  A single neuron is categorized as"multisensory" if there is a statistically
significant difference between the response evoked by an audio-visual stimulus
combination and that evoked by the most effective of its components
individually. Crossmodal enhancement is commonly expressed as a proportion of
the strongest unisensory response. However, being responsive to multiple
sensory modalities does not guarantee that a neuron has actually engaged in
integrating its multiple sensory inputs, rather than simply responding to the
most salient stimulus. Here, we propose an alternative index measuring by how
much the crossmodal response surpasses the level obtainable by optimally
combining the unisensory responses. Optimality is defined by probability
summation combining the unisensory responses under maximal negative stochastic
dependence. The new index is analogous to measuring crossmodal enhancement by
the amount of violation of the "race model inequality", which is widely used in
reaction time studies of multisensory integration. Neurons previously labeled
as "multisensory" may lose that property since the new index tends to be
smaller than the traditional one. This is exemplified with a data set collected
from single SC neurons. The new easy-to-compute index does not require any
specific distributional assumption. It is sensitive to the variability in the
data, in contrast to the traditional index which, by definition, only depends
on the means of the uni- and crossmodal response distributions.

Neurons and Cognition