Eric S. Fortune - US grants

time perception; space perception; neural information processing; behavioral /social science research tag; catfish;

Project Abstract
ASM: Multi-Sensory Control of Tracking Behavior in Weakly Electric Fish
PI: Noah J. Cowan, Dept. of Mechanical Engineering, Johns Hopkins University
Co-PI: Eric S. Fortune, Dept. of Psychological and Brain Sciences, Johns Hopkins University
Intellectual Merit- A tightly integrated and multidisciplinary approach using a uniquely
suited model system will help answer a fundamental question in sensorimotor
integration: how is information processed by the nervous system to control locomotion?
In the model system, weakly electric fish robustly and naturally swim back and forth
to stabilize visual and/or electrosensory images, just as humans smoothly track moving
objects with their eyes to stabilize visual images. This collaborative work builds on the
strengths of the PI, a modeler of sensorimotor locomotion systems and the Co-PI, an
organismal sensory neurobiologist.
The approach incorporates mathematical modeling, behavioral experiments, and
neurophysiological analyses. A mathematical model of the tracking behavior makes
specific, testable predictions of both behavior and neural processing. The model's
predictions of behavior will be tested by systematically varying visual and
electrosensory information available to the fish for tracking a moving sensory
image. The model's predictions will also be tested using central nervous system
recordings in awake, behaving animals. The stimuli will include signals identical
to those used for behavioral experiments, whose input-output relations are
predictable from the model. Broader Impacts Undergraduate and graduate trainees
will receive multidisciplinary training in neuroscience, experimental design, data
collection and analysis, and computational modeling. Further, we will co-teach a
new undergraduate course in sensor-based animal locomotion, and a companion
graduate seminar. Finally, the study of sensorimotor animal behaviors has great
potential to inspire novel strategies for autonomous control in artificial systems.

How do brains control behavior? For most behaviors, animals use information gathered by sensory receptors (like vision, touch, and receptors in muscles) to control movement. When an animal or a person moves through its environment, its movement generates widespread stimulation of sensory receptors, such as the flow of visual images on the retina. These studies examine the relationships between movement, sensing, and brain mechanisms to identify fundamental principles for the control of behavior. The work includes a tightly integrated combination of behavioral experiments, mathematical modeling, and neurophysiological experiments that will be conducted in an ideally suited biological system, weakly electric fishes. These fishes have the ability to produce and detect electric fields, which permit experiments and analyses that are not possible in other animals. The behavioral experiments will measure the natural movements and social signals of these fish in the natural habitat of the Amazon basin and in the laboratory. The results will be mathematically modeled to determine the sensory images experienced by the fish in these settings. Reproductions of these sensory experiences will then be presented to the fish in neurophysiological experiments to examine the neural codes and mechanisms for sensory processing and locomotor control. The ultimate goal of the project is to describe basic principles for sensorimotor control that will be applicable to all animals, and can be translated for use in robotic systems. Interestingly, the behavioral studies in the Amazon basin will require the development and deployment of new electronic systems that will be used for environmental monitoring of critical aquatic habitats. Finally, these experiments will involve the training of promising students in both Ecuador and at the Johns Hopkins University in integrative biology and mathematical modeling.

How do animals, including humans, cooperate? Cooperative behaviors often involve extraordinary precision for success. Consider, for example, the level of coordination and control that is necessary for an Olympic couples' figure skating. The goal of the project is to understand how the brains of two or more individual animals integrate sensory cues to modulate an animal's motor systems to achieve these sorts of remarkable performances. The investigators will study a well-suited animal model system, the plain-tailed wren, which produces a cooperative duet song that is unusually amenable to behavioral and neurophysiological experiments. The investigators will travel to the natural habitats of these birds in the Andes Mountains and work with undergraduates and under-represented students from the United States and Ecuador. These students will be trained to conduct the technically complex experiments, which involve the analysis of brain activity of single neurons. The project will also develop research infrastructure in Ecuador, which will be used in teaching efforts for students from the United States and other countries, and in monitoring of animal activity in unique Andean habitats. These experiments will elucidate the specific neural mechanisms and computations that are used in the coordination of vocal behavior between individual wrens. Because birds and other vertebrate animals (including humans) use nearly identical neural structures and mechanisms, these data will have implications that are relevant across animal species. The work will also include the construction of mathematical models that capture the findings, which will facilitate the translation of insights from the brains of these unique animals to the study of other species and into engineering principles and applications.