Measurement Error Correction in Particle Tracking Microrheology

Abstract

In diverse biological applications, particle tracking of passive microscopic species has become the experimental measurement of choice -when either the materials are of limited volume, or so soft as to deform uncontrollably when manipulated by traditional instruments. In a wide range of particle tracking experiments, a ubiquitous finding is that the mean squared displacement (MSD) of particle positions exhibits a power-law signature, the parameters of which reveal valuable information about the viscous and elastic properties of various biomaterials. However, MSD measurements are typically contaminated by complex and interacting sources of instrumental noise. As these often affect the highfrequency bandwidth to which MSD estimates are particularly sensitive, inadequate error correction can lead to severe bias in power law estimation and thereby, the inferred viscoelastic properties. In this article, we propose a novel strategy to filter high-frequency noise from particle tracking measurements. Our filters are shown theoretically to cover a broad spectrum of high-frequency noises, and lead to a parametric estimator of MSD power-law coefficients for which an efficient computational implementation is presented. Based on numerous analyses of experimental and simulated data, results suggest our methods perform very well compared to other denoising procedures.

Anomalous diffusion, nonergodicity, and ageing for exponentially and logarithmically time-dependent diffusivity: striking differences for massive versus massless particles

“…We mention here the models with 'switching' between different types of (anomalous) diffusion (intermittent processes) [60,124,147,161,162,164,[172][173][174][175]. The importance of particle-localization errors onto determination of 'apparent' subdiffusion [176][177][178][179][180][181] should also be emphasized (see also the recent studies on quantifying error corrections in particle-tracking microrheology [182] and for ergodic ensembles of colloidal particles [183]). Recent applications of anomalous diffusion and nonergodicity [185][186][187][188][189] for the analysis of income growth in gambling are also to be mentioned [190].…”