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Title: Aging power spectrum of membrane protein transport and other subordinated random walks

Journal Article · · Nature Communications
ORCiD logo [1];  [2]; ORCiD logo [3]
  1. Colorado State Univ., Fort Collins, CO (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Bar-Ilan Univ., Ramat Gan (Israel)
  3. Colorado State Univ., Fort Collins, CO (United States); Colorado State Univ., Fort Collins, CO (United States)

Single-particle tracking offers detailed information about the motion of molecules in complex environments such as those encountered in live cells, but the interpretation of experimental data is challenging. One of the most powerful tools in the characterization of random processes is the power spectral density. However, because anomalous diffusion processes in complex systems are usually not stationary, the traditional Wiener-Khinchin theorem for the analysis of power spectral densities is invalid. Here, we employ a recently developed tool named aging Wiener-Khinchin theorem to derive the power spectral density of fractional Brownian motion coexisting with a scale-free continuous time random walk, the two most typical anomalous diffusion processes. Using this analysis, we characterize the motion of voltage-gated sodium channels on the surface of hippocampal neurons. Our results show aging where the power spectral density can either increase or decrease with observation time depending on the specific parameters of both underlying processes.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE Laboratory Directed Research and Development (LDRD) Program; National Science Foundation (NSF); Israel Science Foundation; Colorado State University
Grant/Contract Number:
89233218CNA000001; 2102832; 1898/17
OSTI ID:
1828718
Report Number(s):
LA-UR-21-21176
Journal Information:
Nature Communications, Vol. 12, Issue 1; ISSN 2041-1723
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English

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