Stimulus-evoked oscillatory synchronization of neural assemblies has been described in the olfactory and visual systems of several vertebrates and invertebrates. In locusts, information about odour identity is contained in the timing of action potentials in an oscillatory population response, suggesting that oscillations may reflect a common reference for messages encoded in time. Although the stimulus-evoked oscillatory phenomenon is reliable, its roles in sensation, perception, memory formation and pattern recognition remain to be demonstrated--a task requiring a behavioural paradigm. Using honeybees, we now demonstrate that odour encoding involves, as it does in locusts, the oscillatory synchronization of assemblies of projection neurons and that this synchronization is also selectively abolished by picrotoxin, an antagonist of the GABA(A) (gamma-aminobutyric acid) receptor. By using a behavioural learning paradigm, we show that picrotoxin-induced desynchronization impairs the discrimination of molecularly similar odorants, but not that of dissimilar odorants. It appears, therefore, that oscillatory synchronization of neuronal assemblies is functionally relevant, and essential for fine sensory discrimination. This suggests that oscillatory synchronization and the kind of temporal encoding it affords provide an additional dimension by which the brain could segment spatially overlapping stimulus representations.

We examined the encoding and decoding of odor identity and intensity by neurons in the antennal lobe and the mushroom body, first and second relays, respectively, of the locust olfactory system. Increased odor concentration led to changes in the firing patterns of individual antennal lobe projection neurons (PNs), similar to those caused by changes in odor identity, thus potentially confounding representations for identity and concentration. However, when these time-varying responses were examined across many PNs, concentration-specific patterns clustered by identity, resolving the apparent confound. This is because PN ensemble representations changed relatively continuously over a range of concentrations of each odorant. The PNs' targets in the mushroom body-Kenyon cells (KCs)-had sparse identity-specific responses with diverse degrees of concentration invariance. The tuning of KCs to identity and concentration and the patterning of their responses are consistent with piecewise decoding of their PN inputs over oscillation-cycle length epochs.

Key Words olfaction, olfactory bulb, antennal lobe, learning, dynamical systems, oscillations s Abstract We examine early olfactory processing in the vertebrate and insect olfactory systems, using a computational perspective. What transformations occur between the first and second olfactory processing stages? What are the causes and consequences of these transformations? To answer these questions, we focus on the functions of olfactory circuit structure and on the role of time in odor-evoked integrative processes. We argue that early olfactory relays are active and dynamical networks, whose actions change the format of odor-related information in very specific ways, so as to refine stimulus identification. Finally, we introduce a new theoretical framework ("winnerless competition") for the interpretation of these data. INTRODUCTIONThe olfactory brain converts generally complex air-or water-borne chemical mixtures into singular signatures, experienced as vivid percepts. Such transformations are achieved by way of only a few brain stations-olfactory circuits are shallower than their visual and auditory counterparts-and are strongly tied to emotions and to memories acquired through other modalities. Understanding olfactory coding is thus an ambitious enterprise whose scope goes much beyond that of this review. We focus here on the sensory transformations accomplished 0147-006X/01/0301-0263$14.00 263 Annu. Rev. Neurosci. 2001.24:263-297 264LAURENT ET AL by the first two processing stages, that is, olfactory receptors and postsynaptic structures.As with any sense, understanding olfaction first requires defining the problems it has evolved to solve (Attneave 1954, Barlow 1969: segmenting an odor into its various constituents, as a chemist might do, does not appear to be one of these functions (Lawless 1997, Cain & Potts 1996. Rather, olfaction is a synthetic sense par excellence. Olfaction enables pattern learning, storage, recognition, tracking, or localization and attaches "meaning" to these patterns. By meaning we imply the richer set of associations acquired through other senses as well as hedonic (pleasant/unpleasant) and emotional valence-both of which have no physical reality outside the brain. Each one of these tasks needs to be better defined; recognition, for example, encompasses at least categorization, identification, and separation. The abilities to categorize and to identify a priori each imply very different kinds of processing; for example, categorization disregards small differences, whereas identification emphasizes them. We show how a single circuit can in fact accomplish both, through the use of dynamics.We should also exploit our understanding of the physics of odors. In vision, much attention has been given to the statistics of natural images (Field 1987(Field , 1994Olshausen & Field 1996;Rudderman 1994). Correlations across space and time make natural images highly nonstochastic. Also, the spatial-frequency ( f ) content of a natural image, be it a face or a landscape, obeys a 1/f α distributio...