Modeling the Temperature-Dependent Size Change of Polydisperse Nano-objects using a Deep Generative Model.

Modern microscopy techniques can be used to investigate soft nano-objects at the nanometer scale. However, time-consuming microscopy measurements combined with low numbers of observable polydisperse objects often limit the statistics. We propose a method for identifying the most representative objects from their respective point clouds. These point cloud data are obtained, for example, through the localization of single emitters in super-resolution fluorescence microscopy. External stimuli, such as temperature, can cause changes in the shape and properties of adaptive objects. Due to the demanding and time-consuming nature of super-resolution microscopy experiments, only a limited number of temperature steps can be performed. Therefore, we propose a deep generative model that learns the underlying point distribution of temperature-dependent microgels, enabling the reliable generation of unlimited samples with an arbitrary number of localizations. Our method greatly cuts down the data collection effort across diverse experimental conditions, proving invaluable for soft condensed matter studies.

A revised conceptual framework for mouse vomeronasal pumping and stimulus sampling.

The physiological performance of any sensory organ is determined by its anatomy and physical properties. Consequently, complex sensory structures with elaborate features have evolved to optimize stimulus detection. Understanding these structures and their physical nature forms the basis for mechanistic insights into sensory function. Despite its crucial role as a sensor for pheromones and other behaviorally instructive chemical cues, the vomeronasal organ (VNO) remains a poorly characterized mammalian sensory structure. Fundamental principles of its physico-mechanical function, including basic aspects of stimulus sampling, remain poorly explored. Here, we revisit the classical vasomotor pump hypothesis of vomeronasal stimulus uptake. Using advanced anatomical, histological, and physiological methods, we demonstrate that large parts of the lateral mouse VNO are composed of smooth muscle. Vomeronasal smooth muscle tissue comprises two subsets of fibers with distinct topography, structure, excitation-contraction coupling, and, ultimately, contractile properties. Specifically, contractions of a large population of noradrenaline-sensitive cells mediate both transverse and longitudinal lumen expansion, whereas cholinergic stimulation targets an adluminal group of smooth muscle fibers. The latter run parallel to the VNO's rostro-caudal axis and are ideally situated to mediate antagonistic longitudinal constriction of the lumen. This newly discovered arrangement implies a novel mode of function. Single-cell transcriptomics and pharmacological profiling reveal the receptor subtypes involved. Finally, 2D/3D tomography provides non-invasive insight into the intact VNO's anatomy and mechanics, enables measurement of luminal fluid volume, and allows an assessment of relative volume change upon noradrenergic stimulation. Together, we propose a revised conceptual framework for mouse vomeronasal pumping and, thus, stimulus sampling.

The intra- and inter-rater reproducibility of bone level measurements at strategic mini-implants using dental panoramic radiography.

OBJECTIVES: This experimental study focused on the intra- and inter-rater reproducibility of vertical bone level (VBL) measurements at strategic mini-implants (MI) using digital panoramic radiographs (PR). STUDY DESIGN: VBLs of 152 MIs for removable partial denture stabilization at 50 randomly chosen PRs from a clinical trial were digitally evaluated by three ratters. Rater deviations exceeding 0.5 mm were re-examined. The intra-class correlation coefficient (ICC) was applied to estimate reliability. The smallest detectable change (SDC) was interrelated to the minimal clinically important change of 0.2 mm. RESULTS: The first measurement round revealed intra- and inter-rater ICCs of > 0.8. However, 28 sites (9 %) were unreadable, and 97 sites (32 %) revealed differences between observers of ≥ 0.5 mm. Following a consensus session and re-training, an additional 8 sites were excluded and all remaining VBL differences were ≤ 0.5 mm. Thus, the SDCs with 95 % credibility were improved from 0.73 to 0.31 mm in the intra-rater and from 1.52 to 0.34 mm in the inter-rater statistics. Given a 50 % credibility for this special setting, both the intra- and inter-rater SDCs were 0.11 mm. CONCLUSIONS: Digital PR can be reliably utilized to determine VBLs around MIs under conditions of at least two trained observers, mutual calibration sessions, and exclusion of unquantifiable radiographs. GERMAN CLINICAL TRIALS REGISTER ID: DRKS00007589, www.germanctr.de.

The intra- and inter-rater reproducibility of bone level measurements at strategic mini-implants using dental panoramic radiography

Abstract Objectives: This experimental study focused on the intra- and inter-rater reproducibility of vertical bone level (VBL) measurements at strategic mini-implants (MI) using digital panoramic radiographs (PR). Study design: VBLs of 152 MIs for removable partial denture stabilization at 50 randomly chosen PRs from a clinical trial were digitally evaluated by three ratters. Rater deviations exceeding 0.5 mm were re-examined. The intra-class correlation coefficient (ICC) was applied to estimate reliability. The smallest detectable change (SDC) was interrelated to the minimal clinically important change of 0.2 mm. Results: The first measurement round revealed intra- and inter-rater ICCs of > 0.8. However, 28 sites (9 %) were unreadable, and 97 sites (32 %) revealed differences between observers of ≥ 0.5 mm. Following a consensus session and re-training, an additional 8 sites were excluded and all remaining VBL differences were ≤ 0.5 mm. Thus, the SDCs with 95 % credibility were improved from 0.73 to 0.31 mm in the intra-rater and from 1.52 to 0.34 mm in the interrater statistics. Given a 50 % credibility for this special setting, both the intra- and inter-rater SDCs were 0.11 mm. Conclusions: Digital PR can be reliably utilized to determine VBLs around MIs under conditions of at least two trained observers, mutual calibration sessions, and exclusion of unquantifiable radiographs. German Clinical Trials Register ID:DRKS00007589, www.germanctr.de

Rewarding Capacity of Optogenetically Activating a Giant GABAergic Central-Brain Interneuron in Larval Drosophila.

Larvae of the fruit fly Drosophila melanogaster are a powerful study case for understanding the neural circuits underlying behavior. Indeed, the numerical simplicity of the larval brain has permitted the reconstruction of its synaptic connectome, and genetic tools for manipulating single, identified neurons allow neural circuit function to be investigated with relative ease and precision. We focus on one of the most complex neurons in the brain of the larva (of either sex), the GABAergic anterior paired lateral neuron (APL). Using behavioral and connectomic analyses, optogenetics, Ca2+ imaging, and pharmacology, we study how APL affects associative olfactory memory. We first provide a detailed account of the structure, regional polarity, connectivity, and metamorphic development of APL, and further confirm that optogenetic activation of APL has an inhibiting effect on its main targets, the mushroom body Kenyon cells. All these findings are consistent with the previously identified function of APL in the sparsening of sensory representations. To our surprise, however, we found that optogenetically activating APL can also have a strong rewarding effect. Specifically, APL activation together with odor presentation establishes an odor-specific, appetitive, associative short-term memory, whereas naive olfactory behavior remains unaffected. An acute, systemic inhibition of dopamine synthesis as well as an ablation of the dopaminergic pPAM neurons impair reward learning through APL activation. Our findings provide a study case of complex circuit function in a numerically simple brain, and suggest a previously unrecognized capacity of central-brain GABAergic neurons to engage in dopaminergic reinforcement.SIGNIFICANCE STATEMENT The single, identified giant anterior paired lateral (APL) neuron is one of the most complex neurons in the insect brain. It is GABAergic and contributes to the sparsening of neuronal activity in the mushroom body, the memory center of insects. We provide the most detailed account yet of the structure of APL in larval Drosophila as a neurogenetically accessible study case. We further reveal that, contrary to expectations, the experimental activation of APL can exert a rewarding effect, likely via dopaminergic reward pathways. The present study both provides an example of unexpected circuit complexity in a numerically simple brain, and reports an unexpected effect of activity in central-brain GABAergic circuits.

High-throughput phenotyping of nematode cysts.

The beet cyst nematode Heterodera schachtii is a plant pest responsible for crop loss on a global scale. Here, we introduce a high-throughput system based on computer vision that allows quantifying beet cyst nematode infestation and measuring phenotypic traits of cysts. After recording microscopic images of soil sample extracts in a standardized setting, an instance segmentation algorithm serves to detect nematode cysts in these images. In an evaluation using both ground truth samples with known cyst numbers and manually annotated images, the computer vision approach produced accurate nematode cyst counts, as well as accurate cyst segmentations. Based on such segmentations, cyst features could be computed that served to reveal phenotypical differences between nematode populations in different soils and in populations observed before and after the sugar beet planting period. The computer vision approach enables not only fast and precise cyst counting, but also phenotyping of cyst features under different conditions, providing the basis for high-throughput applications in agriculture and plant breeding research. Source code and annotated image data sets are freely available for scientific use.

Learning to Segment Fine Structures Under Image-Level Supervision With an Application to Nematode Segmentation.

Image segmentation models trained only with image-level labels have become increasingly popular as they require significantly less annotation effort than models trained with scribble, bounding box or pixel-wise annotations. While methods utilizing image-level labels achieve promising performance for the segmentation of larger-scale objects, they perform less well for the fine structures frequently encountered in biological images. In order to address this performance gap, we propose a deep network architecture based on two key principles, Global Weighted Pooling (GWP) and segmentation refinement by low-level image cues, that, together, make segmentation of fine structures possible. We apply our segmentation method to image datasets containing such fine structures, nematodes (worms + eggs) and nematode cysts immersed in organic debris objects, which is an application scenario encountered in automated soil sample screening. Supervised only with image-level labels, our approach achieves Dice coefficients of 79.72% and 58.51 % for nematode and nematode cyst segmentation, respectively.

Mosquito brains encode unique features of human odour to drive host seeking.

A globally invasive form of the mosquito Aedes aegypti specializes in biting humans, making it an efficient disease vector1. Host-seeking female mosquitoes strongly prefer human odour over the odour of animals2,3, but exactly how they distinguish between the two is not known. Vertebrate odours are complex blends of volatile chemicals with many shared components4-7, making discrimination an interesting sensory coding challenge. Here we show that human and animal odours evoke activity in distinct combinations of olfactory glomeruli within the Ae. aegypti antennal lobe. One glomerulus in particular is strongly activated by human odour but responds weakly, or not at all, to animal odour. This human-sensitive glomerulus is selectively tuned to the long-chain aldehydes decanal and undecanal, which we show are consistently enriched in human odour and which probably originate from unique human skin lipids. Using synthetic blends, we further demonstrate that signalling in the human-sensitive glomerulus significantly enhances long-range host-seeking behaviour in a wind tunnel, recapitulating preference for human over animal odours. Our research suggests that animal brains may distil complex odour stimuli of innate biological relevance into simple neural codes and reveals targets for the design of next-generation mosquito-control strategies.

Multiview deconvolution approximation multiphoton microscopy of tissues and zebrafish larvae.

Imaging in three dimensions is necessary for thick tissues and small organisms. This is possible with tomographic optical microscopy techniques such as confocal, multiphoton and light sheet microscopy. All these techniques suffer from anisotropic resolution and limited penetration depth. In the past, Multiview microscopy-imaging the sample from different angles followed by 3D image reconstruction-was developed to address this issue for light sheet microscopy based on fluorescence signal. In this study we applied this methodology to accomplish Multiview imaging with multiphoton microscopy based on fluorescence and additionally second harmonic signal from myosin and collagen. It was shown that isotropic resolution was achieved, the entirety of the sample was visualized, and interference artifacts were suppressed allowing clear visualization of collagen fibrils and myofibrils. This method can be applied to any scanning microscopy technique without microscope modifications. It can be used for imaging tissue and whole mount small organisms such as heart tissue, and zebrafish larva in 3D, label-free or stained, with at least threefold axial resolution improvement which can be significant for the accurate quantification of small 3D structures.

ATP activation of peritubular cells drives testicular sperm transport.

Spermatogenesis, the complex process of male germ cell proliferation, differentiation, and maturation, is the basis of male fertility. In the seminiferous tubules of the testes, spermatozoa are constantly generated from spermatogonial stem cells through a stereotyped sequence of mitotic and meiotic divisions. The basic physiological principles, however, that control both maturation and luminal transport of the still immotile spermatozoa within the seminiferous tubules remain poorly, if at all, defined. Here, we show that coordinated contractions of smooth muscle-like testicular peritubular cells provide the propulsive force for luminal sperm transport toward the rete testis. Using a mouse model for in vivo imaging, we describe and quantify spontaneous tubular contractions and show a causal relationship between peritubular Ca2+ waves and peristaltic transport. Moreover, we identify P2 receptor-dependent purinergic signaling pathways as physiological triggers of tubular contractions both in vitro and in vivo. When challenged with extracellular ATP, transport of luminal content inside the seminiferous tubules displays stage-dependent directionality. We thus suggest that paracrine purinergic signaling coordinates peristaltic recurrent contractions of the mouse seminiferous tubules to propel immotile spermatozoa to the rete testis.

As sperm develop in the testis, the immature cells must make their way through a maze of small tubes known as seminiferous tubules. However, at this stage, the cells do not yet move the long tails that normally allow them to 'swim'; it is therefore unclear how they are able to move through the tubules. Now, Fleck, Kenzler et al. have showed that, in mice, muscle-like cells within the walls of seminiferous tubules can create waves of contractions that push sperm along. Further experiments were then conducted on cells grown in the laboratory. This revealed that a signaling molecule called ATP orchestrates the moving process by activating a cascade of molecular events that result in contractions. Fleck, Kenzler et al. then harnessed an advanced microscopy technique to demonstrate that this mechanism occurs in living mice. Together, these results provide a better understanding of how sperm mature, which could potentially be relevant for both male infertility and birth control.

Identification of Dopaminergic Neurons That Can Both Establish Associative Memory and Acutely Terminate Its Behavioral Expression.

An adaptive transition from exploring the environment in search of vital resources to exploiting these resources once the search was successful is important to all animals. Here we study the neuronal circuitry that allows larval Drosophila melanogaster of either sex to negotiate this exploration-exploitation transition. We do so by combining Pavlovian conditioning with high-resolution behavioral tracking, optogenetic manipulation of individually identified neurons, and EM data-based analyses of synaptic organization. We find that optogenetic activation of the dopaminergic neuron DAN-i1 can both establish memory during training and acutely terminate learned search behavior in a subsequent recall test. Its activation leaves innate behavior unaffected, however. Specifically, DAN-i1 activation can establish associative memories of opposite valence after paired and unpaired training with odor, and its activation during the recall test can terminate the search behavior resulting from either of these memories. Our results further suggest that in its behavioral significance DAN-i1 activation resembles, but does not equal, sugar reward. Dendrogram analyses of all the synaptic connections between DAN-i1 and its two main targets, the Kenyon cells and the mushroom body output neuron MBON-i1, further suggest that the DAN-i1 signals during training and during the recall test could be delivered to the Kenyon cells and to MBON-i1, respectively, within previously unrecognized, locally confined branching structures. This would provide an elegant circuit motif to terminate search on its successful completion.SIGNIFICANCE STATEMENT In the struggle for survival, animals have to explore their environment in search of food. Once food is found, however, it is adaptive to prioritize exploiting it over continuing a search that would now be as pointless as searching for the glasses you are wearing. This exploration-exploitation trade-off is important for animals and humans, as well as for technical search devices. We investigate which of the only 10,000 neurons of a fruit fly larva can tip the balance in this trade-off, and identify a single dopamine neuron called DAN-i1 that can do so. Given the similarities in dopamine neuron function across the animal kingdom, this may reflect a general principle of how search is terminated once it is successful.

Deformation of Microgels at Solid-Liquid Interfaces Visualized in Three-Dimension.

Solid-liquid interfaces play an important role for functional devices. Hence, a detailed understanding of the interaction of soft matter objects with solid supports and of the often concomitant structural deformations is of great importance. We address this topic in a combined experimental and simulation approach. We investigated thermoresponsive poly(N-isopropylmethacrylamide) microgels (µGs) at different surfaces in an aqueous environment. As super-resolution fluorescence imaging method, three-dimensional direct stochastical optical reconstruction microscopy (dSTORM) allowed for visualizing µGs in their three-dimensional (3D) shape, for example, in a "fried-egg" conformation depending on the hydrophilicity of the surface (strength of adsorption). The 3D shape, as defined by point clouds obtained from single-molecule localizations, was analyzed. A new fitting algorithm yielded an isosurface of constant density which defines the deformation of µGs at the different surfaces. The presented methodology quantifies deformation of objects with fuzzy surfaces and allows for comparison of their structures, whereby it is completely independent from the data acquisition method. Finally, the experimental data are complemented with mesoscopic computer simulations in order to (i) rationalize the experimental results and (ii) to track the evolution of the shape with changing surface hydrophilicity; a good correlation of the shapes obtained experimentally and with computer simulations was found.

Instance Segmentation of Nematode Cysts in Microscopic Images of Soil Samples.

Nematodes are plant parasites that cause damage to crops. In order to quantify nematode infestation based on soil samples, we propose an instance segmentation method that will serve as the basis of automatic quantitative analysis. We consider light microscopic images of cluttered object collections as they occur in realistic soil samples. We introduce an algorithm, LMBI (Local Maximum of Boundary Intensity) to propose instance segmentation candidates. In a second step, a SVM classifier separates the nematode cysts among the candidates from soil particles. On a data set of soil sample images, the LMBI detector achieves near-optimal recall with a limited number of candidate segmentations, and the combined detector/classifier achieves recall and precision of 0.7. The pipeline only requires simple dot annotations and ≈moderately sized training data, which enables quick annotating and training in laboratory applications.

larvalign: Aligning Gene Expression Patterns from the Larval Brain of Drosophila melanogaster.

The larval brain of the fruit fly Drosophila melanogaster is a small, tractable model system for neuroscience. Genes for fluorescent marker proteins can be expressed in defined, spatially restricted neuron populations. Here, we introduce the methods for 1) generating a standard template of the larval central nervous system (CNS), 2) spatial mapping of expression patterns from different larvae into a reference space defined by the standard template. We provide a manually annotated gold standard that serves for evaluation of the registration framework involved in template generation and mapping. A method for registration quality assessment enables the automatic detection of registration errors, and a semi-automatic registration method allows one to correct registrations, which is a prerequisite for a high-quality, curated database of expression patterns. All computational methods are available within the larvalign software package: https://github.com/larvalign/larvalign/releases/tag/v1.0.

Normalizing brain activity across individuals using functional reference mapping.

Neural activity can be mapped across individuals using brain atlases, but when spatial relationships are not equal, these techniques collapse. We map activity across individuals using functional registration, based on physiological responses to predetermined reference stimuli. Data from several individuals are integrated into a common multidimensional stimulus space, where dimensionality and axes are defined by these reference stimuli. We used this technique to discriminate volatile compounds with a cohort of Drosophila flies, by recording odor responses in receptor neurons on the flies' antennae. We propose this technique for the development of reliable biological sensors when activity raw data cannot be calibrated. In particular, this technique will be useful for evaluating physiological measurements in natural chemosensory systems, and therefore will allow to exploit the sensitivity and selectivity of olfactory receptors present in the animal kingdom for analytical purposes.

A herbivore-induced plant volatile interferes with host plant and mate location in moths through suppression of olfactory signalling pathways.

BACKGROUND: Plants under herbivore attack release volatiles that attract natural enemies, and herbivores in turn avoid such plants. Whilst herbivore-induced plant volatile blends appeared to reduce the attractiveness of host plants to herbivores, the volatiles that are key in this process and particularly the way in which deterrence is coded in the olfactory system are largely unknown. Here we demonstrate that herbivore-induced cotton volatiles suppress orientation of the moth Spodoptera littoralis to host plants and mates. RESULTS: We found that (E)-4,8-dimethyl-1,3,7-nonatriene (DMNT), an induced volatile, is key in herbivore deterrence: DMNT suppressed plant odour- and pheromone-induced behaviours. We then dissected the neurophysiological basis of this interaction. DMNT-responding glomeruli were also activated by other plant compounds, suggesting that S. littoralis possesses no segregated olfactory circuit dedicated exclusively to DMNT. Instead, DMNT suppressed responses to the main pheromone component, (Z)-9-(E)-11-tetradecenyl acetate, and primarily to (Z)-3-hexenyl acetate, a host plant attractant. CONCLUSION: Our study shows that olfactory sensory inhibition, which has previously been reported without reference to an animal's ecology, can be at the core of coding of ecologically relevant odours. As DMNT attracts natural enemies and deters herbivores, it may be useful in the development or enhancement of push-pull strategies for sustainable agriculture.

More than apples and oranges--detecting cancer with a fruit fly's antenna.

Cancer cells and non-cancer cells differ in their metabolism and they emit distinct volatile compound profiles, allowing to recognise cancer cells by their scent. Insect odorant receptors are excellent chemosensors with high sensitivity and a broad receptive range unmatched by current gas sensors. We thus investigated the potential of utilising the fruit fly's olfactory system to detect cancer cells. Using in vivo calcium imaging, we recorded an array of olfactory receptor neurons on the fruit fly's antenna. We performed multidimensional analysis of antenna responses, finding that cell volatiles from different cell types lead to characteristic response vectors. The distances between these response vectors are conserved across flies and can be used to discriminate healthy mammary epithelial cells from different types of breast cancer cells. This may expand the repertoire of clinical diagnostics, and it is the first step towards electronic noses equipped with biological sensors, integrating artificial and biological olfaction.

Octopamine modulates activity of neural networks in the honey bee antennal lobe.

Neuronal plasticity allows an animal to respond to environmental changes by modulating its response to stimuli. In the honey bee (Apis mellifera), the biogenic amine octopamine plays a crucial role in appetitive odor learning, but little is known about how octopamine affects the brain. We investigated its effect in the antennal lobe, the first olfactory center in the brain, using calcium imaging to record background activity and odor responses before and after octopamine application. We show that octopamine increases background activity in olfactory output neurons, while reducing average calcium levels. Odor responses were modulated both upwards and downwards, with more odor response increases in glomeruli with negative or weak odor responses. Importantly, the octopamine effect was variable across glomeruli, odorants, odorant concentrations and animals, suggesting that the octopaminergic network is shaped by plasticity depending on an individual animal's history and possibly other factors. Using RNA interference, we show that the octopamine receptor AmOA1 (homolog of the Drosophila OAMB receptor) is involved in the octopamine effect. We propose a network model in which octopamine receptors are plastic in their density and located on a subpopulation of inhibitory neurons in a disinhibitory pathway. This would improve odor-coding of behaviorally relevant, previously experienced odors.

Signal extraction from movies of honeybee brain activity: the ImageBee plugin for KNIME.

BACKGROUND: In the antennal lobe, a dedicated olfactory center of the honeybee brain, odours are encoded as activity patterns of coding units, the so-called glomeruli. Optical imaging with calcium-sensitive dyes allows us to record these activity patterns and to gain insight into olfactory information processing in the brain. METHOD: We introduce ImageBee, a plugin for the data analysis platform KNIME. ImageBee provides a variety of tools for processing optical imaging data. The main algorithm behind ImageBee is a matrix factorisation approach. Motivated by a data-specific, non-negative mixture model, the algorithm aims to select the generating extreme vectors of a convex cone that contains the data. It approximates the movie matrix by non-negative combinations of the extreme vectors. These correspond to pure glomerular signals that are not mixed with neighbour signals. RESULTS: Evaluation shows that the proposed algorithm can identify the relevant biological signals on imaging data from the honeybee AL, as well as it can recover implanted source signals from artificial data. CONCLUSIONS: ImageBee enables automated data processing and visualisation for optical imaging data from the insect AL. The modular implementation for KNIME offers a flexible platform for data analysis projects, where modules can be rearranged or added depending on the particular application. AVAILABILITY: ImageBee can be installed via the KNIME update service. Installation instructions are available at http://tech.knime.org/imagebee-analysing-imaging-data-from-the-honeybee-brain.

The looks of an odour--visualising neural odour response patterns in real time.

BACKGROUND: Calcium imaging in insects reveals the neural response to odours, both at the receptor level on the antenna and in the antennal lobe, the first stage of olfactory information processing in the brain. Changes of intracellular calcium concentration in response to odour presentations can be observed by employing calcium-sensitive, fluorescent dyes. The response pattern across all recorded units is characteristic for the odour. METHOD: Previously, extraction of odour response patterns from calcium imaging movies was performed offline, after the experiment. We developed software to extract and to visualise odour response patterns in real time. An adaptive algorithm in combination with an implementation for the graphics processing unit enables fast processing of movie streams. Relying on correlations between pixels in the temporal domain, the calcium imaging movie can be segmented into regions that correspond to the neural units. RESULTS: We applied our software to calcium imaging data recorded from the antennal lobe of the honeybee Apis mellifera and from the antenna of the fruit fly Drosophila melanogaster. Evaluation on reference data showed results comparable to those obtained by previous offline methods while computation time was significantly lower. Demonstrating practical applicability, we employed the software in a real-time experiment, performing segmentation of glomeruli--the functional units of the honeybee antennal lobe--and visualisation of glomerular activity patterns. CONCLUSIONS: Real-time visualisation of odour response patterns expands the experimental repertoire targeted at understanding information processing in the honeybee antennal lobe. In interactive experiments, glomeruli can be selected for manipulation based on their present or past activity, or based on their anatomical position. Apart from supporting neurobiology, the software allows for utilising the insect antenna as a chemosensor, e.g. to detect or to classify odours.