Feedback Neurons Research Articles

Mosaic evolution of a learning and memory circuit in Heliconiini butterflies.

How do neural circuits accommodate changes that produce cognitive variation? We explore this question by analyzing the evolutionary dynamics of an insect learning and memory circuit centered within the mushroom body. Mushroom bodies are composed of a conserved wiring logic, mainly consisting of Kenyon cells, dopaminergic neurons, and mushroom body output neurons. Despite this conserved makeup, there is huge diversity in mushroom body size and shape across insects. However, empirical data on how evolution modifies the function and architecture of this circuit are largely lacking. To address this, we leverage the recent radiation of a Neotropical tribe of butterflies, the Heliconiini (Nymphalidae), which show extensive variation in mushroom body size over comparatively short phylogenetic timescales, linked to specific changes in foraging ecology, life history, and cognition. To understand how such an extensive increase in size is accommodated through changes in lobe circuit architecture, we combined immunostainings of structural markers, neurotransmitters, and neural injections to generate new, quantitative anatomies of the Nymphalid mushroom body lobe. Our comparative analyses across Heliconiini demonstrate that some Kenyon cell sub-populations expanded at higher rates than others in Heliconius and identify an additional increase in GABA-ergic feedback neurons, which are essential for non-elemental learning and sparse coding. Taken together, our results demonstrate mosaic evolution of functionally related neural systems and cell types and identify that evolutionary malleability in an architecturally conserved parallel circuit guides adaptation in cognitive ability.

Visual feedback neurons fine-tune Drosophila male courtship via GABA-mediated inhibition

Many species of animals use vision to regulate their social behaviors. However, the molecular and circuit mechanisms underlying visually guided social interactions remain largely unknown. Here, we show that the Drosophila ortholog of the human GABAA-receptor-associated protein (GABARAP) is required in a class of visual feedback neurons, lamina tangential (Lat) cells, to fine-tune male courtship. GABARAP is a ubiquitin-like protein that maintains cell-surface levels of GABAA receptors. We demonstrate that knocking down GABARAP or GABAAreceptors in Lat neurons or hyperactivating them induces male courtship toward other males. Inhibiting Lat neurons, on the other hand, delays copulation by impairing the ability of males to follow females. Remarkably, the fly GABARAP protein and its human ortholog share a strong sequence identity, and the fly GABARAP function in Lat neurons can be rescued by its human ortholog. Using invivo two-photon imaging and optogenetics, we reveal that Lat neurons are functionally connected to neural circuits that mediate visually guided courtship pursuits in males. Our work identifies a novel physiological function for GABARAP in regulating visually guided courtship pursuits in Drosophila males. Reduced GABAA signaling has been linked to social deficits observed in the autism spectrum and bipolar disorders. The functional similarity between the human and the fly GABARAP raises the possibility of a conserved role for this gene in regulating social behaviors across insects and mammals.

Bulbar projecting subcortical GABAergic neurons send collateral branches extensively and selectively to primary olfactory cortical regions.

Circuit operations of the olfactory bulb are modulated by higher order projections from multiple regions, many of which are themselves targets of bulbar output. Multiple glutamatergic regions project to the olfactory bulb, including the anterior olfactory nucleus (AON), prefrontal cortex (PFC), piriform cortex (PC), entorhinal cortex (EC), and tenia tecta (TT). In contrast, only one region provides GABAergic projections to the bulb. These GABA neurons are located in the horizontal limb of the diagonal band of Broca extending posteriorly through the magnocellular preoptic nucleus to the nucleus of the lateral olfactory bulb. However, it was unclear whether bulbar projecting GABAergic neurons collaterallize projecting to other brain regions. To address this, we mapped collateral projections from bulbar projecting GABAergic neurons using intersectional strategies of viral and traditional tract tracers. This approach revealed bulbar projecting GABAergic neurons show remarkable specificity targeting other primary olfactory cortical regions exhibiting abundant collateral projections into the accessory olfactory bulb, AON, PFC, PC, and TT. The only "nonolfactory" region receiving collateral projections was sparse connectivity to the medial prefrontal orbital cortex. This suggests that basal forebrain inhibitory feedback also modulates glutamatergic feedback areas that are themselves prominent bulbar projection regions. Thus, inhibitory feedback may be simultaneously modulating both synaptic processing of olfactory information in the bulb and associational processing of olfactory information from primary olfactory cortex. We hypothesize that these olfactory GABAergic feedback neurons are a regulator of the entire olfactory system.

Bayesian Integration in a Spiking Neural System for Sensorimotor Control.

The brain continuously estimates the state of body and environment, with specific regions that are thought to act as Bayesian estimator, optimally integrating noisy and delayed sensory feedback with sensory predictions generated by the cerebellum. In control theory, Bayesian estimators are usually implemented using high-level representations. In this work, we designed a new spike-based computational model of a Bayesian estimator. The state estimator receives spiking activity from two neural populations encoding the sensory feedback and the cerebellar prediction, and it continuously computes the spike variability within each population as a reliability index of the signal these populations encode. The state estimator output encodes the current state estimate. We simulated a reaching task at different stages of cerebellar learning. The activity of the sensory feedback neurons encoded a noisy version of the trajectory after actual movement, with an almost constant intrapopulation spiking variability. Conversely, the activity of the cerebellar output neurons depended on the phase of the learning process. Before learning, they fired at their baseline not encoding any relevant information, and the variability was set to be higher than that of the sensory feedback (more reliable, albeit delayed). When learning was complete, their activity encoded the trajectory before the actual execution, providing an accurate sensory prediction; in this case, the variability was set to be lower than that of the sensory feedback. The state estimator model optimally integrated the neural activities of the afferent populations, so that the output state estimate was primarily driven by sensory feedback in prelearning and by the cerebellar prediction in postlearning. It was able to deal even with more complex scenarios, for example, by shifting the dominant source during the movement execution if information availability suddenly changed. The proposed tool will be a critical block within integrated spiking, brain-inspired control systems for simulations of sensorimotor tasks.

Contrastive Similarity Matching for Supervised Learning

We propose a novel biologically plausible solution to the credit assignment problem motivated by observations in the ventral visual pathway and trained deep neural networks. In both, representations of objects in the same category become progressively more similar, while objects belonging to different categories become less similar. We use this observation to motivate a layer-specific learning goal in a deep network: each layer aims to learn a representational similarity matrix that interpolates between previous and later layers. We formulate this idea using a contrastive similarity matching objective function and derive from it deep neural networks with feedforward, lateral, and feedback connections and neurons that exhibit biologically plausible Hebbian and anti-Hebbian plasticity. Contrastive similarity matching can be interpreted as an energy-based learning algorithm, but with significant differences from others in how a contrastive function is constructed.

Characterization of Feedback Neurons in the High-Level Visual Cortical Areas That Project Directly to the Primary Visual Cortex in the Cat

Previous studies indicate that top-down influence plays a critical role in visual information processing and perceptual detection. However, the substrate that carries top-down influence remains poorly understood. Using a combined technique of retrograde neuronal tracing and immunofluorescent double labeling, we characterized the distribution and cell type of feedback neurons in cat’s high-level visual cortical areas that send direct connections to the primary visual cortex (V1: area 17). Our results showed: (1) the high-level visual cortex of area 21a at the ventral stream and PMLS area at the dorsal stream have a similar proportion of feedback neurons back projecting to the V1 area, (2) the distribution of feedback neurons in the higher-order visual area 21a and PMLS was significantly denser than in the intermediate visual cortex of area 19 and 18, (3) feedback neurons in all observed high-level visual cortex were found in layer II–III, IV, V, and VI, with a higher proportion in layer II–III, V, and VI than in layer IV, and (4) most feedback neurons were CaMKII-positive excitatory neurons, and few of them were identified as inhibitory GABAergic neurons. These results may argue against the segregation of ventral and dorsal streams during visual information processing, and support “reverse hierarchy theory” or interactive model proposing that recurrent connections between V1 and higher-order visual areas constitute the functional circuits that mediate visual perception. Also, the corticocortical feedback neurons from high-level visual cortical areas to the V1 area are mostly excitatory in nature.

Lamina feedback neurons regulate the bandpass property of the flicker-induced orientation response in Drosophila.

Natural scenes contain complex visual cues with specific features, including color, motion, flicker, and position. It is critical to understand how different visual features are processed at the early stages of visual perception to elicit appropriate cellular responses, and even behavioral output. Here, we studied the visual orientation response induced by flickering stripes in a novel behavioral paradigm in Drosophila melanogaster. We found that free walking flies exhibited bandpass orientation response to flickering stripes of different frequencies. The most sensitive frequency spectrum was confined to low frequencies of 2-4Hz. Through genetic silencing, we showed that lamina L1 and L2 neurons, which receive visual inputs from R1 to R6 neurons, were the main components in mediating flicker-induced orientation behavior. Moreover, specific blocking of different types of lamina feedback neurons Lawf1, Lawf2, C2, C3, and T1 modulated orientation responses to flickering stripes of particular frequencies, suggesting that bandpass orientation response was generated through cooperative modulation of lamina feedback neurons. Furthermore, we found that lamina feedback neurons Lawf1 were glutamatergic. Thermal activation of Lawf1 neurons could suppress neural activities in L1 and L2 neurons, which could be blocked by the glutamate-gated chloride channel inhibitor picrotoxin (PTX). In summary, lamina monopolar neurons L1 and L2 are the primary components in mediating flicker-induced orientation response. Meanwhile, lamina feedback neurons cooperatively modulate the orientation response in a frequency-dependent way, which might be achieved through modulating neural activities of L1 and L2 neurons.

Separate But Interactive Parallel Olfactory Processing Streams Governed by Different Types of GABAergic Feedback Neurons in the Mushroom Body of a Basal Insect.

The basic organization of the olfactory system has been the subject of extensive studies in vertebrates and invertebrates. In many animals, GABA-ergic neurons inhibit spike activities of higher-order olfactory neurons and help sparsening of their odor representations. In the cockroach, two different types of GABA-immunoreactive interneurons (calyceal giants [CGs]) mainly project to the base and lip regions of the calyces (input areas) of the mushroom body (MB), a second-order olfactory center. The base and lip regions receive axon terminals of two different types of projection neurons, which receive synapses from different classes of olfactory sensory neurons (OSNs), and receive dendrites of different classes of Kenyon cells, MB intrinsic neurons. We performed intracellular recordings from pairs of CGs and MB output neurons (MBONs) of male American cockroaches, the latter receiving synapses from Kenyon cells, and we found that a CG receives excitatory synapses from an MBON and that odor responses of the MBON are changed by current injection into the CG. Such feedback effects, however, were often weak or absent in pairs of neurons that belong to different streams, suggesting parallel organization of the recurrent pathways, although interactions between different streams were also evident. Cross-covariance analysis of the spike activities of CGs and MBONs suggested that odor stimulation produces synchronized spike activities in MBONs and then in CGs. We suggest that there are separate but interactive parallel streams to process odors detected by different OSNs throughout the olfactory processing system in cockroaches.SIGNIFICANCE STATEMENT Organizational principles of the olfactory system have been the subject of extensive studies. In cockroaches, signals from olfactory sensory neurons (OSNs) in two different classes of sensilla are sent to two different classes of projection neurons, which terminate in different areas of the mushroom body (MB), each area having dendrites of different classes of MB intrinsic neurons (Kenyon cells) and terminations of different classes of GABAergic neurons. Physiological and morphological assessments derived from simultaneous intracellular recordings/stainings from GABAergic neurons and MB output neurons suggested that GABAergic neurons play feedback roles and that odors detected by OSNs are processed in separate but interactive processing streams throughout the central olfactory system.

Modeling Interval Timing by Recurrent Neural Nets.

The purpose of this study was to take a new approach in showing how the central nervous system might encode time at the supra-second level using recurrent neural nets (RNNs). This approach utilizes units with a delayed feedback, whose feedback weight determines the temporal properties of specific neurons in the network architecture. When these feedback neurons are coupled, they form a multilayered dynamical system that can be used to model temporal responses to steps of input in multidimensional systems. The timing network was implemented using separate recurrent “Go” and “No-Go” neural processing units to process an individual stimulus indicating the time of reward availability. Outputs from these distinct units on each time step are converted to a pulse reflecting a weighted sum of the separate Go and No-Go signals. This output pulse then drives an integrator unit, whose feedback weight and input weights shape the pulse distribution. This system was used to model empirical data from rodents performing in an instrumental “peak interval timing” task for two stimuli, Tone and Flash. For each of these stimuli, reward availability was signaled after different times from stimulus onset during training. Rodent performance was assessed on non-rewarded trials, following training, with each stimulus tested individually and simultaneously in a stimulus compound. The associated weights in the Go/No-Go network were trained using experimental data showing the mean distribution of bar press rates across an 80 s period in which a tone stimulus signaled reward after 5 s and a flash stimulus after 30 s from stimulus onset. Different Go/No-Go systems were used for each stimulus, but the weighted output of each fed into a final recurrent integrator unit, whose weights were unmodifiable. The recurrent neural net (RNN) model was implemented using Matlab and Matlab’s machine learning tools were utilized to train the network using the data from non-rewarded trials. The neural net output accurately fit the temporal distribution of tone and flash-initiated bar press data. Furthermore, a “Temporal Averaging” effect was also obtained when the flash and tone stimuli were combined. These results indicated that the system combining tone and flash responses were not superposed as in a linear system, but that there was a non-linearity, which interacted between tone and flash. In order to achieve an accurate fit to the empirical averaging data it was necessary to implement non-linear “saliency functions” that limited the output signal of each stimulus to the final integrator when the other was co-present. The model suggests that the central nervous system encodes timing generation as a dynamical system whose timing properties are embedded in the connection weights of the system. In this way, event timing is coded similar to the way other sensory-motor systems, such as the vestibulo-ocular and optokinetic systems, which combine sensory inputs from the vestibular and visual systems to generate the temporal aspects of compensatory eye movements.

Regulation of forward and backward locomotion through intersegmental feedback circuits in Drosophila larvae

Animal locomotion requires spatiotemporally coordinated contraction of muscles throughout the body. Here, we investigate how contractions of antagonistic groups of muscles are intersegmentally coordinated during bidirectional crawling of Drosophila larvae. We identify two pairs of higher-order premotor excitatory interneurons present in each abdominal neuromere that intersegmentally provide feedback to the adjacent neuromere during motor propagation. The two feedback neuron pairs are differentially active during either forward or backward locomotion but commonly target a group of premotor interneurons that together provide excitatory inputs to transverse muscles and inhibitory inputs to the antagonistic longitudinal muscles. Inhibition of either feedback neuron pair compromises contraction of transverse muscles in a direction-specific manner. Our results suggest that the intersegmental feedback neurons coordinate contraction of synergistic muscles by acting as delay circuits representing the phase lag between segments. The identified circuit architecture also shows how bidirectional motor networks could be economically embedded in the nervous system.

Morphology of visual projection neurons supplying premotor area in the brain of the silkmoth Bombyx mori.

Sex pheromones orient male moths toward conspecific female moths; the presence of visual information modulates this behavior. In the current study, we explore candidate neuronal pathways for the interaction between vision and the locomotor signal for pheromone orientation. We describe the connectivity between visual neuropils and brain premotor centers, the posterior slope (PS) and the lateral accessory lobe (LAL), in the silkmoth Bombyx mori. Using a single-cell labeling technique, we analyze visual projection neurons supplying these areas. Neurons from both the medulla and lobula complex projected to the PS but only the neurons originating in the lobula complex had additional processes to the LAL. Further, we identified populations of putative feedback neurons from the premotor centers to the optic lobe. Neurons originating in the PS were likely to project to the medulla, whereas those originating in the LAL were likely to project to the lobula complex. The anatomical study contributes to further understanding of integration of visual information on the locomotor control in the insect brain.

Neural Organization of A3 Mushroom Body Extrinsic Neurons in the Honeybee Brain.

In the insect brain, the mushroom body is a higher order brain area that is key to memory formation and sensory processing. Mushroom body (MB) extrinsic neurons leaving the output region of the MB, the lobes and the peduncle, are thought to be especially important in these processes. In the honeybee brain, a distinct class of MB extrinsic neurons, A3 neurons, are implicated in playing a role in learning. Their MB arborisations are either restricted to the lobes and the peduncle, here called A3 lobe connecting neurons, or they provide feedback information from the lobes to the input region of the MB, the calyces, here called A3 feedback neurons. In this study, we analyzed the morphology of individual A3 lobe connecting and feedback neurons using confocal imaging. A3 feedback neurons were previously assumed to innervate each lip compartment homogenously. We demonstrate here that A3 feedback neurons do not innervate whole subcompartments, but rather innervate zones of varying sizes in the MB lip, collar, and basal ring. We describe for the first time the anatomical details of A3 lobe connecting neurons and show that their connection pattern in the lobes resemble those of A3 feedback cells. Previous studies showed that A3 feedback neurons mostly connect zones of the vertical lobe that receive input from Kenyon cells of distinct calycal subcompartments with the corresponding subcompartments of the calyces. We can show that this also applies to the neck of the peduncle and the medial lobe, where both types of A3 neurons arborize only in corresponding zones in the calycal subcompartments. Some A3 lobe connecting neurons however connect multiple vertical lobe areas. Contrarily, in the medial lobe, the A3 neurons only innervate one division. We found evidence for both input and output areas in the vertical lobe. Thus, A3 neurons are more diverse than previously thought. The understanding of their detailed anatomy might enable us to derive circuit models for learning and memory and test physiological data.

A Non-canonical Feedback Circuit for Rapid Interactions between Somatosensory Cortices

SUMMARYSensory perception depends on interactions among cortical areas. These interactions are mediated by canonical patterns of connectivity in which higher areas send feedback projections to lower areas via neurons in superficial and deep layers. Here, we probed the circuit basis of interactions among two areas critical for touch perception in mice, whisker primary (wS1) and secondary (wS2) somatosensory cortices. Neurons in layer 4 of wS2 (S2L4) formed a major feedback pathway to wS1. Feedback from wS2 to wS1 was organized somatotopically. Spikes evoked by whisker deflections occurred nearly as rapidly in wS2 as in wS1, including among putative S2L4 → S1 feedback neurons. Axons from S2L4 → S1 neurons sent stimulus orientation-specific activity to wS1. Optogenetic excitation of S2L4 neurons modulated activity across both wS2 and wS1, while inhibition of S2L4 reduced orientation tuning among wS1 neurons. Thus, a non-canonical feedback circuit, originating in layer 4 of S2, rapidly modulates early tactile processing.

Feature-Specific Organization of Feedback Pathways in Mouse Visual Cortex

Higher and lower cortical areas in the visual hierarchy are reciprocally connected [1]. Although much is known about how feedforward pathways shape receptive field properties of visual neurons, relatively little is known about the role of feedback pathways in visual processing. Feedback pathways are thought to carry top-down signals, including information about context (e.g., figure-ground segmentation and surround suppression) [2-5], and feedback has been demonstrated to sharpen orientation tuning of neurons in the primary visual cortex (V1) [6, 7]. However, the response characteristics of feedback neurons themselves and how feedback shapes V1 neurons' tuning for other features, such as spatial frequency (SF), remain largely unknown. Here, using a retrograde virus, targeted electrophysiological recordings, and optogenetic manipulations, we show that putatively feedback neurons in layer 5 (hereafter "L5 feedback") in higher visual areas, AL (anterolateral area) and PM (posteromedial area), display distinct visual properties in awake head-fixed mice. AL L5 feedback neurons prefer significantly lower SF (mean: 0.04 cycles per degree [cpd]) compared to PM L5 feedback neurons (0.15 cpd). Importantly, silencing AL L5 feedback reduced visual responses of V1 neurons preferringlow SF (mean change in firing rate: -8.0%), whereas silencing PM L5 feedback suppressed responses of high-SF-preferring V1 neurons (-20.4%). These findings suggest that feedback connections from higher visual areas convey distinctly tuned visual inputs to V1 that serve to boost V1 neurons' responses to SF. Such like-to-like functional organization may represent animportant feature of feedback pathways in sensorysystems and in the nervous system in general.

Long-range population dynamics of anatomically defined neocortical networks.

The coordination of activity across neocortical areas is essential for mammalian brain function. Understanding this process requires simultaneous functional measurements across the cortex. In order to dissociate direct cortico-cortical interactions from other sources of neuronal correlations, it is furthermore desirable to target cross-areal recordings to neuronal subpopulations that anatomically project between areas. Here, we combined anatomical tracers with a novel multi-area two-photon microscope to perform simultaneous calcium imaging across mouse primary (S1) and secondary (S2) somatosensory whisker cortex during texture discrimination behavior, specifically identifying feedforward and feedback neurons. We find that coordination of S1-S2 activity increases during motor behaviors such as goal-directed whisking and licking. This effect was not specific to identified feedforward and feedback neurons. However, these mutually projecting neurons especially participated in inter-areal coordination when motor behavior was paired with whisker-texture touches, suggesting that direct S1-S2 interactions are sensory-dependent. Our results demonstrate specific functional coordination of anatomically-identified projection neurons across sensory cortices.

Spatially segregated feedforward and feedback neurons support differential odor processing in the lateral entorhinal cortex.

The lateral entorhinal cortex (LEC) computes and transfers olfactory information from the olfactory bulb to the hippocampus. Here we established LEC connectivity to upstream and downstream brain regions to understand how the LEC processes olfactory information. We report that, in layer II (LII), reelin- and calbindin-positive (RE(+) and CB(+)) neurons constitute two major excitatory cell types that are electrophysiologically distinct and differentially connected. RE(+) neurons convey information to the hippocampus, while CB(+) neurons project to the olfactory cortex and the olfactory bulb. In vivo calcium imaging revealed that RE(+) neurons responded with higher selectivity to specific odors than CB(+) neurons and GABAergic neurons. At the population level, odor discrimination was significantly better for RE(+) than CB(+) neurons, and was lowest for GABAergic neurons. Thus, we identified in LII of the LEC anatomically and functionally distinct neuronal subpopulations that engage differentially in feedforward and feedback signaling during odor processing.

Morphological Substrates for Parallel Streams of Corticogeniculate Feedback Originating in Both V1 and V2 of the Macaque Monkey

Corticothalamic circuits are essential for reciprocal information exchange between the thalamus and cerebral cortex. Nevertheless, the role of corticothalamic circuits in sensory processing remains a mystery. In the visual system, afferents from retina to the lateral geniculate nucleus (LGN) and from LGN to primary visual cortex (V1) are organized into functionally distinct parallel processing streams. Physiological evidence suggests corticogeniculate feedback may be organized into parallel streams; however, little is known about the diversity of corticogeniculate neurons, their local computations, or the structure-function relationship among corticogeniculate neurons. We used a virus-mediated approach to label and reconstruct the complete dendritic and local axonal arbors of identified corticogeniculate neurons in the macaque monkey. Our results reveal morphological substrates for parallel streams of corticogeniculate feedback based on distinct classes of neurons in V1 and V2. These results support the hypothesis that distinct populations of feedback neurons provide independent and unique information to the LGN.

A neurocognitive approach to recovery of movement following stroke

Background: Most of the therapeutic and research interest following stroke has been directed toward motor impairments, relegating sensory and cognitive aspects involved in the quality of movement to a secondary role. Despite current neurophysiological advances, there are few studies in physical therapy that include all these aspects in stroke patients.Objectives: The present work aimed to review the involvement of mirror neurons in recovering the quality of post-ictal movement in a physical therapy intervention.Major findings: Neurocognitive Therapeutic Exercise (NTE) is a therapeutic approach that includes observation and motor imagery, among others, as perceptual and cognitive functions that generate experiences and afferent information flows without motor activity. Although this approach has shown to be effective on pain and function in shoulder and knee disorders, there is a paucity of evidence in stroke. NTE considers recovery as a learning process, the movement as a means to know and the body as a surface receptor for information. Aspects such as increasing experience, feedback or mirror neurons’ functions are used to allow movements to be improved quantitatively and qualitatively. This could be achieved through the activation of pre-existing neural patterns before the stroke.Conclusions: The neurocognitive approach represents a novel and safe therapeutic intervention supported by neuroscience research. Its implementation in physical therapy could facilitate motor learning in stroke patients. Nevertheless, further research into cognitive strategies in neurological rehabilitation is required to demonstrate their effectiveness.

Neural substrate for higher-order learning in an insect: Mushroom bodies are necessary for configural discriminations

Learning theories distinguish elemental from configural learning based on their different complexity. Although the former relies on simple and unambiguous links between the learned events, the latter deals with ambiguous discriminations in which conjunctive representations of events are learned as being different from their elements. In mammals, configural learning is mediated by brain areas that are either dispensable or partially involved in elemental learning. We studied whether the insect brain follows the same principles and addressed this question in the honey bee, the only insect in which configural learning has been demonstrated. We used a combination of conditioning protocols, disruption of neural activity, and optophysiological recording of olfactory circuits in the bee brain to determine whether mushroom bodies (MBs), brain structures that are essential for memory storage and retrieval, are equally necessary for configural and elemental olfactory learning. We show that bees with anesthetized MBs distinguish odors and learn elemental olfactory discriminations but not configural ones, such as positive and negative patterning. Inhibition of GABAergic signaling in the MB calyces, but not in the lobes, impairs patterning discrimination, thus suggesting a requirement of GABAergic feedback neurons from the lobes to the calyces for nonelemental learning. These results uncover a previously unidentified role for MBs besides memory storage and retrieval: namely, their implication in the acquisition of ambiguous discrimination problems. Thus, in insects as in mammals, specific brain regions are recruited when the ambiguity of learning tasks increases, a fact that reveals similarities in the neural processes underlying the elucidation of ambiguous tasks across species.

Olfactory pathway in Xibalbanus tulumensis: remipedian hemiellipsoid body as homologue of hexapod mushroom body.

The Remipedia have been proposed to be the crustacean sister group of the Hexapoda. These blind cave animals heavily rely on their chemical sense and are thus rewarding subjects for the analysis of olfactory pathways. The evolution of these pathways as a character for arthropod phylogeny has recently received increasing attention. Here, we investigate the situation in Xibalbanus tulumensis by focal dye injections and immunolabelling of the catalytic subunit of the cAMP-dependent protein kinase (DC0), an enzyme particularly enriched in insect mushroom bodies. DC0 labelling of the hemiellipsoid body suggests its subdivision into a cap-like and a core neuropil. Immunofluorescence of the enzyme glutamic acid decarboxylase (GAD), which synthesizes γ-aminobutyric acid (GABA), has revealed a cluster of GABAergic interneurons in the hemiellipsoid body, reminiscent of the characteristic feedback neurons of the mushroom body. Thus, the hemiellipsoid body of Xibalbanus shares many of the characteristics of insect mushroom bodies. Nevertheless, the general neuroanatomy of the olfactory pathway in the Remipedia strongly corresponds to the malacostracan ground pattern. Given that the Remipedia are probably the sister group of the Hexapoda, the phylogenetic appearance of the typical neuropilar compartments in the insect mushroom body has to be assigned to the origins of the Hexapoda.