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This review discusses how the nervous system controls the complex body movements keeping animals up and running. In particular, we revisit how research in insects has shed light on motor control principles that govern movements across the animal kingdom. Starting with the organization and evolution of the insect nervous system, we discuss insights into the neuronal control of behaviors varying in complexity, including escape, flight, crawling, walking, grooming, and courtship. These behaviors share specific control features. For instance, central pattern-generating circuits (CPG), which reside in proximity to the motor neurons and muscles, support the generation of rhythmic motor activity. The number of CPGs involved depends on the complexity of the motor apparatus controlled, such as wing pairs for flight or six pairs of multisegmented legs for walking. The different control architectures are introduced with respect to their organization, topology, and operation. Sensory feedback plays a pivotal role in shaping CPG activity into a functional, well-coordinated motor output. The activity of motor circuits is orchestrated by descending neurons connecting the brain to the ventral nerve cord or spinal cord, which initiate, maintain, modulate, and terminate different actions. We therefore discuss the current understanding of descending control and the contributions of individual, command-like descending neurons and population codes. To highlight how insights in insects help discover fundamental motor control principles, we cross-reference findings from other animals, particularly vertebrates. In addition, we discuss methodological advances that enabled breakthroughs in motor control research, including neurogenetics and connectomics, and discuss key open questions.
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Variability in locomotor dynamics reveals the critical role of feedback in task control
People come in different shapes and sizes, but most will perform similarly well if asked to complete a task requiring fine manual dexterity – such as holding a pen or picking up a single grape. How can different individuals, with different sized hands and muscles, produce such similar movements? One explanation is that an individual’s brain and nervous system become precisely tuned to mechanics of the body’s muscles and skeleton. An alternative explanation is that brain and nervous system use a more “robust” control policy that can compensate for differences in the body by relying on feedback from the senses to guide the movements. To distinguish between these two explanations, Uyanik et al. turned to weakly electric freshwater fish known as glass knifefish. These fish seek refuge within root systems, reed grass and among other objects in the water. They swim backwards and forwards to stay hidden despite constantly changing currents. Each fish shuttles back and forth by moving a long ribbon-like fin on the underside of its body. Uyanik et al. measured the movements of the ribbon fin under controlled conditions in the laboratory, and then used the data to create computer models of the brain and body of each fish. The models of each fish’s brain and body were quite different. To study how the brain interacts with the body, Uyanik et al. then conducted experiments reminiscent of those described in the story of Frankenstein and transplanted the brain from each computer model into the body of different model fish. These “brain swaps” had almost no effect on the model’s simulated swimming behavior. Instead, these “Frankenfish” used sensory feedback to compensate for any mismatch between their brain and body. This suggests that, for some behaviors, an animal’s brain does not need to be precisely tuned to the specific characteristics of its body. Instead, robust control of movement relies on many seemingly redundant systems that provide sensory feedback. This has implications for the field of robotics. It further suggests that when designing robots, engineers should prioritize enabling the robots to use sensory feedback to cope with unexpected events, a well-known idea in control engineering.
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- Award ID(s):
- 1557895
- PAR ID:
- 10230435
- Date Published:
- Journal Name:
- eLife
- Volume:
- 9
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.51219
