BMI Retreat, Stanford University 2012

1. 105 Temporal Features
signal metrics, peaks,
kurtosis, skewedness, entropy,
amplitudes, power bands,
HPSD, auto correlation etc.
PreprocessingFunctional MRI
Spatial and Temporal Features of fMRI Networks to Distinguish Real Networks from Noise
Preliminary work to use patterns of functional networks to classify neuropsychiatric disorder
V. Sochat, Rubin Lab, Stanford University School of Medicine, Stanford CA
Introduction
• Independent Component Analysis ICA is a data-driven method to decompose functional
neuroimaging data into brain networks.
• The decomposed independent components encompass a mix of true neural signal,
machine artifact, motion, and physiological noise that are typically visually distinguished.
• Neurological disorders are beginning to be understood based on aberrant brain structure
and function on the single network level.
• No methods exist for identifying patterns across all networks to distinguish disorder.
What Does the Data Look Like?
How do we Define a Standard?
Lasso L1 Constrained linear regression selects 124 features to distinguish real from
noisy components (N=1518) with a cross validation accuracy of .8675.
Supported by
Microsoft Research, NSF
Stanford Graduate Fellowship
Can We Predict Component Type from Features?
Meeting with MIND Institute 9/24/2012 to finalize
standard development to allow for robust computation
of functional network fingerprints.
Why Should I Care?
What is a network?
There are no standards or
definitions of functional
brain networks beyond
expert opinion.
What is a subnetwork?
Overdetermined ICA
produces “subnetworks,”
but we do not completely
understand how they
match to main networks.
How to Rx Disorder?
Diagnosis of neuro-
psychiatric disorder with
the DSM is categorical,
checklist based, and
terrible.
We need methods to
establish standards for
networks and noise.
Computational definition
of subnetworks matching
to main networks will
allow for investigation of
patterns of neural activity
within main networks.
Biomarkers from
functional imaging can
drive diagnosis of disorder
and subtyping.
1. Standard and Features 2. Subnetwork Definition 3. Classify Disorder
This Project:
Spatial and temporal
features to distinguish real
from noisy components
Next Stage of Work:
Features of subnetworks
and matching to main
networks
Big Picture:
Patterns of functional brain
networks for classification
of neuropsychiatric disorder
unsolvedproblemsobjective
Realign /
Reslice
Motion
Correction
Segmentation Smoothing Filtering Normalization
ICA
n x m n x n n x m
Contact
vsochat@stanford.edu
What Features Define the Networks?
1. Outline: database of “known” networks scattered in
literature. Currently identification is done manually.
1. component type (real, noise, etc.)
2. network type (motor, visual, default mode network)
3. network name (“precuneus posterior cingulate”)
4. intuitive name (“the tie fighter”)
135 Spatial Features
Regional activation,
matter types, kurtosis,
entropy, skewedness,
degree of clustering
Selected Features “Eyeballs” Component
Perfect_total_activation_in_GM
Percent_total_activation_in_WM
Olfactory_R
Skewedness of IC distribution
Avg_distance_btw_10_local_max
Spatial Entropy of IC distribution
Percent_total_activation_in_eyeballs
LASSO cva: 0.9841
2. Teach send database and networks to experts
3. Label: experts use annotation tool to label networks
4. Fingerprint: define networks based on pattern of features
Good / Bad
Network X / Not Network X
42 Networks
11
2
3
4
34
Thank You
Rebecca Sawyer and Kaustubph Supekar, Signal Processing
Daniel Rubin: Best Advisor Ever!
24 healthy control
29 schizophrenia
Network fingerprints will allow for automatic labeling
and filtering of single subject ICA. For the first time,
subnetworks can be assigned meaningful labels, the
main networks they match to.
Different patterns of these subnetworks within the
space of a main network will distinguish disorder.
These methods will be extended to other imaging data
Bad Good
Bad 740 121
Good 78 579
N = 1518 Networks
spatial maps
and timecourses
Please see research journal for preliminary match work