A neuron is categorized as "multisensory" if there is a statistically significant difference between the response evoked, e.g., by a crossmodal stimulus combination and that evoked by the most effective of its components separately. Being responsive to multiple sensory modalities does not guarantee that a neuron has actually engaged in integrating its multiple sensory inputs: it could simply respond to the stimulus component eliciting the strongest response in a given trial. Crossmodal enhancement is commonly expressed as a proportion of the strongest mean unisensory response. This traditional index does not take into account any statistical dependency between the sensory channels under crossmodal stimulation. We propose an alternative index measuring by how much the multisensory response surpasses the level obtainable by optimally combining the unisensory responses, with optimality defined as probability summation under maximal negative stochastic dependence. The new index is analogous to measuring crossmodal enhancement in reaction time studies by the strength of violation of the "race model inequality', a numerical measure of multisensory integration. Since the new index tends to be smaller than the traditional one, neurons previously labeled as "multisensory' may lose that property. The index is easy to compute and it is sensitive to variability in data.