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Previous studies have shown that vector-borne viruses can manipulate the host selection behavior of insect vectors, yet the tripartite interactions of pathogens, host plants and insect vectors have been documented only in a limited number of pathosystems. Here, we report that the host selection behavior of the insect vector of barley yellow dwarf virus-PAV (BYDV-PAV) and cereal yellow dwarf virus-RPS (CYDV-RPS) is dependent on the host plant species and viral co-infection. This study shows that a model cereal plant, Brachypodium distachyon, is a suitable host plant for examining tripartite interactions with BYDV-PAV and CYDV-RPS. We reveal that BYDV-PAV has a different effect on the host selection behavior of its insect vector depending on the host plant species. Viruliferous aphids significantly prefer non-infected plants to virus-infected wheat plants, whereas viral infection on a novel host plant, B. distachyon, is not implicated in the attraction of either viruliferous or nonviruliferous aphids. Furthermore, our findings show that multiple virus infections of wheat with BYDV-PAV and CYDV-RPS alter the preference of their vector aphid. This result indicates that BYDV-PAV acquisition alters the insect vector’s host selection, thereby varying the spread of multiple viruses.

Understanding the host-selection behavior of herbivorous insects is important to clarify their efficacy and safety as biocontrol agents. To explore the host-plant selection of the beetle Ophraella communa, a natural enemy of the alien invasive common ragweed (Ambrosia artemisiifolia), we conducted a series of outdoor choice experiments in cages in 2010 and in open fields in 2010 and 2011 to determine the preference of O. communa for A. artemisiifolia and three non-target plant species: sunflower (Helianthus annuus), cocklebur (Xanthium sibiricum), and giant ragweed (Ambrosia trifida). In the outdoor cage experiment, no eggs were found on sunflowers, and O. communa adults rapidly moved from sunflowers to the other three plant species. Instead, adults preferred to lay eggs on A. artemisiifolia, followed by X. sibiricum and A. trifida, although very few eggs were observed on A. trifida. Observing the host-plant selection of O. communa in an open sunflower field, we found that O. communa adults always chose A. artemisiifolia for feeding and egg laying. Although several adults (<0.02 adults/plant) stayed on H. annuus, no feeding or oviposition were observed, and adults quickly transferred to A. artemisiifolia. In 2010 and 2011, 3 egg masses (96 eggs) were observed on sunflowers, but they failed to hatch or develop into adults. In addition, some O. communa adults crossed the barrier formed by H. annuus to feed and oviposit on A. artemisiifolia planted in the periphery, and persisted in patches of different densities. Additionally, only 10% of O. communa adults chose to feed and oviposit on the X. sibiricum barrier. These findings suggest that O. communa poses no threat to the biosafety of H. anunuus and A. trifida and exhibits a robust dispersal capacity to find and feed on A. artemisiifolia. However, X. sibiricum has the potential to be an alternative host plant for O. communa.

Several studies have shown a strong involvement of the basal ganglia (BG) in action selection and dopamine dependent learning. The dopaminergic signal to striatum, the input stage of the BG, has been commonly described as coding a reward prediction error (RPE), i.e., the difference between the predicted and actual reward. The RPE has been hypothesized to be critical in the modulation of the synaptic plasticity in cortico-striatal synapses in the direct and indirect pathway. We developed an abstract computational model of the BG, with a dual pathway structure functionally corresponding to the direct and indirect pathways, and compared its behavior to biological data as well as other reinforcement learning models. The computations in our model are inspired by Bayesian inference, and the synaptic plasticity changes depend on a three factor Hebbian-Bayesian learning rule based on co-activation of pre- and post-synaptic units and on the value of the RPE. The model builds on a modified Actor-Critic architecture and implements the direct (Go) and the indirect (NoGo) pathway, as well as the reward prediction (RP) system, acting in a complementary fashion. We investigated the performance of the model system when different configurations of the Go, NoGo, and RP system were utilized, e.g., using only the Go, NoGo, or RP system, or combinations of those. Learning performance was investigated in several types of learning paradigms, such as learning-relearning, successive learning, stochastic learning, reversal learning and a two-choice task. The RPE and the activity of the model during learning were similar to monkey electrophysiological and behavioral data. Our results, however, show that there is not a unique best way to configure this BG model to handle well all the learning paradigms tested. We thus suggest that an agent might dynamically configure its action selection mode, possibly depending on task characteristics and also on how much time is available.

1. Push-pull or stimulo-deterrent cropping systems combine a trap crop or other attractant or arrestant stimulus distant from the crop and a deterrent or repellent near or within the target crop, to divert pests, reducing their populations on the target crop. Although the concept is decades old, there are few successful applications in pest management. 2. In this article, we address this shortcoming by offering a mechanistic conceptual framework of push-pull systems, based on the cues, sensory modalities, pest behaviours and spatial ranges over which they can occur during host selection and that can influence pest distribution. 3. We review published work on push-pull systems in the light of this framework, finding that the literature tends to focus on longer-range stimulo-deterrence strategies rather than the full range of cues involved and modalities that can come into play, with imperfect understanding of cues involved in most systems. 4. The imbalance in research emphasis and incomplete understanding of push-pull mechanisms suggest opportunities to improve and broaden the palette of potential push-pull technologies. 5. The framework also helps clarify other aspects important for achieving success with pushpull methods, including the role of synergy, deployment geometry, intraspecific variability and the wider arthropod community in these systems. 6. Synthesis and applications. A conceptual and mechanistic framework is provided for the development of push-pull or stimulo-deterrent pest management approaches. This framework informs a proposed research agenda for designing push-pull technologies. That agenda involves including all cues and modalities, exploiting synergies, tuning deployment geometry in accordance with these factors. It also considers pest and crop dynamics and the arthropod community of the system. The framework can benefit managers by helping them to consider more fully the behaviour of the target pests when creating crop and non-crop geometries to achieve push-pull benefits. Research-based push-pull systems will be better implemented and modified by producers if they understand how insects respond to sources of push and pull in the system, allowing effective monitoring and fine-tuning to increase effectiveness of this specialized component of integrated pest management.

Push‐pull or stimulo‐deterrent cropping systems combine a trap crop or other attractant or arrestant stimulus distant from the crop and a deterrent or repellent near or within the target crop, to divert pests, reducing their populations on the target crop. Although the concept is decades old, there are few successful applications in pest management. In this article, we address this shortcoming by offering a mechanistic conceptual framework of push‐pull systems, based on the cues, sensory modalities, pest behaviours and spatial ranges over which they can occur during host selection and that can influence pest distribution. We review published work on push‐pull systems in the light of this framework, finding that the literature tends to focus on longer‐range stimulo‐deterrence strategies rather than the full range of cues involved and modalities that can come into play, with imperfect understanding of cues involved in most systems. The imbalance in research emphasis and incomplete understanding of push‐pull mechanisms suggest opportunities to improve and broaden the palette of potential push‐pull technologies. The framework also helps clarify other aspects important for achieving success with push‐pull methods, including the role of synergy, deployment geometry, intraspecific variability and the wider arthropod community in these systems. Synthesis and applications. A conceptual and mechanistic framework is provided for the development of push‐pull or stimulo‐deterrent pest management approaches. This framework informs a proposed research agenda for designing push‐pull technologies. That agenda involves including all cues and modalities, exploiting synergies, tuning deployment geometry in accordance with these factors. It also considers pest and crop dynamics and the arthropod community of the system. The framework can benefit managers by helping them to consider more fully the behaviour of the target pests when creating crop and non‐crop geometries to achieve push‐pull benefits. Research‐based push‐pull systems will be better implemented and modified by producers if they understand how insects respond to sources of push and pull in the system, allowing effective monitoring and fine‐tuning to increase effectiveness of this specialized component of integrated pest management.

Decades of research show how what we know about learned reinforcers, as the selectors of behavior, constitutes a significant advancement in behavior analysis. I describe how the learning of new reinforcers results in new operants including verbal operants and verbal developmental cusps, as well as the potential to build still other reinforcers. The lack of particular types of reinforcers, or a limited community of reinforcers, is the root source of many problems in applied work and sources of complex relations in the basic science. In cases where the relevant reinforcers are present, building behavior is the solution; however, when the relevant reinforcers are not present, the use of prosthetic reinforcers does not solve the real problem. In the latter case, the solution is to build new reinforcers, behaviors will follow. I cite decades of work in food preferences, musical taste, social reinforcers, and the identification and establishment of verbal developmental cusps that shows how identifying and building new reinforcers expands what our science can do. The establishment of a rich community of socially significant positive reinforcers is life-altering.

Behaviour selection has been an active research topic for robotics, in particular in the field of human–robot interaction. For a robot to interact autonomously and effectively with humans, the coupling between techniques for human activity recognition and robot behaviour selection is of paramount importance. However, most approaches to date consist of deterministic associations between the recognised activities and the robot behaviours, neglecting the uncertainty inherent to sequential predictions in real-time applications. In this paper, we address this gap by presenting an initial neurorobotics model that embeds, in a simulated robot, computational models of parts of the mammalian brain that resembles neurophysiological aspects of the basal ganglia–thalamus–cortex (BG–T–C) circuit, coupled with human activity recognition techniques. A robotics simulation environment was developed for assessing the model, where a mobile robot accomplished tasks by using behaviour selection in accordance with the activity being performed by the inhabitant of an intelligent home. Initial results revealed that the initial neurorobotics model is advantageous, especially considering the coupling between the most accurate activity recognition approaches and the computational models of more complex animals.

Background Senecio jacobaea contains pyrrolizidine alkaloids that can induce severe hepatic intoxication in horses, either acute when ingested in high amounts or chronic when consumed over a long period. The aim of this study was to determine horses’ rejection behaviour towards the presence of Senecio jacobaea in hay when fed ad libitum. We hypothesized that adult horses can sort Senecio jacobaea out of the contaminated hay when hay is fed ad libitum. Six warmblood geldings with a mean (±SD) age of 15 ± 2 years were included. In a randomized study, Senecio jacobaea contaminated hay (5% or 10% contamination level) was provided at several timepoints over the day for 1 hour to six. Hay was provided ad libitum for the rest of the day. The horses’ rejection behaviour towards Senecio jacobaea was observed. If a horse ingested two Senecio jacobaea plants twice at different timepoints, then the horse was excluded from the experiment. Results Two out of six horses had to be excluded from the study after three out of 12 observation periods due to repeated Senecio jacobaea intake. Two other horses had to be excluded after nine and 11 out of 12 observation periods. Only two horses were able to sort out the various amounts (5 and 10% contamination level) of Senecio jacobaea during the whole experiment. Conclusions Horses’ intake of Senecio jacobaea cannot be avoided despite being fed with hay ad libitum. Due to the risk of chronic intoxication by pyrrolizidine alkaloids intake, feeding Senecio jacobaea contaminated hay must be avoided, and pastures with Senecio jacobaea growth are considered inappropriate for feed production.

Visualizing active neurons and circuits in vivo is critical for investigating the neural activity that underlies behavior. While several established methodologies are available to achieve this end in larval zebrafish, they are limited by the scale of tissue visualization, temporal resolution, need to restrain larvae, and/or accessibility of necessary instruments. Here, we establish a pipeline for the visualization and quantification of spatiotemporally precise whole-brain neural activity in larval zebrafish using CaMPARI2, a genetically-encoded calcium indicator. Using temporally specific photoconverting UV light exposures, we capture whole-brain “snapshots” of neural activity time-locked to stimuli during unrestrained larval behavior. We optimize experimental conditions for recording sub-second neuronal activity changes across acoustically-evoked behavioral paradigms spanning minutes to hours. We then leverage this system to pinpoint brain-wide neural activity changes during non-associative habituation learning, observing distinct activity signatures in the subpallium, preoptic area, and habenulae that are altered through pharmacological disruption of habituation learning. This approach effectively complements the temporal precision achievable through post-hoc activity detection methods and expands the accessibility of large-scale behavioral circuit dissection beyond highly specialized real-time volumetric imaging equipment.

Plant volatile organic compounds (VOCs) are an important link that mediates chemical communication between plants and plants, plants and insects, and plants and natural enemies of insect pests. In this study, we tested the response in the selective behavior of western flower thrips, Frankliniella occidentalis, to the VOCs of kidney bean, Phaseolus vulgaris L., to explore their “attraction” or “repellent” effects regarding their application in integrated pest management (i.e., IPM). The results indicated that 12.7 μL/mL (E, E, E, E)-squalene, 3.2 μL/mL dioctyl phthalate, and 82.2 μL/mL ethyl benzene had a significantly attractive effect on the selective behavior of F. occidentalis, while 10.7 μL/mL and 21.4 μL/mL 2,6-ditert-butyl-4-methyl phenol had a significantly repulsive effect on the selective behavior of F. occidentalis, showing that F. occidentalis responds differently to specific concentrations of VOCs from P. vulgaris plant emissions. Interestingly, the three compounds with the specific above concentrations, after being mixed in pairs, significantly attracted F. occidentalis compared to the control treatment; however, the mixture with the three above compounds had no significant different effect on F. occidentalis compared to the control treatment. It can be seen that the effect with the mixtures of three kinds of VOCs had the same function and may not get better. Simultaneously, the reasons for this result from the transcription levels of odorant-binding protein genes (OBPs) were determined. There were differences in the types and transcription levels of OBPs, which played a major role in the host selection behavior of F. occidentalis under the mixed treatment of different VOCs. It is presumed that there are specific VOCs from P. vulgaris plants that have a good repellent or attracting effect on the selective behavior of F. occidentalis, which can be used for the development of plant-derived insect attractants and repellents to serve as IPM in fields. But attention should be paid to the antagonism between plant-derived preparations and VOCs produced by plants themselves after application.