Analysis of spatial patterns in histological sections of brain tissue using a method based on regression

Richard A. Armstrong*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


A method of determining the spatial pattern of any histological feature in sections of brain tissue which can be measured quantitatively is described and compared with a previously described method. A measurement of a histological feature such as density, area, amount or load is obtained for a series of contiguous sample fields. The regression coefficient (β) is calculated from the measurements taken in pairs, first in pairs of adjacent samples and then in pairs of samples taken at increasing degrees of separation between them, i.e. separated by 2, 3, 4,..., n units. A plot of β versus the degree of separation between the pairs of sample fields reveals whether the histological feature is distributed randomly, uniformly or in clusters. If the feature is clustered, the analysis determines whether the clusters are randomly or regularly distributed, the mean size of the clusters and the spacing of the clusters. The method is simple to apply and interpret and is illustrated using simulated data and studies of the spatial patterns of blood vessels in the cerebral cortex of normal brain, the degree of vacuolation of the cortex in patients with Creutzfeldt-Jacob disease (CJD) and the characteristic lesions present in Alzheimer's disease (AD). Copyright (C) 2000 Elsevier Science B.V.

Original languageEnglish
Pages (from-to)39-45
Number of pages7
JournalJournal of Neuroscience Methods
Issue number1
Publication statusPublished - 31 Jan 2000


  • clustering
  • hstological section
  • lnear regression
  • periodicity of clusters
  • spatial pattern analysis


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