Mc. Wiener et Bj. Richmond, Using response models to estimate channel capacity for neuronal classification of stationary visual stimuli using temporal coding, J NEUROPHYS, 82(6), 1999, pp. 2861-2875
Both spike count and temporal modulation are known to carry information abo
ut which of a set of stimuli elicited a response; but how much information
temporal modulation adds remains a subject of debate. This question usually
is addressed by examining the results of a particular experiment that depe
nd on the specific stimuli used. Developing a response model allows us to a
sk how much more information is carried by the best use of response strengt
h and temporal modulation together (that is, the channel capacity using a c
ode incorporating both) than by the best use of spike count alone (the chan
nel capacity using the spike count code). This replaces dependence on a par
ticular data set with dependence on the accuracy of the model. The model is
constructed by finding statistical. rules obeyed by all the observed respo
nses and assuming that responses to stimuli not presented in our experiment
s obey the same rules. We assume that all responses within the observed dyn
amic range, even if not elicited by a stimulus in our experiment, could be
elicited by some stimulus. The model used here is based on principal compon
ent analysis and includes both response strength and a coarse (+/-10 ms) re
presentation of temporal modulation. Temporal modulation at finer time scal
es carries little information about the identity of stationary visual stimu
li (although it may carry information about stimulus motion or change), and
we present evidence that, given its variability, it should not be expected
to do so. The model makes use of a linear relation between the logarithms
of mean and variance of responses, similar to the widely seen relation betw
een mean and variance of spike count. Responses are modeled using truncated
Gaussian distributions. The amount of stimulus-related information carried
by spike count in our data are 0.35 and 0.31 bits in primary visual and in
ferior temporal cortices, respectively, rising to 0.52 and 0.37 bits for th
e two-principal-component code. The response model estimates that the chann
el capacity is 1.1 and 1.4 bits, respectively, using the spike count only,
rising to 2.0 and 2.2 bits using two principal components. Thus using this
representation of temporal modulation is nearly equivalent to adding a seco
nd independent cell using the spike count code. This is much more than esti
mated using transmitted information but far less than would be expected if
all degrees of freedom provided by the individual spike times carried indep
endent information.