Spike Train Statistics from Empirical Facts to Theory: The Case of the Retina - Modeling in Computational Biology and Biomedicine - page 258

encoding capacity of a visual system should be able to match the properties
and distribution of visual signals in the environment where the organism lives
[ 3 , 20 , 21 , 70 , 72 ]. The anatomical and physiological segregation of different aspects
of a visual scene in separate spatial, temporal and chromatic channels start at the
retina and rely on local “circuits” [ 3 ]. However, how the precise articulation of this
neural network contributes to local solutions and global perception is still largely a
mystery.
G cells, as well as most neurons in the nervous system respond to excitations,
coming from other neurons or from external stimuli, by emitting spike trains. In the
contemporary view [ 48 ], spikes are quantum or bits of information and their spatial
(neuron-dependent) and temporal (spike times) structure carry “information”: This
is called “the” “neural code”. Although this view is strongly based on a contem-
porary analogy with computers, spike trains are not computer-like binary codes.
Indeed, an experiment reproduced several times (e.g., an image presented several
times to the retina) does not reproduce exactly the same spike train, although some
regularity is observed. As a consequence, current attempts to deciphering the neural
code are based on statistical models.

8.2.4 The Ganglion Cells Diversity

The recent use of MEA in retina has lead to the description of a diversity of G
cells type and to the question about their actual early visual capacity. The vertebrate
retina has in fact 15-22 anatomically different class of G cells making it a much
more complex functional neural network than expected [ 24 , 37 , 49 ].
The three most frequent G cells in the retina can be classified from their
morphology in: parasol (primates but α or Y in cats and rabbits) corresponding to 3-
8 % of the total number of G cells; midget ( β or X in cats and rabbits) corresponding
to 45-70 %; and bi-stratified G cells. In physiological terms parasol (Y) cells can be
classified as brisk-transient, and midget (X) as brisk-sustained. They can have an
ON or OFF function.
Although only a reduced fraction of the existing G cells [ 37 , 38 , 62 ] has been
studied in detail [ 24 ], their diversity raises questions such as: How do G cells encode
an image? Which features from a natural visual scene are they coding? Are G cells
independent or collective encoders?
An interesting approach has been advanced by Balasubramanian and Sterling [ 5 ].
The authors propose that the retina organization should use simple coding principles
to carry the maximum of information at low energetic cost. However, as the authors
point out, the statistic distribution (e.g., color, contrast) for natural images is not
Gaussian. Therefore, the classical Gaussian estimator for Shannon information:

I = 1

2 log 2 (1 + SNR ) ,