Computational sensory stimulus recognition pattern discovered in locusts
Neuroscientists have long sought to explain how the brain correctly recognizes a stimulus despite the stimulus appearing under different circumstances with widely variable external factors. For example, with regard to olfactory stimuli, humans can correctly identify the smell of coffee regardless of location, time of day, ambient conditions (such as temperature and humidity), or other potentially confounding contexts. Researchers term this ability "invariant odor recognition," and when generalized to other senses, "invariant stimulus recognition." A new study now offers insight into invariant odor recognition in locusts. Scientists at Washington University in St. Louis, Missouri, United States, found that a simple arithmetical expression of neuron activations reliably predicted when a locust recognized a particular odor. The findings could improve our general understanding of how olfaction operates in animals and improve the performance of artificial chemical sensing systems, which have a range of applications in environmental monitoring, security, medicine, and other fields. See also: Arithmetic; Chemical senses; Olfaction; Neuron
