Natural Behavior Research Articles

Swarm Intelligence and Unmanned Systems: The Potentıal Impact of The Principles of Swarm Intelligence and Collective Behaviour in Nature On Unmanned Systems and Autonomous Organizational Structures

This paper examines the potential implications of the principles of swarm intelligence and collective behavior in nature for unmanned systems and autonomous organizational structures. Swarm intelligence is inspired by natural systems in which individual units interact according to simple rules to form a complex and organized whole. These principles can be observed in a wide range of situations, from the synchronized flight of flocks of birds to the harmonized swimming behavior of schools of fish. The study emphasizes that swarm intelligence principles have the potential to create more flexible, resilient and efficient systems with decentralized control mechanisms and autonomous decision-making processes. Furthermore, it is suggested that these approaches can find applications in many fields, from military operations to agricultural and environmental monitoring, from disaster response to urban planning. The study provides a detailed analysis of swarm behavior in nature and discusses how these behaviors can be emulated and optimized in unmanned systems. In this context, the potential impacts of swarm intelligence and collective behavior principles on unmanned systems are evaluated in terms of increasing their adaptability, optimizing energy efficiency and maximizing mission success. It is also argued that these principles can contribute to making unmanned systems more resilient to contingencies and changing environmental conditions. This theoretical study suggests that swarm intelligence principles can provide innovative solutions for future unmanned systems and autonomous organizational structures.

ONIX: a unified open-source platform for multimodal neural recording and perturbation during naturalistic behavior.

Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge we developed ONIX, an open-source data acquisition system with high data throughput (2 GB s-1) and low closed-loop latencies (<1 ms) that uses a 0.3-mm thin tether to minimize behavioral impact. Head position and rotation are tracked in three dimensions and used to drive active commutation without torque measurements. ONIX can acquire data from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, three-dimensional trackers and other data sources. We performed uninterrupted, long (~7 h) neural recordings in mice as they traversed complex three-dimensional terrain, and multiday sleep-tracking recordings (~55 h). ONIX enabled exploration with similar mobility as nonimplanted animals, in contrast to conventional tethered systems, which have restricted movement. By combining long recordings with full mobility, our technology will enable progress on questions that require high-quality neural recordings during ethologically grounded behaviors.

A stealthy neural recorder for the study of behaviour in primates.

By monitoring brain neural signals, neural recorders allow for the study of neurological mechanisms underlying specific behavioural and cognitive states. However, the large brain volumes of non-human primates and their extensive range of uncontrolled movements and inherent wildness make it difficult to carry out covert and long-term recording and analysis of deep-brain neural signals. Here we report the development and performance of a stealthy neural recorder for the study of naturalistic behaviours in non-human primates. The neural recorder includes a fully implantable wireless and battery-free module for the recording of local field potentials and accelerometry data in real time, a flexible 32-electrode neural probe with a resorbable insertion shuttle, and a repeater coil-based wireless-power-transfer system operating at the body scale. We used the device to record neurobehavioural data for over 1 month in a freely moving monkey and leveraged the recorded data to train an artificial intelligence model for the classification of the animals' eating behaviours.

A normative framework dissociates need and motivation in hypothalamic neurons.

Physiological needs evoke motivational drives that produce natural behaviors for survival. In previous studies, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components. On the basis of classic homeostatic theories, we established a normative framework to derive computational models for need-encoding and motivation-encoding neurons. By combining the model-based predictions and naturalistic experimental paradigms, we demonstrated that agouti-related peptide (AgRP) and lateral hypothalamic leptin receptor (LHLepR) neuronal activities encode need and motivation, respectively. Our model further explains the difference in the dynamics of appetitive behaviors induced by optogenetic stimulation of AgRP or LHLepR neurons. Our study provides a normative modeling framework that explains how hypothalamic neurons separately encode need and motivation in the mammalian brain.

Associating cognitive abilities with naturalistic search behavior

AbstractDifferences in cognitive abilities affect search behaviors, but this has mostly been observed in laboratory experiments. There is limited research on how users search for information in real‐world, naturalistic settings and how real‐world search behaviors relate to cognitive abilities. In this study, we investigated a wide range of behavioral data captured from real‐life search tasks, their association with users' cognitive abilities, and the potential for automatically inferring cognitive abilities from these data. Furthermore, we aimed to determine the data quantity and monitoring duration needed to effectively estimate cognitive abilities from naturalistic behavior. Twenty individuals with βvarying cognitive abilities participated in the experiments in which their everyday search behavior was continuously recorded for 14 days. Their cognitive ability was evaluated through standard tests conducted individually. Data consisted of over 800 h of monitoring, including 2022 queries extracted from 1,442,447 screen frames and associated operating system logs. Using these data, naturalistic search behaviors were associated with cognitive abilities, and predictive models were trained. The results showed that lower selective attention was found to be associated with longer dwelling on selected search results. Faster psychomotor speed and higher fluid intelligence were found to be associated with a greater amount of text read on selected pages. Predictive models exhibited small error rates in predicting cognitive abilities.

The Role of Heater Size and Location in Modulating Natural Convection Behavior in Cu-Water Nanofluid-Loaded Square Enclosures

Enhancing the energy efficiency of thermal systems reduces their consumption, lowers costs, and reduces undesired environmental impact, thus making these systems more sustainable. The current work introduces a passive method for heat transfer enhancement that is carried out using natural convection by nanofluid. This work introduces a computational study of the process of natural convection within a square cavity containing Cu/H2O nanofluid. The cavity wall on the left side undergoes partial isothermal heating, while the opposing side is fully cooled isothermally, with all other boundaries maintained adiabatic. A mathematical model formulated based on a 2-D model was used to provide the solution for the system of governing equations of mass, momentum, and energy conservation, employing the finite element technique. A commercial CFD package is utilized to perform the computational simulation. The present investigation delves into the impact of the Rayleigh number, nanoparticle concentration, heater length, and heater location on the flow field and heat transfer characteristics. The model outcomes were displayed for a wide range of the pertinent parameters as 103 ≤ Ra ≤ 106, 0.25 ≤ lh ≤ 1.0, 0.125 ≤ hc ≤ 0.875, and 0.02 ≤ ϕ ≤ 0.10. Also, correlation equations relating the average Nusselt number to these crucial parameters are derived. These equations are simple and can be applied in practice easily in many fields, such as electric and electronic equipment cooling and thermal management of heat sources. Also, these equations gather all the parameters that affect the heat transfer process. They are shedding light on the intricate interplay between these parameters in the natural convection heat transfer process.

Performance of PSO-GWO, VAGWO, and GWO optimization techniques for economic dispatch problem: studied case of the southeast algerian electrical network

Economic dispatch (ED) aims to identify the most cost-effective strategy for allocating power generation while meeting demand and adhering to the physical constraints of the power system. In this paper, three algorithms are proposed to solve the ED problem in power systems, including a hybrid Particle Swarm Optimization with Grey Wolf Optimizer (PSO-GWO), modified Velocity Aided Grey Wolf Optimizer (VAGWO), and Grey Wolf Optimizer (GWO). PSO is a meta-heuristic optimization technique designed to find the optimal solution to a problem by guiding the movement of particles within a defined exploration space. GWO is also a meta-heuristic optimization algorithm based on the natural behavior of grey wolves. In this paper, to enhance the performance of GWO, it is first combined with the PSO method. VAGWO is employed to refine the GWO formulation by optimizing the convergence steps. At the beginning of the iterations, the distance between the solutions (wolves) is increased to promote exploration of the search space. As the iterations progress, the step size is reduced, allowing for a more precise and efficient convergence toward the optimal solution. These algorithms will be implemented in Matlab software to minimize the fuel cost production of the following test networks: IEEE 30-bus network, Algerian 114-bus network, and Southeast Algerian network. These methods show that the PSO-GWO algorithm offers better results when compared through VAGWO and GWO.

Analysis of the impact of environmental enrichment on the behaviors of bioterium rats

Rats are often used in experimental research due to their intelligence and ease of handling. However, traditional housing conditions can limit their natural behaviors, potentially leading to discomfort. Environmental enrichment aims to increase behavioral diversity, promote healthy behaviors, encourage positive use of the environment, enhance the animal's ability to cope with stressors, and reduce stereotypic behaviors. This study primarily aimed to assess the impact of environmental enrichment on laboratory rat behaviors. A group of 18 rats was selected and divided into three groups (n=6): control, physical enrichment, and feeding enrichment. The enrichment groups were provided with specific objects (a plastic tube for physical enrichment and a seed-filled cardboard roll for feeding enrichment) over a 10-day period, with open field tests conducted on days 1, 5, and 10 to evaluate time spent in central and peripheral zones. Statistical analyses were conducted in RStudio using t-test (p&lt;0.05) to compare open field activity, water intake, and food consumption across groups. Results showed that animals exposed to environmental enrichment displayed fewer stereotypic behaviors and increased feeding frequency. Thus, assessing the impact of physical and feeding enrichment in rats of laboratory demonstrates that enrichment strategies provide positive impacts on animal welfare.

Perceptual Pigeon Galvanized Optimization of Multi-objective CNN on the Identification and Classification of Mango Leaves Disease

Aims The aim of this study is to develop a strong Multi-objective Convolutional Neural Network (MOCNN) optimized using Perceptual Pigeon Galvanized Optimization (PPGO) for accurate identification and classification of mango leaf diseases. This approach aims to increase classification accuracy, computational efficiency, and generalization ability. The ultimate goal is to improve disease management in mango crops through advanced image-based diagnostic techniques. Background Demands for the consumption of mango (Mangifera indica) fruit and its leaves were growing exponentially in all parts of the world due to its large health benefits for various organs in the human body. However, these plants were largely exposed to various kinds of microbial diseases during cultivation despite the application of pesticides. Hence, it is becoming a significant threat to the farmers and to the food industry. Objective The objectives of this study are to develop reliable methods for the early identification of mango leaf diseases, enabling prompt intervention and reducing crop damage. Additionally, the study aims to provide effective disease management applications that will help farmers minimize crop losses and maintain their economic stability. Methods PPGO is an advanced optimization algorithm inspired by the natural foraging behavior of pigeons. It integrates perceptual hashing and galvanic responses to adaptively adjust the search process, allowing for efficient exploration and exploitation of the solution space. The multi-objective convolutional neural network is trained to minimize a composite loss function that considers classification accuracy, computational efficiency, and generalization error. Results The Perceptual Pigeon Galvanized Optimization (PPGO) with a Multi-objective Convolutional Neural Network (MOCNN) demonstrates superior performance compared to traditional CNN optimization techniques. The results show an accuracy of 96%, recall of 94%, precision of 92%, and an F1 score of 92%. These metrics surpass those of existing methods such as Efficient Supervised Learning based on Deep Neural Network (ESDNN), Hierarchical Deep Learning Support Vector Machine (HDLSVM), Ordinal Regression Neural Network (ORNN), Deep Convolutional Generative Adversarial Network (DCGAN), Convolutional Neural Network (CNN), Local Contrast Normalization Convolutional Neural Network (LCNN), and Visual Geometry Group Network (VGGNET 19). Conclusion The integration of Perceptual Pigeon Galvanized Optimization with a Multi-objective Convolutional Neural Network offers a powerful approach for identifying and classifying mango leaf diseases. The proposed method effectively balances multiple performance metrics, leading to a robust and efficient model suitable for real-world agricultural applications.

Alteration of twilight sky brightness profile by light pollution

The phenomenon of twilight has been stipulated as naturally dependent on the variables of solar depression, aerosol concentration and ozone composition. The unique color spectrum of twilight is attributed by ozone layer and aerosol, whereas its brightness is heavily relying on the altitude of sun below horizon. While all the natural dependence is being researched extensively, the impact of light pollution on the brightness of the twilight is not being explored thoroughly. The objective of this study is to find out the alteration of light pollution towards the natural behavior of twilight sky brightness. Total of 84 data of twilight brightness was collected from 2014 until 2022 using Sky Quality Meter, and the specific location with profile classified as urban, suburban and pristine is investigated to study the impact of light pollution on twilight brightness. The result demonstrates that the stability of twilight brightness, which naturally factored by solar depression within the range of 18°, discovered to be heavy influenced by the zenith light pollution of the location sky, as evidenced by location that has zenith pollution of 17.11, 19.77, and 21.39, has horizontal twilight brightness of 14.84, 19.55 and 21.2 and solar depression during brightness stability at 11.5°, 15.67° and 17.49°.

Natural behavior relaxes zoning divisions in the brain

Technological advances allow neurophysiologists to explore the brain during natural behaviors, revealing new functional principles and challenging old ones. In this issue of Neuron, Li1 and colleagues show that the traditional parcellation of the marmoset frontal cortex does not apply to naturalistic conversations.

Impact of a natural rubber-based scratcher as an environmental enrichment on the scratching behavior, cortisol level, and semen quality of stable male goats

Background and Aim: Goats are valuable livestock because they can generate meat and milk for human consumption. Goat husbandry is becoming more intensive due to the growing demand for goat products, which may impact animal welfare and natural behavior. This study aimed to investigate the impact of natural rubber (para rubber)-based scratchers as an environmental enrichment on scratching behavior, cortisol levels, and semen quality in stable bucks (male goats/goats). Materials and Methods: Nine male goats were used in this study. Scratching behavior and cortisol levels were used as welfare indicators, whereas semen quality was evaluated as an indicator of reproductive potential. These indicators were analyzed before and after scratcher installation. Results: After installing the scratchers, the goats showed a significant increase in scratching behavior and a notable decrease in cortisol levels (p &lt; 0.001). Notably, the goats exhibited a marked preference for scratching against the scratcher (p &lt; 0.001) compared to the stable. They significantly preferred using their heads for scratching (p &lt; 0.001) instead of other body parts. In addition, goats preferred to scratch on the softest rubber scratchers at specific installation locations (p &lt; 0.001). Although there was a slight improvement in semen quality, there was no statistically significant difference (p &gt; 0.05). Conclusion: A natural rubber-based scratcher can increase scratching behavior and reduce cortisol levels, indicating its potential to improve the welfare of farm goats. Selecting an appropriate hardness and preferred location is essential to ensure that the scratcher effectively encourages animals to use it. Keywords: cortisol, goat, para rubber, scratcher, semen quality.

Revisiting the Alcohol-Aggression Link: The Impact of Alcohol Consumption Patterns

Laboratory studies have repeatedly reported a link between alcohol and aggression, yet many rely on single-dose administration methods and overlook variations in alcohol consumption patterns. The present study investigates the effects of alcohol on aggressive behavior using a double-blind, placebo-controlled cumulative drinking administration approach that mirrors the natural drinking behaviors often observed in pubs within a laboratory setting. This study also pioneers the examination of how alcohol consumption patterns (light or heavy) moderate the relationship between precise Breath Alcohol Concentration (BrAC) levels and extreme aggressive behavior. Seventy-five light (N=38) and heavy (N=37) alcohol drinkers were randomly assigned to alcohol (N=33) or placebo (N=42) conditions. Participants drank four drinks successively. Taylor's aggression paradigm was completed twenty minutes after each drink. Multilevel modeling was applied to analyze the effects of precise BrAC and account for within-person variability. Alcohol showed a dose-dependent effect on aggression; as alcohol levels rose, so did aggression (p<.001). Alcohol consumption pattern moderated the effect of cumulative BrAC on aggression, such that the effect was more substantial for light as compared with individuals who drink heavily (p=.03). The current study highlights the moderating role of alcohol consumption pattern in the association between precise BrAC levels and extreme aggression, offering insights into individual differences in susceptibility to alcohol-induced aggression, and supporting the I3 meta-theory (Finkel, 2014). The Findings underscore the importance of investigating the interplay between acute and chronic alcohol use on behavior, challenging conventional thresholds for hazardous drinking classification. Implications for future studies, legislators, and policymakers are discussed.

Quantitative evaluation of corrugation severity by using instrumented wheelset

Accurate evaluation of corrugation severity is essential for timely rail maintenance to prevent potential hazards. This paper aims at the excitation characteristics of corrugation and presents a study on the evaluation method using wheel-rail vertical force (WRVF). First, a 3D wheel-rail dynamic model is established by the parameters of service vehicles and track in China’s high-speed railway, corrugated rail was finely modelled with the consideration of out-of-roundness and random track short irregularity. The model was validated with measured data come from instrumented wheelset in time and frequency domain, the stability and dynamic response of the model are studied numerically to explore the excitation characteristics of corrugation. Then, the variation of WRVF with depth and wavelength respectively was discussed, the mapping relationship between the 95th percentile maximum of the WRVF and the corrugation wavelength is revealed, the influences of the natural frequency and contact behavior of the wheel-rail system on the mapping relationship were analyzed. Finally, the corrugation severity index (Csi) is introduced to quantify the degree of rail damage. The applicability of Csi was tested on 65 sets of corrugated sections on high-speed railway, and the results of field measurement showed that the hit rate of Csi in evaluating the severity of corrugation is 93.8%, indicating that the proposed method has a good performance in actual detection. Thus, Csi can provide a scientific reference for the quantitative evaluation of corrugation severity and decision-making for rail grinding in high-speed railway.

EFEITOS DE FÁRMACOS PSICOTRÓPICOS NO TRATAMENTO DE DISTÚRBIOS COMPORTAMENTAIS EM CÃES (CANIS FAMILIARIS)

With the strengthening of human-animal interaction and the scientific recognition of sentience, there has been a significant increase in the perception of atypical behaviors in companion animals, as observed by legal guardians and veterinarians. In general terms, such changes occur due to excessive humanization, stress, fear, or inappropriate environments, leading to variations in temperament, emotional dependency, and/or inhibition of species-specific natural behaviors. The class of psychotropic drugs offers pharmacological treatment for the mental state of these animals by modulating neurotransmitters such as serotonin and dopamine. The objective of this study was to evaluate the pharmacological impact of psychotropic drugs on the social development and emotional resilience of these animals, in conjunction with behavioral therapy. For this purpose, domestic dogs (Canis familiaris) diagnosed with compulsive disorders secondary to other behavioral dysfunctions were treated with trazodone hydrochloride (Group 1) and extracts from Psilocybe cubensis mushrooms (Group 2), and compared to conventional treatment with fluoxetine hydrochloride. The animals were diagnosed and evaluated using questionnaires aimed at diagnosing and monitoring the evolution of treatment, based on the literature referenced in this study. Atypical behaviors associated with primary and secondary disorders were mitigated or eliminated in Group 1 (n=4), Group 2 (n=4), and the conventional treatment group. However, fluoxetine hydrochloride showed a reduction in appetite as a side effect.

The Future of Robotics: Integrating Biological Components in Biohybrid Robotics for Enhanced Functionality and Adaptability

Biohybrid robotics, an emerging interdisciplinary field, combines biological tissues with synthetic robotic systems to create machines that exhibit enhanced functionality, adaptability, and efficiency. By integrating living cells, muscles, or other biological components with engineered structures, biohybrid robots are designed to mimic natural processes and behaviors, offering the potential for significant advancements in soft robotics, medical devices, and autonomous systems. This paper explores the latest developments in biohybrid robotics, focusing on the design principles, challenges in integrating biological and synthetic components, and the potential applications in fields such as healthcare, environmental monitoring, and bioengineering. By leveraging the inherent advantages of biological tissues—such as self-healing, energy efficiency, and adaptive responsiveness—biohybrid robots could outperform conventional robotic systems in tasks that require flexibility, precision, and interaction with dynamic environments. This research also examines the ethical and technical challenges associated with the field, including the sustainability of biological materials and the long-term stability of these systems. The potential for biohybrid robotics to revolutionize industries by blending biological intelligence with synthetic durability underscores the significance of this rapidly evolving technology. Biohybrid robotics not only holds promise for creating more versatile and efficient machines but also represents a major step toward bridging the gap between biology and engineering. By harnessing the unique properties of biological systems, such as their ability to grow, repair, and adapt to changing environments, biohybrid robots can offer solutions to challenges that traditional robotics struggle to address. For example, in the medical field, these robots could assist in developing more effective prosthetics, bio-inspired implants, and even robotic systems that work inside the body to perform tasks with a level of precision and biocompatibility previously unattainable. This research delves into the potential for future advancements in areas such as environmental sustainability, where biohybrid robots could be used for tasks like pollution detection and waste management. Their biological components would enable them to interact with natural ecosystems in more seamless and non-disruptive ways. However, this integration of living tissues with technology also raises important ethical considerations regarding the use of biological materials and the extent to which we can manipulate living organisms for technological purposes. Addressing these challenges will be critical to the successful development and deployment of biohybrid robotics in real-world applications.

Cow comfort, behavior and welfare with specific reference to dairy cattle: A review

Cow comfort is a significant consideration in dairy farming worldwide. Providing an ideal microclimate could offer a comfortable environment for the dairy cows and is essential to ensure a positive relationship with the health condition and productivity so that the animals can adapt and produce optimally. In such an environment, cows should be able to express natural behavior patterns, which are important for their well-being and overall comfort. Various measures have been developed to evaluate and monitor cow welfare and comfort, including examining aspects such as behavior, management and their correlation with thermal stress and economic implications. This article provides details on the different measures used to assess cow comfort, behavioral adjustments, and strategies to manage thermal stress. It also highlights various features that help cows adapt to these conditions, offering valuable insights for enhancing dairy cow management practices. Cow comfort indices are used to assess the comfort and welfare aspects of dairy cows based on four behavioral patterns such as lying down, standing, feeding, and drinking. Indicators of good cow comfort in the dairy farming system include improved milk production, improved reproduction, improved feed intake, most resting time, reduction of injuries, absence of lameness, better adaptation, better health, and better economic efficiency. Thus, there is a need to have a thorough understanding and implementation of physiological and behavioral adaptive features that would help to formulate better management strategies for dairy cows to be comfortable and produce at ease. This will ensure an optimum economic return for dairy farms.

The Impact of Puzzle Feeders, Ice-Pops and Artificial Seaweed on Captive Harbour Seals (Phoca vitulina) Behaviour

Environmental enrichment is used in zoos and aquaria to improve animal welfare through the stimulation of naturalistic behaviours and reduction of stereotypic behaviours. This study investigated the impact of new enrichment items on the behaviour of a group of captive adult harbour seals. Data were collected in summer-autumn 2023 using continuous scan sampling and all behaviours one-zero recording method for 1-minute intervals (4 hours/day, 8 days). Under standard enrichment conditions, more than 90% of the seals’ behavioural budget was represented by naturalistic behaviours, with low levels of pattern group swimming, which occurred mainly before the two daily shows. Group swimming decreased and random swimming increased before the seal shows on days with new enrichment, but these differences were not statistically significant. The presence of new enrichment items led to a significant increase in exploration and a significant decrease in group swimming only during the morning periods when the new items were actually present in the enclosure (p&lt;0.05, Kruskal Wallis test). During these periods the seals interacted most frequently with the submersed fish-filled puzzle feeders and least frequently with the floating artificial seaweed. This study concluded that new environmental enrichment may be beneficial even for seals displaying low levels of stereotypic behaviours as it provides more behavioural choices and helps promote active naturalistic exploratory behaviours which may alleviate captivity induced stress and improve welfare.

Synthetic torpor confers cardioprotection against myocardial ischaemia/reperfusion injury in the rat

Abstract Introduction Torpor is a hypothermic, bradycardic, hypometabolic state enabling animals, such as mice, to survive in unfavourable environmental conditions such as cold exposure or reduced food availability. It is thought to be a cardioprotective state. There is interest in developing models that mimic aspects of torpor in clinical settings such as ischaemia-reperfusion injury. The preoptic area of the hypothalamus (POA) has emerged as a key centre for triggering torpor in the mouse. Purpose Induce a synthetic torpor-like state in a species that does not naturally enter torpor (the rat) by chemoactivation of neurons in the POA that correspond to those that induce torpor in the mouse. Test the cardioprotective effects of synthetic torpor in the Langendorff ischaemia-reperfusion preparation. Methods Designer receptors exclusively activated by designer drugs (DREADDs) were used to exogenously activate excitatory neurons in the POA of the rat hypothalamus. Viral vectors (pAAV-CaMKIIa-hM3D(Gq)-mCherry) were stereotaxically injected bilaterally into the POA under ketamine and medetomidine anaesthesia, resulting in expression of DREADDs in excitatory neurons. Control animals received a vector delivering the gene for a fluorescent protein only. DREADD receptors in transfected neurons were activated by subsequent injection of Clozapine-N-Oxide (CNO, 2mg/kg IP), which results in neuronal activation and induces synthetic torpor. Heart rate and core temperature were monitored using implanted telemeters. 2 weeks after vector injection, animals were anaesthetised using 5% isoflurane and culled by cervical dislocation. Hearts were excised and ex-vivo whole heart perfusion at 37°C was performed using the Langendorff apparatus. Hearts were subjected to 30 minutes of global warm ischaemia followed by 60 minutes of reperfusion. Hearts were stained using tetrazolium triphenyl chloride, and infarct size as a proportion of the total heart area calculated. Results Chemoactivation of rat POA neurons induced synthetic torpor characterised by bradycardia (pre: 341.0 ± 17.73bpm, post: 233.4 ± 20.47bpm, paired t (4) = 5.4791, p = .0054) and hypothermia (36.2 ±0.40°C vs 31.6 ± 0.55°C (paired t (4) = 7.9023, p = .0014). CNO had no effect on heart rate or core temperature in control animals. The mean infarct size was significantly lower in synthetic torpor (21.54 ±2.84%) compared to control hearts (29.62 ±2.59%) (unpaired t (23) = 2.1054, p = .0464). Conclusions Synthetic torpor, induced centrally in a species for which torpor is not a natural behaviour, confers striking cardioprotection in an ex-vivo ischaemia-reperfusion model. This novel approach to cardioprotection against myocardial ischaemia/reperfusion injury should be further investigated as a potential therapeutic target for use in clinical practice.

Just-in-time: Gaze guidance in natural behavior.

Natural eye movements have primarily been studied for over-learned activities such as tea-making, sandwich-making, and hand-washing, which have a fixed sequence of associated actions. These studies demonstrate a sequential activation of low-level cognitive schemas facilitating task completion. However, whether these action schemas are activated in the same pattern when a task is novel and a sequence of actions must be planned in the moment is unclear. Here, we recorded gaze and body movements in a naturalistic task to study action-oriented gaze behavior. In a virtual environment, subjects moved objects on a life-size shelf to achieve a given order. To compel cognitive planning, we added complexity to the sorting tasks. Fixations aligned with the action onset showed gaze as tightly coupled with the action sequence, and task complexity moderately affected the proportion of fixations on the task-relevant regions. Our analysis revealed that gaze fixations were allocated to action-relevant targets just in time. Planning behavior predominantly corresponded to a greater visual search for task-relevant objects before the action onset. The results support the idea that natural behavior relies on the frugal use of working memory, and humans refrain from encoding objects in the environment to plan long-term actions. Instead, they prefer just-in-time planning by searching for action-relevant items at the moment, directing their body and hand to it, monitoring the action until it is terminated, and moving on to the following action.