Bulletin of the American Physical Society
APS March Meeting 2024
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session K28: Statistical Mechanics of the Brain
3:00 PM–6:00 PM,
Tuesday, March 5, 2024
Room: 101I
Sponsoring
Units:
GSNP DBIO
Chair: Christopher Lynn, Yale University
Abstract: K28.00007 : Parameter estimation from an Ornstein-Uhlenbeck process with measurement noise with applications in neuroscience*
4:36 PM–4:48 PM
Presenter:
Helmut H Strey
(Stony Brook University (SUNY))
Authors:
Helmut H Strey
(Stony Brook University (SUNY))
Simon Carter
(Stony Brook University)
This finding results in a situation that initially seems counterintuitive. When multiplicative noise dominates the noise spectrum, we can successfully estimate the parameters for such systems after adding additional white noise to shift the noise balance.
We apply our methods to the analysis of resting-state functional magnetic resonance imaging (rsfMRI), which measures neural activation correlations between brain regions. Here, we combine our measurements of fMRI noise (thermal and multiplicative) using our BrainDancer Dynamic fMRI phantom with the above-described time-series analysis method to improve the estimation of correlation coefficients by simultaneously modeling the noise and signal (OU dynamics). We show that correlation coefficients that are estimated by our methods more accurately describe the "ground truth" correlation coefficients when applied to human rsfMRI measurements.
*NSF BRAIN Initiative, United States (NSFNCS-FR 1926781) and the Baszucki Brain Research Fund, United States.
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