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Download Olfaction in Invertebrates: Manduca. In: Squire LR (ed). Encyclopedia of Neuroscience, vol 7, pp 49-57. Oxford: Academic Press.
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This article was originally published in the Encyclopedia of Neuroscience published by Elsevier, and the attached copy is provided by Elsevier for the author's benefit and for the benefit of the author's institution, for noncommercial research and educational use including without limitation use in instruction at your institution, sending it to specific colleagues who you know, and providing a copy to your institution’s administrator. All other uses, reproduction and distribution, including without limitation commercial reprints, selling or licensing copies or access, or posting on open internet sites, your personal or institution’s website or repository, are prohibited. For exceptions, permission may be sought for such use through Elsevier's permissions site at: http://www.elsevier.com/locate/permissionusematerial Menzel R (2009) Olfaction in Invertebrates: Honeybee. In: Squire LR (ed.) Encyclopedia of Neuroscience, volume 7, pp. 43-48. Oxford: Academic Press. Author's personal copy Olfaction in Invertebrates: Honeybee 43 Olfaction in Invertebrates: Honeybee R Menzel, Freie Universität Berlin, Berlin, Germany ã 2009 Elsevier Ltd. All rights reserved. Olfactory Receptor Neurons and Glomeruli The honeybee’s strong points as a model system for olfaction research are the facts that odor processing can be studied through learning tests, with odor as an appetitive stimulus, and that odor-induced neural excitation can be monitored both at the single-neuron level and at the neural network level. A total of 60 000 olfactory receptor neurons (ORNs) on each antenna project their axons to the antennal lobes (ALs), which are subdivided into approximately 160 identified glomeruli. Most of the ORNs are in groups of 25–20 in pore plates (sensilla placodea). The number and distribution of receptor molecules are unknown, but in analogy with the findings in Drosophila and the mouse – for which a correspondence between the number of olfactory receptor genes and the number of glomeruli has been found – it is assumed that approximately 160 different ORNs may exist on the bee antennae. Extracellular recordings from ORNs in pore plates showed that the respective chemoprofiles are broad and overlapping. Furthermore, the temporal response characteristic of single ORNs can be complex, including both excitatory and inhibitory components to particular odors, indicating antagonistic processing either at the level of intracellular cellular pathways initiated by more than one receptor protein in each ORN, or by neural processing between ORNs within one pore plate. Each ORN innervates only one glomerulus, and axons from ORNs within one pore plate reach different glomeruli. The glomeruli are interconnected by about 4000 local interneurons, and about 800 projection neurons (PNs) lead from the glomeruli to higher order brain centers, such as the mushroom bodies and the lateral protocerebrum. Using calcium imaging, it is possible to measure odor-evoked glomerular activity patterns in about 40 of the 160 glomeruli. Using a computerized morphological atlas of AL glomeruli, it was possible to map the identity of glomerular units onto the physiological recordings done with calcium imaging. With this procedure, it was possible to compare the response profiles of individual glomeruli among specimens (Figure 1). Glomerular Activity Pattern and Odor Identity Two main issues were addressed with the imaging technique: first, whether odor representation is conserved within the species, and second, whether the activity pattern elicited by an odor is sufficient to predict the odor stimulus. The combinatorial pattern of glomerular activity is indeed highly conserved between individuals, indicating a tight developmental control of ORN input processing in the AL. Furthermore, statistical analysis carried out on 18 of the 160 glomeruli of the bee (11%) using a discriminant analysis showed that odor representations of each given odor form a coherent ‘cloud’ in the multidimensional space where axes are defined by each of the identified glomeruli. In 86% of these cases the odor could be identified from the glomerular activity. In a more extensive analysis the generalization profiles of 16 16 pairs of odors were determined using the odor conditioning paradigm and compared with the results from optophysiological recordings. The perceptual distances correlate well with physiological distances. It was concluded that the functional groups of the primary and secondary aliphatic alcohols, aldehydes, and ketones, and carbon-chain lengths, are inner dimensions of the honeybee olfactory space and that neural activity in the AL reflects the perceptual quality of odors. In both of these studies the perceptual similarity measure was the generalization profile, the response probability to an odor that was not learned after the animal had been trained to a particular odor. Another measure of stimulus similarity can be response time. In most examples studied so far, response time and accuracy are inversely related to each other and this appears to apply also for color discrimination of honeybees. Under given conditions of reward and motivation, the brain appears to accumulate the evidence against or in favor of a certain choice until a determined threshold is reached. Free-flying bees can be tested regarding how long they sniff an odor probe, and whether sniffing time differs for the discrimination of more similar or less similar odors. In this study, a behavioral assay was used in which bees had to discriminate odors consisting of mixtures of two components, thus odors that varied greatly between very similar and very different odors. Bees learned to discriminate all of the mixtures, including very similar ones, and even different concentrations of the same odor. Even though discriminating two very similar Encyclopedia of Neuroscience (2009), vol. 7, pp. 43-48 Author's personal copy 44 Olfaction in Invertebrates: Honeybee T1-17 T1-33 Relative response (%) T1-28 100 C10 a c C5 C6 C7 C8 C9 C10 Figure 1 Representation of aliphatic alcohols. (a) Schematic view of the honeybee antennal lobe (AL), with the three glomeruli T1-28, T1-17, and T1-33 as indicated. These three glomeruli are direct neighbors. (b) Responses of the T1-28, T1-17, and T1-33 glomeruli to a series of alcohols, varying in carbon-chain length from C5 (1-pentanol) to C10 (1-decanol). Note that T1-28 responds most strongly to short-chain alcohols, T1-17 to intermediate-chain lengths, and T1-33 to longer chain lengths. Each point represents the average of 14-21 individuals (error bars shown). Responses are shown relative to the response to hexanol in glomerulus T1-28 (asterisk). The shaded area indicates noise levels. (c) Spatial activity patterns elicited by the same six alcohols as those in (b). Red indicates strong activity and dark blue indicates low activity. Glomeruli that could not be measured are shown in gray. Note the continuous shift in activity between T1-28, T1-17, and T1-33 as the carbon-chain length increases. Also note that the response patterns are not limited to these neighboring glomeruli. Adapted from Sachse S, Rappert A, and Galizia CG (1999) The spatial representation of chemical structures in the AL of honeybees: Steps towards the olfactory code. European Journal of Neuroscience 11: 3970–3982. odors appears to be a more difficult task than discriminating two very distinct substances, it was found that the time needed to make a choice (690 ms) for or against an odor was independent of odor similarity. These data suggest that, irrespective of the nature of the olfactory code, the bee olfactory system evaluates odor quality after a constant interval. This may ensure that odors are only assessed after the olfactory network has optimized its representation, an aspect which will be addressed in the following sections. Neural Processing in the AL Glomeruli are connected by about 4000 local interneurons, many of which are immunoreactive to g-aminobutyric acid (GABA). Comparing the activity patterns of glomeruli as measured predominantly from the input and the output sites of the glomeruli indicated a sharpening of the odor-induced patterns, decorrelating the activity patterns for different odors. Frequently inhibitory responses and ‘off’ responses were found in the output neurons of the glomeruli, the PNs. Interglomerular inhibition is most likely to occur between glomeruli with similar response profiles in order to sharpen their somewhat fuzzy response profiles. Glomeruli with similar responses were often found to be direct neighbors, and such neighbors may mutually inhibit each other demonstrating lateral inhibitory mechanisms. However, interglomerular inhibition is not limited to direct neighbors, for the following reasons. First, all glomeruli are approximately equidistant from the center of the antennal lobe: the AL is spherical, with all glomeruli covering the outside of the sphere. Local interneurons innervate several glomeruli; however, their neurites do not travel from one glomerulus to a neighbor, but rather from one glomerulus to the central neuropil and from there to other glomeruli. Second, not all glomeruli with similar response profiles are direct neighbors. To investigate the underlying mechanisms, the GABA-receptor antagonist picrotoxin (PTX) was applied and two separate inhibitory networks were found: one that is GABAergic and modulates overall AL activity, another that is PTX-insensitive and glomerulus-specific. The net result of the two inhibitory networks together is a globally modulated, contrast-enhanced, and predictable representation of odors in the olfactory output neurons. Encyclopedia of Neuroscience (2009), vol. 7, pp. 43-48 Author's personal copy Olfaction in Invertebrates: Honeybee 45 Connecting the ALs with the Mushroom Bodies The second-order neuropils of olfactory processing in the insect brain are the mushroom bodies and the lateral horns (LHs) (Figure 2 (a)). Four different morphological types of PNs leave the AL, two of Mushroom body d Clawed KC l-ACT PN v Antennal a Clawed KCs (∼20 000) KC + − + PN GABA − l-ACT PNs (∼500) b c Figure 2 The olfactory pathway in the bee brain and olfactory processing in the MB. (a) Scheme of the bee brain. Lateral antennocerebral tract (l-ACT) projection neurons (PN, green) were optically recorded at their dendrites in the antennal lobe (AL) and at their presynaptic boutons in the lip of the MB calyx. Dendrites and somata of clawed Kenyon cells (clawed KC, red) were recorded in the MB calyx. Yellow arrows indicate sites of dye injection: 1 for recording PN dendrites in the AL, 2 for recording PN boutons in the MB calyces, and 3 for recording KCs in the MB calyces. Squares represent the two imaged areas, AL (for measuring PN dendrites) and MB calyx (for measuring PN boutons and/or clawed KCs). (b) The wiring diagram illustrates the divergent and convergent connectivity between PNs and clawed KCs. About 400 cholinergic l-ACT PNs synapse onto roughly 20 000 clawed KCs. The dendrites of clawed KCs are small, arranged in columns, and feature few clawlike synaptic specializations (black circles). (c) Within the lip region, PNs synapse onto GABAergic neurons which, in turn, make inhibitory synapses with PNs and KCs. Moreover, GABAergic feedback neurons receive input in the MB lobes and send their axons to calyx lip region. Since they leave out the ventral vertical lobe, they presumably do not receive input from clawed KCs. Thus, GABAergic neurons may provide local, PN-driven inhibitory microcircuits within the MB calyx lip, and a more global inhibitory feedback loop between the MB output and input region. Adapted from Ganeshina O and Menzel R (2001) GABA-immunoreactive neurons in the mushroom bodies of the honeybee: An electron microscopic study. Journal of Comparative Neurology 437: 335–349. which project to the lip region of the mushroom body (MB) and to the lateral protocerebrum, the LH. PNs in these two pathways have been analyzed more closely by intracellular recordings. PNs in the median antennocerebral tract (m-ACT) code odors by latency differences or specific inhibitory phases in combination with excitatory phases, have more specific activity profiles for different odors, and thus convey the information with odor-specific delay. The PNs of the lateral antennocerebral tract (l-ACT) code odors by spike rate differences, have broader activity profiles for different odors, and convey the information more quickly. Thus, less precise information about the olfactory stimulus appears to reach the MB and the LH via neurons of the l-ACT, and odor information subsequently becomes more specified by activities of neurons of the m-ACT. It was concluded that the separation into two neural pathways from the primary to the secondary centers of olfactory processing is not related to the distinction between different odors, but rather relates to a dual coding of the same odor by two different neuronal strategies in the time domain. Part of the olfactory information may also lie in the timing of action potentials. For example, when olfactory processing is disturbed by applying the GABA-antagonist PTX (which also affects the temporal pattern of AL neuron firing, but may also affect the spatial representation of odors), similar odors are no longer distinguished by honeybees. Many more experiments are needed to understand the relationship between temporal and spatial odor representation in both the insect and the vertebrate brain. One difficulty lies in the paucity of electrophysiologically recorded cells whose innervated glomeruli have been identified, and which can therefore be used to correlate the observed spatial and temporal activity patterns. The atlas of the AL in the bee brain is an excellent tool to establish, for each glomerulus, an olfactory response profile and temporal response patterns, both for the ORN input and the output via the PNs. Learning-Related Plasticity in the AL The plasticity of the neural network of the AL has been studied from two perspectives, that of neural correlates of sensory memory and that of associative memory after olfactory reward conditioning. Sensory memory is a short-lived persistence of a sensory stimulus in the nervous system, such as iconic memory in the visual system. The effect of an odor stimulus on the postsynaptic responses in PNs was measured within the glomeruli. A single-odor presentation changed the timing of spontaneous activity across glomeruli, enhancing the probability Encyclopedia of Neuroscience (2009), vol. 7, pp. 43-48 Author's personal copy 46 Olfaction in Invertebrates: Honeybee of coactivity of glomeruli that had been active during odor stimulation shortly before. Moreover, during the first few minutes after odor presentation, correlations between the spontaneous activity fluctuations suffice to reconstruct the stimulus. These results were interpreted to reflect modifiable fluctuations as substrates for Hebbian reverberations and sensory memory, a mechanism that might well be generalized to other neural systems. Imaging glomerular activity during appetitive learning of an odor leads to an increased response in those glomeruli that are activated by the learned odor, but not in those that respond to a specifically untrained odor. The odor-specific activity pattern was not changed qualitatively, but only quantitatively. Since glomerular activity can also be enhanced by higher concentration of the odor, it is not yet clear how the learning-induced enhancement can be separated from the odor-concentration effect. Since these experiments were carried out under conditions in which the animal was trained to an odor, they not only documented a learning-specific plasticity in the AL, but also proved that the staining with the Ca-fluorescence dye and the imaging procedure did not interfere with the neural processing in the bee brain. Recently similar associative conditioning experiments combined with Ca imaging were performed with specific staining of a subset of the postsynaptic elements in the glomeruli, the uniglomerular PNs of the lateral antennoglomerular tract. It was found that their responses to odors were remarkably resistant to plasticity following a variety of appetitive olfactory learning paradigms. There was no significant difference in the changes of odor-evoked activity between single- and multiple-trial forward or backward conditioning, differential conditioning, or unrewarded successive odor stimulation. PNs of the lateral antennoglomerular tract may thus be more involved in reliable odor coding rather than modified by learning. The role in olfactory learning and memory retrieval of PNs other than those of the imaged lateral antennoglomerular tract remains to be investigated. Odor Processing in the MB PNs convey the output of glomeruli to the MB and the LH (Figure 2 (a)). Whereas nothing is known so far about odor processing in the LH, the MBs have been studied recently with Ca-imaging techniques. The MBs are multisensory integration centers that play a dominant role in odor learning. They are densely packed with 170 000 Kenyon cells (KCs), which receive second-order sensory input in the MB calyces, with different modalities innervating spatially distinct areas. Olfactory input is confined to the lip region. KC axons target output neurons in the vertical and medial lobes of the MB. In these areas, GABAergic feedback neurons receive input and project back to the MB lip region, forming an inhibitory loop (Figure 2 (b)). Electrophysiological recordings in locusts and imaging experiments in Drosophila indicated that odor representations do indeed differ remarkably in the AL and the MB. Unlike PNs, KCs respond to odors in a sparse way. However, it is unclear whether this transformation of odor representation is a result of the KCs’ integration properties (as suggested for locust), or pre- and postsynaptic processing within the MB lip region. Since the bouton-like PN terminals in the MB lip are involved in reciprocal and feedback and forward microcircuits between GABAergic neurons and PNs, information flow from PNs onto KCs may not only be shaped by feed-forward processes, but also may include interactions between PNs and GABAergic neurons within the MB microcircuits. It was, therefore, asked whether output activity of PN boutons is modified by presynaptic processing within the MB, by comparing odor-evoked responses in PN dendrites within the AL glomeruli and their boutons at the KC synapse. To reveal transformations taking place in the postsynaptic KCs, odor-evoked responses in KCs were recorded and compared to their presynaptic input from PNs (Figure 3). At all three processing stages (AL glomeruli, presynaptic boutons of PNs in the MB lip, and postsynaptic spine activity of KCs) odors reliably evoke combinatorial activity patterns. However, in contrast to PNs, KCs code odors in a sparse way, and generate only brief responses at stimulus onset. The KCs’ high degree of odor specificity originates at two steps: first, in a presynaptic sharpening of PN synaptic output, and second, in a diminishing KC response. Interestingly, the temporal sharpening of KCs’ responses is established only at the postsynaptic side. These results also show that PN activity generated within the first 200 ms determines whether a KC will respond. Thus, the complex temporal response patterns of PNs are transformed into brief phasic responses in KCs. Thus, two types of transformations occur within the MB: diminishment of a combinatorial code, mediated by pre- and postsynaptic processing within the MB microcircuits, and temporal sharpening of postsynaptic KC responses, probably involving a broader loop of inhibitory recurrent neurons. Sniffing and Odor Discrimination As mentioned previously, bees need a constant sniffing time to discriminate similar and different odors. A task-independent choice time implies that quality is assessed after a predetermined time span, and not as soon as the neural codes for distinct odors differ to a sufficient degree in order to justify a decision. As Encyclopedia of Neuroscience (2009), vol. 7, pp. 43-48 Author's personal copy Olfaction in Invertebrates: Honeybee 47 Excitation Somata 5% Inhibition 1% a b a hx1 lim lio oc2 b c 2s 1% 1% a b mint d Max ∆F/F 0 Merged, hx1-lio e hx1 lim lio oc2 Min Merged, hx1-oc2 f Odor Figure 3 Response properties of l-ACT PNs. (a) Dendritic responses to odor stimulation in uniglomerular l-ACT PNs imaged in the frontal AL glomeruli. Traces represent the time courses of Ca2þ transients evoked by 1-hexanol in two glomeruli, (a, b). d, dorsal; m, medial; l, lateral; v, ventral. (b) Color-coded Ca2þ signals superimposed on the raw fluorescence image show that different odors activated overlapping combinatorial sets of PN dendrites. (c) Traces show representative excitatory and inhibitory dendritic odor responses in the AL (n ¼ 10 bees). Ca2þ transients typically followed complex temporal dynamics. Odor stimulus is highlighted. (d) Odor responses in axon terminals (boutons) of PNs in the MB calyx. Boutons are visible in the raw fluorescence image. Stimulation with peppermint induced Ca2þ increase in many of the boutons (single measurement). (e) Different odors evoked excitatory and inhibitory responses in distinct boutons. The merged images of excitatory 1-hexanol (hx1, red) and linalool (lio, green) responses visualize distinct sets of activated boutons. In contrast, 1-hexanol (red) and 2-octanol (oc2, green) activated overlapping sets of boutons. All traces represent single measurements; images represent the averages of three stimulations. (f) Odor-evoked Ca2þ transients in PN boutons (n ¼ 8 bees) show complex dynamics, as is the case in the dendrites. In the entire figure, traces ¼ DF/F; scale bars ¼ 50 mm. Adapted from Szyszka P, Ditzen M, Galkin A, et al. (2005) Sparsening and temporal sharpening of olfactory representations in the honeybee mushroom bodies. Journal of Neurophysiology. 94: 3303–3313. Encyclopedia of Neuroscience (2009), vol. 7, pp. 43-48 Author's personal copy 48 Olfaction in Invertebrates: Honeybee pointed out by Ditzen et al. in 2003, this finding may be important in the context of olfactory coding, since it implies that information about the odor is only available at a predefined time point after stimulus onset. In the case of a ‘combinatorial code,’ one would have to postulate that the across-glomeruli activity patterns are only read out after a given delay. An internal ‘clock’ may provide such a signal in the form of odor-evoked oscillations. If these oscillations have a frequency of about 30 Hz in the bee brain – as in the locust brain – a time span of 690 ms gives a high-end estimate of 21 cycles, from which the time not involved in odor detection, such as further processing in the brain, and motor commands, will have to be subtracted. Both the ‘synchrony code’ (as suggested for the locust) and a combinatorial code that develops its optimal spatial coding over time (as shown for the honeybee AL) rely on the sequence of activity patterns. The sequences of two very different odors may differ earlier than the sequences of two very similar odors. Under these conditions, one would expect that the brain would continuously monitor the evidence in favor of each alternative, and make a choice as soon as the evidence suffices for one, as has been shown in other experimental paradigms. However, the results reported in the foregoing text suggest that odor evaluation is not incremental, but rather occurs in single information units, consisting of the entire sequence of neural activity following an odor sample. It has been suggested by Ditzen et al. that an interim storage of the sequence would be needed in order to explain the time constancy. Obviously, in the odor coding models provided so far, there is a missing component: a mechanism that would allow for a constant readout time of olfactory quality. This constant time requirement for odor choice may guarantee that odor quality is assessed when its coding is optimal. See also: Olfaction in Invertebrates: Manduca; Olfaction in Invertebrates: Drosophila; Olfactory Receptors; Olfactory Cortex Physiology; Olfactory System Theory; Olfactory System: Circuit Dynamics and Neural Coding in the Locust. Further Reading Chittka L, Dyer AG, Bock F, et al. (2003) Psychophysics: Bees trade off foraging speed for accuracy. Nature 424: 388. Ditzen M, Evers JF, and Galizia CG (2003) Odor similarity does not influence the time needed for odor processing. Chemical Senses 28: 781–789. Faber T, Joerges J, and Menzel R (1999) Associative learning modifies neural representations of odors in the insect brain. Nature Neuroscience 2: 74–78. Galán RF, Weidert M, Menzel R, et al. (2006) Sensory memory for odors is encoded in spontaneous correlated activity between olfactory glomeruli. Neural Computation 18: 10–25. Galizia CG, Küttner A, Joerges J, et al. (2000) Odour representation in honeybee olfactory glomeruli shows slow temporal dynamics: An optical recording study using a voltage-sensitive dye. Journal of Insect Physiology 46: 877–886. Galizia CG and Menzel R (2000) Odour perception in honeybees: Coding information in glomerular patterns. Current Opinion in Neurobiology 10: 504–510. Galizia CG, Sachse S, Rappert A, et al. (1999) The glomerular code for odor representation is species specific in the honeybee Apis mellifera. Nature Neuroscience 2: 473–478. Ganeshina O and Menzel R (2001) GABA-immunoreactive neurons in the mushroom bodies of the honeybee: An electron microscopic study. Journal of Comparative Neurology 437: 335–349. Getz WM and Akers RP (1994) Honeybee olfactory sensilla behave as integrated processing units. Behavioral and Neural Biology 61: 191–195. Guerrieri F, Schubert M, Sandoz JC, et al. (2005) Perceptual and neural olfactory similarity in honeybees. PLoS Biology 3: e60. Joerges J, Küttner A, Galizia CG, et al. (1997) Representation of odours and odour mixtures visualized in the honeybee brain. Nature 387: 285–288. Laurent GJ (2003) Olfactory network dynamics and the coding of multidimensional signals (review). Nature Reviews Neuroscience 3: 884–895. Müller D, Abel R, Brandt R, et al. (2002) Differential parallel processing of olfactory information in the honeybee, Apis mellifera L. Journal of Comparative Physiology A 188: 359–370. Peele P, Ditzen M, Menzel R, et al. (2006) Appetitive odor learning does not change olfactory coding in a subpopulation of honeybee antennal lobe neurons. Journal of Comparative Physiology A 192: 1083–1103. Sachse S and Galizia CG (2002) The role of inhibition for temporal and spatial odor representation in olfactory output neurons: A calcium imaging study. Journal of Neurophysiology 87: 1106–1117. Sachse S and Galizia CG (2003) The coding of odour-intensity in the honeybee antennal lobe: Local computation optimizes odour representation. European Journal Neuroscience. 18: 2119–2132. Stopfer M and Laurent GJ (1999) Short-term memory in olfactory network dynamics. Nature. 402: 664–668. Stopfer M, Bhagavan S, Smith BH, et al. (1997) Impaired odour discrimination on desynchronization of odour-encoding neural assemblies. Nature. 390: 70–74. Stopfer M, Jayaraman V, and Laurent G (2003) Intensity versus identity coding in an olfactory system. Neuron. 39: 991–1004. Szyszka P, Ditzen M, Galkin A, et al. (2005) Sparsening and temporal sharpening of olfactory representations in the honeybee mushroom bodies. Journal of Neurophysiology. 94: 3303–3313. Encyclopedia of Neuroscience (2009), vol. 7, pp. 43-48