Accession Number:

ADA455958

Title:

Hidden Process Models

Descriptive Note:

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE

Personal Author(s):

• Mitchell, Tom M.
• Hutchinson, Rebecca
• Rustandi, Indrayana

Report Date:

2006-02-17

Pagination or Media Count:

14.0

Abstract:

We introduce the Hidden Process Model HPM,a probabilistic model for multivariate time series data intended to model complex, poorly understood, overlapping and linearly additive processes. HPMs are motivated by our interest in modeling cognitive processes given brain image data. We define HPMs. present inference and learning algorithms study their characteristics using synthetic data, and demonstrate their use for tracking human cognitive processes using fMRI data.

Descriptors:

• *ALGORITHMS
• *MULTIVARIATE ANALYSIS
• *COGNITION
• DECISION MAKING
• TIME SERIES ANALYSIS
• IMAGES
• LEARNING
• TRACKING
• BRAIN
• MODELS
• HUMANS

Subject Categories:

• Psychology
• Numerical Mathematics
• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE