Incremental Cluster-wise Regression Analysis
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Incremental Cluster-wise Regression Analysis of Functional fMRI data. Sennay Ghebreab. Informatics Institute, Faculty of Science University of Amsterdam, The Netherlands. Background. What and how to map?. Sensory Stimulation. Brain Activation. What (visual) features to address ?

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Incremental Cluster-wise Regression Analysis of Functional fMRI data

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Incremental cluster wise regression analysis of functional fmri data

Incremental Cluster-wise Regression Analysis

of Functional fMRI data

Sennay Ghebreab

Informatics Institute, Faculty of Science

University of Amsterdam, The Netherlands


Incremental cluster wise regression analysis of functional fmri data

Background

What and how to map?

Sensory Stimulation

Brain Activation

  • What (visual) features to address ?

  • What fMRI analysis approach to use ?


Incremental cluster wise regression analysis of functional fmri data

Background

+ no prior model required

+ spatial & temporal pattern

- patterns may be meaningless

- work on all voxels

PCA

ICA

data-driven

CVA

PLS

+ soft prior model required

+ spatial & temporal pattern

- work on all voxels

data-driven + model-based

multivariate

+ meaningful patterns

- good model/design required

- spatial pattern only

- work on single voxels

GLM

Model-based

univariate


Incremental cluster wise regression analysis of functional fmri data

Background

CSCA video experiment

Brain reading competition experiment


Incremental cluster wise regression analysis of functional fmri data

Motivation

Exploit data characteristics: data is continuous and multivariate, not discrete

Exploit activation characteristic: activations are localized in time and space, not voxel specific or volume specific

Functional data analysis

Incremental Cluster-wise Regression


Incremental cluster wise regression analysis of functional fmri data

Standard data analysis

Mapping to high-level vector space

  • disregard of spatial correlation

  • disregard of multi-feature nature


Incremental cluster wise regression analysis of functional fmri data

Functional data analysis

Mapping to high-level functional space

feature 1

time

feature 2

  • continuous data representation

  • multivariate data representation


Incremental cluster wise regression analysis of functional fmri data

Functional data analysis

registration

functional PCA

functional GLM


Incremental cluster wise regression analysis of functional fmri data

Incremental cluster-wise regression

Find fMRI functional subspace that best explains stimulation

FD of HRF convolved amusement feature rating by subject 1 over 20 minutes

(stimulation)

FD of fmri of subject1 from BRC

(64x64x32 voxels/FDs) while

watching 20 minute movie (tr 1.75)


Incremental cluster wise regression analysis of functional fmri data

Incremental cluster-wise regression

Functional PCA

Data described by 3 functional pca’s

(capturing 91% of variability )


Incremental cluster wise regression analysis of functional fmri data

Incremental cluster-wise regression

Selection of activations similar to stimulation


Incremental cluster wise regression analysis of functional fmri data

Incremental cluster-wise regression

Cluster-wise GLM regression

Y = XB + E


Incremental cluster wise regression analysis of functional fmri data

Incremental cluster-wise regression

After a few increments you end up with

  • Spatial patterns (voxel clusters)

  • Temporal patterns (activation cluster, predictor model)

  • HRF patterns (hrf estimation model)

Do this for all subjects separately, then repeat same

procedure for all resulting activation clusters of all subjects

to say something about a group of subjects


Incremental cluster wise regression analysis of functional fmri data

Example result

Brain Reading Competition

Cluster wise GLM fit F-statistics

(green line: p<0.05)

Prediction of amusement rating in movie 2

by subject 2, based on amusement rating

and fmri of subject1 (red=prediction, blue=true rating)


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