Neurons in the insect antennal lobe represent odors as spatiotemporal patterns of activity that unfold over multiple time scales. As these patterns unspool they decrease the overlap between odor representations and thereby increase the ability of the olfactory system to discriminate odors. Using a realistic model of the insect antennal lobe we examined two competing components of this process –lateral excitation from local excitatory interneurons, and slow inhibition from local inhibitory interneurons. We found that lateral excitation amplified differences between representations of similar odors by recruiting projection neurons that did not receive direct input from olfactory receptors. However, this increased sensitivity also amplified noisy variations in input and compromised the ability of the system to respond reliably to multiple presentations of the same odor. Slow inhibition curtailed the spread of projection neuron activity and increased response reliability. These competing influences must be finely balanced in order to decorrelate odor representations.
The antennal lobe of insects and the olfactory bulb of vertebrates represent the first centers of the olfactory system where information about odor properties can be reorganized and optimized for further processing. Complex excitatory and inhibitory synaptic interactions within the antennal lobe and the olfactory bulb alter the responses of the principal neurons throughout the duration of the odor stimulation. These dynamic changes progressively increase the difference between firing patterns evoked by structurally similar odors, potentially helping the animal distinguish one odor from another. However, this process, called odor decorrelation, appears to oppose another important goal of olfactory processing, to minimize the inevitable noisy variations in representations of the same odor encountered under different environmental conditions; such variations could potentially lead to misclassification. It remains an interesting mystery how olfactory circuitry can solve these two seemingly contradictory goals as they process olfactory stimuli: first, separating different but chemically similar odors (sensitivity, capacity); and second, identifying representations of the same odor in a noisy environment (reliability). Our results suggest a balance between inhibitory and excitatory connections mediated by local antennal lobe interneurons enhances the decorrelation of similar odors while keeping the representation robust in the presence of noise.
Neural circuits exploit numerous strategies for encoding information. Although the functional significance of individual coding mechanisms has been investigated, ways in which multiple mechanisms interact and integrate are not well understood. The locust olfactory system, in which dense, transiently synchronized spike trains across ensembles of antenna lobe (AL) neurons are transformed into a sparse representation in the mushroom body (MB; a region associated with memory), provides a well-studied preparation for investigating the interaction of multiple coding mechanisms. Recordings made in vivo from the insect MB demonstrated highly specific responses to odors in Kenyon cells (KCs). Typically, only a few KCs from the recorded population of neurons responded reliably when a specific odor was presented. Different odors induced responses in different KCs. Here, we explored with a biologically plausible model the possibility that a form of plasticity may control and tune synaptic weights of inputs to the mushroom body to ensure the specificity of KCs' responses to familiar or meaningful odors. We found that plasticity at the synapses between the AL and the MB efficiently regulated the delicate tuning necessary to selectively filter the intense AL oscillatory output and condense it to a sparse representation in the MB. Activity-dependent plasticity drove the observed specificity, reliability, and expected persistence of odor representations, suggesting a role for plasticity in information processing and making a testable prediction about synaptic plasticity at AL-MB synapses.
The way in which the brain encodes, processes, transforms, and stores sensory information is a fundamental question in systems neuroscience. One challenge is to understand how neural oscillations, synchrony, population coding, and sparseness interact in the process of transforming and transferring information. Another question is how synaptic plasticity, the ability of synapses to change their strength, interacts efficiently with these different coding strategies to support learning and information storage. We approached these questions, rarely accessible to direct experimental investigation, in the olfactory system of the locust, a well-studied example. Here, the neurons in the antennal lobe carry neural representations of odor identity using dense, spatially distributed, oscillatory synchronized patterns of neural activity. Odor information cannot be interpreted by considering their activity independently. On the contrary, in the mushroom body—the next processing region, involved in the storage and retrieval of olfactory memories and analogous to the olfactory cortex—odor representations are sparse and carried by more selective neurons. Sparse information coding by ensembles of neurons provides several important advantages including high memory capacity, low overlap between stored objects, and easy information retrieval. How is this sparseness achieved? Here, with a rigorous computational model of the olfactory system, we demonstrate that plasticity at the input afferents to the mushroom body can efficiently mediate the delicate tuning necessary to selectively filter intense sensory input, condensing it to the sparse responses observed in the mushroom body. Our results suggest a general mechanism for plasticity-enabled sparse representations in other sensory systems, such as the visual system. Overall, we illustrate a potential central role for plasticity in the transfer of information across different coding strategies within neural systems.
The discrimination of complex sensory stimuli in a noisy environment is an immense computational task. Sensory systems often encode stimulus features in a spatiotemporal fashion through the complex firing patterns of individual neurons. To identify these temporal features, we have developed an analysis that allows the comparison of statistically significant features of spike trains localized over multiple scales of time-frequency resolution. Our approach provides an original way to utilize the discrete wavelet transform to process instantaneous rate functions derived from spike trains, and select relevant wavelet coefficients through statistical analysis. Our method uncovered localized features within olfactory projection neuron (PN) responses in the moth antennal lobe coding for the presence of an odor mixture and the concentration of single component odorants, but not for compound identities. We found that odor mixtures evoked earlier responses in biphasic response type PNs compared to single components, which led to differences in the instantaneous firing rate functions with their signal power spread across multiple frequency bands (ranging from 0 to 45.71 Hz) during a time window immediately preceding behavioral response latencies observed in insects. Odor concentrations were coded in excited response type PNs both in low frequency band differences (2.86 to 5.71 Hz) during the stimulus and in the odor trace after stimulus offset in low (0 to 2.86 Hz) and high (22.86 to 45.71 Hz) frequency bands. These high frequency differences in both types of PNs could have particular relevance for recruiting cellular activity in higher brain centers such as mushroom body Kenyon cells. In contrast, neurons in the specialized pheromone-responsive area of the moth antennal lobe exhibited few stimulus-dependent differences in temporal response features. These results provide interesting insights on early insect olfactory processing and introduce a novel comparative approach for spike train analysis applicable to a variety of neuronal data sets.
For animals to execute odor-driven behaviors, the olfactory system must process complex odor signals and maintain stimulus identity in the face of constantly changing odor intensities [1–5]. Surprisingly, how the olfactory system maintains identity of complex odors is unclear [6–10]. We took advantage of the plant-pollinator relationship between the Sacred Datura (Datura wrightii) and the moth Manduca sexta [11, 12] to determine how olfactory networks in this insect’s brain represent odor mixtures. We combined gas chromatography and neural-ensemble recording in the moth’s antennal lobe to examine population codes for the floral mixture and its fractionated components. Although the floral scent of D. wrightii comprises at least 60 compounds, only nine of those elicited robust neural responses. Behavioral experiments confirmed that these nine odorants mediate flower-foraging behaviors, but only as a mixture. Moreover, the mixture evoked equivalent foraging behaviors over a 1000-fold range in dilution, suggesting a singular percept across this concentration range. Furthermore, neural-ensemble recordings in the moth’s antennal lobe revealed that reliable encoding of the floral mixture is organized through synchronized activity distributed across a population of glomerular coding units, and this timing mechanism may bind the features of a complex stimulus into a coherent odor percept.
The honeybee Apis mellifera has a remarkable ability to detect and locate food sources during foraging, and to associate odor cues with food rewards. In the honeybee’s olfactory system, sensory input is first processed in the antennal lobe (AL) network. Uniglomerular projection neurons (PNs) convey the sensory code from the AL to higher brain regions via two parallel but anatomically distinct pathways, the lateral and the medial antenno-cerebral tract (l- and m-ACT). Neurons innervating either tract show characteristic differences in odor selectivity, concentration dependence, and representation of mixtures. It is still unknown how this differential stimulus representation is achieved within the AL network. In this contribution, we use a computational network model to demonstrate that the experimentally observed features of odor coding in PNs can be reproduced by varying lateral inhibition and gain control in an otherwise unchanged AL network. We show that odor coding in the l-ACT supports detection and accurate identification of weak odor traces at the expense of concentration sensitivity, while odor coding in the m-ACT provides the basis for the computation and following of concentration gradients but provides weaker discrimination power. Both coding strategies are mutually exclusive, which creates a tradeoff between detection accuracy and sensitivity. The development of two parallel systems may thus reflect an evolutionary solution to this problem that enables honeybees to achieve both tasks during bee foraging in their natural environment, and which could inspire the development of artificial chemosensory devices for odor-guided navigation in robots.
dual pathway odor coding; mixture coding; antennal lobe; computational model; honeybee foraging
Odors are represented by specific spatio-temporal activity patterns in the olfactory bulb of vertebrates and its insect analogue, the antennal lobe. In honeybees inhibitory circuits in the AL are involved in the processing of odors to shape afferent odor responses. GABA is known as an inhibitory transmitter in the antennal lobe, but not all interneurons are GABAergic. Therefore we sought to analyze the functional role of the inhibitory transmitter histamine for the processing of odors in the honeybee AL.
We optically recorded the representation of odors before, during and after histamine application at the input level (estimated from a compound signal), and at the output level (by selectively measuring the projection neurons). For both, histamine led to a strong and reversible reduction of odor-evoked responses.
We propose that histamine, in addition to GABA, acts as an inhibitory transmitter in the honeybee AL and is therefore likely to play a role in odor processing.
Animals typically perceive natural odor cues in their olfactory environment as a complex mixture of chemically diverse components. In insects, the initial representation of an odor mixture occurs in the first olfactory center of the brain, the antennal lobe (AL). The contribution of single neurons to the processing of complex mixtures in insects, and in particular moths, is still largely unknown. Using a novel multicomponent stimulus system to equilibrate component and mixture concentrations according to vapor pressure, we performed intracellular recordings of projection and interneurons in an attempt to quantitatively characterize mixture representation and integration properties of single AL neurons in the moth. We found that the fine spatiotemporal representation of 2–7 component mixtures among single neurons in the AL revealed a highly combinatorial, non-linear process for coding host mixtures presumably shaped by the AL network: 82% of mixture responding projection neurons and local interneurons showed non-linear spike frequencies in response to a defined host odor mixture, exhibiting an array of interactions including suppression, hypoadditivity, and synergism. Our results indicate that odor mixtures are represented by each cell as a unique combinatorial representation, and there is no general rule by which the network computes the mixture in comparison to single components. On the single neuron level, we show that those differences manifest in a variety of parameters, including the spatial location, frequency, latency, and temporal pattern of the response kinetics.
odor processing; network; intracellular; electrophysiological recording; single cell
Odors are initially represented in the olfactory bulb (OB) by patterns of sensory input across the array of glomeruli. Although activated glomeruli are often widely distributed, glomeruli responding to stimuli sharing molecular features tend to be loosely clustered and thus establish a fractured chemotopic map. Neuronal circuits in the OB transform glomerular patterns of sensory input into spatiotemporal patterns of output activity and thereby extract information about a stimulus. It is, however, unknown whether the chemotopic spatial organization of glomerular inputs is maintained during these computations. To explore this issue, we measured spatiotemporal patterns of odor-evoked activity across thousands of individual neurons in the zebrafish OB by temporally deconvolved two-photon Ca2+ imaging. Mitral cells and interneurons were distinguished by transgenic markers and exhibited different response selectivities. Shortly after response onset, activity patterns exhibited foci of activity associated with certain chemical features throughout all layers. During the subsequent few hundred milliseconds, however, MC activity was locally sparsened within the initial foci in an odor-specific manner. As a consequence, chemotopic maps disappeared and activity patterns became more informative about precise odor identity. Hence, chemotopic maps of glomerular input activity are initially transmitted to OB outputs, but not maintained during pattern processing. Nevertheless, transient chemotopic maps may support neuronal computations by establishing important synaptic interactions within the circuit. These results provide insights into the functional topology of neural activity patterns and its potential role in circuit function.
Many sensory brain areas contain topographic maps where the physical location of neuronal activity contains information about a stimulus feature. In the first central processing center of the olfactory pathway, the olfactory bulb, chemically distinct odors often elicit spatially segregated input activity so that general chemical features are initially represented in a topographic fashion. It is, however, unclear whether this “chemotopic” organization of odor representations is maintained at subsequent stages of odor processing. To address this question, we visualized activity patterns across thousands of individual neurons in the intact olfactory bulb of zebrafish over time using two-photon calcium imaging. Our results demonstrate that odor-evoked activity across the output neurons of the olfactory bulb is chemotopically organized shortly after stimulus onset but becomes more widely distributed during the subsequent few hundred milliseconds of the response. This reorganization of olfactory bulb output activity is most likely mediated by inhibitory feedback and reduces the redundancy in activity patterns evoked by related stimuli. These results indicate that topographically organized activity maps in the olfactory bulb are not maintained during information processing, but contribute to the function of local circuits.
Two-photon calcium imaging in the zebrafish olfactory bulb reveals that mitral cells show more selective responses to odors than interneurons, and odor-evoked firing patterns of populations of mitral cells evolve over hundreds of milliseconds to become more distinct for different odors, thus providing more information about odor identity.
In animals, odor qualities are represented as both spatial activity patterns of glomeruli and temporal patterns of synchronized oscillatory signals in the primary olfactory centers. By optical imaging of a voltage-sensitive dye (VSD) and intracellular recording from secondary olfactory interneurons, we examined possible neural correlates of the spatial and temporal odor representations in the primary olfactory center, the antennal lobe (AL), of the cockroach Periplaneta americana. Voltage-sensitive dye imaging revealed that all used odorants induced odor-specific temporal patterns of depolarizing potentials in specific combinations of anterior glomeruli of the AL. The depolarizing potentials evoked by different odorants were temporally synchronized across glomeruli and were termed “synchronized potentials.” These observations suggest that odor qualities are represented by spatio-temporal activity patterns of the synchronized potentials across glomeruli. We also performed intracellular recordings and stainings from secondary olfactory interneurons, namely projection neurons and local interneurons. We analyzed the temporal structures of enanthic acid-induced action potentials of secondary olfactory interneurons using simultaneous paired intracellular recording from two given neurons. Our results indicated that the multiple local interneurons synchronously fired in response to the olfactory stimulus. In addition, all stained enanthic acid-responsive projection neurons exhibited dendritic arborizations within the glomeruli where the synchronized potentials were evoked. Since multiple local interneurons are known to synapse to a projection neuron in each glomerulus in the cockroach AL, converging inputs from local interneurons to the projection neurons appear to contribute the odorant specific spatio-temporal activity patterns of the synchronized potentials.
olfaction; synchronized potentials; optical imaging; voltage-sensitive dye; intracellular recording; local interneurons; projection neurons; insects
To gain insight into which parameters of neural activity are important in shaping the perception of odors, we combined a behavioral measure of odor perception with optical imaging of odor representations at the level of receptor neuron input to the rat olfactory bulb. Instead of the typical test of an animal's ability to discriminate two familiar odorants by exhibiting an operant response, we used a spontaneously expressed response to a novel odorant—exploratory sniffing—as a measure of odor perception. This assay allowed us to measure the speed with which rats perform spontaneous odor discriminations. With this paradigm, rats discriminated and began responding to a novel odorant in as little as 140 ms. This time is comparable to that measured in earlier studies using operant behavioral readouts after extensive training. In a subset of these trials, we simultaneously imaged receptor neuron input to the dorsal olfactory bulb with near-millisecond temporal resolution as the animal sampled and then responded to the novel odorant. The imaging data revealed that the bulk of the discrimination time can be attributed to the peripheral events underlying odorant detection: receptor input arrives at the olfactory bulb 100–150 ms after inhalation begins, leaving only 50–100 ms for central processing and response initiation. In most trials, odor discrimination had occurred even before the initial barrage of receptor neuron firing had ceased and before spatial maps of activity across glomeruli had fully developed. These results suggest a coding strategy in which the earliest-activated glomeruli play a major role in the initial perception of odor quality, and place constraints on coding and processing schemes based on simple changes in spike rate.
Olfactory stimuli elicit temporally complex patterns of activity across groups of receptor neurons as well as across central neurons. It remains unclear which parameters among these complex activity patterns are important in shaping odor perception. To address this issue, we imaged from the olfactory bulb of awake rats as they detected and responded to odorants. We used a spontaneously expressed response to novel odorants—exploratory sniffing—as a behavioral measure of odor perception. This assay allowed us to measure the speed with which rats perform simple odor discriminations by monitoring changes in respiration. Rats discriminated a novel odorant from a learned one in as little as 140 ms. Simultaneously imaging the sensory input to the olfactory bulb carried by receptor neurons revealed that the bulk of the response time is due to the peripheral events underlying odorant detection (inhalation and receptor neuron activation), leaving only 50–100 ms for central processing and response initiation. In most trials, responses to a novel odorant began before the initial barrage of input had ceased and before spatial patterns of input to the bulb had fully developed. These results suggest a coding strategy in which the earliest inputs play a major role in the initial perception of odor quality and place constraints on coding schemes based on simple changes in firing rate.
Imaging the olfactory bulb of awake rats reveals that odor discrimination occurs about 100 ms after sensory input reaches the brain, sharply limiting the role that spike rate and temporal integration can play in coding odor identity.
The non-topographical representation of odor quality space differentiates early olfactory representations from those in other sensory systems. Decorrelation among olfactory representations with respect to physical odorant similarities has been proposed to rely upon local feed-forward inhibitory circuits in the glomerular layer that decorrelate odor representations with respect to the intrinsically high-dimensional space of ligand–receptor potency relationships. A second stage of decorrelation is likely to be mediated by the circuitry of the olfactory bulb external plexiform layer. Computations in this layer, or in the analogous interneuronal network of the insect antennal lobe, are dependent on fast network oscillations that regulate the timing of mitral cell and projection neuron (MC/PN) action potentials; this suggests a largely spike timing-dependent metric for representing odor information, here proposed to be a precedence code. We first illustrate how the rate coding metric of the glomerular layer can be transformed into a spike precedence code in MC/PNs. We then show how this mechanism of representation, combined with spike timing-dependent plasticity at MC/PN output synapses, can progressively decorrelate high-dimensional, non-topographical odor representations in third-layer olfactory neurons. Reducing MC/PN oscillations abolishes the spike precedence code and blocks this progressive decorrelation, demonstrating the learning network's selectivity for these sparsely synchronized MC/PN spikes even in the presence of temporally disorganized background activity. Finally, we apply this model to odor representations derived from calcium imaging in the honeybee antennal lobe, and show how odor learning progressively decorrelates odor representations, and how the abolition of PN oscillations impairs odor discrimination.
olfaction; gamma oscillations; sparse synchronization; STDP; olfactory bulb; antennal lobe; odor learning; conditioning
In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and generation of testable hypotheses of the functional mechanisms underlying odor representation in the olfactory bulb circuit. Specifically, we demonstrate that lateral inhibition emerges within the olfactory bulb network through recurrent dendrodendritic synapses when constrained by a range of balanced excitatory and inhibitory conductances. We find that the spatio-temporal dynamics of lateral inhibition plays a critical role in building the glomerular-related cell clusters observed in experiments, through the modulation of synaptic weights during odor training. Lateral inhibition also mediates the development of sparse and synchronized spiking patterns of mitral cells related to odor inputs within the network, with the frequency of these synchronized spiking patterns also modulated by the sniff cycle.
In the paper we address the role of lateral inhibition in a neuronal network. It is an essential and widespread mechanism of neural processing that has been demonstrated in many brain systems. A key finding that would reveal how and to what extent it can modulate input signals and give rise to some form of perception would involve network-wide recording of individual cells during in vivo behavioral experiments. While this problem has been intensely investigated, it is beyond current methods to record from a reasonable set of cells experimentally to decipher the emergent properties and behavior of the network, leaving the underlying computational and functional roles of lateral inhibition still poorly understood. We addressed this problem using a large-scale model of the olfactory bulb. The model demonstrates how lateral inhibition modulates the evolving dynamics of the olfactory bulb network, generating mitral and granule cell responses that account for critical experimental findings. It also suggests how odor identity can be represented by a combination of temporal and spatial patterns of mitral cell activity, with both feedforward excitation and lateral inhibition via dendrodendritic synapses as the underlying mechanisms facilitating network self-organization and the emergence of synchronized oscillations.
Odors evoke complex spatiotemporal responses in the insect antennal lobe (AL) and mammalian olfactory bulb. However, the behavioral relevance of spatiotemporal coding remains unclear. In the present work we combined behavioral analyses with calcium imaging of odor induced activity in the honey bee AL to evaluate the relevance of this temporal dimension in the olfactory code. We used a new way for evaluation of odor similarity of binary mixtures in behavioral studies, which involved testing if a match of odor sampling time is necessary between training and testing conditions for odor recognition during associative learning. Using graded changes in the similarity of the mixture ratios, we found high correlations between the behavioral generalization across those mixtures and a gradient of activation in AL output. Furthermore, short odor stimuli of 500 ms or less affected how well odors were matched with a memory template, and this time corresponded to a shift from a sampling-time-dependent to a sampling-time-independent memory. Accordingly, 375 ms corresponded to the time required for spatiotemporal AL activity patterns to reach maximal separation according to imaging studies. Finally, we compared spatiotemporal representations of binary mixtures in trained and untrained animals. AL activity was modified by conditioning to improve separation of odor representations. These data suggest that one role of reinforcement is to “tune” the AL such that relevant odors become more discriminable.
olfaction; synchrony; transients; spatiotemporal coding; plasticity; calcium imaging; discrimination
A unifying feature of mammalian and insect olfactory systems is that olfactory sensory neurons (OSNs) expressing the same unique odorant receptor gene converge onto the same glomeruli in the brain (1–7). Most odorants activate a combination of receptors and thus distinct patterns of glomeruli, forming a proposed combinatorial spatial code that could support discrimination between a large number of odorants (8–11). OSNs also exhibit odor-evoked responses with complex temporal dynamics (11), but the contribution of this activity to behavioral odor discrimination has received little attention (12). Here we investigated the importance of spatial encoding in the relatively simple Drosophila antennal lobe. We show that Drosophila can learn to discriminate between two odorants with one functional class of Or83b-expressing OSNs. Furthermore, these flies encode one odorant from a mixture, and cross-adapt to odorants that activate the relevant OSN class, demonstrating that they discriminate odorants using the same OSNs. Lastly, flies with a single class of Or83b-expressing OSNs recognize a specific odorant across a range of concentration indicating that they encode odorant identity. Therefore flies can distinguish odorants without discrete spatial codes in the antennal lobe, implying an important role for odorant-evoked temporal dynamics in behavioral odorant discrimination.
Neural representations of odors are subject to computations that involve sequentially convergent and divergent anatomical connections across different areas of the brains in both mammals and insects. Furthermore, in both mammals and insects higher order brain areas are connected via feedback connections. In order to understand the transformations and interactions that this connectivity make possible, an ideal experiment would compare neural responses across different, sequential processing levels. Here we present results of recordings from a first order olfactory neuropile – the antennal lobe (AL) – and a higher order multimodal integration and learning center – the mushroom body (MB) – in the honey bee brain. We recorded projection neurons (PN) of the AL and extrinsic neurons (EN) of the MB, which provide the outputs from the two neuropils. Recordings at each level were made in different animals in some experiments and simultaneously in the same animal in others. We presented two odors and their mixture to compare odor response dynamics as well as classification speed and accuracy at each neural processing level. Surprisingly, the EN ensemble significantly starts separating odor stimuli rapidly and before the PN ensemble has reached significant separation. Furthermore the EN ensemble at the MB output reaches a maximum separation of odors between 84–120 ms after odor onset, which is 26 to 133 ms faster than the maximum separation at the AL output ensemble two synapses earlier in processing. It is likely that a subset of very fast PNs, which respond before the ENs, may initiate the rapid EN ensemble response. We suggest therefore that the timing of the EN ensemble activity would allow retroactive integration of its signal into the ongoing computation of the AL via centrifugal feedback.
Successful cooperation depends on reliable identification of friends and foes. Social insects discriminate colony members (nestmates/friends) from foreign workers (non-nestmates/foes) by colony-specific, multi-component colony odors. Traditionally, complex processing in the brain has been regarded as crucial for colony recognition. Odor information is represented as spatial patterns of activity and processed in the primary olfactory neuropile, the antennal lobe (AL) of insects, which is analogous to the vertebrate olfactory bulb. Correlative evidence indicates that the spatial activity patterns reflect odor-quality, i.e., how an odor is perceived. For colony odors, alternatively, a sensory filter in the peripheral nervous system was suggested, causing specific anosmia to nestmate colony odors. Here, we investigate neuronal correlates of colony odors in the brain of a social insect to directly test whether they are anosmic to nestmate colony odors and whether spatial activity patterns in the AL can predict how odor qualities like “friend” and “foe” are attributed to colony odors.
Using ant dummies that mimic natural conditions, we presented colony odors and investigated their neuronal representation in the ant Camponotus floridanus. Nestmate and non-nestmate colony odors elicited neuronal activity: In the periphery, we recorded sensory responses of olfactory receptor neurons (electroantennography), and in the brain, we measured colony odor specific spatial activity patterns in the AL (calcium imaging). Surprisingly, upon repeated stimulation with the same colony odor, spatial activity patterns were variable, and as variable as activity patterns elicited by different colony odors.
Ants are not anosmic to nestmate colony odors. However, spatial activity patterns in the AL alone do not provide sufficient information for colony odor discrimination and this finding challenges the current notion of how odor quality is coded. Our result illustrates the enormous challenge for the nervous system to classify multi-component odors and indicates that other neuronal parameters, e.g., precise timing of neuronal activity, are likely necessary for attribution of odor quality to multi-component odors.
Experience related plasticity is an essential component of networks involved in early olfactory processing. However, the mechanisms and functions of plasticity in these neural networks are not well understood. We studied nonassociative plasticity by evaluating responses to two pure odors (A and X) and their binary mixture using calcium imaging of odor elicited activity in output neurons of the honey bee antennal lobe. Unreinforced exposure to A or X produced no change in the neural response elicited by the pure odors. However, exposure to one odor (e.g. A) caused the response to the mixture to become more similar to the other component (X). We also show in behavioral analyses that unreinforced exposure to A caused the mixture to become perceptually more similar to X. These results suggest that nonassociative plasticity modifies neural networks in such a way that it affects local competitive interactions among mixture components. We used a computational model to evaluate the most likely targets for modification. Hebbian modification of synapses from inhibitory local interneurons to projection neurons most reliably produces the observed shift in response to the mixture. These results are consistent with a model in which the antennal lobe acts to filter olfactory information according to its relevance for performing a particular task.
Olfaction; learning; antennal lobe; plasticity; Apis mellifera
We identified the neurons comprising the Drosophila mushroom body (MB), an associative center in invertebrate brains, and provide a comprehensive map describing their potential connections. Each of the 21 MB output neuron (MBON) types elaborates segregated dendritic arbors along the parallel axons of ∼2000 Kenyon cells, forming 15 compartments that collectively tile the MB lobes. MBON axons project to five discrete neuropils outside of the MB and three MBON types form a feedforward network in the lobes. Each of the 20 dopaminergic neuron (DAN) types projects axons to one, or at most two, of the MBON compartments. Convergence of DAN axons on compartmentalized Kenyon cell–MBON synapses creates a highly ordered unit that can support learning to impose valence on sensory representations. The elucidation of the complement of neurons of the MB provides a comprehensive anatomical substrate from which one can infer a functional logic of associative olfactory learning and memory.
One of the key goals of neuroscience is to understand how specific circuits of brain cells enable animals to respond optimally to the constantly changing world around them. Such processes are more easily studied in simpler brains, and the fruit fly—with its small size, short life cycle, and well-developed genetic toolkit—is widely used to study the genes and circuits that underlie learning and behavior.
Fruit flies can learn to approach odors that have previously been paired with food, and also to avoid any odors that have been paired with an electric shock, and a part of the brain called the mushroom body has a central role in this process. When odorant molecules bind to receptors on the fly's antennae, they activate neurons in the antennal lobe of the brain, which in turn activate cells called Kenyon cells within the mushroom body. The Kenyon cells then activate output neurons that convey signals to other parts of the brain.
It is known that relatively few Kenyon cells are activated by any given odor. Moreover, it seems that a given odor activates different sets of Kenyon cells in different flies. Because the association between an odor and the Kenyon cells it activates is unique to each fly, each fly needs to learn through its own experiences what a particular pattern of Kenyon cell activation means.
Aso et al. have now applied sophisticated molecular genetic and anatomical techniques to thousands of different transgenic flies to identify the neurons of the mushroom body. The resulting map reveals that the mushroom body contains roughly 2200 neurons, including seven types of Kenyon cells and 21 types of output cells, as well as 20 types of neurons that use the neurotransmitter dopamine. Moreover, this map provides insights into the circuits that support odor-based learning. It reveals, for example, that the mushroom body can be divided into 15 anatomical compartments that are each defined by the presence of a specific set of output and dopaminergic neuron cell types. Since the dopaminergic neurons help to shape a fly's response to odors on the basis of previous experience, this organization suggests that these compartments may be semi-autonomous information processing units.
In contrast to the rest of the insect brain, the mushroom body has a flexible organization that is similar to that of the mammalian brain. Elucidating the circuits that support associative learning in fruit flies should therefore make it easier to identify the equivalent mechanisms in vertebrate animals.
mushroom body; olfactory learning; associative memory; neuronal circuits; dopamine; plasticity; D. melanogaster
Odor information is predominantly perceived as complex odor blends. For Drosophila melanogaster one of the most attractive blends is emitted by an over-ripe banana. To analyze how the fly's olfactory system processes natural blends we combined the experimental advantages of gas chromatography and functional imaging (GC-I). In this way, natural banana compounds were presented successively to the fly antenna in close to natural occurring concentrations. This technique allowed us to identify the active odor components, use these compounds as stimuli and measure odor-induced Ca2+ signals in input and output neurons of the Drosophila antennal lobe (AL), the first olfactory neuropil. We demonstrate that mixture interactions of a natural blend are very rare and occur only at the AL output level resulting in a surprisingly linear blend representation. However, the information regarding single components is strongly modulated by the olfactory circuitry within the AL leading to a higher similarity between the representation of individual components and the banana blend. This observed modulation might tune the olfactory system in a way to distinctively categorize odor components and improve the detection of suitable food sources. Functional GC-I thus enables analysis of virtually any unknown natural odorant blend and its components in their relative occurring concentrations and allows characterization of neuronal responses of complete neural assemblies. This technique can be seen as a valuable complementary method to classical GC/electrophysiology techniques, and will be a highly useful tool in future investigations of insect-insect and insect-plant chemical interactions.
Drosophila; gas chromatography; in vivo calcium imaging; olfaction; blend coding; insect antennal lobe
The honeybee has to detect, process and learn numerous complex odours from her natural environment on a daily basis. Most of these odours are floral scents, which are mixtures of dozens of different odorants. To date, it is still unclear how the bee brain unravels the complex information contained in scent mixtures.
This study investigates learning of complex odour mixtures in honeybees using a simple olfactory conditioning procedure, the Proboscis-Extension-Reflex (PER) paradigm. Restrained honeybees were trained to three scent mixtures composed of 14 floral odorants each, and then tested with the individual odorants of each mixture. Bees did not respond to all odorants of a mixture equally: They responded well to a selection of key odorants, which were unique for each of the three scent mixtures. Bees showed less or very little response to the other odorants of the mixtures. The bees' response to mixtures composed of only the key odorants was as good as to the original mixtures of 14 odorants. A mixture composed of the other, non-key-odorants elicited a significantly lower response. Neither an odorant's volatility or molecular structure, nor learning efficiencies for individual odorants affected whether an odorant became a key odorant for a particular mixture. Odorant concentration had a positive effect, with odorants at high concentration likely to become key odorants.
Our study suggests that the brain processes complex scent mixtures by predominantly learning information from selected key odorants. Our observations on key odorant learning lend significant support to previous work on olfactory learning and mixture processing in honeybees.
In many insects, mate finding relies on female-released sex pheromones, which have to be deciphered by the male olfactory system within an odorous background of plant volatiles present in the environment of a calling female. With respect to pheromone-mediated mate localization, plant odorants may be neutral, favorable, or disturbing. Here we examined the impact of plant odorants on detection and coding of the major sex pheromone component, (Z)-11-hexadecenal (Z11-16:Ald) in the noctuid moth Heliothis virescens. By in vivo imaging the activity in the male antennal lobe (AL), we monitored the interference at the level of olfactory sensory neurons (OSN) to illuminate mixture interactions. The results show that stimulating the male antenna with Z11-16:Ald and distinct plant-related odorants simultaneously suppressed pheromone-evoked activity in the region of the macroglomerular complex (MGC), where Z11-16:Ald-specific OSNs terminate. Based on our previous findings that antennal detection of Z11-16:Ald involves an interplay of the pheromone binding protein (PBP) HvirPBP2 and the pheromone receptor (PR) HR13, we asked if the plant odorants may interfere with any of the elements involved in pheromone detection. Using a competitive fluorescence binding assay, we found that the plant odorants neither bind to HvirPBP2 nor affect the binding of Z11-16:Ald to the protein. However, imaging experiments analyzing a cell line that expressed the receptor HR13 revealed that plant odorants significantly inhibited the Z11-16:Ald-evoked calcium responses. Together the results indicate that plant odorants can interfere with the signaling process of the major sex pheromone component at the receptor level. Consequently, it can be assumed that plant odorants in the environment may reduce the firing activity of pheromone-specific OSNs in H. virescens and thus affect mate localization.
pheromone detection; antennal lobe; pheromone receptor; pheromone binding protein; olfaction
We investigate the interplay of odor identity and concentration coding in the antennal lobe (AL) of the honeybee Apis mellifera. In this primary olfactory center of the honeybee brain, odors are encoded by the spatio-temporal response patterns of olfactory glomeruli. With rising odor concentration, further glomerular responses are recruited into the patterns, which affects distances between the patterns. Based on calcium-imaging recordings, we found that such pattern broadening renders distances between glomerular response patterns closer to chemical distances between the corresponding odor molecules. Our results offer an explanation for the honeybee's improved odor discrimination performance at higher odor concentrations.
calcium-imaging; honeybees; glomerular pattern; odor concentration coding; odor identity coding; chemical dissimilarity
Honey bees have a rich repertoire of olfactory learning behaviors, and they therefore are an excellent model to study plasticity in olfactory circuits. Recent behavioral, physiological, and molecular evidence suggested that the antennal lobe, the first relay of the olfactory system in insects and analog to the olfactory bulb in vertebrates, is involved in associative and nonassociative olfactory learning. Here we use calcium imaging to reveal how responses across antennal lobe projection neurons change after association of an input odor with appetitive reinforcement. After appetitive conditioning to 1-hexanol, the representation of an odor mixture containing 1-hexanol becomes more similar to this odor and less similar to the background odor acetophenone. We then apply computational modeling to investigate how changes in synaptic connectivity can account for the observed plasticity. Our study suggests that experience-dependent modulation of inhibitory interactions in the antennal lobe aids perception of salient odor components mixed with behaviorally irrelevant background odors.
antennal lobe; honey bees; olfaction; olfactory learning
Sensory systems must be able to extract features of environmental cues within the context of the different physiological states of the organism and often temper their activity in a state-dependent manner via the process of neuromodulation. We examined the effects of the neuromodulator serotonin on a well-characterized sensory circuit, the antennal lobe of Drosophila melanogaster, using two-photon microscopy and the genetically expressed calcium indicator, G-CaMP. Serotonin enhances sensitivity of the antennal lobe output projection neurons in an odor-specific manner. For odorants that sparsely activate the antennal lobe, serotonin enhances projection neuron responses and causes an offset of the projection neuron tuning curve, most likely by increasing projection neuron sensitivity. However, for an odorant that evokes a broad activation pattern, serotonin enhances projection neuron responses in some, but not all, glomeruli. Further, serotonin enhances the responses of inhibitory local interneurons, resulting in a reduction of neurotransmitter release from the olfactory sensory neurons via GABAB receptor-dependent presynaptic inhibition, which may be a mechanism underlying the odorant-specific modulation of projection neuron responses. Our data suggest that the complexity of serotonin modulation in the antennal lobe accommodates coding stability in a glomerular pattern and flexible projection neuron sensitivity under different physiological conditions.
olfaction; neuromodulation; serotonin; antennal lobes
The rules by which odor receptors encode odors and allow behavior are still largely unexplored. Although large data sets of electrophysiological responses of receptors to odors have been generated, few hypotheses have been tested with behavioral assays. We use a data set on odor responses of Drosophila larval odor receptors coupled with chemotaxis behavioral assays to examine rules of odor coding. Using mutants of odor receptors, we have found that odor receptors with similar electrophysiological responses to odors across concentrations play non-redundant roles in odor coding at specific odor concentrations. We have also found that high affinity receptors for odors determine behavioral response thresholds, but the rules for determining peak behavioral responses are more complex. While receptor mutants typically show loss of attraction to odors, some receptor mutants result in increased attraction at specific odor concentrations. The odor receptor mutants were rescued using transgenic expression of odor receptors, validating assignment of phenotypes to the alleles. Vapor pressures alone cannot fully explain behavior in our assay. Finally, some odors that did not elicit strong electrophysiological responses are associated with behavioral phenotypes upon examination of odor receptor mutants. This result is consistent with the role of sensory neurons in lateral inhibition via local interneurons in the antennal lobe. Taken together, our results suggest a complexity of odor coding rules even in a simple olfactory sensory system.
Odor receptors; Olfaction; Drosophila; Or42a; Or42b