JSM 2005 - Toronto

Abstract #303436

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Activity Number: 473
Type: Topic Contributed
Date/Time: Thursday, August 11, 2005 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #303436
Title: An Angular Regression Model for Phase-only fMRI Data
Author(s): Christopher Meller*+ and Daniel B. Rowe
Companies: Medical College of Wisconsin and Medical College of Wisconsin
Address: 17550 Katie Ct, Gurnee, IL, 60031, United States
Keywords: Angular Regression ; fMRI Phase ; Signal-to-Noise Ratio
Abstract:

Magnitude-only data models have dominated fMRI analysis since the inception of the technology. However, when such analyses are done, half the data---which may or may not contain valuable information---is disregarded. This overlooked data is called the phase and is restricted to values between pi and pi. When phase time series are analyzed, ordinary least squares (OLS) regression has been the technique of choice. However, OLS models perform poorly when "wrap-around" or low SNR is present. We explored alternatives to the OLS model, which will account for the angular response of the phase while also allowing us the flexibility to develop similar hypothesis tests. We adopted a model by Fisher and Lee (1992) to our analysis of the generally discarded fMRI phase time series and show its improvement over the OLS model for both parameter estimation and data prediction for various conditions. We fit the model to both simulated data and acquired data from an actual fMRI experiment.

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