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Modeling Causality of Mean and Variance between Sets of Signals

Modeling Causality of Mean and Variance between Sets of Signals. Syed Ashrafulla February 3, 2012. Causality: Models and Methods. Agriculture Phillipines. EPA. Granger1969, Econometrica. NASA. All over Albany. Model: autoregression with conditional heteroscedasticity.

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Modeling Causality of Mean and Variance between Sets of Signals

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  1. Modeling Causality of Mean and Variance between Sets of Signals Syed Ashrafulla February 3, 2012

  2. Causality: Models and Methods Agriculture Phillipines EPA Granger1969, Econometrica NASA All over Albany Model: autoregression with conditional heteroscedasticity Sims1972, Amer Eco Rev Engle1985, Econ Th Causality in Mean Causality in Variance  change in the mean when given the past  change in the variance when given the past Geweke1982, J Amer Stat Assoc Hafner2008, Econ Anal of Stat

  3. Canonical Granger Causality Ashrafulla2012, Proc IEEE ISBI • Why regional causality? • Sensitivity • Cross-talk • Long-range • Why canonical? • Fewer parameters • Signals of interest Optimization • Nonlinear conjugate gradient descent Granger causality Ashrafulla2013, in process

  4. Application: Visuomotor Processing • Causality during task • Difference between stimuli • Difference between stimuli • CGC finds significant task & stimulus differences. Stimuli Diamond Line Response Ashrafulla2012, Biomag NoGO GO

  5. This work was funded under the NIBIB T32EB00438 Bioinformatics Training Program and NIH grants R01EB009048 and R01 5R01EB000473. Acknowledgements

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