betacells              package:spatstat              R Documentation

_B_e_t_a _G_a_n_g_l_i_o_n _C_e_l_l_s _i_n _C_a_t _R_e_t_i_n_a

_D_e_s_c_r_i_p_t_i_o_n:

     Point pattern of cells in the retina, each cell classified as `on'
     or `off'. A bivariate point pattern.

_U_s_a_g_e:

     data(betacells)

_F_o_r_m_a_t:

     'betacells' is an object of class '"ppp"' representing the point
     pattern of cell locations. Entries include

       'x'      Cartesian x-coordinate of cell
       'y'      Cartesian y-coordinate of cell
       'marks'  factor with levels 'off' and 'on'
                indicating ``off'' and ``on'' cells

     See 'ppp.object' for details of the format. Cartesian coordinates
     are given in microns.

     'betacells.extra' is a list with one component 'area' which is the
     vector of areas (in square microns) of the cells in the pattern.

_N_o_t_e_s:

     This is a new, corrected version of the old dataset 'ganglia'. See
     below.

     These data represent a pattern of beta-type ganglion cells in the
     retina of a cat recorded by W\"assle et al. (1981). Beta cells are
     associated with the resolution of fine detail in the cat's visual
     system. They can be classified anatomically as ``on'' or ``off''.

     Statistical independence of the arrangement of the ``on''- and
     ``off''-components would strengthen the evidence for Hering's
     (1878) `opponent theory' that there are two separate channels for
     sensing ``brightness'' and ``darkness''. See W\"assle et al
     (1981). There is considerable current interest in the arrangement
     of cell mosaics in the retina, see Rockhill et al (2000).

     The dataset is a multitype point pattern giving the locations and
     types (``on'' or ``off'') of beta cells observed in a rectangle of
     dimensions 750 x 990 microns. Coordinates are given in microns
     (thousandths of a millimetre).

     The original source is Figure 6 of W\"assle et al (1981), which is
     a manual drawing of the beta mosaic observed in a microscope
     field-of-view of a whole mount of the retina. Thus, all beta cells
     in the retina were effectively projected onto the same
     two-dimensional plane.

     The data were scanned in 2004 by Stephen Eglen from Figure 6(a) of
     W\"assle et al (1981). Image analysis software was used to
     identify the soma (cell body). The x,y location of each cell was
     taken to be the centroid of the soma. The type of each cell
     (``on'' or `off'') was identified by referring to Figures 6(b) and
     6(d).

     The area of each soma (in square microns) was also computed, and
     is provided in the dataset 'betacells.extra'.

     Note that this is a corrected version of the 'ganglia'   dataset
     provided in earlier versions of 'spatstat'. The earlier data
     'ganglia' were not faithful to the scale in the original paper and
     contain some scanning errors.

_S_o_u_r_c_e:

     W\"assle et al (1981), Figure 6(a), scanned and processed by
     Stephen Eglen S.J.Eglen@damtp.cam.ac.uk

_R_e_f_e_r_e_n_c_e_s:

     Hering, E. (1878) Zur Lehre von Lichtsinn. Vienna.

     Van Lieshout, M.N.M. and Baddeley, A.J. (1999) Indices of
     dependence between types in multivariate point patterns.
     _Scandinavian Journal of Statistics_ *26*, 511-532.

     Rockhill, R.L., Euler, T. and Masland, R.H. (2000) Spatial order
     within but not between types of retinal neurons. _Proc. Nat. Acad.
     Sci. USA_ *97*(5), 2303-2307.

     W\"assle, H., Boycott, B. B. & Illing, R.-B. (1981). Morphology
     and mosaic of on- and off-beta cells in the cat retina and some
     functional considerations. _Proc. Roy. Soc. London Ser. B_ *212*,
     177-195.

_E_x_a_m_p_l_e_s:

        data(betacells)
        plot(betacells)
        plot(betacells$window, main="beta cells")
        symbols(betacells$x, betacells$y,
            circles=sqrt(betacells.extra$area/pi),
            inches=FALSE, add=TRUE)

