CABAL is a research group in the Department of Philosophy at Carnegie Mellon University.
We are focused on developing, testing and applying statistical causal inference algorithms to brain functional imaging data. Our research spans:
- Causal search on fMRI data at region of interest level
- High-dimensional, big data causal search at voxelwise level
- Causal search on task and resting state fMRI
- Population classification based on causal networks
- Connectivity based sub-regions of interest definition
- Feedback and non-stationarity connectivity
We are also part of the Center for Causal Discovery, a partnership among data scientists from the University of Pittsburgh, Carnegie Mellon University, and the Pittsburgh Supercomputing Center, to develop algorithms, software, and system architecture needed by biomedical scientists seeking to discover and represent causality using large and diverse data sets.