Oscillations and sparsening of odor representations in the mushroom body

Perceptual inference predicts contextual modulations of sensory responses

Sensory receptive fields (RFs) vary as a function of stimulus properties and measurement methods. Previous stimuli or surrounding stimuli facilitate, suppress, or change the selectivity of sensory neurons' responses. Here, we propose that these spatiotemporal contextual dependencies are signatures of efficient perceptual inference and can be explained by a single neural mechanism, input targeted divisive inhibition. To respond both selectively and reliably, sensory neurons should behave as active predictors rather than passive filters. In particular, they should remove input they can predict ("explain away") from the synaptic inputs to all other neurons. This implies that RFs are constantly and dynamically reshaped by the spatial and temporal context, while the true selectivity of sensory neurons resides in their "predictive field." This approach motivates a reinvestigation of sensory representations and particularly the role and specificity of surround suppression and adaptation in sensory areas.

Experimental evidence for sparse firing in the neocortex

The advent of unbiased recording and imaging techniques to evaluate firing activity across neocortical neurons has revealed substantial heterogeneity in response properties in vivo, and that a minority of neurons are responsible for the majority of spikes. Despite the computational advantages to sparsely firing populations, experimental data defining the fraction of responsive neurons and the range of firing rates have not been synthesized. Here we review data about the distribution of activity across neuronal populations in primary sensory cortex. Overall, the firing output of granular and infragranular layers is highest. Although subthreshold activity across supragranular neurons is decidedly non-sparse, spikes are much less frequent and some cells are silent. Superficial layers of the cortex may employ specific cell and circuit mechanisms to increase sparseness.

Psychophysical properties of odor processing can be quantitatively described by relative action potential latency patterns in mitral and tufted cells

Electrophysiological and population imaging data in rodents show that olfactory bulb (OB) activity is profoundly modulated by the odor sampling process while behavioral experiments indicate that odor discrimination can occur within a single sniff. This paper addresses the question of whether action potential (AP) latencies occurring across the mitral and tufted cell (M/TC) population within an individual sampling cycle could account for the psychophysical properties of odor processing. To determine this we created an OB model (50,000 M/TCs) exhibiting hallmarks of published in vivo properties and used a template-matching algorithm to assess stimulus separation. Such an AP latency-based scheme showed high reproducibility and sensitivity such that odor stimuli could be reliably separated independent of concentration. As in behavioral experiments we found that very dissimilar odors (“A vs. B”) were accurately and rapidly discerned while very similar odors (binary mixtures, 0.4A/0.6B vs. 0.6A/0.4B) required up to 90 ms longer. As in lesion studies we find that AP latency-based representation is rather insensitive to disruption of large regions of the OB. The AP latency-based scheme described here, therefore, captures both temporal and psychophysical properties of olfactory processing and suggests that the onset patterns of M/TC activity in the OB represent stimulus specific features of olfactory stimuli.

Neuropeptides in insect mushroom bodies

Owing to their experimental amenability, insect nervous systems continue to be in the foreground of investigations into information processing in - ostensibly - simple neuronal networks. Among the cerebral neuropil regions that hold a particular fascination for neurobiologists are the paired mushroom bodies, which, despite their function in other behavioral contexts, are most renowned for their role in learning and memory. The quest to understand the processes that underlie these capacities has been furthered by research focusing on unraveling neuroanatomical connections of the mushroom bodies and identifying key players that characterize the molecular machinery of mushroom body neurons. However, on a cellular level, communication between intrinsic and extrinsic mushroom body neurons still remains elusive. The present account aims to provide an overview on the repertoire of neuropeptides expressed in and utilized by mushroom body neurons. Existing data for a number of insect representatives is compiled and some open gaps in the record are filled by presenting additional original data.

Impaired long-range synchronization of gamma oscillations in the neocortex of a mouse lacking Kv3.2 potassium channels

Inhibitory interneurons play a critical role in the generation of gamma (20-50 Hz) oscillations, either by forming mutually inhibitory networks or as part of recurrent networks with pyramidal cells. A key property of fast spiking interneurons is their ability to generate brief spikes and high-frequency spike trains with little accommodation. However, the role of their firing properties in network oscillations has not been tested in vivo. Studies in hippocampus in vitro have shown that high-frequency spike doublets in interneurons play a key role in the long-range synchronization of gamma oscillations with little phase lag despite long axonal conduction delays. We generated a knockout (KO) mouse lacking Kv3.2 potassium channel subunits, where infragranular inhibitory interneurons lose the ability both to sustain high-frequency firing and reliably generate high-frequency spike doublets. We recorded cortical local field potentials in anesthetized and awake, restrained mice. Spontaneous activity of the KO and the wild-type (WT) showed similar content of gamma and slow (0.1-15 Hz) frequencies, but the KO showed a significantly larger decay of synchronization of gamma oscillations with distance. Coronal cuts in the cortex of WT mice decreased synchronization to values similar to the intact KO. The synchronization of the slow oscillation showed little decay with distance in both mice and was largely reduced after coronal cuts. Our results show that the firing properties of inhibitory interneurons are critical for long-range synchronization of gamma oscillations, and emphasize that intrinsic electrophysiological properties of single cells may play a key role in the spatiotemporal characteristics of network activity.

Synaptic inhibition controls transient oscillatory synchronization in a model of the insect olfactory system

In a variety of neuronal systems it has been hypothesized that inhibitory interneurons corral principal neurons into synchronously firing groups that encode sensory information and sub-serve behavior (Buzsáki and Chrobak, 1995; Buzsáki, 2008). This mechanism is particularly relevant to the olfactory system where spatiotemporal patterns of projection neuron (PN) activity act as robust markers of odor attributes (Laurent et al., 1996; Wehr and Laurent, 1996). In the insect antennal lobe (AL), a network of local inhibitory interneurons arborizes extensively throughout the AL (Leitch and Laurent, 1996) providing inhibitory input to the cholinergic PNs. Our theoretical work has attempted to elaborate the exact role of inhibition in the generation of odor specific PN responses (Bazhenov et al., 2001a,b; Assisi et al., 2011). In large-scale AL network models we characterized the inhibitory sub-network by its coloring (Assisi et al., 2011) and showed that it can entrain excitatory PNs to the odor specific patterns of transient synchronization. In this focused review, we further examine the dynamics of entrainment in more detail by simulating simple model networks in various parameter regimes. Our simulations in conjunction with earlier studies point to the key role played by lateral (between inhibitory interneurons) and feedback (from inhibitory interneurons to principal cells) inhibition in the generation of experimentally observed patterns of transient synchrony.

Spontaneous olfactory receptor neuron activity determines follower cell response properties

Noisy or spontaneous activity is common in neural systems and poses a challenge to detecting and discriminating signals. Here we use the locust to answer fundamental questions about noise in the olfactory system: Where does spontaneous activity originate? How is this activity propagated or reduced throughout multiple stages of neural processing? What mechanisms favor the detection of signals despite the presence of spontaneous activity? We found that spontaneous activity long observed in the secondary projection neurons (PNs) originates almost entirely from the primary olfactory receptor neurons (ORNs) rather than from spontaneous circuit interactions in the antennal lobe, and that spontaneous activity in ORNs tonically depolarizes the resting membrane potentials of their target PNs and local neurons (LNs) and indirectly tonically depolarizes tertiary Kenyon cells (KCs). However, because these neurons have different response thresholds, in the absence of odor stimulation, ORNs and PNs display a high spontaneous firing rate but KCs are nearly silent. Finally, we used a simulation of the olfactory network to show that discrimination of signal and noise in the KCs is best when threshold levels are set so that baseline activity in PNs persists. Our results show how the olfactory system benefits from making a signal detection decision after a point of maximal information convergence, e.g., after KCs pool inputs from many PNs.

Conditional modulation of spike-timing-dependent plasticity for olfactory learning

Mushroom bodies are a well-known site for associative learning in insects. Yet the precise mechanisms that underlie plasticity there and ensure their specificity remain elusive. In locusts, the synapses between the intrinsic mushroom body neurons and their postsynaptic targets obey a Hebbian spike-timing-dependent plasticity (STDP) rule. Although this property homeostatically regulates the timing of mushroom body output, its potential role in associative learning is unknown. Here we show in vivo that pre-post pairing causing STDP can, when followed by the local delivery of a reinforcement-mediating neuromodulator, specify the synapses that will undergo an associative change. At these synapses, and there only, the change is a transformation of the STDP rule itself. These results illustrate the multiple actions of STDP, including a role in associative learning, despite potential temporal dissociation between the pairings that specify synaptic modification and the delivery of reinforcement-mediating neuromodulator signals.

Encoding odorant identity by spiking packets of rate-invariant neurons in awake mice

BACKGROUND

How do neural networks encode sensory information? Following sensory stimulation, neural coding is commonly assumed to be based on neurons changing their firing rate. In contrast, both theoretical works and experiments in several sensory systems showed that neurons could encode information as coordinated cell assemblies by adjusting their spike timing and without changing their firing rate. Nevertheless, in the olfactory system, there is little experimental evidence supporting such model.

METHODOLOGY/PRINCIPAL FINDINGS

To study these issues, we implanted tetrodes in the olfactory bulb of awake mice to record the odorant-evoked activity of mitral/tufted (M/T) cells. We showed that following odorant presentation, most M/T neurons do not significantly change their firing rate over a breathing cycle but rather respond to odorant stimulation by redistributing their firing activity within respiratory cycles. In addition, we showed that sensory information can be encoded by cell assemblies composed of such neurons, thus supporting the idea that coordinated populations of globally rate-invariant neurons could be efficiently used to convey information about the odorant identity. We showed that different coding schemes can convey high amount of odorant information for specific read-out time window. Finally we showed that the optimal readout time window corresponds to the duration of gamma oscillations cycles.

CONCLUSION

We propose that odorant can be encoded by population of cells that exhibit fine temporal tuning of spiking activity while displaying weak or no firing rate change. These cell assemblies may transfer sensory information in spiking packets sequence using the gamma oscillations as a clock. This would allow the system to reach a tradeoff between rapid and accurate odorant discrimination.

Establishing Communication between Neuronal Populations through Competitive Entrainment

The role of gamma frequency oscillation in neuronal interaction, and the relationship between oscillation and information transfer between neurons, has been the focus of much recent research. While the biological mechanisms responsible for gamma oscillation and the properties of resulting networks are well studied, the dynamics of changing phase coherence between oscillating neuronal populations are not well understood. To this end we develop a computational model of competitive selection between multiple stimuli, where the selection and transfer of population-encoded information arises from competition between converging stimuli to entrain a target population of neurons. Oscillation is generated by Pyramidal-Interneuronal Network Gamma through the action of recurrent synaptic connections between a locally connected network of excitatory and inhibitory neurons. Competition between stimuli is driven by differences in coherence of oscillation, while transmission of a single selected stimulus is enabled between generating and receiving neurons via Communication-through-Coherence. We explore the effect of varying synaptic parameters on the competitive transmission of stimuli over different neuron models, and identify a continuous region within the parameter space of the recurrent synaptic loop where inhibition-induced oscillation results in entrainment of target neurons. Within this optimal region we find that competition between stimuli of equal coherence results in model output that alternates between representation of the stimuli, in a manner strongly resembling well-known biological phenomena resulting from competitive stimulus selection such as binocular rivalry.

A model of ant route navigation driven by scene familiarity

In this paper we propose a model of visually guided route navigation in ants that captures the known properties of real behaviour whilst retaining mechanistic simplicity and thus biological plausibility. For an ant, the coupling of movement and viewing direction means that a familiar view specifies a familiar direction of movement. Since the views experienced along a habitual route will be more familiar, route navigation can be re-cast as a search for familiar views. This search can be performed with a simple scanning routine, a behaviour that ants have been observed to perform. We test this proposed route navigation strategy in simulation, by learning a series of routes through visually cluttered environments consisting of objects that are only distinguishable as silhouettes against the sky. In the first instance we determine view familiarity by exhaustive comparison with the set of views experienced during training. In further experiments we train an artificial neural network to perform familiarity discrimination using the training views. Our results indicate that, not only is the approach successful, but also that the routes that are learnt show many of the characteristics of the routes of desert ants. As such, we believe the model represents the only detailed and complete model of insect route guidance to date. What is more, the model provides a general demonstration that visually guided routes can be produced with parsimonious mechanisms that do not specify when or what to learn, nor separate routes into sequences of waypoints.

Behavioral and neurophysiological study of olfactory perception and learning in honeybees

The honeybee Apis mellifera has been a central insect model in the study of olfactory perception and learning for more than a century, starting with pioneer work by Karl von Frisch. Research on olfaction in honeybees has greatly benefited from the advent of a range of behavioral and neurophysiological paradigms in the Lab. Here I review major findings about how the honeybee brain detects, processes, and learns odors, based on behavioral, neuroanatomical, and neurophysiological approaches. I first address the behavioral study of olfactory learning, from experiments on free-flying workers visiting artificial flowers to laboratory-based conditioning protocols on restrained individuals. I explain how the study of olfactory learning has allowed understanding the discrimination and generalization ability of the honeybee olfactory system, its capacity to grant special properties to olfactory mixtures as well as to retain individual component information. Next, based on the impressive amount of anatomical and immunochemical studies of the bee brain, I detail our knowledge of olfactory pathways. I then show how functional recordings of odor-evoked activity in the brain allow following the transformation of the olfactory message from the periphery until higher-order central structures. Data from extra- and intracellular electrophysiological approaches as well as from the most recent optical imaging developments are described. Lastly, I discuss results addressing how odor representation changes as a result of experience. This impressive ensemble of behavioral, neuroanatomical, and neurophysiological data available in the bee make it an attractive model for future research aiming to understand olfactory perception and learning in an integrative fashion.

Emerging Pharmacological Properties of Cholinergic Synaptic Transmission: Comparison between Mammalian and Insect Synaptic and Extrasynaptic Nicotinic Receptors

Acetylcholine (ACh) is probably the oldest signalling neurotransmitter which appeared in evolution before the nervous system. It is present in bacteria, algae, protozoa and plants. In insects and mammals it is involved in cell-to-cell communications in various neuronal and non-neuronal tissues. The discovery of nicotinic acetylcholine receptors (nAChRs) as the main receptors involved in rapid cholinergic neurotransmission has helped to understand the role of ACh at synaptic level. Recently, several lines of evidence have indicated that extrasynaptically expressed nAChRs display distinct pharmacological properties from the ones expressed at synaptic level. The role of both nAChRs at insect extrasynaptic and/or synaptic levels has been underestimated due to the lack of pharmacological tools to identify different nicotinic receptor subtypes. In the present review, we summarize recent electrophysiological and pharmacological studies on the extrasynaptic and synaptic differences between insect and mammalian nAChR subtypes and we discuss on the pharmacological impact of several drugs such as neonicotinoid insecticides targeting these receptors. In fact, nAChRs are involved in a wide range of pathophysiological processes such as epilepsy, pain and a wide range of neurodegenerative and psychiatric disorders. In addition, they are the target sites of neonicotinoid insecticides which are known to act as nicotinic agonists causing severe poisoning in insects and mammals.

Criteria for robustness of heteroclinic cycles in neural microcircuits

We introduce a test for robustness of heteroclinic cycles that appear in neural microcircuits modeled as coupled dynamical cells. Robust heteroclinic cycles (RHCs) can appear as robust attractors in Lotka-Volterra-type winnerless competition (WLC) models as well as in more general coupled and/or symmetric systems. It has been previously suggested that RHCs may be relevant to a range of neural activities, from encoding and binding to spatio-temporal sequence generation.The robustness or otherwise of such cycles depends both on the coupling structure and the internal structure of the neurons. We verify that robust heteroclinic cycles can appear in systems of three identical cells, but only if we require perturbations to preserve some invariant subspaces for the individual cells. On the other hand, heteroclinic attractors can appear robustly in systems of four or more identical cells for some symmetric coupling patterns, without restriction on the internal dynamics of the cells.

Cortical processing of odor objects

Natural odors, generally composed of many monomolecular components, are analyzed by peripheral receptors into component features and translated into spatiotemporal patterns of neural activity in the olfactory bulb. Here, we will discuss the role of the olfactory cortex in the recognition, separation and completion of those odor-evoked patterns, and how these processes contribute to odor perception. Recent findings regarding the neural architecture, physiology, and plasticity of the olfactory cortex, principally the piriform cortex, will be described in the context of how this paleocortical structure creates odor objects.

Neuronal filtering of multiplexed odour representations

Neuronal activity patterns contain information in their temporal structure, indicating that information transfer between neurons may be optimized by temporal filtering. In the zebrafish olfactory bulb, subsets of output neurons (mitral cells) engage in synchronized oscillations during odour responses, but information about odour identity is contained mostly in non-oscillatory firing rate patterns. Using optogenetic manipulations and odour stimulation, we found that firing rate responses of neurons in the posterior zone of the dorsal telencephalon (Dp), a target area homologous to olfactory cortex, were largely insensitive to oscillatory synchrony of mitral cells because passive membrane properties and synaptic currents act as low-pass filters. Nevertheless, synchrony influenced spike timing. Moreover, Dp neurons responded primarily during the decorrelated steady state of mitral cell activity patterns. Temporal filtering therefore tunes Dp neurons to components of mitral cell activity patterns that are particularly informative about precise odour identity. These results demonstrate how temporal filtering can extract specific information from multiplexed neuronal codes.

Circuit neuroscience in zebrafish

A central goal of modern neuroscience is to obtain a mechanistic understanding of higher brain functions under healthy and diseased conditions. Addressing this challenge requires rigorous experimental and theoretical analysis of neuronal circuits. Recent advances in optogenetics, high-resolution in vivo imaging, and reconstructions of synaptic wiring diagrams have created new opportunities to achieve this goal. To fully harness these methods, model organisms should allow for a combination of genetic and neurophysiological approaches in vivo. Moreover, the brain should be small in terms of neuron numbers and physical size. A promising vertebrate organism is the zebrafish because it is small, it is transparent at larval stages and it offers a wide range of genetic tools and advantages for neurophysiological approaches. Recent studies have highlighted the potential of zebrafish for exhaustive measurements of neuronal activity patterns, for manipulations of defined cell types in vivo and for studies of causal relationships between circuit function and behavior. In this article, we summarize background information on the zebrafish as a model in modern systems neuroscience and discuss recent results.

Detailed Characterization of Local Field Potential Oscillations and Their Relationship to Spike Timing in the Antennal Lobe of the Moth Manduca sexta

The transient oscillatory model of odor identity encoding seeks to explain how odorants with spatially overlapped patterns of input into primary olfactory networks can be discriminated. This model provides several testable predictions about the distributed nature of network oscillations and how they control spike timing. To test these predictions, 16 channel electrode arrays were placed within the antennal lobe (AL) of the moth Manduca sexta. Unitary spiking and multi site local field potential (LFP) recordings were made during spontaneous activity and in response to repeated presentations of an odor panel. We quantified oscillatory frequency, cross correlations between LFP recording sites, and spike-LFP phase relationships. We show that odor-driven AL oscillations in Manduca are frequency modulating (FM) from ∼100 to 30 Hz; this was odorant and stimulus duration dependent. FM oscillatory responses were localized to one or two recording sites suggesting a localized (perhaps glomerular) not distributed source. LFP cross correlations further demonstrated that only a small (r < 0.05) distributed and oscillatory component was present. Cross spectral density analysis demonstrated the frequency of these weakly distributed oscillations was state dependent (spontaneous activity = 25-55 Hz; odor-driven = 55-85 Hz). Surprisingly, vector strength analysis indicated that unitary phase locking of spikes to the LFP was strongest during spontaneous activity and dropped significantly during responses. Application of bicuculline, a GABA(A) receptor antagonist, significantly lowered the frequency content of odor-driven distributed oscillatory activity. Bicuculline significantly reduced spike phase locking generally, but the ubiquitous pattern of increased phase locking during spontaneous activity persisted. Collectively, these results indicate that oscillations perform poorly as a stimulus-mediated spike synchronizing mechanism for Manduca and hence are incongruent with the transient oscillatory model.

An efficient coding hypothesis links sparsity and selectivity of neural responses

To what extent are sensory responses in the brain compatible with first-order principles? The efficient coding hypothesis projects that neurons use as few spikes as possible to faithfully represent natural stimuli. However, many sparsely firing neurons in higher brain areas seem to violate this hypothesis in that they respond more to familiar stimuli than to nonfamiliar stimuli. We reconcile this discrepancy by showing that efficient sensory responses give rise to stimulus selectivity that depends on the stimulus-independent firing threshold and the balance between excitatory and inhibitory inputs. We construct a cost function that enforces minimal firing rates in model neurons by linearly punishing suprathreshold synaptic currents. By contrast, subthreshold currents are punished quadratically, which allows us to optimally reconstruct sensory inputs from elicited responses. We train synaptic currents on many renditions of a particular bird's own song (BOS) and few renditions of conspecific birds' songs (CONs). During training, model neurons develop a response selectivity with complex dependence on the firing threshold. At low thresholds, they fire densely and prefer CON and the reverse BOS (REV) over BOS. However, at high thresholds or when hyperpolarized, they fire sparsely and prefer BOS over REV and over CON. Based on this selectivity reversal, our model suggests that preference for a highly familiar stimulus corresponds to a high-threshold or strong-inhibition regime of an efficient coding strategy. Our findings apply to songbird mirror neurons, and in general, they suggest that the brain may be endowed with simple mechanisms to rapidly change selectivity of neural responses to focus sensory processing on either familiar or nonfamiliar stimuli. In summary, we find support for the efficient coding hypothesis and provide new insights into the interplay between the sparsity and selectivity of neural responses.

Cellular-resolution population imaging reveals robust sparse coding in the Drosophila mushroom body

Sensory stimuli are represented in the brain by the activity of populations of neurons. In most biological systems, studying population coding is challenging since only a tiny proportion of cells can be recorded simultaneously. Here we used two-photon imaging to record neural activity in the relatively simple Drosophila mushroom body (MB), an area involved in olfactory learning and memory. Using the highly sensitive calcium indicator GCaMP3, we simultaneously monitored the activity of >100 MB neurons in vivo (∼5% of the total population). The MB is thought to encode odors in sparse patterns of activity, but the code has yet to be explored either on a population level or with a wide variety of stimuli. We therefore imaged responses to odors chosen to evaluate the robustness of sparse representations. Different odors activated distinct patterns of MB neurons; however, we found no evidence for spatial organization of neurons by either response probability or odor tuning within the cell body layer. The degree of sparseness was consistent across a wide range of stimuli, from monomolecular odors to artificial blends and even complex natural smells. Sparseness was mainly invariant across concentrations, largely because of the influence of recent odor experience. Finally, in contrast to sensory processing in other systems, no response features distinguished natural stimuli from monomolecular odors. Our results indicate that the fundamental feature of odor processing in the MB is to create sparse stimulus representations in a format that facilitates arbitrary associations between odor and punishment or reward.

Insect olfactory coding and memory at multiple timescales

Insects can learn, allowing them great flexibility for locating seasonal food sources and avoiding wily predators. Because insects are relatively simple and accessible to manipulation, they provide good experimental preparations for exploring mechanisms underlying sensory coding and memory. Here we review how the intertwining of memory with computation enables the coding, decoding, and storage of sensory experience at various stages of the insect olfactory system. Individual parts of this system are capable of multiplexing memories at different timescales, and conversely, memory on a given timescale can be distributed across different parts of the circuit. Our sampling of the olfactory system emphasizes the diversity of memories, and the importance of understanding these memories in the context of computations performed by different parts of a sensory system.

Selectivity of pyramidal cells and interneurons in the human medial temporal lobe

Neurons in the medial temporal lobe (MTL) respond selectively to pictures of specific individuals, objects, and places. However, the underlying mechanisms leading to such degree of stimulus selectivity are largely unknown. A necessary step to move forward in this direction involves the identification and characterization of the different neuron types present in MTL circuitry. We show that putative principal cells recorded in vivo from the human MTL are more selective than putative interneurons. Furthermore, we report that putative hippocampal pyramidal cells exhibit the highest degree of selectivity within the MTL, reflecting the hierarchical processing of visual information. We interpret these differences in selectivity as a plausible mechanism for generating sparse responses.

Expression patterns of nicotinic subunits α2, α7, α8, and β1 affect the kinetics and pharmacology of ACh-induced currents in adult bee olfactory neuropiles

Acetylcholine (ACh) is the main excitatory neurotransmitter of the insect brain, where nicotinic acetylcholine receptors (nAChRs) mediate fast cholinergic synaptic transmission. In the honeybee Apis mellifera, nAChRs are expressed in diverse structures including the primary olfactory centers of the brain, the antennal lobes (ALs) and the mushroom bodies (MBs), where they participate in olfactory information processing. To understand the nature and properties of the nAChRs involved in these processes, we performed a pharmacological and molecular characterization of nAChRs on cultured Kenyon cells of the MBs, using whole cell patch-clamp recordings combined with single-cell RT-PCR. In all cells, applications of ACh as well as nicotinic agonists such as nicotine and imidacloprid induced inward currents with fast desensitization. These currents were fully blocked by saturating doses of the antagonists α-bungarotoxin (α-BGT), dihydroxy-β-erythroidine (DHE), and methyllycaconitine (MLA) (MLA ≥ α-BGT ≥ DHE). Molecular analysis of ACh-responding cells revealed that of the 11 nicotinic receptor subunits encoded within the honeybee genome, α2, α8, and β1 subunits were expressed in adult Kenyon cells. Comparison with the expression pattern of adult AL cells revealed the supplementary presence of subunit α7, which could be responsible for the kinetic and pharmacological differences observed when comparing ACh-induced currents from AL and Kenyon cells. Together, our data demonstrate the existence of functional nAChRs on adult MB Kenyon cells that differ from nAChRs on AL cells in both their molecular composition and pharmacological properties, suggesting that changing receptor subsets could mediate different processing functions depending on the brain structure within the olfactory pathway.

Efficient computation via sparse coding in electrosensory neural networks

The electric sense combines spatial aspects of vision and touch with temporal features of audition. Its accessible neural architecture shares similarities with mammalian sensory systems and allows for recordings from successive brain areas to test hypotheses about neural coding. Further, electrosensory stimuli encountered during prey capture, navigation, and communication, can be readily synthesized in the laboratory. These features enable analyses of the neural circuitry that reveal general principles of encoding and decoding, such as segregation of information into separate streams and neural response sparsification. A systems level understanding arises via linkage between cellular differentiation and network architecture, revealed by in vitro and in vivo analyses, while computational modeling reveals how single cell dynamics and connectivity shape the sparsification process.

The neurobiology of insect olfaction: sensory processing in a comparative context

The simplicity and accessibility of the olfactory systems of insects underlie a body of research essential to understanding not only olfactory function but also general principles of sensory processing. As insect olfactory neurobiology takes advantage of a variety of species separated by millions of years of evolution, the field naturally has yielded some conflicting results. Far from impeding progress, the varieties of insect olfactory systems reflect the various natural histories, adaptations to specific environments, and the roles olfaction plays in the life of the species studied. We review current findings in insect olfactory neurobiology, with special attention to differences among species. We begin by describing the olfactory environments and olfactory-based behaviors of insects, as these form the context in which neurobiological findings are interpreted. Next, we review recent work describing changes in olfactory systems as adaptations to new environments or behaviors promoting speciation. We proceed to discuss variations on the basic anatomy of the antennal (olfactory) lobe of the brain and higher-order olfactory centers. Finally, we describe features of olfactory information processing including gain control, transformation between input and output by operations such as broadening and sharpening of tuning curves, the role of spiking synchrony in the antennal lobe, and the encoding of temporal features of encounters with an odor plume. In each section, we draw connections between particular features of the olfactory neurobiology of a species and the animal's life history. We propose that this perspective is beneficial for insect olfactory neurobiology in particular and sensory neurobiology in general.

Sparse and dense coding of natural stimuli by distinct midbrain neuron subpopulations in weakly electric fish

While peripheral sensory neurons respond to natural stimuli with a broad range of spatiotemporal frequencies, central neurons instead respond sparsely to specific features in general. The nonlinear transformations leading to this emergent selectivity are not well understood. Here we characterized how the neural representation of stimuli changes across successive brain areas, using the electrosensory system of weakly electric fish as a model system. We found that midbrain torus semicircularis (TS) neurons were on average more selective in their responses than hindbrain electrosensory lateral line lobe (ELL) neurons. Further analysis revealed two categories of TS neurons: dense coding TS neurons that were ELL-like and sparse coding TS neurons that displayed selective responses. These neurons in general responded to preferred stimuli with few spikes and were mostly silent for other stimuli. We further investigated whether information about stimulus attributes was contained in the activities of ELL and TS neurons. To do so, we used a spike train metric to quantify how well stimuli could be discriminated based on spiking responses. We found that sparse coding TS neurons performed poorly even when their activities were combined compared with ELL and dense coding TS neurons. In contrast, combining the activities of as few as 12 dense coding TS neurons could lead to optimal discrimination. On the other hand, sparse coding TS neurons were better detectors of whether their preferred stimulus occurred compared with either dense coding TS or ELL neurons. Our results therefore suggest that the TS implements parallel detection and estimation of sensory input.

A subpopulation of mushroom body intrinsic neurons is generated by protocerebral neuroblasts in the tobacco hornworm moth, Manduca sexta (Sphingidae, Lepidoptera)

Subpopulations of Kenyon cells, the intrinsic neurons of the insect mushroom bodies, are typically sequentially generated by dedicated neuroblasts that begin proliferating during embryogenesis. When present, Class III Kenyon cells are thought to be the first born population of neurons by virtue of the location of their cell somata, farthest from the position of the mushroom body neuroblasts. In the adult tobacco hornworm moth Manduca sexta, the axons of Class III Kenyon cells form a separate Y tract and dorsal and ventral lobelet; surprisingly, these distinctive structures are absent from the larval Manduca mushroom bodies. BrdU labeling and immunohistochemical staining reveal that Class III Kenyon cells are in fact born in the mid-larval through adult stages. The peripheral position of their cell bodies is due to their genesis from two previously undescribed protocerebral neuroblasts distinct from the mushroom body neuroblasts that generate the other Kenyon cell types. These findings challenge the notion that all Kenyon cells are produced solely by the mushroom body neuroblasts, and may explain why Class III Kenyon cells are found sporadically across the insects, suggesting that when present, they may arise through de novo recruitment of neuroblasts outside of the mushroom bodies. In addition, lifelong neurogenesis by both the Class III neuroblasts and the mushroom body neuroblasts was observed, raising the possibility that adult neurogenesis may play a role in mushroom body function in Manduca.

Olfactory trace conditioning in Drosophila

The neural representation of a sensory stimulus evolves with time, and animals keep that representation even after stimulus cessation (i.e., a stimulus "trace"). To contrast the memories of an odor and an odor trace, we here establish a rigorous trace conditioning paradigm in the fruit fly, Drosophila melanogaster. We modify the olfactory associative learning paradigm, in which the odor and electric shock are presented with a temporal overlap (delay conditioning). Given a few-second temporal gap between the presentations of the odor and the shock in trace conditioning, the odor trace must be kept until the arrival of electric shock to form associative memory. We found that memories after trace and delay conditioning have striking similarities: both reached the same asymptotic learning level, although at different rates, and both kinds of memory have similar decay kinetics and highly correlated generalization profiles across odors. In search of the physiological correlate of the odor trace, we used in vivo calcium imaging to characterize the odor-evoked activity of the olfactory receptor neurons in the antennal lobe. After the offset of odor presentation, the receptor neurons showed persistent, odor-specific response patterns that lasted for a few seconds and were fundamentally different from the response patterns during the stimulation. Weak correlation between the behavioral odor generalization profile in trace conditioning and the physiological odor similarity profiles in the antennal lobe suggest that the odor trace used for associative learning may be encoded downstream of the olfactory receptor neurons.

Precise olfactory responses tile the sniff cycle

In terrestrial vertebrates, sniffing controls odorant access to receptors, and therefore sets the timescale of olfactory stimuli. We found that odorants evoked precisely sniff-locked activity in mitral/tufted cells in the olfactory bulb of awake mouse. The trial-to-trial response jitter averaged 12 ms, a precision comparable to other sensory systems. Individual cells expressed odor-specific temporal patterns of activity and, across the population, onset times tiled the duration of the sniff cycle. Responses were more tightly time-locked to the sniff phase than to the time after inhalation onset. The spikes of single neurons carried sufficient information to discriminate odors. In addition, precise locking to sniff phase may facilitate ensemble coding by making synchrony relationships across neurons robust to variation in sniff rate. The temporal specificity of mitral/tufted cell output provides a potentially rich source of information for downstream olfactory areas.

Insect olfaction from model systems to disease control

Great progress has been made in the field of insect olfaction in recent years. Receptors, neurons, and circuits have been defined in considerable detail, and the mechanisms by which they detect, encode, and process sensory stimuli are being unraveled. We provide a guide to recent progress in the field, with special attention to advances made in the genetic model organism Drosophila. We highlight key questions that merit additional investigation. We then present our view of how recent advances may be applied to the control of disease-carrying insects such as mosquitoes, which transmit disease to hundreds of millions of people each year. We suggest how progress in defining the basic mechanisms of insect olfaction may lead to means of disrupting host-seeking and other olfactory behaviors, thereby reducing the transmission of deadly diseases.

Are mushroom bodies cerebellum-like structures?

The mushroom bodies are distinctive neuropils in the protocerebral brain segments of many protostomes. A defining feature of mushroom bodies is their intrinsic neurons, masses of cytoplasm-poor globuli cells that form a system of lobes with their densely-packed, parallel-projecting axon-like processes. In insects, the role of the mushroom bodies in olfactory processing and associative learning and memory has been studied in depth, but several lines of evidence suggest that the function of these higher brain centers cannot be restricted to these roles. The present account considers whether insight into an underlying function of mushroom bodies may be provided by cerebellum-like structures in vertebrates, which are similarly defined by the presence of masses of tiny granule cells that emit thin parallel fibers forming a dense molecular layer. In vertebrates, the shared neuroarchitecture of cerebellum-like structures has been suggested to underlie a common functional role as adaptive filters for the removal of predictable sensory elements, such as those arising from reafference, from the total sensory input. Cerebellum-like structures include the vertebrate cerebellum, the electrosensory lateral line lobe, dorsal and medial octavolateral nuclei of fish, and the dorsal cochlear nucleus of mammals. The many architectural and physiological features that the insect mushroom bodies share with cerebellum-like structures suggest that it might be fruitful to consider mushroom body function in light of a possible role as adaptive sensory filters. The present account thus presents a detailed comparison of the insect mushroom bodies with vertebrate cerebellum-like structures.

Comparison of microglomerular structures in the mushroom body calyx of neopteran insects

Mushroom bodies (MBs) are prominent neuropils in the insect brain involved in higher order processing such as sensory integration, learning and memory, and spatial orientation. The size and general morphology of MBs are diverse across insects. In this study we comparatively investigated the microstructure of synaptic complexes (microglomeruli) in major sensory input regions of the MBs, the calyces, across various neopteran insect species. Pre- and postsynaptic compartments of microglomeruli were analyzed using anti-synapsin immunocytochemistry, f-actin-phalloidin labeling and high-resolution confocal microscopy. Our results suggest that calycal microglomeruli are present across all investigated neopteran insect species, but differences are found in the distribution of synapsin and f-actin within their pre- and postsynaptic compartments. Hymenopteran MBs contain the highest number and packing density of microglomeruli compared to all other species from the different insect orders we investigated. We conclude that the evolution of high numbers of microglomeruli in Hymenoptera may reflect an increase in synaptic microcircuits, which could enhance the computational capacities of the MBs.

Mushroom body output neurons encode odor-reward associations

Neural correlates of learning and memory formation have been reported at different stages of the olfactory pathway in both vertebrates and invertebrates. However, the contribution of different neurons to the formation of a memory trace is little understood. Mushroom bodies (MBs) in the insect brain are higher-order structures involved in integration of olfactory, visual, and mechanosensory information and in memory formation. Here we focus on the ensemble spiking activity of single MB output neurons (ENs) when honeybees learned to associate an odor with reward. A large group of ENs (∼50%) changed their odor response spectra by losing or gaining sensitivity for specific odors. This response switching was dominated by the rewarded stimulus (CS+), which evoked exclusively recruitment. The remaining ENs did not change their qualitative odor spectrum but modulated their tuning strength, again dominated by increased responses to the CS+. While the bees showed a conditioned response (proboscis extension) after a few acquisition trials, no short-term effects were observed in the neuronal activity. In both EN types, associative plastic changes occurred only during retention 3 h after conditioning. Thus, long-term but not short-term memory was reflected by increased EN activity to the CS+. During retention, the EN ensemble separated the CS+ most differently from the CS- and control odors ∼140 ms after stimulus onset. The learned behavioral response appeared ∼330 ms later. It is concluded that after memory consolidation, the ensemble activity of the MB output neurons predicts the meaning of the stimulus (reward) and may provide the prerequisite for the expression of the learned behavior.

Multiple memory traces after associative learning in the honey bee antennal lobe

We investigated the effect of associative learning on early sensory processing, by combining classical conditioning with in vivo calcium-imaging of secondary olfactory neurons, the projection neurons (PNs) in the honey bee antennal lobe (AL). We trained bees in a differential conditioning paradigm in which one odour (A+) was paired with a reward, while another odour (B-) was presented without a reward. Two to five hours after differential conditioning, the two odour-response patterns became more different in bees that learned to discriminate between A and B, but not in bees that did not discriminate. This learning-related change in neural odour representations can be traced back to glomerulus-specific neural plasticity, which depended on the response profile of the glomerulus before training. (i) Glomeruli responding to A but not to B generally increased in response strength. (ii) Glomeruli responding to B but not to A did not change in response strength. (iii) Glomeruli responding to A and B decreased in response strength. (iv) Glomeruli not responding to A or B increased in response strength. The data are consistent with a neural network model of the AL, which we based on two plastic synapse types and two well-known learning rules: associative, reinforcer-dependent Hebbian plasticity at synapses between olfactory receptor neurons (ORNs) and PNs; and reinforcer-independent Hebbian plasticity at synapses between local interneurons and ORNs. The observed changes strengthen the idea that odour learning optimizes odour representations, and facilitates the detection and discrimination of learned odours.

Mind the gap: olfactory trace conditioning in honeybees

Trace conditioning is a form of classical conditioning, where a neutral stimulus (conditioned stimulus, CS) is associated with a following appetitive or aversive stimulus (unconditioned stimulus, US). Unlike classical delay conditioning, in trace conditioning there is a stimulus-free gap between CS and US, and thus a poststimulus neural representation (trace) of the CS is required to bridge the gap until its association with the US. The properties of such stimulus traces are not well understood, nor are their underlying physiological mechanisms. Using behavioral and physiological approaches, we studied appetitive olfactory trace conditioning in honeybees. We found that single-odor presentation created a trace containing information about odor identity. This trace conveyed odor information about the initial stimulus and was robust against interference by other odors. Memory acquisition decreased with increasing CS-US gap length. The maximum learnable CS-US gap length could be extended by previous trace-conditioning experience. Furthermore, acquisition improved when an additional odor was presented during the CS-US gap. Using calcium imaging, we tested whether projection neurons in the primary olfactory brain area, the antennal lobe, contain a CS trace. We found odor-specific persistent responses after stimulus offset. These post-odor responses, however, did not encode the CS trace, and perceived odor quality could be predicted by the initial but not by the post-odor response. Our data suggest that olfactory trace conditioning is a less reflexive form of learning than classical delay conditioning, indicating that odor traces might involve higher-level cognitive processes.

Neuronal processing of complex mixtures establishes a unique odor representation in the moth antennal lobe

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.

Normalization for sparse encoding of odors by a wide-field interneuron

Sparse coding presents practical advantages for sensory representations and memory storage. In the insect olfactory system, the representation of general odors is dense in the antennal lobes but sparse in the mushroom bodies, only one synapse downstream. In locusts, this transformation relies on the oscillatory structure of antennal lobe output, feed-forward inhibitory circuits, intrinsic properties of mushroom body neurons, and connectivity between antennal lobe and mushroom bodies. Here we show the existence of a normalizing negative-feedback loop within the mushroom body to maintain sparse output over a wide range of input conditions. This loop consists of an identifiable "giant" nonspiking inhibitory interneuron with ubiquitous connectivity and graded release properties.

Neural circuit mechanisms for pattern detection and feature combination in olfactory cortex

Odors are initially encoded in the brain as a set of distinct physicochemical characteristics but are ultimately perceived as a unified sensory object--a "smell." It remains unclear how chemical features encoded by diverse odorant receptors and segregated glomeruli in the main olfactory bulb (MOB) are assembled into integrated cortical representations. Combining patterned optical microstimulation of MOB with in vivo electrophysiological recordings in anterior piriform cortex (PCx), we assessed how cortical neurons decode complex activity patterns distributed across MOB glomeruli. PCx firing was insensitive to single-glomerulus photostimulation. Instead, individual cells reported higher-order combinations of coactive glomeruli resembling odor-evoked sensory maps. Intracellular recordings revealed a corresponding circuit architecture providing each cortical neuron with weak synaptic input from a distinct subpopulation of MOB glomeruli. PCx neurons thus detect specific glomerular ensembles, providing an explicit neural representation of chemical feature combinations that are the hallmark of complex odor stimuli.

Presynaptic Ca2+ stores contribute to odor-induced responses in Drosophila olfactory receptor neurons

In both vertebrates and invertebrates, olfactory receptor neurons (ORNs) respond to several odors. They also adapt to stimulus variations, and this is considered to be a simple form of non-associative learning and neuronal plasticity. Different mechanisms have been described to support neuronal and/or synaptic plasticity. For example in vertebrates, presynaptic Ca(2+) stores relying on either the ryanodine receptor (RyR) or the inositol (1,4,5)-trisphosphate receptor (InsP(3)R) have been reported to participate in synaptic transmission, in hippocampal pyramidal neurons, and in basket cell-Purkinje cell synapses. However, in invertebrates, especially in sensory neurons such as ORNs, similar mechanisms have not yet been detected. In this study, using Drosophila and taking advantage of an in vivo bioluminescence Ca(2+)-imaging technique in combination with genetic and pharmacological tools, first we show that the GFP-aequorin Ca(2+) sensor is sensitive enough to detect odor-induced responses of various durations. Second, we show that for a relatively long (5 s) odor application, odor-induced Ca(2+) responses occurring in the axon terminals of ORNs involve intracellular Ca(2+) stores. This response is decreased by specifically targeting InsP(3)R or RyR by RNAi, or application of the specific blockers thapsigargin or ryanodine, suggesting that Ca(2+) stores serve to amplify the presynaptic signal. Furthermore, we show that disrupting the intracellular Ca(2+) stores in the ORNs has functional consequences since InsP(3)R- or RyR-RNAi expressing flies were defective in olfactory behavior. Altogether, our results indicate that for long odor applications in Drosophila, the olfactory response depends on intracellular Ca(2+) stores within the axon terminals of the ORNs.

Sparse coding in striate and extrastriate visual cortex

Theoretical studies of mammalian cortex argue that efficient neural codes should be sparse. However, theoretical and experimental studies have used different definitions of the term "sparse" leading to three assumptions about the nature of sparse codes. First, codes that have high lifetime sparseness require few action potentials. Second, lifetime-sparse codes are also population-sparse. Third, neural codes are optimized to maximize lifetime sparseness. Here, we examine these assumptions in detail and test their validity in primate visual cortex. We show that lifetime and population sparseness are not necessarily correlated and that a code may have high lifetime sparseness regardless of how many action potentials it uses. We measure lifetime sparseness during presentation of natural images in three areas of macaque visual cortex, V1, V2, and V4. We find that lifetime sparseness does not increase across the visual hierarchy. This suggests that the neural code is not simply optimized to maximize lifetime sparseness. We also find that firing rates during a challenging visual task are higher than theoretical values based on metabolic limits and that responses in V1, V2, and V4 are well-described by exponential distributions. These findings are consistent with the hypothesis that neurons are optimized to maximize information transmission subject to metabolic constraints on mean firing rate.

β-Band correlates of the fMRI BOLD response

Oscillatory activity in the β-band (15-30 Hz) has been studied in detail in the sensorimotor cortex. It has been postulated that β-activity acts as a localized gating of cortical activity. Here, the induced oscillatory response in the β-band is measured by magnetoencephalography, and the hemodynamic response is measured by fMRI. We assess the linearity of the responses to stimuli of varying duration in the primary motor cortex and to a sinusoidal drifting grating of varying contrast amplitude and drift frequency in the visual cortex. In this way, we explore the nature of β-oscillations and their relationship with hemodynamic effects. Excellent spatial colocalization of BOLD and β-activity in both central and lateral (MT) visual areas and sensorimotor areas suggests that the two are intimately related. In contrast to the BOLD response, the level of β-desynchronization is not modulated by stimulus contrast or by stimulus duration, consistent with a gating role. The amplitude of β-desynchronization in the central visual area is however modulated by drift frequency, and this seems to parallel the modulation in BOLD amplitude at the same location.

Local interneuron diversity in the primary olfactory center of the moth Manduca sexta

Local interneurons (LNs) play important roles in shaping and modulating the activity of output neurons in primary olfactory centers. Here, we studied the morphological characteristics, odor responses, and neurotransmitter content of LNs in the antennal lobe (AL, the insect primary olfactory center) of the moth Manduca sexta. We found that most LNs are broadly tuned, with all LNs responding to at least one odorant. 70% of the odorants evoked a response, and 22% of the neurons responded to all the odorants tested. Some LNs showed excitatory (35%) or inhibitory (33%) responses only, while 33% of the neurons showed both excitatory and inhibitory responses, depending on the odorant. LNs that only showed inhibitory responses were the most responsive, with 78% of the odorants evoking a response. Neurons were morphologically diverse, with most LNs innervating almost all glomeruli and others innervating restricted portions of the AL. 61 and 39% of LNs were identified as GABA-immunoreactive (GABA-ir) and non-GABA-ir, respectively. We found no correlations between odor responses and GABA-ir, neither between morphology and GABA-ir. These results show that, as observed in other insects, LNs are diverse, which likely determines the complexity of the inhibitory network that regulates AL output.

Using the structure of inhibitory networks to unravel mechanisms of spatiotemporal patterning

Neuronal networks exhibit a rich dynamical repertoire, a consequence of both the intrinsic properties of neurons and the structure of the network. It has been hypothesized that inhibitory interneurons corral principal neurons into transiently synchronous ensembles that encode sensory information and subserve behavior. How does the structure of the inhibitory network facilitate such spatiotemporal patterning? We established a relationship between an important structural property of a network, its colorings, and the dynamics it constrains. Using a model of the insect antennal lobe, we show that our description allows the explicit identification of the groups of inhibitory interneurons that switch, during odor stimulation, between activity and quiescence in a coordinated manner determined by features of the network structure. This description optimally matches the perspective of the downstream neurons looking for synchrony in ensembles of presynaptic cells and allows a low-dimensional description of seemingly complex high-dimensional network activity.

A model study on the circuit mechanism underlying decision-making in Drosophila

Previous elegant experiments in a flight simulator showed that conditioned Drosophila is able to make a clear-cut decision to avoid potential danger. When confronted with conflicting visual cues, the relative saliency of two competing cues is found to be a sensory ruler for flies to judge which cue should be used for decision-making. Further genetic manipulations and immunohistological analysis revealed that the dopamine system and mushroom bodies are indispensable for such a clear-cut or nonlinear decision. The neural circuit mechanism, however, is far from being clear. In this paper, we adopt a computational modeling approach to investigate how different brain areas and the dopamine system work together to drive a fly to make a decision. By developing a systems-level neural network, a two-pathway circuit is proposed. Besides a direct pathway from a feature binding area to the motor center, another connects two areas via the mushroom body, a target of dopamine release. A raised dopamine level is hypothesized to be induced by complex choice tasks and to enhance lateral inhibition and steepen the units' response gain in the mushroom body. Simulations show that training helps to assign values to formerly neutral features. For a circuit model with a blocked mushroom body, the direct pathway passes all alternatives to the motor center without changing original values, giving rise to a simple choice characterized by a linear choice curve. With respect to an intact circuit, enhanced lateral inhibition dependent on dopamine critically promotes competition between alternatives, turning the linear- into nonlinear choice behavior. Results account well for experimental data, supporting the reasonableness of model working hypotheses. Several testable predictions are made for future studies.

Brain organization and the roots of anticipation in Drosophila olfactory conditioning

Defining learning at the molecular and physiological level has been one of the greatest challenges in biology. Recent research suggests that by studying fruit fly (Drosophila melanogaster) brain organization we can now begin to unravel some of these mysteries. The fruit fly brain is organized into executive centers that regulate anatomically separate behavioral systems. The mushroom body is an example of an executive center which is modified by olfactory conditioning. During this simple form of learning, an odor is paired with either food or shock. Either experience alters distinguishable specific circuitry within the mushroom body. Results suggest that after conditioning an odor to food, the mushroom body will activate a feeding system via a subset of its circuitry. After conditioning an odor to shock, the mushroom body will instead activate an avoidance system with other subsets of mushroom body neurons. The results of these experiments demonstrate a mechanism for flies to display anticipation of their environment after olfactory conditioning has occurred. However, these results fail to provide evidence for reinforcement, a consequence of action, as part of this mechanism. Instead, specific subsets of dopaminergic and octopaminergic neurons provide a simple pairing signal, in contrast to a reinforcement signal, which allows for prediction of the environment after experience. This view has implications for models of conditioning.

Olfactory learning in Drosophila

Studies of olfactory learning in Drosophila have provided key insights into the brain mechanisms underlying learning and memory. One type of olfactory learning, olfactory classical conditioning, consists of learning the contingency between an odor with an aversive or appetitive stimulus. This conditioning requires the activity of molecules that can integrate the two types of sensory information, the odorant as the conditioned stimulus and the aversive or appetitive stimulus as the unconditioned stimulus, in brain regions where the neural pathways for the two stimuli intersect. Compelling data indicate that a particular form of adenylyl cyclase functions as a molecular integrator of the sensory information in the mushroom body neurons. The neuronal pathway carrying the olfactory information from the antennal lobes to the mushroom body is well described. Accumulating data now show that some dopaminergic neurons provide information about aversive stimuli and octopaminergic neurons about appetitive stimuli to the mushroom body neurons. Inhibitory inputs from the GABAergic system appear to gate olfactory information to the mushroom bodies and thus control the ability to learn about odors. Emerging data obtained by functional imaging procedures indicate that distinct memory traces form in different brain regions and correlate with different phases of memory. The results from these and other experiments also indicate that cross talk between mushroom bodies and several other brain regions is critical for memory formation.

Parasitoidism, not sociality, is associated with the evolution of elaborate mushroom bodies in the brains of hymenopteran insects

The social brain hypothesis posits that the cognitive demands of social behaviour have driven evolutionary expansions in brain size in some vertebrate lineages. In insects, higher brain centres called mushroom bodies are enlarged and morphologically elaborate (having doubled, invaginated and subcompartmentalized calyces that receive visual input) in social species such as the ants, bees and wasps of the aculeate Hymenoptera, suggesting that the social brain hypothesis may also apply to invertebrate animals. In a quantitative and qualitative survey of mushroom body morphology across the Hymenoptera, we demonstrate that large, elaborate mushroom bodies arose concurrent with the acquisition of a parasitoid mode of life at the base of the Euhymenopteran (Orussioidea + Apocrita) lineage, approximately 90 Myr before the evolution of sociality in the Aculeata. Thus, sociality could not have driven mushroom body elaboration in the Hymenoptera. Rather, we propose that the cognitive demands of host-finding behaviour in parasitoids, particularly the capacity for associative and spatial learning, drove the acquisition of this evolutionarily novel mushroom body architecture. These neurobehavioural modifications may have served as pre-adaptations for central place foraging, a spatial learning-intensive behaviour that is widespread across the Aculeata and may have contributed to the multiple acquisitions of sociality in this taxon.