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Sample Drift Correction Following 4D Confocal Time-lapse Imaging

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Noise-induced drift in two-dimensional anisotropic systems.

¹Department of Biomedical Engineering and Ilse Katz Institute for Nanoscale Science and Technology, Ben-Gurion University of the Negev, Be'er Sheva 85105, Israel.

Physical Review. E

|January 20, 2018

Summary

In heterogeneous systems, particles can drift without physical forces due to spatially varying diffusivity. This study reveals novel drift behaviors in 2D anisotropic systems, impacting protein diffusion.

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Area of Science:

Physics
Physical Chemistry
Biophysics

Background:

Brownian dynamics describes particle motion influenced by random forces.
Spatially varying diffusivity leads to noise-induced drift, previously studied in 1D.
Anisotropic systems exhibit direction-dependent diffusion properties.

Purpose of the Study:

To investigate noise-induced drift in 2D anisotropic systems.
To derive a general expression for the mean displacement vector in such systems.
To analyze the novel drifting effects arising from anisotropic diffusion.

Main Methods:

Theoretical derivation of mean displacement vector for Brownian dynamics.
Analysis of a symmetric diffusion tensor with unequal diagonal elements.
Verification using Langevin dynamics simulations.

Main Results:

A general expression for mean displacement was derived, comprising two distinct drift vectors.
The first drift vector generalizes 1D noise-induced drift towards higher diffusivity regions.
A novel second drift vector arises from the spatial rotation of principal diffusion axes.

Conclusions:

The study elucidates complex noise-induced drift phenomena in 2D anisotropic systems.
The derived expressions accurately predict particle displacement in heterogeneous environments.
Applied to transmembrane proteins, the model shows a rapid increase in their average separation.