Chapter 2 - Genetic dissection of rhythmic motor networks in mice

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Abstract

Simple motor behaviors such as locomotion and respiration involve rhythmic and coordinated muscle movements that are generated by central pattern generator (CPG) networks in the spinal cord and hindbrain. These CPG networks produce measurable behavioral outputs and thus represent ideal model systems for studying the operational principles that the nervous system uses to produce specific behaviors. Recent advances in our understanding of the transcriptional code that controls neuronal development have provided an entry point into identifying and targeting distinct neuronal populations that make up locomotor CPG networks in the spinal cord. This has spurred the development of new genetic approaches to dissect and manipulate neuronal networks both in the spinal cord and hindbrain. Here we discuss how the advent of molecular genetics together with anatomical and physiological methods has begun to revolutionize studies of the neuronal networks controlling rhythmic motor behaviors in mice.

Section snippets

Rhythmic motor circuits in the hindbrain and spinal cord

The core neuronal networks that control rhythmic respiratory and locomotor motor behaviors reside in the hindbrain and spinal cord, respectively. These CPG networks generate simple organized motor rhythms in an autonomous manner. Initial efforts to decipher the general organization of these simple motor CPGs in vertebrates relied heavily on electrophysiological and pharmacological approaches. Such efforts were greatly aided by the development of in vitro hindbrain–spinal cord preparations in

The developmental program of the caudal neuroaxis

The developmental events that pattern the caudal neural tube play a central role in assembling sensorimotor circuits in the hindbrain and spinal cord (Goulding, 2009, Jessell, 2000). The position that a progenitor cell occupies along the dorsoventral (DV) axis confers a specific genetic code to these cells and thus serves as a major determinant of cell identity (Fig. 1a). This DV patterning program segregates newborn neurons into generic populations that are arrayed as longitudinal columns

Genetically defined interneuronal populations that shape the locomotor rhythm

The identification of genetic markers for different spinal interneuronal populations has laid the foundation for functional studies aimed at assessing the contribution that genetically defined cell types make to the CPG networks controlling locomotor or respiratory rhythmogenesis (Chapter 3 in this book). These efforts have been centered on broad interneuron classes including the V0, V1, V2a, and V3 interneurons (Stepien and Arber, 2008); however, attention is now turning to subtypes within

New genetic approaches for studying motor circuits in the spinal cord

The elaboration of a genetic classification scheme for the interneuron cell types involved in spinal motor control has opened up new routes for manipulating the spinal motor system and determining how specific motor behaviors are generated. The approaches used so far involve deleting or inactivating broad interneuron classes and assessing how this affects network activity (Table 2). This is usually achieved by generating transgenic animals in which a recombination event such as Cre-mediated

Conclusion

The delineation of the transcriptional code for neuronal cell populations in the ventral spinal cord and the emergence of several genetic approaches to manipulate cells of interest have paved the way for genetically and functionally dissecting the neural circuits controlling locomotion. The embryonic building blocks that make up these motor circuits are shared between the networks controlling respiration and locomotion. Thus, understanding how neuronal cell populations that comprise the

Acknowledgments

K. S. G. is funded by a Feodor Lynen Fellowship from Alexander von Humboldt Foundation. Research in the Goulding lab is supported by grants from the National Institutes of Health (NS031249, NS031978 and NS037075) and the Christopher and Dana Reeve Foundation. We would particularly like to thank Tim Hendricks, Floor Stam, and other members of the Goulding Lab for allowing us to cite their unpublished findings.

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