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Reliable individual
functional networks
and their relationship
to behavior 

Emily S. Finn, PhD

Section on Functional Ima...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral data
3
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
H...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
Why study individual differences?
Controls
Patients
Why study individual differences?
Controls
Patients
• Basic neuroscience: mapping from individual brains to individual beha...
Why study individual differences?
Controls
Patients
• Basic neuroscience: mapping from individual brains to individual beha...
Why study individual differences?
Categorical approach
Controls
Patients
• Basic neuroscience: mapping from individual brai...
Why study individual differences?
Categorical approach
Controls
Patients
• Basic neuroscience: mapping from individual brai...
Why study individual differences?
Categorical approach
Controls
Patients
• Basic neuroscience: mapping from individual brai...
Why study individual differences?
Categorical approach
Controls
Patients
• Basic neuroscience: mapping from individual brai...
Why study individual differences?
Categorical approach Dimensional approach
Controls
Patients
• Basic neuroscience: mapping...
Why study individual differences?
Categorical approach Dimensional approach
Controls
Patients
• Basic neuroscience: mapping...
Why study individual differences?
Motor
Mt
Emotion
Em
Language
Lg
Working memory
WM
Resting
R1
+
Resting
R2
+
Why study individual differences?
Motor
Mt
Emotion
Em
Language
Lg
Working memory
WM
Resting
R1
Resting
R2
Why study individual differences?
Motor
Mt
Emotion
Em
Language
Lg
Working memory
WM
Resting
R1
Resting
R2
Why study individual differences?
Finn et al., Nat Neurosci (2015)
Why study individual differences?
0.93 0.84 0.63
0.72 0.79 0.67
0.64 0.60 0.54
R1
WM
Mt
R2 Lg Em
Database
Target
ID rate
0....
Why study individual differences?
You always look most like yourself,
regardless of what you’re doing
0.93 0.84 0.63
0.72 0...
Why study individual differences?
You always look most like yourself,
regardless of what you’re doing
0.93 0.84 0.63
0.72 0...
Why study individual differences?
You always look most like yourself,
regardless of what you’re doing
0.93 0.84 0.63
0.72 0...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
Q. Do you need HCP-quality data?
Q. Do you need HCP-quality data?
A. Not really
Q. Do you need HCP-quality data?
A. Not really
ID is fairly robust even at more standard spatial & temporal resolutions:
Q. Do you need HCP-quality data?
A. Not really
Airan et al., Hum Brain Mapp (2016)
ID is fairly robust even at more standa...
Q. Do you need HCP-quality data?
A. Not really
Airan et al., Hum Brain Mapp (2016)
ID is fairly robust even at more standa...
Q. Do you need HCP-quality data?
A. Not really
• More nodes —> higher identification rate
Airan et al., Hum Brain Mapp (201...
Q. Do you need HCP-quality data?
A. Not really
• More nodes —> higher identification rate
‣ Parcellation method (random vs....
Q. Do you need HCP-quality data?
A. Not really
• More nodes —> higher identification rate
‣ Parcellation method (random vs....
Q. Do you need HCP-quality data?
A. Not really
• More nodes —> higher identification rate
‣ Parcellation method (random vs....
Q. What about amount of data?
Q. What about amount of data?
A. Scan duration matters!
Q. What about amount of data?
A. Scan duration matters!
Longer acquisitions are better:
Q. What about amount of data?
A. Scan duration matters!
Longer acquisitions are better:
• higher reliability within subjec...
Q. What about amount of data?
A. Scan duration matters!
Finn et al., Nat Neurosci (2015)
• higher identifiability across su...
Q. What about amount of data?
A. Scan duration matters!
Finn et al., Nat Neurosci (2015)
• higher identifiability across su...
Q. What about amount of data?
A. Scan duration matters!
Finn et al., Nat Neurosci (2015)
• higher identifiability across su...
Q. What about amount of data?
A. Scan duration matters!
Finn et al., Nat Neurosci (2015)
• higher identifiability across su...
Q. Does scan condition matter?
Q. Does scan condition matter?
A. Yes!
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Does scan condition matter?
A. Yes!
Rest has become the default condition for FC & individual differences,
but tasks ma...
Q. Is rest best?
Q. Is rest best?
A. Probably not
Q. Is rest best?
A. Probably not
Tasks may stabilize individuals’ functional architecture, increase SNR:
Q. Is rest best?
A. Probably not
‣ some task pairs give better ID than the two rest sessions
Tasks may stabilize individua...
Q. Is rest best?
A. Probably not
‣ some task pairs give better ID than the two rest sessions
Target
Database
Day 1 Day 2
I...
Q. Is rest best?
A. Probably not
‣ some task pairs give better ID than the two rest sessions
Target
Database
Day 1 Day 2
I...
Q. Is rest best?
A. Probably not
‣ some task pairs give better ID than the two rest sessions
Target
Database
Day 1 Day 2
I...
Q. Is rest best?
A. Probably not
Q. Is rest best?
A. Probably not
Consider naturalistic tasks:
Q. Is rest best?
A. Probably not
Consider naturalistic tasks:
Inscapes: Vanderwal et al., NeuroImage 2015

headspacestudio...
Q. Is rest best?
A. Probably not
Consider naturalistic tasks:
Q. Is rest best?
A. Probably not
Consider naturalistic tasks:
‣ ID rate is just as good as (if not better than) rest
Q. Is rest best?
A. Probably not
Consider naturalistic tasks:
Session 1
Rest Inscapes Ocean’s 11
Session 2
‣ ID rate is ju...
Q. Is rest best?
A. Probably not
Consider naturalistic tasks:
Session 1
Rest Inscapes Ocean’s 11
Session 2
‣ ID rate is ju...
Q. Is rest best?
A. Probably not
Consider naturalistic tasks:
Session 1
Rest Inscapes Ocean’s 11
Session 2
‣ ID rate is ju...
Q. Is rest best?
A. Probably not
Q. Is rest best?
A. Probably not
Tasks also have purely practical advantages:
‣ increase subject compliance (i.e., decrease head motion), especially in certain populations
Q. Is rest best?
A. Probably...
‣ increase subject compliance (i.e., decrease head motion), especially in certain populations
Huijbers et al., NeuroImage ...
‣ increase subject compliance (i.e., decrease head motion), especially in certain populations
ChildrenAdults
Vanderwal et ...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
How to choose behavior
How to choose behavior
Is it stable?
How to choose behavior
Is it stable?
• Trait vs. state
• State variables may be better
suited to within-subject analysis
How to choose behavior
Is it stable?
• Trait vs. state
• State variables may be better
suited to within-subject analysis
B...
How to choose behavior
Is it stable?
• Trait vs. state
• State variables may be better
suited to within-subject analysis
B...
How to choose behavior
Is it stable?
• Trait vs. state
• State variables may be better
suited to within-subject analysis
B...
How to choose behavior
Is it stable?
Does it show a good distribution
in your population?
• Trait vs. state
• State variab...
How to choose behavior
Is it stable?
Does it show a good distribution
in your population?
• Trait vs. state
• State variab...
How to choose behavior
Is it stable?
Does it show a good distribution
in your population?
• Trait vs. state
• State variab...
How to choose behavior
Is it stable?
Does it show a good distribution
in your population?
• Trait vs. state
• State variab...
How to choose behavior
Is it stable?
Does it show a good distribution
in your population?
• Trait vs. state
• State variab...
How to choose behavior
Is it stable?
Does it show a good distribution
in your population?
Is it something you expect to be...
Behavior: Mitigating confounds
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
Siegel et al., Cerebral Cortex (...
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
Siegel et al., Cerebral Cortex (...
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
‣ Check for correlation in your ...
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
‣ Check for correlation in your ...
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
‣ Check for correlation in your ...
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
‣ Check for correlation in your ...
Behavior: Mitigating confounds
Many behaviors/phenotypes are correlated with head motion!
‣ Check for correlation in your ...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
Outline
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2
How to relate
brain to behavior
4
L...
Brain behavior: Cross-validate!
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Brain behavior: Cross-validate!
Find a brain-behavior relationship in one sample, see if it holds in another sample
‣ leav...
Q. What is the best brain state?
Q. What is the best brain state?
A. Maybe it depends on your behavior
Q. What is the best brain state?
A. Maybe it depends on your behavior
Certain task conditions generate better predictions ...
Q. What is the best brain state?
A. Maybe it depends on your behavior
n = 716, 10-fold cross-validation
Connectome-based P...
Q. What is the best brain state?
A. Maybe it depends on your behavior
n = 716, 10-fold cross-validation
Connectome-based P...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Take-home points
Introduction:
Why study
individual
differences?
1 How to get good
brain data
2 How to get good
behavioral...
Open data sets with brain & behavior
➡ Use these on their own or in combination with your own data
to generate or test hyp...
Further reading
Building a science of individual differences from fMRI
Dubois & Adolphs, Trends in Cognitive Sciences (201...
Learn more at OHBM 2017
Symposium:
Collect your thoughts: Individual differences in the networks underlying intelligence
T...
Finn ohbm2017 ed_workshop
Finn ohbm2017 ed_workshop
Finn ohbm2017 ed_workshop
Finn ohbm2017 ed_workshop
Finn ohbm2017 ed_workshop
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Reliable individual functional networks and their relationship to behavior

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Finn ohbm2017 ed_workshop

  1. 1. Reliable individual functional networks and their relationship to behavior Emily S. Finn, PhD Section on Functional Imaging Methods Laboratory of Brain & Cognition, NIMH emily.finn@nih.gov Taking Connectivity to a Skeptical Future Educational Workshop | OHBM Annual Meeting June 25, 2017 @esfinn
  2. 2. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3
  3. 3. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 How to get good behavioral data 3
  4. 4. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  5. 5. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  6. 6. Why study individual differences? Controls Patients
  7. 7. Why study individual differences? Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors
  8. 8. Why study individual differences? Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors • Eventual clinical applications:
  9. 9. Why study individual differences? Categorical approach Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors • Eventual clinical applications:
  10. 10. Why study individual differences? Categorical approach Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors • Eventual clinical applications:
  11. 11. Why study individual differences? Categorical approach Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors • Eventual clinical applications:
  12. 12. Why study individual differences? Categorical approach Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors • Eventual clinical applications: p < 0.05*
  13. 13. Why study individual differences? Categorical approach Dimensional approach Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors • Eventual clinical applications: p < 0.05*
  14. 14. Why study individual differences? Categorical approach Dimensional approach Controls Patients • Basic neuroscience: mapping from individual brains to individual behaviors • Eventual clinical applications: p < 0.05*
  15. 15. Why study individual differences? Motor Mt Emotion Em Language Lg Working memory WM Resting R1 + Resting R2 +
  16. 16. Why study individual differences? Motor Mt Emotion Em Language Lg Working memory WM Resting R1 Resting R2
  17. 17. Why study individual differences? Motor Mt Emotion Em Language Lg Working memory WM Resting R1 Resting R2
  18. 18. Why study individual differences? Finn et al., Nat Neurosci (2015)
  19. 19. Why study individual differences? 0.93 0.84 0.63 0.72 0.79 0.67 0.64 0.60 0.54 R1 WM Mt R2 Lg Em Database Target ID rate 0.5 1.0 Finn et al., Nat Neurosci (2015)
  20. 20. Why study individual differences? You always look most like yourself, regardless of what you’re doing 0.93 0.84 0.63 0.72 0.79 0.67 0.64 0.60 0.54 R1 WM Mt R2 Lg Em Database Target ID rate 0.5 1.0 Finn et al., Nat Neurosci (2015)
  21. 21. Why study individual differences? You always look most like yourself, regardless of what you’re doing 0.93 0.84 0.63 0.72 0.79 0.67 0.64 0.60 0.54 R1 WM Mt R2 Lg Em Database Target ID rate 0.5 1.0 Finn et al., Nat Neurosci (2015)
  22. 22. Why study individual differences? You always look most like yourself, regardless of what you’re doing 0.93 0.84 0.63 0.72 0.79 0.67 0.64 0.60 0.54 R1 WM Mt R2 Lg Em Database Target ID rate 0.5 1.0 Individual differences in FC predict individual differences in behavior Finn et al., Nat Neurosci (2015)
  23. 23. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  24. 24. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  25. 25. Q. Do you need HCP-quality data?
  26. 26. Q. Do you need HCP-quality data? A. Not really
  27. 27. Q. Do you need HCP-quality data? A. Not really ID is fairly robust even at more standard spatial & temporal resolutions:
  28. 28. Q. Do you need HCP-quality data? A. Not really Airan et al., Hum Brain Mapp (2016) ID is fairly robust even at more standard spatial & temporal resolutions:
  29. 29. Q. Do you need HCP-quality data? A. Not really Airan et al., Hum Brain Mapp (2016) ID is fairly robust even at more standard spatial & temporal resolutions: Courtesy of Jason Druzgal
  30. 30. Q. Do you need HCP-quality data? A. Not really • More nodes —> higher identification rate Airan et al., Hum Brain Mapp (2016) ID is fairly robust even at more standard spatial & temporal resolutions: Courtesy of Jason Druzgal
  31. 31. Q. Do you need HCP-quality data? A. Not really • More nodes —> higher identification rate ‣ Parcellation method (random vs. functional) did not matter Airan et al., Hum Brain Mapp (2016) ID is fairly robust even at more standard spatial & temporal resolutions: Courtesy of Jason Druzgal
  32. 32. Q. Do you need HCP-quality data? A. Not really • More nodes —> higher identification rate ‣ Parcellation method (random vs. functional) did not matter ‣ Caution: Higher resolution may amplify effects of anatomical diffs/registration error Airan et al., Hum Brain Mapp (2016) ID is fairly robust even at more standard spatial & temporal resolutions: Courtesy of Jason Druzgal
  33. 33. Q. Do you need HCP-quality data? A. Not really • More nodes —> higher identification rate ‣ Parcellation method (random vs. functional) did not matter ‣ Caution: Higher resolution may amplify effects of anatomical diffs/registration error ‣ Parcellations in the 200-300 node range seem like a good compromise Airan et al., Hum Brain Mapp (2016) ID is fairly robust even at more standard spatial & temporal resolutions: Courtesy of Jason Druzgal
  34. 34. Q. What about amount of data?
  35. 35. Q. What about amount of data? A. Scan duration matters!
  36. 36. Q. What about amount of data? A. Scan duration matters! Longer acquisitions are better:
  37. 37. Q. What about amount of data? A. Scan duration matters! Longer acquisitions are better: • higher reliability within subjects Birn et al., NeuroImage (2013)
  38. 38. Q. What about amount of data? A. Scan duration matters! Finn et al., Nat Neurosci (2015) • higher identifiability across subjects Longer acquisitions are better: • higher reliability within subjects Birn et al., NeuroImage (2013)
  39. 39. Q. What about amount of data? A. Scan duration matters! Finn et al., Nat Neurosci (2015) • higher identifiability across subjects ‣ higher sampling rate (shorter TR) cannot make up for shorter scan duration Longer acquisitions are better: • higher reliability within subjects Birn et al., NeuroImage (2013)
  40. 40. Q. What about amount of data? A. Scan duration matters! Finn et al., Nat Neurosci (2015) • higher identifiability across subjects ‣ higher sampling rate (shorter TR) cannot make up for shorter scan duration Airan et al., Hum Brain Mapp (2016) Longer acquisitions are better: • higher reliability within subjects Birn et al., NeuroImage (2013)
  41. 41. Q. What about amount of data? A. Scan duration matters! Finn et al., Nat Neurosci (2015) • higher identifiability across subjects ‣ higher sampling rate (shorter TR) cannot make up for shorter scan duration Airan et al., Hum Brain Mapp (2016) Shah et al., Brain & Behav (2016) Longer acquisitions are better: • higher reliability within subjects Birn et al., NeuroImage (2013)
  42. 42. Q. Does scan condition matter?
  43. 43. Q. Does scan condition matter? A. Yes!
  44. 44. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise
  45. 45. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise 0.93 0.84 0.63 0.72 0.79 0.67 0.64 0.60 0.54 R1 WM Mt R2 Lg Em Database Target ID rate 0.5 1.0
  46. 46. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise
  47. 47. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise Finn et al., NeuroImage (2017)
  48. 48. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise Finn et al., NeuroImage (2017)
  49. 49. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise Finn et al., NeuroImage (2017)
  50. 50. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise Finn et al., NeuroImage (2017)
  51. 51. Q. Does scan condition matter? A. Yes! Rest has become the default condition for FC & individual differences, but tasks may increase signal-to-noise ‣ for a set scan duration, tasks may be more reliable than rest ‣ tasks may converge faster on a subject’s “true” profile Finn et al., NeuroImage (2017)
  52. 52. Q. Is rest best?
  53. 53. Q. Is rest best? A. Probably not
  54. 54. Q. Is rest best? A. Probably not Tasks may stabilize individuals’ functional architecture, increase SNR:
  55. 55. Q. Is rest best? A. Probably not ‣ some task pairs give better ID than the two rest sessions Tasks may stabilize individuals’ functional architecture, increase SNR:
  56. 56. Q. Is rest best? A. Probably not ‣ some task pairs give better ID than the two rest sessions Target Database Day 1 Day 2 IDrate Day1Day2 Tasks may stabilize individuals’ functional architecture, increase SNR: Finn et al., NeuroImage (2017)
  57. 57. Q. Is rest best? A. Probably not ‣ some task pairs give better ID than the two rest sessions Target Database Day 1 Day 2 IDrate Day1Day2 ‣ consider a combination of rest and task Tasks may stabilize individuals’ functional architecture, increase SNR: Finn et al., NeuroImage (2017)
  58. 58. Q. Is rest best? A. Probably not ‣ some task pairs give better ID than the two rest sessions Target Database Day 1 Day 2 IDrate Day1Day2 ‣ consider a combination of rest and task Tasks may stabilize individuals’ functional architecture, increase SNR: Finn et al., NeuroImage (2017) Finn et al., Nat Neurosci (2015)
  59. 59. Q. Is rest best? A. Probably not
  60. 60. Q. Is rest best? A. Probably not Consider naturalistic tasks:
  61. 61. Q. Is rest best? A. Probably not Consider naturalistic tasks: Inscapes: Vanderwal et al., NeuroImage 2015 headspacestudios.org
  62. 62. Q. Is rest best? A. Probably not Consider naturalistic tasks:
  63. 63. Q. Is rest best? A. Probably not Consider naturalistic tasks: ‣ ID rate is just as good as (if not better than) rest
  64. 64. Q. Is rest best? A. Probably not Consider naturalistic tasks: Session 1 Rest Inscapes Ocean’s 11 Session 2 ‣ ID rate is just as good as (if not better than) rest
  65. 65. Q. Is rest best? A. Probably not Consider naturalistic tasks: Session 1 Rest Inscapes Ocean’s 11 Session 2 ‣ ID rate is just as good as (if not better than) rest Vanderwal et al., NeuroImage (2017)
  66. 66. Q. Is rest best? A. Probably not Consider naturalistic tasks: Session 1 Rest Inscapes Ocean’s 11 Session 2 ‣ ID rate is just as good as (if not better than) rest Vanderwal et al., NeuroImage (2017)
  67. 67. Q. Is rest best? A. Probably not
  68. 68. Q. Is rest best? A. Probably not Tasks also have purely practical advantages:
  69. 69. ‣ increase subject compliance (i.e., decrease head motion), especially in certain populations Q. Is rest best? A. Probably not Tasks also have purely practical advantages:
  70. 70. ‣ increase subject compliance (i.e., decrease head motion), especially in certain populations Huijbers et al., NeuroImage (2017) Q. Is rest best? A. Probably not Tasks also have purely practical advantages:
  71. 71. ‣ increase subject compliance (i.e., decrease head motion), especially in certain populations ChildrenAdults Vanderwal et al., NeuroImage (2015)Huijbers et al., NeuroImage (2017) Q. Is rest best? A. Probably not Tasks also have purely practical advantages:
  72. 72. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  73. 73. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  74. 74. How to choose behavior
  75. 75. How to choose behavior Is it stable?
  76. 76. How to choose behavior Is it stable? • Trait vs. state • State variables may be better suited to within-subject analysis
  77. 77. How to choose behavior Is it stable? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  78. 78. How to choose behavior Is it stable? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  79. 79. How to choose behavior Is it stable? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  80. 80. How to choose behavior Is it stable? Does it show a good distribution in your population? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  81. 81. How to choose behavior Is it stable? Does it show a good distribution in your population? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  82. 82. How to choose behavior Is it stable? Does it show a good distribution in your population? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  83. 83. How to choose behavior Is it stable? Does it show a good distribution in your population? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  84. 84. How to choose behavior Is it stable? Does it show a good distribution in your population? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  85. 85. How to choose behavior Is it stable? Does it show a good distribution in your population? Is it something you expect to be reflected in brain function? • Trait vs. state • State variables may be better suited to within-subject analysis Betzel et al., Sci Rep (2017)
  86. 86. Behavior: Mitigating confounds
  87. 87. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion!
  88. 88. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion! Siegel et al., Cerebral Cortex (2016) Negatively: Positively:
  89. 89. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion! Siegel et al., Cerebral Cortex (2016) Negatively: Positively: Geerligs et al., Hum Brain Mapp (2017) Age, vascular health:
  90. 90. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion!
  91. 91. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion! ‣ Check for correlation in your sample
  92. 92. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion! ‣ Check for correlation in your sample ‣ Consider excluding particularly high-motion subjects
  93. 93. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion! ‣ Check for correlation in your sample ‣ Consider excluding particularly high-motion subjects ‣ Choose appropriate preprocessing techniques
  94. 94. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion! ‣ Check for correlation in your sample ‣ Consider excluding particularly high-motion subjects ‣ Choose appropriate preprocessing techniques Ciric et al., NeuroImage (2017)
  95. 95. Behavior: Mitigating confounds Many behaviors/phenotypes are correlated with head motion! ‣ Check for correlation in your sample ‣ Consider excluding particularly high-motion subjects ‣ Choose appropriate preprocessing techniques ‣ Use motion as an explicit covariate Ciric et al., NeuroImage (2017)
  96. 96. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  97. 97. Outline Introduction: Why study individual differences? 1 How to get good brain data 2 How to relate brain to behavior 4 Learn more5How to get good behavioral data 3
  98. 98. Brain behavior: Cross-validate!
  99. 99. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample
  100. 100. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017)
  101. 101. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) 2 7.5 4 6.3
  102. 102. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) 2 7.5 4 6.3
  103. 103. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  104. 104. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  105. 105. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  106. 106. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  107. 107. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  108. 108. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  109. 109. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  110. 110. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  111. 111. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3
  112. 112. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) ‣ even better: cross-dataset Sustained attention model Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3 Rosenberg et al., Nature Neuroscience (2016) Rosenberg et al., Trends in Cog Sci (2017)
  113. 113. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) ‣ even better: cross-dataset Sustained attention model Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3 Rosenberg et al., Nature Neuroscience (2016) Rosenberg et al., Trends in Cog Sci (2017) Observed behav Predictedbehav n = 25 adults
  114. 114. Brain behavior: Cross-validate! Find a brain-behavior relationship in one sample, see if it holds in another sample ‣ leave-one-subject-out (within dataset) ‣ even better: cross-dataset Sustained attention model Connectome-based Predictive Modeling Shen et al., Nature Protocols (2017) Predictedbehav Observed behav 2 7.5 4 6.3 Rosenberg et al., Nature Neuroscience (2016) Rosenberg et al., Trends in Cog Sci (2017) Observed behav Predictedbehav n = 25 adults Observed ADHD score n = 113 children PredictedADHDscore
  115. 115. Q. What is the best brain state?
  116. 116. Q. What is the best brain state? A. Maybe it depends on your behavior
  117. 117. Q. What is the best brain state? A. Maybe it depends on your behavior Certain task conditions generate better predictions of behavior:
  118. 118. Q. What is the best brain state? A. Maybe it depends on your behavior n = 716, 10-fold cross-validation Connectome-based Predictive Modeling (CPM; Shen et al., Nat Protocols 2017) Modelinputdata Target behavior Certain task conditions generate better predictions of behavior:
  119. 119. Q. What is the best brain state? A. Maybe it depends on your behavior n = 716, 10-fold cross-validation Connectome-based Predictive Modeling (CPM; Shen et al., Nat Protocols 2017) Modelinputdata Target behavior Certain task conditions generate better predictions of behavior: Consider tailoring scan condition to behavior of interest ➡“Stress test”?
  120. 120. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5
  121. 121. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical
  122. 122. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better!
  123. 123. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks
  124. 124. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks ‣ improve compliance
  125. 125. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks ‣ improve compliance ‣ increase sensitivity
  126. 126. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks ‣ improve compliance ‣ increase sensitivity • Choose an interesting behavior with a good distribution
  127. 127. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks ‣ improve compliance ‣ increase sensitivity • Choose an interesting behavior with a good distribution • Consider potential confounds and take steps to mitigate them
  128. 128. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks ‣ improve compliance ‣ increase sensitivity • Choose an interesting behavior with a good distribution • Consider potential confounds and take steps to mitigate them • Cross-validate whenever possible
  129. 129. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks ‣ improve compliance ‣ increase sensitivity • Choose an interesting behavior with a good distribution • Consider potential confounds and take steps to mitigate them • Cross-validate whenever possible • Consider tailoring your scan condition to behavior of interest
  130. 130. Take-home points Introduction: Why study individual differences? 1 How to get good brain data 2 How to get good behavioral data 3 How to relate brain to behavior 4 Learn more5 • Data quality ≠ critical • Longer scans are better! • Consider using tasks ‣ improve compliance ‣ increase sensitivity • Choose an interesting behavior with a good distribution • Consider potential confounds and take steps to mitigate them • Cross-validate whenever possible • Consider tailoring your scan condition to behavior of interest
  131. 131. Open data sets with brain & behavior ➡ Use these on their own or in combination with your own data to generate or test hypotheses, see if a finding generalizes, etc Philadelphia Neurodevelopmental Cohort
  132. 132. Further reading Building a science of individual differences from fMRI Dubois & Adolphs, Trends in Cognitive Sciences (2016) From regions to connections and networks: new bridges between brain and behavior Misic & Sporns, Current Opinion in Neurobiology (2016) Can brain state be manipulated to emphasize individual differences in functional connectivity? Finn et al., NeuroImage (2017) Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience Gabrieli, Ghosh & Gabrieli, Neuron (2015) Selected reviews:
  133. 133. Learn more at OHBM 2017 Symposium: Collect your thoughts: Individual differences in the networks underlying intelligence Tues 8:00-9:15am Symposium: Relating connectivity to inter- and intra-individual differences in attention and cognition Weds 8:00-9:15am Poster #4042: Can brain state be manipulated to emphasize individual differences in functional connectivity? Finn et al. Poster #4040: Large-scale functional connectivity networks predict attention fluctuations Rosenberg et al. Poster #2110: Functional connectivity-based predictors of naturalistic reading comprehension Jangraw et al. Poster #4029: FMRI connectivity is differentially associated with performance across tasks in a multi-task study Topolski et al. @esfinn

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