Cracking the code: using educational gaming for high-level thinking in physiology education.

The multidisciplinary nature of physiology requires students to acquire, retain, apply, and evaluate knowledge from different scientific disciplines. Optimal learning techniques, such as active learning, interleaving topics and conditions, and recall, can greatly enhance the speed and effectiveness with which students achieve this type of higher-order thinking. However, developing and implementing optimal learning techniques in the classroom can be both time-intensive and challenging for the instructor. In addition, students may be resistant or slow to accept novel learning processes. One way to potentially introduce these learning techniques in a fun and engaging way is through educational gaming, or using a game or game elements intentionally to support learning. In this article we present an easy-to-implement adaptation of the Codenames board game for the physiology classroom. The activity requires minimal preparation while addressing high-level learning outcomes. Postintervention surveys of students were collected in three different health-related academic programs, both graduate and undergraduate, at two different institutions. Results suggest that participating in the activity both actively engaged the students and pushed them toward high-level, integrative thinking regardless of class level.NEW & NOTEWORTHY An easy-to-implement word game (Codenames) was used to engage students in higher-level Bloom's thinking about physiology. The gameplay required students to recall, apply, evaluate, and debate as they developed and guessed clues as part of the game. Students found the activity fun, engaging, and challenging. The activity is relatively easy to implement both online and in person, requiring at minimum a simple list of vocabulary terms.

An insect-inspired model for visual binding I: learning objects and their characteristics.

Visual binding is the process of associating the responses of visual interneurons in different visual submodalities all of which are responding to the same object in the visual field. Recently identified neuropils in the insect brain termed optic glomeruli reside just downstream of the optic lobes and have an internal organization that could support visual binding. Working from anatomical similarities between optic and olfactory glomeruli, we have developed a model of visual binding based on common temporal fluctuations among signals of independent visual submodalities. Here we describe and demonstrate a neural network model capable both of refining selectivity of visual information in a given visual submodality, and of associating visual signals produced by different objects in the visual field by developing inhibitory neural synaptic weights representing the visual scene. We also show that this model is consistent with initial physiological data from optic glomeruli. Further, we discuss how this neural network model may be implemented in optic glomeruli at a neuronal level.

INSECT FLIGHT. Luminance-dependent visual processing enables moth flight in low light.

Animals must operate under an enormous range of light intensities. Nocturnal and twilight flying insects are hypothesized to compensate for dim conditions by integrating light over longer times. This slowing of visual processing would increase light sensitivity but should also reduce movement response times. Using freely hovering moths tracking robotic moving flowers, we showed that the moth's visual processing does slow in dim light. These longer response times are consistent with models of how visual neurons enhance sensitivity at low light intensities, but they could pose a challenge for moths feeding from swaying flowers. Dusk-foraging moths avoid this sensorimotor tradeoff; their nervous systems slow down but not so much as to interfere with their ability to track the movements of real wind-blown flowers.

Feedback control as a framework for understanding tradeoffs in biology.

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), and aerial environments (flight control by moths) to highlight how one can use control theory to understand the way feedback mechanisms interact with the physical dynamics of animals to determine their stability and response to sensory inputs and perturbations. Each case study is cast as a control problem with sensory input, neural processing, and motor dynamics, the output of which feeds back to the sensory inputs. Collectively, the interaction of these systems in a closed loop determines the behavior of the entire system.

Flexible strategies for flight control: an active role for the abdomen.

Moving animals orchestrate myriad motor systems in response to multimodal sensory inputs. Coordinating movement is particularly challenging in flight control, where animals deal with potential instability and multiple degrees of freedom of movement. Prior studies have focused on wings as the primary flight control structures, for which changes in angle of attack or shape are used to modulate lift and drag forces. However, other actuators that may impact flight performance are reflexively activated during flight. We investigated the visual-abdominal reflex displayed by the hawkmoth Manduca sexta to determine its role in flight control. We measured the open-loop stimulus-response characteristics (measured as a transfer function) between the visual stimulus and abdominal response in tethered moths. The transfer function reveals a 41 ms delay and a high-pass filter behavior with a pass band starting at ~0.5 Hz. We also developed a simplified mathematical model of hovering flight wherein articulation of the thoracic-abdominal joint redirects an average lift force provided by the wings. We show that control of the joint, subject to a high-pass filter, is sufficient to maintain stable hovering, but with a slim stability margin. Our experiments and models suggest a novel mechanism by which articulation of the body or 'airframe' of an animal can be used to redirect lift forces for effective flight control. Furthermore, the small stability margin may increase flight agility by easing the transition from stable flight to a more maneuverable, unstable regime.

Non-directional motion detectors can be used to mimic optic flow dependent behaviors.

Insect navigational behaviors including obstacle avoidance, grazing landings, and visual odometry are dependent on the ability to estimate flight speed based only on visual cues. In honeybees, this visual estimate of speed is largely independent of both the direction of motion and the spatial frequency content of the image. Electrophysiological recordings from the motion-sensitive cells believed to underlie these behaviors have long supported spatio-temporally tuned correlation-type models of visual motion detection whose speed tuning changes as the spatial frequency of a stimulus is varied. The result is an apparent conflict between behavioral experiments and the electrophysiological and modeling data. In this article, we demonstrate that conventional correlation-type models are sufficient to reproduce some of the speed-dependent behaviors observed in honeybees when square wave gratings are used, contrary to the theoretical predictions. However, these models fail to match the behavioral observations for sinusoidal stimuli. Instead, we show that non-directional motion detectors, which underlie the correlation-based computation of directional motion, can be used to mimic these same behaviors even when narrowband gratings are used. The existence of such non-directional motion detectors is supported both anatomically and electrophysiologically, and they have been hypothesized to be critical in the Dipteran elementary motion detector (EMD) circuit.

The spatial frequency tuning of optic-flow-dependent behaviors in the bumblebee Bombus impatiens.

Insects use visual estimates of flight speed for a variety of behaviors, including visual navigation, odometry, grazing landings and flight speed control, but the neuronal mechanisms underlying speed detection remain unknown. Although many models and theories have been proposed for how the brain extracts the angular speed of the retinal image, termed optic flow, we lack the detailed electrophysiological and behavioral data necessary to conclusively support any one model. One key property by which different models of motion detection can be differentiated is their spatiotemporal frequency tuning. Numerous studies have suggested that optic-flow-dependent behaviors are largely insensitive to the spatial frequency of a visual stimulus, but they have sampled only a narrow range of spatial frequencies, have not always used narrowband stimuli, and have yielded slightly different results between studies based on the behaviors being investigated. In this study, we present a detailed analysis of the spatial frequency dependence of the centering response in the bumblebee Bombus impatiens using sinusoidal and square wave patterns.