Sensory stimuli in natural environments are dynamic and complex. The neural circuits of sensory systems in the brain are therefore adapted to extract meaningful information from this dynamic input. An attractive model system for understanding how such sensory input is processed in neural circuits is the mammalian olfactory bulb (OB). The OB has a convenient dorsal anatomical location for e.g. probe implantation, viral delivery and a well-defined circuit architecture. Furthermore, olfaction in rodent models is extremely behaviourally salient and OB circuit function can therefore be efficiently investigated in the context of behavioural response. Historically, investigation of OB function has focused on encoding of odour quality, utilising static, square pulse stimuli to explore this problem. This is in stark contrast to odour transmission in natural environments, which is governed by the chaotic structure of air turbulence, creating odour plumes. There are a number of lines of evidence suggesting that temporal information in odour plumes β the fluctuations in odour concentration within this structure β can be behaviourally relevant for olfactory based navigation and odour scene segmentation. I here posit that temporal correlations in concentration for mixtures of odours transmitted in plumes are a potential mechanism by which animals identify odour objects: mixtures of odours emanating from a common source. Using neuronal imaging, high-throughput behavioural methods, high-speed odour delivery and physical recording of odour plume dynamics, I show that temporal correlations exist between pairs of odours emanating from the same source; that mice can perceive this correlation structure and that temporal correlation is represented in the output cells of the olfactory bulb. These results indicate that mammalian olfaction operates at a higher temporal bandwidth than previously thought, and that detection of temporal features in odour signals may represent a potential mechanism for olfactory scene segmenetation
