Metabolism underpins all life‐sustaining processes and varies profoundly with body size, temperature and locomotor activity. A current theory explains some of the size‐dependence of metabolic rate ...(its mass exponent, b) through changes in metabolic level (L). We propose two predictive advances that: (a) combine the above theory with the evolved avoidance of oxygen limitation in water‐breathers experiencing warming, and (b) quantify the overall magnitude of combined temperatures and degrees of locomotion on metabolic scaling across air‐ and water‐breathers. We use intraspecific metabolic scaling responses to temperature (523 regressions) and activity (281 regressions) in diverse ectothermic vertebrates (fish, reptiles and amphibians) to show that b decreases with temperature‐increased L in water‐breathers, supporting surface area‐related avoidance of oxygen limitation, whereas b increases with activity‐increased L in air‐breathers, following volume‐related influences. This new theoretical integration quantitatively incorporates different influences (warming, locomotion) and respiration modes (aquatic, terrestrial) on animal energetics.
Metabolic scaling (i.e. size‐dependence of metabolism) varies widely with temperature and locomotor activity. We here show that intraspecific changes in metabolic scaling with warming and increasing activity differ between water‐ and air‐breathing ectothermic vertebrates. By combining evolved responses to oxygen limitation and influences of volume‐related processes, our study quantitatively incorporates temperature, activity and respiration modes to explain animal energetics.
The acquisition of information from parallel sensory pathways is a hallmark of coordinated movement in animals. Insect flight, for example, relies on both mechanosensory and visual pathways. Our ...challenge is to disentangle the relative contribution of each modality to the control of behavior. Toward this end, we show an experimental and analytical framework leveraging sensory conflict, a means for independently exciting and modeling separate sensory pathways within a multisensory behavior. As a model, we examine the hovering flower-feeding behavior in the hawkmoth Manduca sexta. In the laboratory, moths feed from a robotically actuated two-part artificial flower that allows independent presentation of visual and mechanosensory cues. Freely flying moths track lateral flower motion stimuli in an assay spanning both coupled motion, in which visual and mechanosensory cues follow the same motion trajectory, and sensory conflict, in which the two sensory modalities encode different motion stimuli. Applying a frequency-domain system identification analysis, we find that the tracking behavior is, in fact, multisensory and arises from a linear summation of visual and mechanosensory pathways. The response dynamics are highly preserved across individuals, providing a model for predicting the response to novel multimodal stimuli. Surprisingly, we find that each pathway in and of itself is sufficient for driving tracking behavior. When multiple sensory pathways elicit strong behavioral responses, this parallel architecture furnishes robustness via redundancy.
The universal phenomenon of evolution consists of change after change in flow configuration in a time direction that is perceptible to the observer. This reality clashes with the doctrine of precise ...optima, minima, and maxima, now rigidly in place because of calculus and computational simulations of all kinds of flowing and changing configurations. With two dissimilar examples, access on an area (a human settlement) and along a line (animal locomotion), it is shown that even a 1-percent imperfection in performance is accompanied by a sizable bandwidth of freedom to hit the ‘target’, that is, an easily accessible design with close to perfect performance. The evolutionary designs reveal the physics behind the phenomenon of diminishing returns in the vicinity of the mathematical optimum. In evolution what works is kept.
Machine learning for modeling animal movement Wijeyakulasuriya, Dhanushi A; Eisenhauer, Elizabeth W; Shaby, Benjamin A ...
PloS one,
07/2020, Letnik:
15, Številka:
7
Journal Article
Recenzirano
Odprti dostop
Animal movement drives important ecological processes such as migration and the spread of infectious disease. Current approaches to modeling animal tracking data focus on parametric models used to ...understand environmental effects on movement behavior and to fill in missing tracking data. Machine Learning and Deep learning algorithms are powerful and flexible predictive modeling tools but have rarely been applied to animal movement data. In this study we present a general framework for predicting animal movement that is a combination of two steps: first predicting movement behavioral states and second predicting the animal's velocity. We specify this framework at the individual level as well as for collective movement. We use Random Forests, Neural and Recurrent Neural Networks to compare performance predicting one step ahead as well as long range simulations. We compare results against a custom constructed Stochastic Differential Equation (SDE) model. We apply this approach to high resolution ant movement data. We found that the individual level Machine Learning and Deep Learning methods outperformed the SDE model for one step ahead prediction. The SDE model did comparatively better at simulating long range movement behaviour. Of the Machine Learning and Deep Learning models the Long Short Term Memory (LSTM) individual level model did best at long range simulations. We also applied the Random Forest and LSTM individual level models to model gull migratory movement to demonstrate the generalizability of this framework. Machine Learning and deep learning models are easier to specify compared to traditional parametric movement models which can have restrictive assumptions. However, machine learning and deep learning models are less interpretable than parametric movement models. The type of model used should be determined by the goal of the study, if the goal is prediction, our study provides evidence that machine learning and deep learning models could be useful tools.
Alcohol use disorder (AUD) is a leading cause of preventable death in the United States, however existing treatments are ineffective and produce aversive side effects such as nausea and fatigue. One ...potential therapeutic for AUD is the α3β4 nicotinic acetylcholine receptor (nAChR) antagonist 18-methoxycoronaridine (18-MC). Prior work has shown that 18-MC reduces ethanol consumption in rodent models. The present study sought to further examine the therapeutic potential of 18-MC by testing its effects on nonconsummatory behaviors. We examined 2 behavioral measures: ethanol-induced locomotor stimulation, which measures euphoric properties of the drug, and the expression of locomotor sensitization which models neuroadaptations in response to repeated exposure. We tested dose-dependent effects of 18-MC (0, 10, 20 and 30 mg/kg) administration on ethanol stimulation and locomotor sensitization in female and male DBA/2J mice. 18-MC had no effect on acute ethanol-induced stimulation, but the highest dose (30 mg/kg) significantly decreased the expression of locomotor sensitization. Our results support the involvement of α3β4 nAChR in the expression of ethanol-induced locomotor sensitization and suggest that 18-MC may be a therapeutic for AUD.
Public Health Significance
The present study found that 18-methoxycoronaridine (18-MC) specifically reduced expression of ethanol-induced locomotor sensitization, which is a behavioral measure that models neural adaptations to chronic alcohol use and is thought to reflect dependence. These results support the involvement of α3β4 nicotinic acetylcholine receptors in ethanol sensitization and support 18-MC as a potential therapeutic for individuals suffering from alcohol use disorder.
Our movements can hinder our ability to sense the world. Movements can induce sensory input (for example, when you hit something) that is indistinguishable from the input that is caused by external ...agents (for example, when something hits you). It is critical for nervous systems to be able to differentiate between these two scenarios. A ubiquitous strategy is to route copies of movement commands to sensory structures. These signals, which are referred to as corollary discharge (CD), influence sensory processing in myriad ways. Here we review the CD circuits that have been uncovered by neurophysiological studies and suggest a functional taxonomic classification of CD across the animal kingdom. This broad understanding of CD circuits lays the groundwork for more challenging studies that combine neurophysiology and psychophysics to probe the role of CD in perception.
The body of most creatures is composed of interconnected joints. During motion, the spatial location of these joints changes, but they must maintain their distances to one another, effectively moving ...semirigidly. This pattern, termed "biological motion" in the literature, can be used as a visual cue, enabling many animals (including humans) to distinguish animate from inanimate objects. Crucially, even artificially created scrambled stimuli, with no recognizable structure but that maintains semirigid movement patterns, are perceived as animated. However, to date, biological motion perception has only been reported in vertebrates. Due to their highly developed visual system and complex visual behaviors, we investigated the capability of jumping spiders to discriminate biological from nonbiological motion using point-light display stimuli. These kinds of stimuli maintain motion information while being devoid of structure. By constraining spiders on a spherical treadmill, we simultaneously presented 2 point-light displays with specific dynamic traits and registered their preference by observing which pattern they turned toward. Spiders clearly demonstrated the ability to discriminate between biological motion and random stimuli, but curiously turned preferentially toward the latter. However, they showed no preference between biological and scrambled displays, results that match responses produced by vertebrates. Crucially, spiders turned toward the stimuli when these were only visible by the lateral eyes, evidence that this task may be eye specific. This represents the first demonstration of biological motion recognition in an invertebrate, posing crucial questions about the evolutionary history of this ability and complex visual processing in nonvertebrate systems.
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