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Multitype point process analysis of spines on the dendrite network of a neuron
Author(s) -
Baddeley Adrian,
Jammalamadaka Aruna,
Nair Gopalan
Publication year - 2014
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12054
Subject(s) - dendrite (mathematics) , point process , biological system , cluster analysis , point (geometry) , point pattern analysis , function (biology) , process (computing) , computer science , common spatial pattern , statistical physics , mathematics , pattern recognition (psychology) , artificial intelligence , geometry , physics , statistics , biology , evolutionary biology , operating system
Summary We develop methods for analysing the spatial pattern of events, classified into several types, that occur on a network of lines. The motivation is the study of small protrusions called ‘spines’ which occur on the dendrite network of a neuron. The spatially varying density of spines is modelled by using relative distributions and regression trees. Spatial correlations are investigated by using counterparts of the K ‐function and pair correlation function, where the main problem is to compensate for the network geometry. This application illustrates the need for careful analysis of spatial variation in the intensity of points, before assessing any evidence of clustering.