Cognitive Science Program

Toward experimental validation of a model for human sensorimotor learning and control in teleoperation (2017)
Eatai Roth, Darrin Howell, Cydney Beckwith and Samuel A Burden
International Society for Optics and Photonics. 10194 101941X

Abstract

Humans, interacting with cyber–physical systems (CPS), formulate beliefs about the system’s dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human–cyber–physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system’s dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator’s ability to learn and invert such models, and distinguish this behavior from that achieved by …

Honeybees in a virtual reality environment learn unique combinations of colour and shape (2017)
Claire Rusch, Eatai Roth, Clément Vinauger and Jeffrey A Riffell
Journal of Experimental Biology, 220 (19), 3478-3487

Abstract

Honeybees are well-known models for the study of visual learning and memory. Whereas most of our knowledge of learned responses comes from experiments using free-flying bees, a tethered preparation would allow fine-scale control of the visual stimuli as well as accurate characterization of the learned responses. Unfortunately, conditioning procedures using visual stimuli in tethered bees have been limited in their efficacy. In this study, using a novel virtual reality environment and a differential training protocol in tethered walking bees, we show that the majority of honeybees learn visual stimuli, and need only six paired training trials to learn the stimulus. We found that bees readily learn visual stimuli that differ in both shape and colour. However, bees learn certain components over others (colour versus shape), and visual stimuli are learned in a non-additive manner with the interaction of specific colour and …

Integration of parallel mechanosensory and visual pathways resolved through sensory conflict (2016)
Eatai Roth, Robert W Hall, Thomas L Daniel and Simon Sponberg
Proceedings of the National Academy of Sciences, 113 (45), 12832-12837

Abstract

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 …

A comparative approach to closed-loop computation (2014)
Eatai Roth, Simon Sponberg and Noah J Cowan
Elsevier Current Trends. 25 54-62

Abstract

Neural computation is inescapably closed-loop: the nervous system processes sensory signals to shape motor output, and motor output consequently shapes sensory input. Technological advances have enabled neuroscientists to close, open, and alter feedback loops in a wide range of experimental preparations. The experimental capability of manipulating the topology—that is, how information can flow between subsystems—provides new opportunities to understand the mechanisms and computations underlying behavior. These experiments encompass a spectrum of approaches from fully open-loop, restrained preparations to the fully closed-loop character of free behavior. Control theory and system identification provide a clear computational framework for relating these experimental approaches. We describe recent progress and new directions for translating experiments at one level in this spectrum to …

Feedback control as a framework for understanding tradeoffs in biology (2014)
Noah J Cowan, Mert M Ankarali, Jonathan P Dyhr, Manu S Madhav, Eatai Roth, Shahin Sefati ...
American Zoologist, 54 (2), 223-237

Abstract

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathematical basis for understanding the role of feedback in the stability (or change) of dynamical systems. It provides a framework for understanding any system with regulation via feedback, including biological ones such as regulatory gene networks, cellular metabolic systems, sensorimotor dynamics of moving animals, and even ecological or evolutionary dynamics of organisms and populations. Here, we focus on four case studies of the sensorimotor dynamics of animals, each of which involves the application of principles from control theory to probe stability and feedback in an organism’s response to perturbations. We use examples from aquatic (two behaviors performed by electric fish), terrestrial (following of walls by cockroaches …

Cellular mechanisms for integral feedback in visually guided behavior (2014)
Bettina Schnell, Peter T Weir, Eatai Roth, Adrienne L Fairhall and Michael H Dickinson
Proceedings of the National Academy of Sciences, 111 (15), 5700-5705

Abstract

Sensory feedback is a ubiquitous feature of guidance systems in both animals and engineered vehicles. For example, a common strategy for moving along a straight path is to turn such that the measured rate of rotation is zero. This task can be accomplished by using a feedback signal that is proportional to the instantaneous value of the measured sensory signal. In such a system, the addition of an integral term depending on past values of the sensory input is needed to eliminate steady-state error [proportional-integral (PI) control]. However, the means by which nervous systems implement such a computation are poorly understood. Here, we show that the optomotor responses of flying Drosophila follow a time course consistent with temporal integration of horizontal motion input. To investigate the cellular basis of this effect, we performed whole-cell patch-clamp recordings from the set of identified visual …

A task-level model for optomotor yaw regulation in drosophila melanogaster: A frequency-domain system identification approach (2012)
Eatai Roth, Michael B Reiser, Michael H Dickinson and Noah J Cowan
3721-3726

Abstract

Fruit flies adeptly coordinate flight maneuvers to seek, avoid, or otherwise interact with salient objects in their environment. In the laboratory, tethered flies modulate yaw torque to steer towards a dark vertical visual stimulus. This stripe-fixation behavior is robust and repeatable, making it a powerful paradigm for the study of optomotor control in flies. In this work, we study stripe fixation through a series of closed-loop perturbation experiments; flies are observed stabilizing moving stripes oscillating over a range of frequencies. A system identification analysis of input-output data furnishes a frequency response function (FRF), a nonparametric description of the behavior. We parameterize this FRF description to hypothesize a Proportional-Integral-Derivative (PID) control model for the fixation behavior. Lastly, we revisit previous work in which discrepancies in open- and closed-loop performance in stripe fixation were …

Active sensing via movement shapes spatiotemporal patterns of sensory feedback (2012)
Sarah A Stamper, Eatai Roth, Noah J Cowan and Eric S Fortune
Journal of Experimental Biology, 215 (9), 1567-1574

Abstract

Previous work has shown that animals alter their locomotor behavior to increase sensing volumes. However, an animal’s own movement also determines the spatial and temporal dynamics of sensory feedback. Because each sensory modality has unique spatiotemporal properties, movement has differential and potentially independent effects on each sensory system. Here we show that weakly electric fish dramatically adjust their locomotor behavior in relation to changes of modality-specific information in a task in which increasing sensory volume is irrelevant. We varied sensory information during a refuge-tracking task by changing illumination (vision) and conductivity (electroreception). The gain between refuge movement stimuli and fish tracking responses was functionally identical across all sensory conditions. However, there was a significant increase in the tracking error in the dark (no visual cues). This was …

Task-level Models for Image-stabilization Behaviors in Animals (2012)
Eatai Roth

Abstract

This research addresses a fundamental question in biology and neuroscience: how do animals process sensory information for the control of locomotor behaviors? Behaviors can be described as a sensorimotor loop: sensing (sensori-) governs action (-motor), action changes the environment, and these changes are perceived via sensing. Animal behavior arises from a concert of sensory, computational, and mechanical systems. Often, these mechanisms are studied independently (and often isolated from the context of the behavior) and the behavioral model is constructed from knowledge of the constituents, a bottom-up synthesis. Complementary to this approach, we model behavior at the level of the sensorimotor loop (the task-level) and subsequently generate hypotheses as to the mechanistic constituents. These top-down models serve to constrain permissible mechanisms and identify necessary neural computations. We design an assay of experiments and frequency-domain analyses to identify task-level behavioral models, specifically for image-stabilization behaviors. Imagestabilization describes a broad class of behaviors in which animals modulate movement to fixate a sensory signal. In this dissertation, we study analogous behaviors in two ii