Computing spatial information from Fourier coefficient distributions

William F. Heinz, Jeffrey L. Werbin, Eaton Lattman, Jan H. Hoh

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The spatial relationships between molecules can be quantified in terms of information. In the case of membranes, the spatial organization of molecules in a bilayer is closely related to biophysically and biologically important properties. Here, we present an approach to computing spatial information based on Fourier coefficient distributions. The Fourier transform (FT) of an image contains a complete description of the image, and the values of the FT coefficients are uniquely associated with that image. For an image where the distribution of pixels is uncorrelated, the FT coefficients are normally distributed and uncorrelated. Further, the probability distribution for the FT coefficients of such an image can readily be obtained by Parseval's theorem. We take advantage of these properties to compute the spatial information in an image by determining the probability of each coefficient (both real and imaginary parts) in the FT, then using the Shannon formalism to calculate information. By using the probability distribution obtained from Parseval's theorem, an effective distance from the uncorrelated or most uncertain case is obtained. The resulting quantity is an information computed in k-space (kSI). This approach provides a robust, facile and highly flexible framework for quantifying spatial information in images and other types of data (of arbitrary dimensions). The kSI metric is tested on a 2D Ising model, frequently used as a model for lipid bilayer; and the temperature-dependent phase transition is accurately determined from the spatial information in configurations of the system.

Original languageEnglish (US)
Pages (from-to)59-68
Number of pages10
JournalJournal of Membrane Biology
Volume241
Issue number2
DOIs
StatePublished - May 1 2011

Keywords

  • Information theory
  • Ising model
  • Membrane
  • Spatial organization

ASJC Scopus subject areas

  • Biophysics
  • Physiology
  • Cell Biology

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