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• W2053369108 abstract "Are central motor networks composed of task-specific dedicated neurons or are the neurons multifunctional, entering shifting coalitions for particular tasks to form different functional networks? Recent experiments elegantly indicate the latter. Are central motor networks composed of task-specific dedicated neurons or are the neurons multifunctional, entering shifting coalitions for particular tasks to form different functional networks? Recent experiments elegantly indicate the latter. Multifunctional networks have been the darlings of systems neuroscientists since their clear articulation in a seminal review by Peter Getting in 1989 [1Getting P.A. Emerging principles governing the operation of neural networks.Annu. Rev. Neurosci. 1989; 12: 185-204Crossref PubMed Scopus (444) Google Scholar]. The anatomical substrate of synaptic connectivity within the nervous system only sets the limits of network inclusion. The ultimate configuration of a functional network, however, depends on hormonal, modulatory and activity state, and the same neurons are configured in different ways by these forces for different functional roles. Getting was led to this conclusion when he realized that the same neurons that participate in local withdrawal reflexes to weak stimuli are configured by strong stimuli to form an escape swimming pattern-generating network in the mollusk Tritonia[2Getting P.A. Dekin M.S. Mechanisms of pattern generation underlying swimming in Tritonia. IV. Gating of central pattern generator.J. Neurophysiol. 1985; 53: 466-480PubMed Google Scholar]. Invertebrate nervous systems, owing to their limited cell numbers and identifiably of individual neurons, have contributed most to this concept, because it has been possible to show how a given neuron participates in more than one functional circuit [3Shaw B.K. Kristan Jr., W.B. The neuronal basis of the behavioral choice between swimming and shortening in the leech: control is not selectively exercised at higher circuit levels.J. Neurosci. 1997; 17: 786-795PubMed Google Scholar, 4Popescu I.R. Frost W.N. Highly dissimilar behaviors mediated by a multifunctional network in the marine mollusk Tritonia diomedea.J. Neurosci. 2002; 22: 1985-1993PubMed Google Scholar, 5Jing J. Cropper E.C. Hurwitz I. Weiss K.R. The construction of movement with behavior-specific and behavior-independent modules.J. Neurosci. 2004; 24: 6315-6325Crossref PubMed Scopus (79) Google Scholar]. Still these ideas have infiltrated the thinking of systems neuroscientists working at all levels within the vertebrate nervous system, and progress has been made in research on the vertebrate spinal cord in defining multifunctional interneurons that participate in a variety of movements [6Li W.C. Higashijima S. Parry D.M. Roberts A. Soffe S.R. Primitive roles for inhibitory interneurons in developing frog spinal cord.J. Neurosci. 2004; 24: 5840-5848Crossref PubMed Scopus (81) Google Scholar, 7Berkowitz A. Physiology and morphology indicate that individual spinal interneurons contribute to diverse limb movements.J. Neurophysiol. 2005; 94: 4455-4470Crossref PubMed Scopus (42) Google Scholar]. Leading the way has been work on the stomatogastric nervous system that controls foregut movements in crustacea [8Marder E. Bucher D. Understanding circuit dynamics using the stomatogastric nervous system of lobsters and crabs.Annu. Rev. Physiol. 2006; 69: 13.1-13.26Google Scholar]. The stomatogastric ganglion, consisting of approximately 30 neurons, comprises three different pattern-generating networks that form from shifting coalitions of neurons; indeed, some neurons participate in more than one functional network simultaneously and express frequency components of the disparate rhythms that can be quantified as a measure of how much each neuron contributes to each functional network [9Bucher D. Taylor A.L. Marder E. Central pattern generating neurons simultaneously express fast and slow rhythmic activities in the stomatogastric ganglion.J. Neurophysiol. 2006; 95: 3617-3632Crossref PubMed Scopus (42) Google Scholar]. While this model has been startling in its usefulness and impact on modern thinking, still there are niggling doubters, who wondered whether such extensive multifunctionality would be apparent throughout the wider central nervous system (CNS) in its control of whole body behaviors. Approaching this issue in the wider CNS has not been easy even with the restricted nervous systems of invertebrates. Assessing the degree that individual neurons participate in different functional networks on a large scale is daunting with single-cell recording techniques. Moreover, early attempts at defining circuit overlap using voltage-sensitive dyes that permit simultaneous recordings from tens to hundreds of cells produced scary results. Thus Tsau et al.[10Tsau Y. Wu J.Y. Hopp H.P. Cohen L.B. Schiminovich D. Falk C.X. Distributed aspects of the response to siphon touch in Aplysia: spread of stimulus information and cross-correlation analysis.J. Neurosci. 1994; 14: 4167-4184PubMed Google Scholar] estimated that a light siphon touch sufficient to evoke the gill withdrawal reflex of Aplysia activated some 220 neurons (∼20% of the population) in the abdominal ganglion, 110 neurons in the pleural ganglion, and 650 neurons in the pedal ganglion; and Wu et al.[11Wu J.Y. Cohen L.B. Falk C.X. Neuronal activity during different behaviors in Aplysia: a distributed organization?.Science. 1994; 263: 820-823Crossref PubMed Scopus (104) Google Scholar] estimated that more than 90% of the neurons activated in the abdominal ganglion during the gill withdrawal reflex were also activated during respiratory pumping! Still, these studies pointed the way in the use of voltage-sensitive dyes and by indicating the need to develop and apply analysis tools for interpreting such data. Enter the medicinal leech. With only 10,000 neurons in its CNS, distributed largely in iterated segmental ganglia, the leech early promised to be ideal for functional circuit analysis [12Stent G.S. Kristan Jr., W.B. Friesen W.O. Ort C.A. Poon M. Calabrese R.L. Neuronal generation of the leech swimming movement.Science. 1978; 200: 1348-1357Crossref PubMed Scopus (123) Google Scholar], but it lost steam when taking cells two or three at a time descended into drudgery. Still, progress was made and neuronal networks for behaviors such as swimming, shortening and local bending began to be identified [13Kristan Jr., W.B. Calabrese R.L. Friesen W.O. Neuronal control of leech behavior.Prog. Neurobiol. 2005; 76: 279-327Crossref PubMed Scopus (271) Google Scholar]. Shaw and Kristan [3Shaw B.K. Kristan Jr., W.B. The neuronal basis of the behavioral choice between swimming and shortening in the leech: control is not selectively exercised at higher circuit levels.J. Neurosci. 1997; 17: 786-795PubMed Google Scholar] showed that whole body shortening and swimming, two incompatible behaviors, in fact share neurons at all levels of their respective functional networks, from sensory interneurons to circuit-gating neurons, to pattern-generating interneurons. Now, there has been a happy confluence of more refined voltage-sensitive dye monitoring techniques and sophisticated data analysis [14Briggman K.L. Abarbanel H.D. Kristan Jr., W.B. From crawling to cognition: analyzing the dynamical interactions among populations of neurons.Curr. Opin. Neurobiol. 2006; 16: 135-144Crossref PubMed Scopus (24) Google Scholar], permitting a more ambitious assessment of the degree of overlap and independence of functional networks that is dazzling in its elegance. Briggman and Kristan [15Briggman K.L. Kristan Jr., W.B. Imaging dedicated and multifunctional neural circuits generating distinct behaviors.J. Neurosci. 2006; 26: 10925-10933Crossref PubMed Scopus (101) Google Scholar] now report imaging ∼80% of the neurons of a segmental ganglion (∼400) using voltage-sensitive FRET dyes during execution of the swimming and crawling motor patterns in isolated nerve cords. The two motor patterns were elicited from the same nerve cord using different patterns of nerve stimulation. Neurons were associated with each pattern by measuring coherence of their voltage waveforms with identified individual neurons (usually a motor neuron) known to be involved in each network and active at a particular phase in the pattern (Figure 1A,B). This procedure not only permitted unambiguous assignment of a neuron to a functional network but also provided a phase measure — the relative timing of an individual neuron's electrical activity in each motor pattern. They found that ∼188 cells are active in crawling and ∼90 neurons active in swimming with 84 cells overlapping (Figure 1C). This startling result not only nails down the concept of multifunctionality on a large scale, but also suggests that the ganglionic circuit for crawling is reconfigured into one for swimming by 84 cells shifting their coalition, from their crawling partners to a new coalition with as few as six new members. It also suggests that crawling — as might have been expected from its greater diversity of muscle synergies and antagonisms, its more complex timing and its greater sensory dependence — requires a larger coalition of neurons to be implemented as a functional circuit. Somewhat surprising was the result of an analysis of the activity phase of the overlapping neurons in the two patterns: the activity phase in one pattern was found to have no predictive power for the phase in the other, suggesting that the two functional networks operate with different core mechanisms to produce their rhythmic patterns. Who are the members of these coalitions? Many of the neurons and their synaptic interactions in the swimming network are known from previous investigation with conventional recording/stimulating techniques [13Kristan Jr., W.B. Calabrese R.L. Friesen W.O. Neuronal control of leech behavior.Prog. Neurobiol. 2005; 76: 279-327Crossref PubMed Scopus (271) Google Scholar], so it was possible to analyze membership partially [15Briggman K.L. Kristan Jr., W.B. Imaging dedicated and multifunctional neural circuits generating distinct behaviors.J. Neurosci. 2006; 26: 10925-10933Crossref PubMed Scopus (101) Google Scholar]. Some are the pedestrian hacks we would expect — for example, motor neurons co-opted to play different roles for the different networks — but are there individual neurons that play key, albeit different, roles in the two functional pattern-generating networks? The beauty of the leech and the approach used by Briggman and Kristan [15Briggman K.L. Kristan Jr., W.B. Imaging dedicated and multifunctional neural circuits generating distinct behaviors.J. Neurosci. 2006; 26: 10925-10933Crossref PubMed Scopus (101) Google Scholar] is that previously unidentified neurons now shown to be active in both functional networks can then be tested with conventional techniques to determine their respective roles. One such neuron studied, cell 255, can perturb both ongoing crawling and swimming motor patterns when its activity is altered by intracellular current injection, indicating that it indeed plays a key pattern-generating role and will certainly be worthy of further investigation [15Briggman K.L. Kristan Jr., W.B. Imaging dedicated and multifunctional neural circuits generating distinct behaviors.J. Neurosci. 2006; 26: 10925-10933Crossref PubMed Scopus (101) Google Scholar]. Like may papers that history judges as seminal, the new one of Briggman and Kristan [15Briggman K.L. Kristan Jr., W.B. Imaging dedicated and multifunctional neural circuits generating distinct behaviors.J. Neurosci. 2006; 26: 10925-10933Crossref PubMed Scopus (101) Google Scholar] raises more questions than it answers; one itches for the detailed circuit analysis that only further electrophysiological experiments can currently render. Perhaps most vexing are questions arising from seeing previously identified neurons known to be involved in one network through the prism of the other. Cell 208 is such a player (Figure 1B); originally identified electrophysiologically as a member of the swimming pattern generator, this neuron was recently implicated by Briggman et al.[16Briggman K.L. Abarbanel H.D. Kristan Jr., W.B. Optical imaging of neuronal populations during decision-making.Science. 2005; 307: 896-901Crossref PubMed Scopus (229) Google Scholar], using similar imaging and analysis techniques, as a member of a small cadre of neurons that appear to determine the choice of whether the swimming circuit or the crawling network is configured — the behavioral choice to swim or crawl. Depolarizing this neuron biases the nerve cord to produce the crawl motor pattern, while hyperpolarizing this neuron biases this nerve cord toward the swimming motor program. Cell 208 is now found to be a member of both the swimming and the crawling networks [15Briggman K.L. Kristan Jr., W.B. Imaging dedicated and multifunctional neural circuits generating distinct behaviors.J. Neurosci. 2006; 26: 10925-10933Crossref PubMed Scopus (101) Google Scholar]. Apparently after throwing its weight toward which coalition will be formed, it merrily participates in either." @default.
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• W2053369108 title "Motor Networks: Shifting Coalitions" @default.
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