Methods Copy
Brain Research Methods Copycoburgpsych
 
Magnetoencephalography
MagnetoencephalographyMagnetoencephalography
MagnetoencephalographyNeurologyKota
 
EEG signal background and real-time processing
EEG signal background and real-time processingEEG signal background and real-time processing
EEG signal background and real-time processingRadboud University
 
Magnetoencephalogram-MEG
Magnetoencephalogram-MEGMagnetoencephalogram-MEG
Magnetoencephalogram-MEGSimmiRockzz
 
Normal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate diseaseNormal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate diseaseRahul Kumar
 

What's hot (20)

EEG Artifact and How to Resolve
EEG Artifact and How to ResolveEEG Artifact and How to Resolve
EEG Artifact and How to Resolve
 
Event Related Potentials
Event Related PotentialsEvent Related Potentials
Event Related Potentials
 
NEUROIMAGING IN PSYCHIATRY
NEUROIMAGING IN PSYCHIATRYNEUROIMAGING IN PSYCHIATRY
NEUROIMAGING IN PSYCHIATRY
 
Brain Stimulation & Neuromodulation September 2016 - BH Summit
Brain Stimulation & Neuromodulation September 2016 - BH SummitBrain Stimulation & Neuromodulation September 2016 - BH Summit
Brain Stimulation & Neuromodulation September 2016 - BH Summit
 
The Human Connectome Project multimodal cortical parcellation: new avenues fo...
The Human Connectome Project multimodal cortical parcellation: new avenues fo...The Human Connectome Project multimodal cortical parcellation: new avenues fo...
The Human Connectome Project multimodal cortical parcellation: new avenues fo...
 
Diffusion MRI, Tractography,and Connectivity: what machine learning can do?
Diffusion MRI, Tractography,and Connectivity: what machine learning can do?Diffusion MRI, Tractography,and Connectivity: what machine learning can do?
Diffusion MRI, Tractography,and Connectivity: what machine learning can do?
 
Neruoimaging final
Neruoimaging finalNeruoimaging final
Neruoimaging final
 
Introduction to resting state fMRI preprocessing and analysis
Introduction to resting state fMRI preprocessing and analysisIntroduction to resting state fMRI preprocessing and analysis
Introduction to resting state fMRI preprocessing and analysis
 
Neurophysiological investigations
Neurophysiological investigationsNeurophysiological investigations
Neurophysiological investigations
 
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
 
Brain Research Methods Copy
Brain Research Methods CopyBrain Research Methods Copy
Brain Research Methods Copy
 
Recognition of abnormal EEG.
Recognition of abnormal EEG.Recognition of abnormal EEG.
Recognition of abnormal EEG.
 
qeeg Neuroshow
qeeg Neuroshowqeeg Neuroshow
qeeg Neuroshow
 
Magnetoencephalography
MagnetoencephalographyMagnetoencephalography
Magnetoencephalography
 
EEG signal background and real-time processing
EEG signal background and real-time processingEEG signal background and real-time processing
EEG signal background and real-time processing
 
Sleep EEG
Sleep EEGSleep EEG
Sleep EEG
 
EEG Generators
EEG GeneratorsEEG Generators
EEG Generators
 
Magnetoencephalogram-MEG
Magnetoencephalogram-MEGMagnetoencephalogram-MEG
Magnetoencephalogram-MEG
 
Normal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate diseaseNormal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate disease
 
Magnetoencephalography
MagnetoencephalographyMagnetoencephalography
Magnetoencephalography
 

More from Russell James

Charitable bequest fundraising: New results from 100 years of national data
Charitable bequest fundraising: New results from 100 years of national dataCharitable bequest fundraising: New results from 100 years of national data
Charitable bequest fundraising: New results from 100 years of national dataRussell James
 
Major gifts of assets in the aftermath of Covid-19
Major gifts of assets in the aftermath of Covid-19Major gifts of assets in the aftermath of Covid-19
Major gifts of assets in the aftermath of Covid-19Russell James
 
10 Strategies for Post COVID-19 fundraising in complex and major gifts
10 Strategies for Post COVID-19 fundraising in complex and major gifts10 Strategies for Post COVID-19 fundraising in complex and major gifts
10 Strategies for Post COVID-19 fundraising in complex and major giftsRussell James
 
Top 10 charitable planning strategies for financial advisors 2020
Top 10 charitable planning strategies for financial advisors 2020Top 10 charitable planning strategies for financial advisors 2020
Top 10 charitable planning strategies for financial advisors 2020Russell James
 
The Statistics & Psychology of Baby Boomer Lifetime & Legacy Giving
The Statistics & Psychology of Baby Boomer Lifetime & Legacy GivingThe Statistics & Psychology of Baby Boomer Lifetime & Legacy Giving
The Statistics & Psychology of Baby Boomer Lifetime & Legacy GivingRussell James
 
Using "natural philanthropy" in fundraising
Using "natural philanthropy" in fundraisingUsing "natural philanthropy" in fundraising
Using "natural philanthropy" in fundraisingRussell James
 
Top 10 legacy fundraising strategies from scientific research: National data ...
Top 10 legacy fundraising strategies from scientific research: National data ...Top 10 legacy fundraising strategies from scientific research: National data ...
Top 10 legacy fundraising strategies from scientific research: National data ...Russell James
 
Natural philanthropy: How the natural origins of donor motivations drive powe...
Natural philanthropy: How the natural origins of donor motivations drive powe...Natural philanthropy: How the natural origins of donor motivations drive powe...
Natural philanthropy: How the natural origins of donor motivations drive powe...Russell James
 
Top 10 charitable planning strategies for financial advisors under the new ta...
Top 10 charitable planning strategies for financial advisors under the new ta...Top 10 charitable planning strategies for financial advisors under the new ta...
Top 10 charitable planning strategies for financial advisors under the new ta...Russell James
 
Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...
Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...
Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...Russell James
 
Top 10 charitable planning strategies updated for the new tax law
Top 10 charitable planning strategies updated for the new tax lawTop 10 charitable planning strategies updated for the new tax law
Top 10 charitable planning strategies updated for the new tax lawRussell James
 
Using donor surveys in planned giving
Using donor surveys in planned givingUsing donor surveys in planned giving
Using donor surveys in planned givingRussell James
 
The hidden code behind death-related financial decisions
The hidden code behind death-related financial decisions The hidden code behind death-related financial decisions
The hidden code behind death-related financial decisions Russell James
 
Counting Revocable Planned Gifts in Fundraising - Return from Fantasy Island
Counting Revocable Planned Gifts in Fundraising - Return from Fantasy IslandCounting Revocable Planned Gifts in Fundraising - Return from Fantasy Island
Counting Revocable Planned Gifts in Fundraising - Return from Fantasy IslandRussell James
 
Planned Giving Words that Work Part II
Planned Giving Words that Work Part IIPlanned Giving Words that Work Part II
Planned Giving Words that Work Part IIRussell James
 
Church seminar in charitable estate planning
Church seminar in charitable estate planningChurch seminar in charitable estate planning
Church seminar in charitable estate planningRussell James
 
Ponzis, Pyramids, and Bubbles: An introduction to financial fraud
Ponzis, Pyramids, and Bubbles: An introduction to financial fraudPonzis, Pyramids, and Bubbles: An introduction to financial fraud
Ponzis, Pyramids, and Bubbles: An introduction to financial fraudRussell James
 
Messages that encourage bequest giving to cancer research
Messages that encourage bequest giving to cancer researchMessages that encourage bequest giving to cancer research
Messages that encourage bequest giving to cancer researchRussell James
 
Private foundations and donor advised funds
Private foundations and donor advised fundsPrivate foundations and donor advised funds
Private foundations and donor advised fundsRussell James
 
The secret to understanding planned giving
The secret to understanding planned givingThe secret to understanding planned giving
The secret to understanding planned givingRussell James
 

More from Russell James (20)

Charitable bequest fundraising: New results from 100 years of national data
Charitable bequest fundraising: New results from 100 years of national dataCharitable bequest fundraising: New results from 100 years of national data
Charitable bequest fundraising: New results from 100 years of national data
 
Major gifts of assets in the aftermath of Covid-19
Major gifts of assets in the aftermath of Covid-19Major gifts of assets in the aftermath of Covid-19
Major gifts of assets in the aftermath of Covid-19
 
10 Strategies for Post COVID-19 fundraising in complex and major gifts
10 Strategies for Post COVID-19 fundraising in complex and major gifts10 Strategies for Post COVID-19 fundraising in complex and major gifts
10 Strategies for Post COVID-19 fundraising in complex and major gifts
 
Top 10 charitable planning strategies for financial advisors 2020
Top 10 charitable planning strategies for financial advisors 2020Top 10 charitable planning strategies for financial advisors 2020
Top 10 charitable planning strategies for financial advisors 2020
 
The Statistics & Psychology of Baby Boomer Lifetime & Legacy Giving
The Statistics & Psychology of Baby Boomer Lifetime & Legacy GivingThe Statistics & Psychology of Baby Boomer Lifetime & Legacy Giving
The Statistics & Psychology of Baby Boomer Lifetime & Legacy Giving
 
Using "natural philanthropy" in fundraising
Using "natural philanthropy" in fundraisingUsing "natural philanthropy" in fundraising
Using "natural philanthropy" in fundraising
 
Top 10 legacy fundraising strategies from scientific research: National data ...
Top 10 legacy fundraising strategies from scientific research: National data ...Top 10 legacy fundraising strategies from scientific research: National data ...
Top 10 legacy fundraising strategies from scientific research: National data ...
 
Natural philanthropy: How the natural origins of donor motivations drive powe...
Natural philanthropy: How the natural origins of donor motivations drive powe...Natural philanthropy: How the natural origins of donor motivations drive powe...
Natural philanthropy: How the natural origins of donor motivations drive powe...
 
Top 10 charitable planning strategies for financial advisors under the new ta...
Top 10 charitable planning strategies for financial advisors under the new ta...Top 10 charitable planning strategies for financial advisors under the new ta...
Top 10 charitable planning strategies for financial advisors under the new ta...
 
Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...
Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...
Why cash is not king in fundraising: Results from 1 million nonprofit tax ret...
 
Top 10 charitable planning strategies updated for the new tax law
Top 10 charitable planning strategies updated for the new tax lawTop 10 charitable planning strategies updated for the new tax law
Top 10 charitable planning strategies updated for the new tax law
 
Using donor surveys in planned giving
Using donor surveys in planned givingUsing donor surveys in planned giving
Using donor surveys in planned giving
 
The hidden code behind death-related financial decisions
The hidden code behind death-related financial decisions The hidden code behind death-related financial decisions
The hidden code behind death-related financial decisions
 
Counting Revocable Planned Gifts in Fundraising - Return from Fantasy Island
Counting Revocable Planned Gifts in Fundraising - Return from Fantasy IslandCounting Revocable Planned Gifts in Fundraising - Return from Fantasy Island
Counting Revocable Planned Gifts in Fundraising - Return from Fantasy Island
 
Planned Giving Words that Work Part II
Planned Giving Words that Work Part IIPlanned Giving Words that Work Part II
Planned Giving Words that Work Part II
 
Church seminar in charitable estate planning
Church seminar in charitable estate planningChurch seminar in charitable estate planning
Church seminar in charitable estate planning
 
Ponzis, Pyramids, and Bubbles: An introduction to financial fraud
Ponzis, Pyramids, and Bubbles: An introduction to financial fraudPonzis, Pyramids, and Bubbles: An introduction to financial fraud
Ponzis, Pyramids, and Bubbles: An introduction to financial fraud
 
Messages that encourage bequest giving to cancer research
Messages that encourage bequest giving to cancer researchMessages that encourage bequest giving to cancer research
Messages that encourage bequest giving to cancer research
 
Private foundations and donor advised funds
Private foundations and donor advised fundsPrivate foundations and donor advised funds
Private foundations and donor advised funds
 
The secret to understanding planned giving
The secret to understanding planned givingThe secret to understanding planned giving
The secret to understanding planned giving
 

Recently uploaded

How to Add a New Field in Existing Kanban View in Odoo 17
How to Add a New Field in Existing Kanban View in Odoo 17How to Add a New Field in Existing Kanban View in Odoo 17
How to Add a New Field in Existing Kanban View in Odoo 17Celine George
 
Patterns of Written Texts Across Disciplines.pptx
Patterns of Written Texts Across Disciplines.pptxPatterns of Written Texts Across Disciplines.pptx
Patterns of Written Texts Across Disciplines.pptxMYDA ANGELICA SUAN
 
Clinical Pharmacy Introduction to Clinical Pharmacy, Concept of clinical pptx
Clinical Pharmacy  Introduction to Clinical Pharmacy, Concept of clinical pptxClinical Pharmacy  Introduction to Clinical Pharmacy, Concept of clinical pptx
Clinical Pharmacy Introduction to Clinical Pharmacy, Concept of clinical pptxraviapr7
 
CAULIFLOWER BREEDING 1 Parmar pptx
CAULIFLOWER BREEDING 1 Parmar pptxCAULIFLOWER BREEDING 1 Parmar pptx
CAULIFLOWER BREEDING 1 Parmar pptxSaurabhParmar42
 
How to Add a many2many Relational Field in Odoo 17
How to Add a many2many Relational Field in Odoo 17How to Add a many2many Relational Field in Odoo 17
How to Add a many2many Relational Field in Odoo 17Celine George
 
AUDIENCE THEORY -- FANDOM -- JENKINS.pptx
AUDIENCE THEORY -- FANDOM -- JENKINS.pptxAUDIENCE THEORY -- FANDOM -- JENKINS.pptx
AUDIENCE THEORY -- FANDOM -- JENKINS.pptxiammrhaywood
 
Drug Information Services- DIC and Sources.
Drug Information Services- DIC and Sources.Drug Information Services- DIC and Sources.
Drug Information Services- DIC and Sources.raviapr7
 
Practical Research 1 Lesson 9 Scope and delimitation.pptx
Practical Research 1 Lesson 9 Scope and delimitation.pptxPractical Research 1 Lesson 9 Scope and delimitation.pptx
Practical Research 1 Lesson 9 Scope and delimitation.pptxKatherine Villaluna
 
Maximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdf
Maximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdfMaximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdf
Maximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdfTechSoup
 
How to Use api.constrains ( ) in Odoo 17
How to Use api.constrains ( ) in Odoo 17How to Use api.constrains ( ) in Odoo 17
How to Use api.constrains ( ) in Odoo 17Celine George
 
DUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRA
DUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRADUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRA
DUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRATanmoy Mishra
 
How to Solve Singleton Error in the Odoo 17
How to Solve Singleton Error in the  Odoo 17How to Solve Singleton Error in the  Odoo 17
How to Solve Singleton Error in the Odoo 17Celine George
 
How to Make a Field read-only in Odoo 17
How to Make a Field read-only in Odoo 17How to Make a Field read-only in Odoo 17
How to Make a Field read-only in Odoo 17Celine George
 
CapTechU Doctoral Presentation -March 2024 slides.pptx
CapTechU Doctoral Presentation -March 2024 slides.pptxCapTechU Doctoral Presentation -March 2024 slides.pptx
CapTechU Doctoral Presentation -March 2024 slides.pptxCapitolTechU
 
In - Vivo and In - Vitro Correlation.pptx
In - Vivo and In - Vitro Correlation.pptxIn - Vivo and In - Vitro Correlation.pptx
In - Vivo and In - Vitro Correlation.pptxAditiChauhan701637
 
Philosophy of Education and Educational Philosophy
Philosophy of Education  and Educational PhilosophyPhilosophy of Education  and Educational Philosophy
Philosophy of Education and Educational PhilosophyShuvankar Madhu
 
Education and training program in the hospital APR.pptx
Education and training program in the hospital APR.pptxEducation and training program in the hospital APR.pptx
Education and training program in the hospital APR.pptxraviapr7
 
How to Filter Blank Lines in Odoo 17 Accounting
How to Filter Blank Lines in Odoo 17 AccountingHow to Filter Blank Lines in Odoo 17 Accounting
How to Filter Blank Lines in Odoo 17 AccountingCeline George
 
How to Print Employee Resume in the Odoo 17
How to Print Employee Resume in the Odoo 17How to Print Employee Resume in the Odoo 17
How to Print Employee Resume in the Odoo 17Celine George
 

Recently uploaded (20)

How to Add a New Field in Existing Kanban View in Odoo 17
How to Add a New Field in Existing Kanban View in Odoo 17How to Add a New Field in Existing Kanban View in Odoo 17
How to Add a New Field in Existing Kanban View in Odoo 17
 
Patterns of Written Texts Across Disciplines.pptx
Patterns of Written Texts Across Disciplines.pptxPatterns of Written Texts Across Disciplines.pptx
Patterns of Written Texts Across Disciplines.pptx
 
Clinical Pharmacy Introduction to Clinical Pharmacy, Concept of clinical pptx
Clinical Pharmacy  Introduction to Clinical Pharmacy, Concept of clinical pptxClinical Pharmacy  Introduction to Clinical Pharmacy, Concept of clinical pptx
Clinical Pharmacy Introduction to Clinical Pharmacy, Concept of clinical pptx
 
CAULIFLOWER BREEDING 1 Parmar pptx
CAULIFLOWER BREEDING 1 Parmar pptxCAULIFLOWER BREEDING 1 Parmar pptx
CAULIFLOWER BREEDING 1 Parmar pptx
 
How to Add a many2many Relational Field in Odoo 17
How to Add a many2many Relational Field in Odoo 17How to Add a many2many Relational Field in Odoo 17
How to Add a many2many Relational Field in Odoo 17
 
AUDIENCE THEORY -- FANDOM -- JENKINS.pptx
AUDIENCE THEORY -- FANDOM -- JENKINS.pptxAUDIENCE THEORY -- FANDOM -- JENKINS.pptx
AUDIENCE THEORY -- FANDOM -- JENKINS.pptx
 
Drug Information Services- DIC and Sources.
Drug Information Services- DIC and Sources.Drug Information Services- DIC and Sources.
Drug Information Services- DIC and Sources.
 
Practical Research 1 Lesson 9 Scope and delimitation.pptx
Practical Research 1 Lesson 9 Scope and delimitation.pptxPractical Research 1 Lesson 9 Scope and delimitation.pptx
Practical Research 1 Lesson 9 Scope and delimitation.pptx
 
Maximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdf
Maximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdfMaximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdf
Maximizing Impact_ Nonprofit Website Planning, Budgeting, and Design.pdf
 
How to Use api.constrains ( ) in Odoo 17
How to Use api.constrains ( ) in Odoo 17How to Use api.constrains ( ) in Odoo 17
How to Use api.constrains ( ) in Odoo 17
 
DUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRA
DUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRADUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRA
DUST OF SNOW_BY ROBERT FROST_EDITED BY_ TANMOY MISHRA
 
How to Solve Singleton Error in the Odoo 17
How to Solve Singleton Error in the  Odoo 17How to Solve Singleton Error in the  Odoo 17
How to Solve Singleton Error in the Odoo 17
 
How to Make a Field read-only in Odoo 17
How to Make a Field read-only in Odoo 17How to Make a Field read-only in Odoo 17
How to Make a Field read-only in Odoo 17
 
Personal Resilience in Project Management 2 - TV Edit 1a.pdf
Personal Resilience in Project Management 2 - TV Edit 1a.pdfPersonal Resilience in Project Management 2 - TV Edit 1a.pdf
Personal Resilience in Project Management 2 - TV Edit 1a.pdf
 
CapTechU Doctoral Presentation -March 2024 slides.pptx
CapTechU Doctoral Presentation -March 2024 slides.pptxCapTechU Doctoral Presentation -March 2024 slides.pptx
CapTechU Doctoral Presentation -March 2024 slides.pptx
 
In - Vivo and In - Vitro Correlation.pptx
In - Vivo and In - Vitro Correlation.pptxIn - Vivo and In - Vitro Correlation.pptx
In - Vivo and In - Vitro Correlation.pptx
 
Philosophy of Education and Educational Philosophy
Philosophy of Education  and Educational PhilosophyPhilosophy of Education  and Educational Philosophy
Philosophy of Education and Educational Philosophy
 
Education and training program in the hospital APR.pptx
Education and training program in the hospital APR.pptxEducation and training program in the hospital APR.pptx
Education and training program in the hospital APR.pptx
 
How to Filter Blank Lines in Odoo 17 Accounting
How to Filter Blank Lines in Odoo 17 AccountingHow to Filter Blank Lines in Odoo 17 Accounting
How to Filter Blank Lines in Odoo 17 Accounting
 
How to Print Employee Resume in the Odoo 17
How to Print Employee Resume in the Odoo 17How to Print Employee Resume in the Odoo 17
How to Print Employee Resume in the Odoo 17
 

fMRI terms: HRF and BOLD

  • 1. Hi, kids! My name is Vickie Voxel. I’m going to tell you ● ● about fMRI, HRF & BOLD. Intro to fMRI Part I: HRF & BOLD Dr. Russell James, Texas Tech University
  • 2. An fMRI picture of the brain is made up of thousands of boxes, called voxels, just like me! ● ●
  • 3. We voxels are small – usually about the size of one ● ● peppercorn
  • 4. Inside each of us voxels are thousands of neurons ● ●
  • 5. When a lot of these neurons start to fire, the body rushes in ● ● oxygen to help
  • 6. This rush of oxygen comes through the blood and makes me ● ● start to change color
  • 7. As my blood oxygen increases, I get redder ● ●
  • 9. If this keeps going, I will be totally red from all of the oxygen in my ● ● blood
  • 10. But then, if the neurons don’t keep firing, the body will stop ● ● rushing oxygen to me
  • 11. And my color will start to return to normal ● ●
  • 12. I can get a bit blue at the end if my oxygen drops too low, right before it ● ● returns to normal
  • 13. In 20 seconds after the neurons fired, I will be back to my normal ● ● color again
  • 14. This whole color change process is called my hemodynamic ● ● response
  • 15. “Hemo” means blood. “Dynamic” means change. ● ● So, hemodynamic response is my “blood-change” Blood Oxygen Level ● ● ● ● response. ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS after neurons fire  
  • 16. When we model this change with math, we call it a ● ● hemodynamic response function Blood Oxygen Level ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS after neurons fire  
  • 17. But, saying “hemodynamic response ● ● function” takes too long, so we will just call it Blood Oxygen Level ● ● ● ● the HRF ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS after neurons fire  
  • 18. ● The HRF Blood Oxygen Level ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS after neurons fire  
  • 19. The fMRI machine can see my color change because blood with a lot of oxygen (red) is less attracted to magnets than blood without much oxygen (pink or blue). ● ● ● ●
  • 20. But, instead of showing pictures in red, pinks, and blues, the fMRI creates black and white pictures. Differences in magnetism are shown as shades of light and dark. ● ● ● ● ● ● ● ●
  • 21. The fMRI machine is measuring a BOLD signal because the color is Blood Oxygen Level Dependent ● ● ● ● High blood oxygen Low blood oxygen ● ● ● ●
  • 22. So, instead of an HRF looking like this… ● ● Blood Oxygen Level ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS after neurons fire  
  • 23. The fMRI shows an HRF that looks like this… ● ● Blood Oxygen Level ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS after neurons fire  
  • 24. Because the color tells us the blood oxygen level, we ● ● really don’t need a vertical axis… Blood Oxygen Level ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS after neurons fire  
  • 25. We can just use one line ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 SECONDS after neurons fire  
  • 26. And, if we always take a picture every 2 seconds, then we don’t even need the seconds on the bottom ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 SECONDS after neurons fire  
  • 27. So, all of our HRF information is shown on the Neuron timeline below firing starts ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
  • 28. But, instead of a Neuron firing series of colors, starts the fMRI machine gives us numbers 180 200         250       305        249         201       182       172         180 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
  • 29. The fMRI records a Neuron number for the firing magnetism of each voxel starts at each time 180 200         250       305        249         201       182       172         180 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
  • 30. If we take a picture every 3 seconds for 7 minutes, we get 140 numbers for each voxel
  • 31. And we might have 100,000 or so voxels in the whole brain
  • 32. 20 images per minute X 7 minutes X 100,000 voxels X 20 people = 280 million data points We can’t track it by hand!
  • 33. So we have to ask the computer to analyze the data
  • 34. But the computer needs to know WHAT to look for and WHEN to look for it
  • 35. So WHAT are we looking for?
  • 36. We are looking for changes in the signal that look like this ● ● Blood Oxygen Level ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS
  • 37. We are looking for changes in the signal that look like this ● ● Blood Oxygen Level ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0  1  2  3  4  5  6  7  8  9  10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 SECONDS
  • 38. We are looking for changes in the signal that look like this… because this looks like an HRF, meaning it was caused by a large group of neurons firing 180 200         250       305        249         201       182       172         180 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
  • 39. We are looking for changes in the signal that look like this… because this looks like an HRF, meaning it was caused by a large group of neurons firing 180 200         250       305        249         201       182       172         180 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●
  • 40. WHEN are we looking for this HRF-like signal?
  • 41. We are interested in the HRF-like signals that happen right after the subject experiences something + + + + +
  • 42. Then we can estimate the likelihood that a voxel, or group of voxels, is responding to the stimulus
  • 43. This simple concept can be difficult in practice because: 1. The signal change is small 2. The brain is noisy
  • 44. This simple concept can be difficult in practice because: 1. The signal change is small 2. The brain is noisy Overcoming these barriers requires: Good study design + Good data analysis
  • 45. Bye for now! Next time we will look at how to create a good study ● ● design. Intro to fMRI Part I: HRF & BOLD Dr. Russell James, Texas Tech University