Development of site fidelity in the nocturnal amblypygid, \u3ci\u3ePhrynus marginemaculatus\u3c/i\u3e

Amblypygids are capable of navigation in the complex terrain of rainforests in near complete darkness. Path integration is unnecessary for successful homing, and the alternative mechanisms by which they navigate have yet to be elucidated. Here, our aims were to determine whether the amblypygid Phrynus marginemaculatus could be trained to reliably return to a target shelter in a laboratory arena—indicating goal recognition—and to document changes in behavior associated with the development of fidelity. We recorded nocturnal movements and space use by individuals over five nights in an arena in which subjects were provided with two shelters that differed in quality. The target shelter, unlike the alternative shelter, shielded subjects from light in daylight hours. Individuals consistently exited and returned to a shelter each night and from the third night onward chose the target shelter more often than the alternative shelter. Indeed, on the fifth night, every subject chose the target shelter. This transition was associated with changes in movement and space use in the arena. Notably, the movement features of outbound and inbound paths differed but did not change across nights. Individuals were also characterized by distinct behavioral strategies reflecting candidate homing mechanisms

Importance of the antenniform legs, but not vision, for homing by the neotropical whip spider \u3ci\u3eParaphrynus laevifrons\u3c/i\u3e

Amblypygids, or whip spiders, are nocturnal, predatory arthropods that display a robust ability to navigate to their home refuge. Prior field observations and displacement studies in amblypygids demonstrated an ability to home from distances as far away as 10 m. In the current study, micro-transmitters were used to take morning position fixes of individual Paraphrynus laevifrons following an experimental displacement of 10 m from their home refuge. The intention was to assess the relative importance of vision compared with sensory input acquired from the antenniform legs for navigation as well as other aspects of their spatial behavior. Displaced individuals were randomly assigned to three treatment groups: (i) control individuals; (ii) visiondeprived individuals, VD; and (iii) individuals with sensory input from the tips of their antenniform legs compromised, AD. Control and VD subjects were generally successful in returning home, and the direction of their movement on the first night following displacement was homeward oriented. By contrast, AD subjects experienced a complete loss of navigational ability, and movement on the first night indicated no hint of homeward orientation. The data strongly support the hypothesis that sensory input from the tips of the antenniform legs is necessary for successful homing in amblypygids following displacement to an unfamiliar location, and we hypothesize an essential role of olfaction for this navigational ability

Development of site fidelity in the nocturnal amblypygid, \u3ci\u3ePhrynus marginemaculatus\u3c/i\u3e

Amblypygids are capable of navigation in the complex terrain of rainforests in near complete darkness. Path integration is unnecessary for successful homing, and the alternative mechanisms by which they navigate have yet to be elucidated. Here, our aims were to determine whether the amblypygid Phrynus marginemaculatus could be trained to reliably return to a target shelter in a laboratory arena—indicating goal recognition—and to document changes in behavior associated with the development of fidelity. We recorded nocturnal movements and space use by individuals over five nights in an arena in which subjects were provided with two shelters that differed in quality. The target shelter, unlike the alternative shelter, shielded subjects from light in daylight hours. Individuals consistently exited and returned to a shelter each night and from the third night onward chose the target shelter more often than the alternative shelter. Indeed, on the fifth night, every subject chose the target shelter. This transition was associated with changes in movement and space use in the arena. Notably, the movement features of outbound and inbound paths differed but did not change across nights. Individuals were also characterized by distinct behavioral strategies reflecting candidate homing mechanisms

Computer Vision and Deep Learning Methods for Measuring and Modeling Animal Behavior

The study of animal behavior is a fundamental pursuit for answering scientific questions across a variety of fields — including neuroscience, psychology, ecology, genetics, and evolution.While the task of collecting accurate and complete behavioral data has typically always been difficult, laborious, and subjective, in recent years there has been rapid progress in methods for automatically quantifying behavior objectively and at scale. This progress has been primarily driven by the emergence of new computational hardware, software, and algorithms for measuring behavior. In order to reveal core insights about how animals organize their behavior with the increased quality and resolution of these data comes the need for new methods for data-driven modeling. Here, in this thesis, I focus on computational tools—the development of new algorithms and software—for measuring and modeling behavior using methods from computer vision, deep learning, Bayesian inference, and probabilistic programming, while also synthesizing these approaches with ideas from other relevant areas such as information theory, nonlinear dynamics, and statistical physics. First, I developed a barcode tracking system for automated behavioral studies where the location and identity of individuals can be reliably tracked over several weeks (or potentially longer) using conventional computer vision (Chapter 1). Next, I developed general-purpose deep learning methods for measuring animal posture — any set of user-selected body parts — in the laboratory and field (Chapter 2). Finally, I introduce methods for using these posture data to model behavior with techniques from machine learning andBayesian statistical inference (Chapter 3). Together these methods reduce barriers to measuring and modeling animal behavior and allow researchers to answer scientific questions that were previously intractablepublishe

Importance of the antenniform legs, but not vision, for homing by the neotropical whip spider \u3ci\u3eParaphrynus laevifrons\u3c/i\u3e

Amblypygids, or whip spiders, are nocturnal, predatory arthropods that display a robust ability to navigate to their home refuge. Prior field observations and displacement studies in amblypygids demonstrated an ability to home from distances as far away as 10 m. In the current study, micro-transmitters were used to take morning position fixes of individual Paraphrynus laevifrons following an experimental displacement of 10 m from their home refuge. The intention was to assess the relative importance of vision compared with sensory input acquired from the antenniform legs for navigation as well as other aspects of their spatial behavior. Displaced individuals were randomly assigned to three treatment groups: (i) control individuals; (ii) visiondeprived individuals, VD; and (iii) individuals with sensory input from the tips of their antenniform legs compromised, AD. Control and VD subjects were generally successful in returning home, and the direction of their movement on the first night following displacement was homeward oriented. By contrast, AD subjects experienced a complete loss of navigational ability, and movement on the first night indicated no hint of homeward orientation. The data strongly support the hypothesis that sensory input from the tips of the antenniform legs is necessary for successful homing in amblypygids following displacement to an unfamiliar location, and we hypothesize an essential role of olfaction for this navigational ability

Amblypygids: Model Organisms for the Study of Arthropod Navigation Mechanisms in Complex Environments?

Navigation is an ideal behavioral model for the study of sensory system integration and the neural substrates associated with complex behavior. For this broader purpose, however, it may be profitable to develop new model systems that are both tractable and sufficiently complex to ensure that information derived from a single sensory modality and path integration are inadequate to locate a goal. Here, we discuss some recent discoveries related to navigation by amblypygids, nocturnal arachnids that inhabit the tropics and sub-tropics. Nocturnal displacement experiments under the cover of a tropical rainforest reveal that these animals possess navigational abilities that are reminiscent, albeit on a smaller spatial scale, of true-navigating vertebrates. Specialized legs, called antenniform legs, which possess hundreds of olfactory and tactile sensory hairs, and vision appear to be involved. These animals also have enormous mushroom bodies, higher-order brain regions that, in insects, integrate contextual cues and may be involved in spatial memory. In amblypygids, the complexity of a nocturnal rainforest may impose navigational challenges that favor the integration of information derived from multimodal cues. Moreover, the movement of these animals is easily studied in the laboratory and putative neural integration sites of sensory information can be manipulated. Thus, amblypygids could serve as model organisms for the discovery of neural substrates associated with a unique and potentially sophisticated navigational capability. The diversity of habitats in which amblypygids are found also offers an opportunity for comparative studies of sensory integration and ecological selection pressures on navigation mechanisms

Vortex phase matching as a strategy for schooling in robots and in fish

It has long been proposed that flying and swimming animals could exploit neighbour-induced flows. Despite this it is still not clear whether, and if so how, schooling fish coordinate their movement to benefit from the vortices shed by others. To address this we developed bio-mimetic fish-like robots which allow us to measure directly the energy consumption associated with swimming together in pairs (the most common natural configuration in schooling fish). We find that followers, in any relative position to a near-neighbour, could obtain hydrodynamic benefits if they exhibit a tailbeat phase difference that varies linearly with front-back distance, a strategy we term 'vortex phase matching'. Experiments with pairs of freely-swimming fish reveal that followers exhibit this strategy, and that doing so requires neither a functioning visual nor lateral line system. Our results are consistent with the hypothesis that fish typically, but not exclusively, use vortex phase matching to save energy.publishe

Un sistema de seguimiento de códigos de barras automatizado para estudios de comportamiento en aves

Los recientes avances en tecnología permiten a los investigadores automatizar la medición del comportamiento animal. Estos métodos tienen múltiples ventajas sobre las observaciones directas y la entrada manual de datos, ya que reducen el sesgo relacionado con la percepción humana y la fatiga, y brindan conjuntos de datos más extensos y completos que mejoran el poder estadístico. Un desafío importante que la automatización puede superar es la observación de muchos individuos a la vez, lo que permite el seguimiento de todo el grupo o de toda la población.Recent advances in technology allow researchers to automate the measurement of animal behavior. These methods have multiple advantages over direct observations and manual data entry, reducing bias related to human perception and fatigue, and providing larger and more comprehensive data sets that improve statistical power. A major challenge that automation can overcome is the observation of many individuals at once, allowing the monitoring of the entire group or the entire population

Un sistema de seguimiento de códigos de barras automatizado para estudios de comportamiento en aves

Los recientes avances en tecnología permiten a los investigadores automatizar la medición del comportamiento animal. Estos métodos tienen múltiples ventajas sobre las observaciones directas y la entrada manual de datos, ya que reducen el sesgo relacionado con la percepción humana y la fatiga, y brindan conjuntos de datos más extensos y completos que mejoran el poder estadístico. Un desafío importante que la automatización puede superar es la observación de muchos individuos a la vez, lo que permite el seguimiento de todo el grupo o de toda la población.Recent advances in technology allow researchers to automate the measurement of animal behavior. These methods have multiple advantages over direct observations and manual data entry, reducing bias related to human perception and fatigue, and providing larger and more comprehensive data sets that improve statistical power. A major challenge that automation can overcome is the observation of many individuals at once, allowing the monitoring of the entire group or the entire population