methods for whole-brain comparisons of resting state functional connectivity stephen j. gotts...
TRANSCRIPT
![Page 1: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/1.jpg)
Methods for Whole-Brain Comparisons of Resting State Functional Connectivity
Stephen J. GottsLaboratory of Brain and Cognition
NIMH/NIHBethesda, MD
![Page 2: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/2.jpg)
Functional Connectivity of Spontaneous Activity at Rest(i.e. "Resting State")
![Page 3: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/3.jpg)
Functional Connectivity of Spontaneous Activity at Rest(i.e. "Resting State")• very popular (easy and fast to administer)
• subjects passively view a fixation cross
• fluctuations in spontaneous activity (< .1 Hz) are correlated throughout the brain in a spatially restricted manner
![Page 4: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/4.jpg)
For review:
Fox & Raichle (2007). Nat Rev Neurosci
Power, Schlaggar, & Petersen (2014).Neuron
Functional Connectivity of Spontaneous Activity at Rest(i.e. "Resting State")• very popular (easy and fast to administer)
• subjects passively view a fixation cross
• fluctuations in spontaneous activity (< .1 Hz) are correlated throughout the brain in a spatially restricted manner
![Page 5: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/5.jpg)
Problem: How can we do brain-wide testing in fMRI?
![Page 6: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/6.jpg)
Problem: How can we do brain-wide testing in fMRI?
Typical methods for Task-based fMRI:
![Page 7: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/7.jpg)
Problem: How can we do brain-wide testing in fMRI?
Typical methods for Task-based fMRI:
• Multiple regression to get Beta Weights per condition/subject
![Page 8: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/8.jpg)
Problem: How can we do brain-wide testing in fMRI?
Typical methods for Task-based fMRI:
• Multiple regression to get Beta Weights per condition/subject
• Test Beta Weights in a voxel-wise manner across subjects (using t-tests, ANOVA, correlation, etc.)
![Page 9: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/9.jpg)
Problem: How can we do brain-wide testing in fMRI?
Typical methods for Task-based fMRI:
• Multiple regression to get Beta Weights per condition/subject
• Test Beta Weights in a voxel-wise manner across subjects (using t-tests, ANOVA, correlation, etc.)
• threshold statistic and correct for voxel-wise comparisons using cluster-size from Monte Carlo simulations or FDR
![Page 10: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/10.jpg)
Problem: How can we do brain-wide testing in fMRI?
Typical methods for Task-based fMRI:
• Multiple regression to get Beta Weights per condition/subject
• Test Beta Weights in a voxel-wise manner across subjects (using t-tests, ANOVA, correlation, etc.)
• threshold statistic and correct for voxel-wise comparisons using cluster-size from Monte Carlo simulations or FDR
• This holds for single whole-brain tests and can be adjusted for multiple tests on the same data using Bonferroni on the corrected p-value
![Page 11: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/11.jpg)
Problem: How can we do brain-wide testing in fMRI?
Typical methods for Task-based fMRI:
• Multiple regression to get Beta Weights per condition/subject
• Test Beta Weights in a voxel-wise manner across subjects (using t-tests, ANOVA, correlation, etc.)
• threshold statistic and correct for voxel-wise comparisons using cluster-size from Monte Carlo simulations or FDR
• This holds for single whole-brain tests and can be adjusted for multiple tests on the same data using Bonferroni on the corrected p-value
But what to do for functional connectivity studies?
![Page 12: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/12.jpg)
Problem: Brain-wide testing for functional connectivity?
![Page 13: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/13.jpg)
Problem: Brain-wide testing for functional connectivity?
The number of comparisons explodes for voxel-wise tests. Every voxel with every voxel is a lot of tests for 40,000 voxels:
![Page 14: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/14.jpg)
Problem: Brain-wide testing for functional connectivity?
The number of comparisons explodes for voxel-wise tests. Every voxel with every voxel is a lot of tests for 40,000 voxels:
40,000 x 39,999 / 2 ≈ 8.0 x 108 tests
![Page 15: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/15.jpg)
Problem: Brain-wide testing for functional connectivity?
The number of comparisons explodes for voxel-wise tests. Every voxel with every voxel is a lot of tests for 40,000 voxels:
40,000 x 39,999 / 2 ≈ 8.0 x 108 testsP < .05/(8.0 x 108) = 6.125 x 10-11 (Bonferroni)
![Page 16: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/16.jpg)
Problem: Brain-wide testing for functional connectivity?
The number of comparisons explodes for voxel-wise tests. Every voxel with every voxel is a lot of tests for 40,000 voxels:
40,000 x 39,999 / 2 ≈ 8.0 x 108 testsP < .05/(8.0 x 108) = 6.125 x 10-11 (Bonferroni)
False Discovery Rate might work (if most p-values are low), but not for more selective differences in typical sized datasets
![Page 17: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/17.jpg)
Problem: Brain-wide testing for functional connectivity?
The number of comparisons explodes for voxel-wise tests. Every voxel with every voxel is a lot of tests for 40,000 voxels:
40,000 x 39,999 / 2 ≈ 8.0 x 108 testsP < .05/(8.0 x 108) = 6.125 x 10-11 (Bonferroni)
False Discovery Rate might work (if most p-values are low), but not for more selective differences in typical sized datasets
Other options:
![Page 18: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/18.jpg)
Problem: Brain-wide testing for functional connectivity?
The number of comparisons explodes for voxel-wise tests. Every voxel with every voxel is a lot of tests for 40,000 voxels:
40,000 x 39,999 / 2 ≈ 8.0 x 108 testsP < .05/(8.0 x 108) = 6.125 x 10-11 (Bonferroni)
False Discovery Rate might work (if most p-values are low), but not for more selective differences in typical sized datasets
Other options:
• Predefined Regions of Interest- but might not capture the full picture
![Page 19: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/19.jpg)
Problem: Brain-wide testing for functional connectivity?
The number of comparisons explodes for voxel-wise tests. Every voxel with every voxel is a lot of tests for 40,000 voxels:
40,000 x 39,999 / 2 ≈ 8.0 x 108 testsP < .05/(8.0 x 108) = 6.125 x 10-11 (Bonferroni)
False Discovery Rate might work (if most p-values are low), but not for more selective differences in typical sized datasets
Other options:
• Predefined Regions of Interest- but might not capture the full picture
• Methods that decompose the data into smaller numbers of elements, such as ICA
- requires some assumptions about the nature of the data
![Page 20: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/20.jpg)
Today's Talk
![Page 21: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/21.jpg)
Today's Talk
Two different whole-brain approaches that are more purely statistical (based in cluster-size correction), with fewer a priori assumptions about network structure:
![Page 22: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/22.jpg)
Today's Talk
Two different whole-brain approaches that are more purely statistical (based in cluster-size correction), with fewer a priori assumptions about network structure:
• Using average "connectedness" (centrality)
![Page 23: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/23.jpg)
Today's Talk
Two different whole-brain approaches that are more purely statistical (based in cluster-size correction), with fewer a priori assumptions about network structure:
• Using average "connectedness" (centrality)
• Testing every voxel as a seed (without averaging)
![Page 24: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/24.jpg)
Average Connectedness (Centrality)
![Page 25: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/25.jpg)
Compress the all-to-all voxels problem into a single map of "connectedness" for each subject (per condition)
time (TRs)% s
igna
l cha
nge
Seed Voxel
8 min
"Connectedness" =
Σ rSeed,i
N
ir =
Z=+17L L
0
1
r-val (df=134)
Average Connectedness (Centrality)
![Page 26: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/26.jpg)
* a la Bob Cox and his AFNI group
Compress the all-to-all voxels problem into a single map of "connectedness" for each subject (per condition)
time (TRs)% s
igna
l cha
nge
Seed Voxel
8 min
"Connectedness" =
Σ rSeed,i
N
ir =
Z=+17L L
0
1
r-val (df=134)
Average Connectedness (Centrality)
![Page 27: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/27.jpg)
X=-2
Z=-11
0.25
0
Rz'
Group Average Connectedness (per condition):
Compress the all-to-all voxels problem into a single map of "connectedness" for each subject (per condition)
Average Connectedness (Centrality)
![Page 28: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/28.jpg)
Compress the all-to-all voxels problem into a single map of "connectedness" for each subject (per condition)
Average Connectedness (Centrality)
![Page 29: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/29.jpg)
Pro: Preserves a lot of the spatial resolution in the data,Regardless of the group comparison, has a shot at
finding "under" or "over-connected" voxelsCon: Might miss more spatially restricted effects and
mixtures of under/over-connection
Compress the all-to-all voxels problem into a single map of "connectedness" for each subject (per condition)
Average Connectedness (Centrality)
![Page 30: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/30.jpg)
Example: Autism (ASD) vs. Typically Developing (TD)
![Page 31: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/31.jpg)
Altered Functional Connectivity in Autism Spectrum Disorders (ASD)
31 High-Functioning ASD adolescents• Using DSM-IV criteria + ADI, ADOS
• "Triad" of impairments:• Impaired social functioning• Restricted interests/repetitive behaviors• Language/communication impairments
29 Typically Developing (TD) controls
![Page 32: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/32.jpg)
31 High-Functioning ASD adolescents• Using DSM-IV criteria + ADI, ADOS
• "Triad" of impairments:• Impaired social functioning• Restricted interests/repetitive behaviors• Language/communication impairments
29 Typically Developing (TD) controls
Groups matched on:AGE: ~17 (12-24)IQ: ~113 (85-143)Sex 95% male subjects
Altered Functional Connectivity in Autism Spectrum Disorders (ASD)
![Page 33: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/33.jpg)
31 High-Functioning ASD adolescents• Using DSM-IV criteria + ADI, ADOS
• "Triad" of impairments:• Impaired social functioning• Restricted interests/repetitive behaviors• Language/communication impairments
29 Typically Developing (TD) controls
Groups matched on:AGE: ~17 (12-24)IQ: ~113 (85-143)Sex 95% male subjects
Scanned at rest with 3.5 sec TR for 8 min 10 sec with1.7 x 1.7 x 3 voxels
Altered Functional Connectivity in Autism Spectrum Disorders (ASD)
![Page 34: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/34.jpg)
How is functional connectivity altered in ASD ?
Altered Functional Connectivity in Autism Spectrum Disorders (ASD)
![Page 35: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/35.jpg)
How is functional connectivity altered in ASD ?
Altered Functional Connectivity in Autism Spectrum Disorders (ASD)
• Generalized disruption of all ‘circuits’ ?
... or System-specific disruption ? (e.g. circuits involved in social processing)
![Page 36: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/36.jpg)
How is functional connectivity altered in ASD ?
• Generalized disruption of all ‘circuits’ ?
... or System-specific disruption ? (e.g. circuits involved in social processing)
• Increase in Local Interactions ? (**)
Altered Functional Connectivity in Autism Spectrum Disorders (ASD)
![Page 37: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/37.jpg)
The "Social Brain" (a la Brothers, 1990; Frith & Frith, 2007; Adolphs, 2009)
![Page 38: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/38.jpg)
Using Group Connectedness to Find Seeds
ASD TD
X=-2
Z=-11
0.25
0
Rz'
![Page 39: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/39.jpg)
Using Group Connectedness to Find Seeds
TD - ASD
X=-2
X=-27
Z=-16
X=+29
2.0
4.0
t-val (df=58)
![Page 40: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/40.jpg)
Using Group Connectedness to Find Seeds
TD - ASD
X=-2
X=-27
Z=-16
X=+29
2.0
4.0
t-val (df=58)
Seeds:• p<.05• at least 100 voxels
Yields 14 Seeds
![Page 41: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/41.jpg)
Z=-14
L
X=-27 X=+30
X=-43 X=+44
X=-50 X=+55
TD > ASD: Seed ROIs
TD > ASD: Non-seed voxels (p<.001, corrected)
Seeds + Seed Tests --> 27 Total Regions of Interest
![Page 42: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/42.jpg)
Y-coordinate
Z-co
ordi
nate
Rostral Caudal
Dorsal
Ventral
Seeds + Seed Tests --> 27 Total Regions of Interest
![Page 43: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/43.jpg)
Y-coordinate
Z-co
ordi
nate
Rostral Caudal
Dorsal
Ventral
Seeds + Seed Tests --> 27 Total Regions of Interest
How do these areas relate to each other ?
![Page 44: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/44.jpg)
Visualizing ROI-ROI correlations with Multi-Dimensional Scaling and K-Means Clustering (K=3)
Dimension 1
Dim
ensi
on 2
TD ROI
![Page 45: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/45.jpg)
Visualizing ROI-ROI correlations with Multi-Dimensional Scaling and K-Means Clustering (K=3)
Dimension 1
Dim
ensi
on 2
ASD ROITD ROI
![Page 46: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/46.jpg)
Visualizing ROI-ROI correlations with Multi-Dimensional Scaling and K-Means Clustering (K=3)
Dimension 1
Dim
ensi
on 2
ASD ROITD ROI
Cluster 1Cluster 3
Cluster 2
![Page 47: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/47.jpg)
% V
aria
nce
Expl
aine
d
Number of Clusters (K)
Visualizing ROI-ROI correlations with Multi-Dimensional Scaling and K-Means Clustering (K=3)
Dimension 1
Dim
ensi
on 2
ASD ROITD ROI
Cluster 1Cluster 3
Cluster 2
![Page 48: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/48.jpg)
% V
aria
nce
Expl
aine
d
Number of Clusters (K)
Dimension 1
Dim
ensi
on 2
Y-coordinate
X-coordinate
Z-co
ordi
nate
P<.05 (Bonferroni-corrected)P<.05 (uncorrected)
TD > ASD (t-val)
![Page 49: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/49.jpg)
![Page 50: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/50.jpg)
Cluster 1:Social inference/affective
Cluster 2:Control/selection-retrieval
Cluster 3:Social perceptionForm / motion
![Page 51: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/51.jpg)
Back to ROI-ROI Correlation Matrices
![Page 52: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/52.jpg)
TD
r-val
Back to ROI-ROI Correlation Matrices
Cluster 1 Cluster 3Cluster 2
Clus
ter 1
Clus
ter 3
Clus
ter 2
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ASD
Back to ROI-ROI Correlation Matrices
Cluster 1 Cluster 3Cluster 2
Clus
ter 1
Clus
ter 3
Clus
ter 2 r-val
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t-val (df=58)
TD - ASD
Back to ROI-ROI Correlation Matrices
Cluster 1 Cluster 3Cluster 2
Clus
ter 1
Clus
ter 3
Clus
ter 2
![Page 55: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/55.jpg)
Is this clinically relevant?
‘Functional decoupling’
Cluster 1:Social inference/affective
Cluster 2:Language / communication
Cluster 3:Social perceptionForm / action
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Correlations of Social Responsiveness Scale (SRS) ROI x ROI correlations in ASD sample alone (N=29)
ASD: Correlation with SRS (adjusted for Age,IQ)
Cluster 1 Cluster 3Cluster 2
Clus
ter 1
Clus
ter 3
Clus
ter 2
ASD median rC1 ROIs with C2,C3 ROIs (adjusted for Age,IQ)
SRS
(adj
uste
d fo
r Age
,IQ)
partial r = -.390(P<.05)
partial r (df=25)
TD > ASD t-val (df=58)
![Page 57: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/57.jpg)
Z=-14
Correlations of Social Responsiveness Scale (SRS) with Connectednessin ASD sample alone (N=29)
L
Z=-12
X=-27
Y=-3
n.s.
P < .01
P < .001
P<.05 (corrected)
X=-27
![Page 58: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/58.jpg)
• At least for high-functioning ASD subjects, the largest differences in correlation were concentrated among regions of the 'social brain'
• We observed a fractionation of social brain circuits into two parts
• Social/affective component (Cluster 1) was ‘functionally’ decoupled from language and visuomotor components
Summary for ASD Study
![Page 59: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/59.jpg)
Applying the same method to ChildhoodOnset Schizophrenia(vs. Typ. Developing)
Collaboration with:Becky BermanHarrison McAdamsNitin GogtayJudy Rapoportet al.
X=-40 X=-6
Z=+5Z=+48
X=+45X=+6
Y=-10 Y=-55
Red cluster:Social-cognitive
Green cluster:Sensorimotor
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TD - COSTD COS
% v
aria
nce
unex
plai
ned
Number of clusters (K)
100
80
60
40
20
00 2 4 6 8
Dimension 10 5-5 10
0
5
-5
Dim
ensi
on 2
0.6
0.4
0.2
0
5
-50
-0.2
0.8
r-val1.0
t-val(df=43)
0 5-5 10Dimension 1
Dim
ensi
on 2
0
-2
-4
2
Red Cluster Green Cluster Red Cluster Green Cluster Red Cluster Green Cluster
Red
Clus
ter
Gre
en C
lust
er
PCA with K-means (K=2) MDS with K-means (K=2) Elbow plotA B C
D E F
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` `
`
Correlation with Positive Symptoms (SAPS)(covarying age, motion)
Correlation with Negative Symptoms (SANS)(covarying age, motion)
Red
Clus
ter
Gre
en C
lust
er
partial r partial r
Red Cluster Green Cluster Red Cluster Green Cluster
spatial overlap with seed-based symptom correlation analyses (p<.05, corrected by cluster size)
![Page 62: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/62.jpg)
` `
`
Correlation with Positive Symptoms (SAPS)(covarying age, motion)
Correlation with Negative Symptoms (SANS)(covarying age, motion)
Red
Clus
ter
Gre
en C
lust
er
partial r partial r
Red Cluster Green Cluster Red Cluster Green Cluster
spatial overlap with seed-based symptom correlation analyses (p<.05, corrected by cluster size)Group t-tests:
![Page 63: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/63.jpg)
Increased Resting Correlations in Primary Lateral Sclerosis (PLS)Collaboration with Mary Kay Floeter (NINDS) and Avner Meoded (Johns Hopkins):
![Page 64: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/64.jpg)
Controls PLS PLS-ControlCorrelation with
ALSFRS
Increased Resting Correlations in Primary Lateral Sclerosis (PLS)Collaboration with Mary Kay Floeter (NINDS) and Avner Meoded (Johns Hopkins):
![Page 65: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/65.jpg)
Summary for Connectedness
![Page 66: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/66.jpg)
Summary for Connectedness
Group tests of whole-brain connectedness, along with subsequent seed tests, can detect brain regions that are related to behavioral functions of interest (e.g. social ability in Autism)
![Page 67: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/67.jpg)
Summary for Connectedness
Group tests of whole-brain connectedness, along with subsequent seed tests, can detect brain regions that are related to behavioral functions of interest (e.g. social ability in Autism)
However, it's still not clear that everything is being detected:
![Page 68: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/68.jpg)
Summary for Connectedness
Group tests of whole-brain connectedness, along with subsequent seed tests, can detect brain regions that are related to behavioral functions of interest (e.g. social ability in Autism)
However, it's still not clear that everything is being detected:• problem of mixtures that cancel
![Page 69: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/69.jpg)
Summary for Connectedness
Group tests of whole-brain connectedness, along with subsequent seed tests, can detect brain regions that are related to behavioral functions of interest (e.g. social ability in Autism)
However, it's still not clear that everything is being detected:• problem of mixtures that cancel• spatially restricted effects can fail to be detected
![Page 70: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/70.jpg)
Testing Every Voxel as a Seed
![Page 71: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/71.jpg)
Eliminates the averaging approach, but can take a long time (~ 2 weeks on a fast desktop with 32 GB of RAM)
Testing Every Voxel as a Seed
![Page 72: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/72.jpg)
Eliminates the averaging approach, but can take a long time (~ 2 weeks on a fast desktop with 32 GB of RAM)
Testing Every Voxel as a Seed
Basic Approach: Adjust Monte Carlo simulations of cluster-size to handle testing of all seeds
![Page 73: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/73.jpg)
Eliminates the averaging approach, but can take a long time (~ 2 weeks on a fast desktop with 32 GB of RAM)
Testing Every Voxel as a Seed
Basic Approach: Adjust Monte Carlo simulations of cluster-size to handle testing of all seeds• Generate random data for N simulated subjects
![Page 74: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/74.jpg)
Eliminates the averaging approach, but can take a long time (~ 2 weeks on a fast desktop with 32 GB of RAM)
Testing Every Voxel as a Seed
Basic Approach: Adjust Monte Carlo simulations of cluster-size to handle testing of all seeds• Generate random data for N simulated subjects• Spatially blur to match average smoothness of actual data
![Page 75: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/75.jpg)
Eliminates the averaging approach, but can take a long time (~ 2 weeks on a fast desktop with 32 GB of RAM)
Testing Every Voxel as a Seed
Basic Approach: Adjust Monte Carlo simulations of cluster-size to handle testing of all seeds• Generate random data for N simulated subjects• Spatially blur to match average smoothness of actual data• Conduct correlation tests using every voxel as a seed, keeping track of the
largest cluster ever detected surviving a particular voxel-wise p-value
![Page 76: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/76.jpg)
Eliminates the averaging approach, but can take a long time (~ 2 weeks on a fast desktop with 32 GB of RAM)
Testing Every Voxel as a Seed
Basic Approach: Adjust Monte Carlo simulations of cluster-size to handle testing of all seeds• Generate random data for N simulated subjects• Spatially blur to match average smoothness of actual data• Conduct correlation tests using every voxel as a seed, keeping track of the
largest cluster ever detected surviving a particular voxel-wise p-value• Repeat many times (e.g. 5000 iterations) to determine the cluster size
needed for P<.05 FWE
![Page 77: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/77.jpg)
Eliminates the averaging approach, but can take a long time (~ 2 weeks on a fast desktop with 32 GB of RAM)
Testing Every Voxel as a Seed
Basic Approach: Adjust Monte Carlo simulations of cluster-size to handle testing of all seeds• Generate random data for N simulated subjects• Spatially blur to match average smoothness of actual data• Conduct correlation tests using every voxel as a seed, keeping track of the
largest cluster ever detected surviving a particular voxel-wise p-value• Repeat many times (e.g. 5000 iterations) to determine the cluster size
needed for P<.05 FWE• Do same tests on actual data using these critical thresholds to find corrected
results
![Page 78: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/78.jpg)
Larger ASD/TD Dataset (Martin lab)
56 ASD, 62 TD, separated into two independent sets (Sets 1 and 2: 28 ASD, 31 TD each) that are matched for Motion and Age (P>.1 for all)
All voxel-wise t-tests also include Motion and Age as covariates(AFNI's 3dttest++, with common median centering)
![Page 79: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/79.jpg)
P<.05 288 704 2.44P<.01 73 200 2.74P<.005 49 152 3.10P<.001 22 88 4.00P<.0005 16 72 4.50P<.0001 8 48 6.00P<.00005 6 40 6.67
1 testTest AllVoxels
Factor ofExpansion
VoxelwiseP-value
Cluster-size Thresholds from Monte Carlo Simulations (5000 iterations)
P<.05
Analysis Mask(85% of Both ASD/TD Groups)
Z=+10
X=0
L
![Page 80: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/80.jpg)
Larger ASD/TD Dataset (Martin lab)Set 1 (28 ASD, 31 TD)Seed Voxels involved in significant differences for which TD > ASD (ranging from P<.05 down to P<.00005, corrected):
![Page 81: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/81.jpg)
Larger ASD/TD Dataset (Martin lab)Set 1 (28 ASD, 31 TD)Seed Voxels involved in significant differences for which TD > ASD (ranging from P<.05 down to P<.00005, corrected):
Z=-14 Z=0 Z=+40
X=-50 X=+50
![Page 82: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/82.jpg)
Larger ASD/TD Dataset (Martin lab)Set 1 (28 ASD, 31 TD)Seed Voxels involved in significant differences for which ASD > TD (ranging from P<.05 down to P<.00005, corrected):
![Page 83: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/83.jpg)
Larger ASD/TD Dataset (Martin lab)Set 1 (28 ASD, 31 TD)Seed Voxels involved in significant differences for which ASD > TD (ranging from P<.05 down to P<.00005, corrected):
Z=0
X=-50 X=+50
Z=+10 Z=+20
![Page 84: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/84.jpg)
What is the relationship to Connectedness comparisons?
... and the previously reported results? (Brain 2012)
![Page 85: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/85.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Connectedness Tests (TD-ASD),P<.05, uncorrected (>100 voxels)
![Page 86: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/86.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Connectedness Tests (TD-ASD),P<.05, uncorrected (>100 voxels)
![Page 87: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/87.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Connectedness Tests (TD-ASD),P<.05, corrected
![Page 88: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/88.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Connectedness Tests (TD-ASD),Replication Across Two Sets, P<.05, corrected
![Page 89: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/89.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Testing All Voxels as Seeds (TD-ASD),Replication Across Two Sets, P<.05, corrected
![Page 90: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/90.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Testing All Voxels as Seeds (TD-ASD),Replication Across Two Sets, ASD>TD
![Page 91: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/91.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Testing All Voxels as Seeds (TD-ASD),Replication Across Two Sets, P<.05, corrected
![Page 92: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/92.jpg)
27 ROIs (ANATICOR)
Z=-15
L
X=-27 X=+30
X=-43 X=+51
Z=+10
Brain 2012 ROIs(31 ASD, 29 TD)
Larger NIMH Dataset(56 ASD, 62 TD)
Connectedness Tests (TD-ASD),P<.05, corrected
![Page 93: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/93.jpg)
Summary
![Page 94: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/94.jpg)
Summary• Massive voxel-wise testing of functional connectivity data
is indeed possible, with robust replication across independent datasets
![Page 95: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/95.jpg)
Summary• Massive voxel-wise testing of functional connectivity data
is indeed possible, with robust replication across independent datasets
• Voxel-wise seed testing does a better job than connectedness tests at identifying locations with mixed results (TD>ASD and ASD>TD), although results are not radically different
![Page 96: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/96.jpg)
Summary• Massive voxel-wise testing of functional connectivity data
is indeed possible, with robust replication across independent datasets
• Voxel-wise seed testing does a better job than connectedness tests at identifying locations with mixed results (TD>ASD and ASD>TD), although results are not radically different
• Such tests do not require a priori assumptions about common network structure in control and clinical groups (as group ICA methods commonly do)
![Page 97: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/97.jpg)
Summary• Massive voxel-wise testing of functional connectivity data
is indeed possible, with robust replication across independent datasets
• Voxel-wise seed testing does a better job than connectedness tests at identifying locations with mixed results (TD>ASD and ASD>TD), although results are not radically different
• Such tests do not require a priori assumptions about common network structure in control and clinical groups (as group ICA methods commonly do)
• Searches are possible for any type of test statistic for which p-values can be calculated (e.g. correlation with behavioral measures, more complex ANOVAs, etc.)
![Page 98: Methods for Whole-Brain Comparisons of Resting State Functional Connectivity Stephen J. Gotts Laboratory of Brain and Cognition NIMH/NIH Bethesda, MD](https://reader035.vdocument.in/reader035/viewer/2022062517/56649eb05503460f94bb56b6/html5/thumbnails/98.jpg)
Acknowledgements:
Section on Cognitive Neuropsychology, LBC (NIMH) Alex Martin, ChiefKyle Simmons (now at LIBR, Tulsa)Lydia MilburyGreg Wallace
Scientific and Statistical Computing Core (NIMH)Bob Cox, ChiefZiad SaadGang Chen