Movements in the dark : flying, landing and walking in insects

Flying, as well as walking insects rely on vision to regulate locomotion, even in the dark when the visual system is much less reliable. To manage visual control of these behaviours at low light intensities, many insects have evolved optical adaptations, such as larger facet lenses and wider rhabdoms, and neural adaptations, such as spatial and temporal summation, to increase their visual sensitivity.To investigate the effect of light intensity on flight control in crepuscular insects, I filmed bumblebees flying through an experimental tunnel at different light intensities. I found that bumblebees control their flight well even in dim light but fly slower as light levels fall. We also measured the effect of light intensity on the response speed of bee photoreceptors and found that they respond more slowly at lower light intensities. These results indicate that bumblebees compensate both behaviourally and visually to be able to fly in dim light.Next, I examined the final moments of landing in bumblebees by training them to land on a flat platform that could be rotated to different orientations. I found that bumblebees adjust their body and head posture depending upon the orientation of the platform and that leg extension occurred at a constant distance from the surface (except at low platform tilts). I also investigated the effect of light intensity on the landing precision in bumblebees while landing at the same platform at two different orientations and at different light intensities. I found that bumblebees perform well-controlled landings in dim light, however, as light intensity decreased, the bees oriented their body more vertically and their head more horizontally relative to the horizontal plane and extended their legs further away from the platform. These results indicate that bumblebees rely on visual cues to perform smooth landings even in dim light.Finally, to investigate how walking insects adapt to dim light, we analysed the orientation performance of diurnal and nocturnal dung beetles while rolling their dung balls from the centre to the periphery of a circular arena in the lab as well as in the field. We found that both species oriented well to a point light source, such as the moon or an artificial light. When only wide-field cues were present, such as starlight or the polarization pattern around the moon, the nocturnal beetles were much better oriented. Moreover, we found no effect of light intensity on ball-rolling speed, suggesting that these beetles do not employ temporal summation strategies, but rather a spatial summation approach to adapt to dim light.To summarize, the data presented in this thesis has broadened our knowledge about insect flight, landing, walking and orientation performance in dim light and has given insights into which adaptations they might use to meet the challenges of unreliable visual signals

Identifying Plant and Feedback in Human Posture Control

Human upright bipedal stance is a classic example of a control system consisting of a plant (i.e., the physical body and its actuators) and feedback (i.e., neural control) operating continuously in a closed loop. Determining the mechanistic basis of behavior in a closed loop control system is problematic because experimental manipulations or deficits due to trauma/injury influence all parts of the loop. Moreover, experimental techniques to open the loop (e.g., isolate the plant) are not viable because bipedal upright stance is not possible without feedback. The goal of the proposed study is to use a technique called closed loop system identification (CLSI) to investigate properties of the plant and feedback separately. Human upright stance has typically been approximated as a single-joint inverted pendulum, simplifying not only the control of a multi-linked body but also how sensory information is processed relative to body dynamics. However, a recent study showed that a single-joint approximation is inadequate. Trunk and leg segments are in-phase at frequencies below 1 Hz of body sway and simultaneously anti-phase at frequencies above 1 Hz during quiet stance. My dissertation studies have investigated the coordination between the leg and trunk segments and how sensory information is processed relative to that coordination. For example, additional sensory information provided through visual or light touch information led to a change of the in-phase pattern but not the anti-phase pattern, indicating that the anti-phase pattern may not be neurally controlled, but more a function of biomechanical properties of a two-segment body. In a subsequent study, I probed whether an internal model of the body processes visual information relative to a single or double-linked body. The results suggested a simple control strategy that processes sensory information relative to a single-joint internal model providing further evidence that the anti-phase pattern is biomechanically driven. These studies suggest potential mechanisms but cannot rule out alternative hypotheses because the source of behavioral changes can be attributed to properties of the plant and/or feedback. Here I adopt the CLSI approach using perturbations to probe separate processes within the postural control loop. Mechanical perturbations introduce sway as an input to the feedback, which in turn generates muscle activity as an output. Visual perturbations elicit muscle activity (a motor command) as an input to the plant, which then triggers body sway as an output. Mappings of muscle activity to body sway and body sway to muscle activity are used to identify properties of the plant and feedback, respectively. The results suggest that feedback compensates for the low-pass properties of the plant, except at higher frequencies. An optimal control model minimizing the amount of muscle activation suggests that the mechanism underlying this lack of compensation may be due to an uncompensated time delay. These techniques have the potential for more precise identification of the source of deficits in the postural control loop, leading to improved rehabilitation techniques and treatment of balance deficits, which currently contributes to 40% of nursing home admissions and costs the US health care system over $20B per year

Postural Coordination Patterns: Visual Rotation and Translation

Recent studies have shown co-existing trunk-leg coordination patterns during quiet stance: in-phase and anti-phase for frequencies below and above 1 Hz, respectively. Two experiments investigated whether the nervous system assumes a multilinked internal model in sensory coupling? In the first experiment, we investigated the influence of the addition or removal of sensory information on these patterns. Trunk-leg coherence decreased with the addition of static vision and light touch, in the AP and ML directions, respectively, at frequencies below 1 Hz, suggesting the in-phase pattern may be more affected by neural control than the anti-phase pattern. In the second experiment, we compared translation of the visual field to a rotation relative to the ankle/hip. Gain and phase between the trunk/leg angles relative to the visual display showed only minor condition differences. The overall results suggest the nervous system adopts a simple control strategy of a single-link internal model at low frequencies

The role of peripheral vision in flow parsing

Identifying moving objects while we are moving is an important everyday skill. This ability allows us to monitor our surroundings, successfully interact with objects or people, and avoid potential hazards. Self-movement generates optical flow on the retina that complicates the recognition of moving objects from retinal motion alone. Rushton and Warren (2005) proposed a purely visual solution to this problem. They suggest that, in order to assess scene-relative object movement, the brain identifies and parses out (globally subtracts) patterns of visual flow that are consistent with self-movement. Existing research has demonstrated evidence of this flow parsing process in central vision (i.e. Warren & Rushton, 2008). This thesis aims to characterise the role of peripheral visual flow in this process. Research from the wider self-motion literature has often distinguished between central and peripheral vision. Some researchers have claimed that peripheral vision is specialised for self-motion perception, whilst more recent studies have challenged this assertion. This thesis investigates whether peripheral visual motion, traditionally considered to be a strong cue to self-movement, also contributes to flow parsing. The experimental work employed a simulated self-movement paradigm to isolate retinal motion from other non-visual cues. Thus, observers remained stationary whilst computer generated stimuli moved to produce patterns of retinal motion associated with actual self-movement. In the first set of experiments, I demonstrate that peripheral flow simulating forward or backward self-movement gives rise to characteristic flow parsing effects. This finding generalises to rotational observer motion (Chapter 3). Chapter 4 considers whether peripheral flow contributes to parsing for judgements of object size change. Finally, Chapter 5 investigates whether there is a benefit of peripheral information under conditions where central flow is potentially ambiguous. The results indicate that peripheral visual flow contributes to the flow parsing process. The contribution of flow in the near periphery appears to be maximally important