Christian Habeck, PhD
Taub Institute

Christian Habeck

P & S Box 16
630 West 168th Street
New York, NY 10032

Ongoing Research:

Early Alzheimer’s detection with Arterial Spin Labeling (NIA 5R01AG026114)
Arterial Spin Labeling (ASL) is a recent MRI scanning innovation that can measure cerebral blood flow with absolute quantification without the need for arterial injection of any contrast agents. It is therefore substantially cheaper and more comfortable. We are testing ASL and its suitability as an early systems-level biomarker for Alzheimer’s disease by contrasting 20 healthy elderly control participants and 20 early AD patients. Blood flow patterns that are derived from this comparison will be tested for their diagnostic/prognostic ability in 60 participants with Mild Cognitive Impairment. Follow-up data will be available for further validation.

Multivariate Approaches to Brain Imaging Data Analysis (NIBIB 5R01EB006204)
We apply multivariate techniques both to (1) resting data for the purposes of early detection of Alzheimer's disease and (2) to functional data of healthy volunteers for the purposes of understanding how basic cognitive mechanisms are implemented in the brain.
In contrast to the standard univariate techniques in PET and fMRI data analysis, which do not provide any information about region-by-region correlation in the brain, multivariate techniques identify distributed brain networks underlying cognitive function. With my colleague J. Moeller I am extending the covariance-based Subprofile Scaling Model (SSM), pioneered here at Columbia and successfully applied to PET, to fMRI and EEG data, employing both Monte-Carlo simulations as well as empirical surveys of real-world data sets. This proves useful for a better understanding of the techniques, and ultimately of the brain itself.

Representative Recent Publications

  1. C. Habeck, J.R. Moeller, Intrinsic Functional-Connectivity Networks for Diagnosis: Just Beautiful Pictures? Brain Connectivity. 1, 99-103.

  2. C. Habeck. Basics of Multivariate Analysis in Neuroimaging Data. Journal of Visual Experiments 2010: 41, doi: 10.3791/1988 PMCID: PMC3074457

  3. C. Habeck, Y. Stern, and the Alzheimer’s Disease Neuroimaging Initiative. Multivariate data analysis for neuroimaging data: overview and applications to Alzheimer’s Disease. Cell Biochemistry and Biophysics 2010: 58: 53-67

Software package for spatial covariance analysis with documentation
Email me (ch629 AT columbia DOT edu) for code and extensive documentation for performing generalized covariance analysis (GCVA). The code contains standard PLS, PCA and Ordinal Trend Analysis with non-parametric bootstrap and permutation tests.

Popular science reading
By David Dobbs from Scientific American Mind, April 2005
This is a nice article about the current challenges of fMRI research, and refers to our work described on this homepage.

2) Also check article in "Symmetry Magazine"