Intersegmental coordination in invertebrates and vertebrates

Current Opinion in Neurobiology

Volumn 8, Issue 6, 1998, Pages 725-732

  Skinner, Frances K ^a   Mulloney, Brian ^b  

^a TORONTO WESTERN HOSPITAL   (Canada)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CRAYFISH; EXCITABILITY; INVERTEBRATE; LAMPREY; LOCOMOTION; MOTOR CONTROL; MOTOR COORDINATION; MUSCLE CONTRACTION; MUSCULOSKELETAL SYSTEM; NERVE CELL NETWORK; NONHUMAN; OSCILLATOR; PRIORITY JOURNAL; REVIEW; SWIMMING; TADPOLE; VERTEBRATE;

EID: 0031700609     PISSN: 09594388     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-4388(98)80114-1     Document Type: Article

References (54)

1. Wállen P, Williams TL. Fictive locomotion in the lamprey spinal cord in vitro compared with swimming in the intact and spinal animal. J Physiol. 347:1984;225-239.
2. McClellan AD. Organization of spinal locomotor networks: contributions from model systems. Comm Theor Biol. 4:1996;63-91.
3. Cohen AH, Holmes PJ, Rand RH. The nature of the coupling between segmental oscillators of the lamprey spinal generator for locomotion: a mathematical model. J Math Biol. 13:1982;345-369.
4. Kopell N, Ermentrout GB. Symmetry and phaselocking in chains of weakly coupled oscillators. Comm Pure Appl Math. 39:1986;623-660.
5. Kopell N, Ermentrout GB. Coupled oscillators and the design of central pattern generators. Math Biosci. 90:1988;87-109.
6. Kopell N, Ermentrout GB. Phase transitions and other phenomena in chains of coupled oscillators. SIAM J Appl Math. 50:1990;1014-1052.
7. Cohen AH, Ermentrout GB, Kiemel T, Kopell N, Sigvardt KA, Williams TL. Modelling of intersegmental coordination in the lamprey central pattern generator for locomotion. Trends Neurosci. 15:1992;434-438.
8. Sigvardt KA, Williams TL. Effects of local oscillator frequency on intersegmental coordination in the lamprey locomotor CPG: theory and experiment. J Neurophysiol. 76:1996;4094-4103.
9. Williams TL, Sigvardt KA. Intersegmental phase lags in the lamprey spinal cord: experimental confirmation of the existence of a boundary region. J Comput Neurosci. 1:1994;61-68.
10. Dale N. Excitatory synaptic drive for swimming mediated by amino acid receptors in the lamprey. J Neurosci. 6:1986;2662-2675.
11. Rouse DT Jr, McClellan AD. Descending propriospinal neurons in normal and spinal cord-transected lamprey. Exp Neurol. 146:1997;113-124.
12. Mellen N, Kiemel T, Cohen AH. Correlational analysis of fictive swimming in the lamprey reveals strong functional intersegmental coupling. J Neurophysiol. 73:1995;1020-1030.
13. Kiemel T, Cohen AH. Estimation of coupling strength in regenerated lamprey spinal cords based on a stochastic phase model. of outstanding interest J Comput Neurosci. 5:1998;267-284 Presents a simple stochastic model of two coupled phase oscillators and a method for fitting the model to experimental spike-train data or to sequences of burst times, with the goal of estimating coupling strengths. Unlike the spike-train cross-correlation histogram (CCH), this method is resistant to changes in the level of dynamic noise and in relative oscillator frequency. When applied to lesioned isolated lamprey spinal cords, significant coupling strength could be detected using the method although no interaction was observed in the CCH.
14. Hagevik A, McClellan AD. Coupling of spinal locomotor networks in larval lamprey revealed by receptor blockers for inhibitory amino acids: neurophysiology and computer modeling. J Neurophysiol. 72:1994;1810-1829.
15. McClellan AD, Hagevik A. Coordination of spinal locomotor activity in the lamprey: long distance coupling of spinal oscillators. of outstanding interest Exp Brain Res. 1998; In this experimental study, the authors stimulated the hindbrain, rather than using the standard pharmacological tools, to elicit swimming in lamprey. They found that information that affected intersegmental coordination extended at least 40 segments from its origin, considerably farther than had been suspected. However, this study also confirms that the dominant factors controlling intersegmental phase differences extend only a few segments on each side of their origin.
16. Miller WL, Sigvardt KA. Spectral analysis of oscillatory neural circuits. of special interest J Neurosci Methods. 80:1998;113-128 To assess unambiguously the effects of various experimental manipulations, the authors used Fourier spectral analysis to determine the frequency and intersegmental phase of a motor pattern, as well as their respective variabilities. The authors applied this technique to study the lamprey motor pattern after blocking short-range coupling and found that coupling extends over 20 segments and that short-range coupling is needed to maintain an appropriate and stable value of phase lag.
17. Cohen AH, Kiemel T. Intersegmental coordination: lessons from modeling systems of coupled non-linear oscillators. Am Zool. 33:1993;54-65.
18. Grillner S, Matsushima T, Wadden T, Tegnér J, El Manira A, Wallén P. The neurophysiological bases of undulatory locomotion in vertebrates. Semin Neurosci. 5:1993;17-27.
19. Matsushima T, Grillner S. Intersegmental coordination of undulatory movements - a 'trailing oscillator' hypothesis. Neuroreport. 1:1990;97-100.
20. Grillner S, Deliagina T, Ekeberg Ö, El Manira A, Hill RH, Lansner A, Orlovsky GN, Wallén P. Neural networks that coordinate locomotion and body orientation in lamprey. Trends Neurosci. 18:1995;270-279.
21. Hellgren J, Grillner S, Lansner A. Computer simulation of the segmental neural network generating locomotion in lamprey by using populations of network interneurons. Biol Cybern. 68:1992;1-13.
22. Grillner S, Matsushima T. The neural network underlying locomotion in lamprey - synaptic and cellular mechanisms. Neuron. 7:1991;1-15.
23. Wadden T, Hellgren J, Lansner A, Grillner S. Intersegmental coordination in the lamprey: simulations using a network model without segmental boundaries. Biol Cybern. 76:1997;1-9.
24. Tegnér J, Hellgren-Kotaleski J, Lansner A, Grillner S. Low-voltage-activated calcium channels in the lamprey locomotor network - simulation and experiment. J Neurophysiol. 77:1997;1795-1812.
25. Tegnér J, Lansner A, Grillner S. Modulation of burst frequency by calcium-dependent potassium channels in the lamprey locomotor system: dependence of the activity level. of special interest J Comput Neurosci. 5:1998;121-140 The authors designed a detailed segmental model of the lamprey spinal cord to account for the activity-dependent effects of apamin on the lamprey locomotor system. According to their model, the calcium-activated potassium conductance is affected by calcium entering during an action potential, but not by calcium entering through NMDA channels. Comparisons between a relaxation oscillator and the detailed lamprey model to negative current pulses suggests that the simpler model reasonably approximates the situation of NMDA-induced tetrodotoxin (TTX)-resistant membrane oscillations.
26. Williams TL. Phase coupling by synaptic spread in chains of coupled neuronal oscillators. Science. 258:1992;662-665.
27. Williams TL. Phase coupling in simulated chains of coupled oscillators representing the lamprey spinal cord. Neural Computation. 4:1992;546-558.
28. Williams TL, Bowtell G. The calculation of frequency-shift functions for chains of coupled oscillators, with application to a network model of the lamprey locomotor pattern generator. of outstanding interest J Comput Neurosci. 4:1997;47-55 This study builds on earlier work by Williams in which the abstract coupling function (the H-function in the PCO model) could be estimated (C-function) from a connectionist model of lamprey swimming using a cellular representation of the segmental oscillator. The authors designed an algorithm that calculates the H-function in terms of a single oscillator. Using the algorithm, they characterized the interactions between coupled oscillators and applied them to the lamprey CPG. This method make it possible to view 'biologically' the abstract PCO model, and should advance our understanding of what its predictions mean in biological terms.
29. Tunstall MJ, Sillar KT. Physiological and developmental aspects of intersegmental coordination in Xenopus embryos and tadpoles. Semin Neurosci. 5:1993;29-40.
30. Roberts A, Soffe SR, Perrins R. Spinal networks controlling swimming in hatchling Xenopus tadpoles. Stein PSG, Grillner S, Selverston AI, Stuart DG. Neurons, Networks, and Motor Behavior. 1997;83-89 MIT Press, Cambridge, Massachusetts.
31. Dale N. Experimentally derived model for the locomotor pattern generator in the Xenopus embryo. J Physiol (Lond). 489:1995;489-510.
32. Scrymgeour-Wedderburn JF, Reith CA, Sillar KT. Voltage oscillations in Xenopus spinal cord neurons: developmental onset and dependence on co-activation of NMDA and 5HT receptors. Eur J Neurosci. 9:1997;1473-1482.
33. McDearmid JR, Scrymgeour-Wedderburn JF, Sillar KT. Aminergic modulation of glycine release in a spinal network controlling swimming in Xenopus laevis. J Physiol (Lond). 503:1997;111-117.
34. + channels in motor pattern generation in the Xenopus embryo. of special interest J Neurosci. 18:1998;1602-1612 In agreement with an earlier model [31] of the swimming motor pattern in Xenopus embryo, the authors found that the slow potassium current plays a more important role in generating swimming than the fast potassium current, despite the fact that the fast current constitutes 80% of the outward current.
35. Tunstall MJ, Roberts A. A longitudinal gradient of synaptic drive in the spinal cord of Xenopus embryos and its role in coordination of swimming. J Physiol. 474:1994;393-405.
36. Tabak J, Moore LE. Simulation and parameter estimation study of a simple neuronal model of rhythm generation: role of NMDA and non-NMDA receptors. J Comput Neurosci. 5:1998;209-235.
37. Braun G, Mulloney B. Cholinergic modulation of the swimmeret system in crayfish. J Neurophysiol. 70:1993;2391-2398.
38. Ikeda K, Wiersma CAG. Autogenic rhythmicity in the abdominal ganglion of the crayfish: the control of swimmeret movements. Comp Biochem Physiol. 12:1964;107-115.
39. Mulloney B. A test of the excitability-gradient hypothesis in the swimmeret system of crayfish. of special interest J Neurosci. 17:1997;1860-1868 The idea that differences in the excitation, or in the excitability, of oscillators might account for orderly phase progressions is attractive because it is readily comprehensible; the hypothesis that such a gradient of excitability exists in the swimmeret system was proposed many years ago [38]. This paper demonstrates experimentally that, contrary to the predictions of the excitability-gradient hypothesis, there is no significant difference between the excitability of anterior and posterior segmental oscillators in this system.
40. Braun G, Mulloney B. Coordination in the crayfish swimmeret system: differential excitation causes changes in intersegmental phase. J Neurophysiol. 73:1995;880-885.
41. Skinner FK, Kopell N, Mulloney B. How does the crayfish swimmeret system work? Insights from nearest-neighbor coupled oscillator models. of special interest J Comput Neurosci. 4:1997;151-160 A systems-level model approach used for lamprey was adapted for the swimmeret system. A chain of four equally activated oscillators bidirectionally coupled to their nearest neighbors was used to match data from uniform and nonuniform excitation experiments. The results suggest four systems-level predictions: first, coupling is asymmetric (see Figure 1); second, ascending and descending synaptic strengths are approximately the same: third, changes in excitation must affect each oscillator's intrinsic frequency and might affect the intersegmental coupling; fourth, either ascending or descending coupling alone could produce the 25% phase lag observed in vivo.
42. Paul DH, Mulloney B. Intersegmental coordination of swimmeret rhythms in isolated nerve cords of crayfish. J Comp Physiol [A]. 158:1986;215-224.
43. Skinner FK, Mulloney B. Intersegmental coordination of limb movements during locomotion: mathematical models predict circuits that drive swimmeret beating. of outstanding interest J Neurosci. 18:1998;3831-3842 Can we make progress in understanding neural organization before all the critical components have been described? This computational paper addresses the (unknown) organization of the intersegmental coordinating circuits of the swimmeret system by constructing, first, a minimal cellular model of the local pattern-generating module that drives each limb, and then constructing a series of alternative coordinating circuits to see if any match the performance of the real system. The structure of the kernel of local circuits was constrained by experimental evidence, and the list of alternative intersegmental circuits was constrained both by predictions from a PCO model and by experimental results. The results include an intersegmental circuit whose dynamics match many features of the swimmeret system.
44. Friesen WO, Pearce RA. Mechanisms of intersegmental coordination in leech locomotion. Semin Neurosci. 5:1993;41-47.
45. Pearce RA, Friesen WO. A model for intersegmental coordination in the leech nerve cord. Biol Cybern. 58:1988;301-311.
46. Cheng J, Stein RB, Jovanovic K, Yoshida K, Bennett DJ, Han Y. Identification, localization, and modulation of neural networks for walking in the mudpuppy (necturus maculatus) spinal cord. of outstanding interest J Neurosci. 18:1998;4295-4304 An experimental attempt to locate and examine the spinal circuits responsible for extension and flexion of individual joints during walking. Both the mechanics of walking and the intersegmental coordination of limb movements require a different performance from the animals axial musculature. This paper gives some insight into how the nervous system achieves this difference.
47. Brown TG. The intrinsic factors in the act of progression in the mammal. Proc Roy Soc Lond [Biol]. 84:1911;308-319.
48. Stein PSG, McCullough ML, Currie SN. Reconstruction of flexor/extensor alternation during fictive rostral scratching by two-site stimulation in the spinal turtle with a transverse spinal hemisection. of outstanding interest J Neurosci. 18:1998;467-479 An insightful experimental study of the organization of turtle spinal cord. The authors found that movements about the hip joint, unlike movements about the knee or ankle, are controlled by a bilateral circuit. This feature suggests that this hip circuitry might be the place to explore evolutionary homologies between reptilian and lamprey spinal cord.
49. Delvolve I, Bem T, Cabelguen JM. Epaxial and limb muscle activity during swimming and terrestrial stepping in the adult newt, pleurodeles waltl. of outstanding interest J Neurophysiol. 78:1997;638-650 An experimental study of the interactions between the segmental circuits controlling limbs and those controlling axial musculature during swimming and walking. The existence of these separate circuits has been conjectural, but this paper shows that they do exist and can be studied electrophysiologically in these animals.
50. Canavier CC, Butera RJ, Dror RO, Baxter DA, Clark JW, Byrne JH. Phase response characteristics of model neurons determine which patterns are expressed in a ring circuit model of gait generation. Biol Cybern. 74:1997;367-380.
51. Grillner S. Ion channels and locomotion. Science. 278:1997;1087-1088.
52. Skinner FK, Kopell N, aiMarder E. Mechanisms for oscillation and frequency control in reciprocally inhibitory model neural networks. J Comput Neurosci. 1:1994;69-87.
53. Dale N, Kuenzi FM. Ionic currents, transmitters and models of motor pattern generators. Curr Opin Neurobiol. 7:1997;790-796.
54. Marder E, Kopell N, Sigvardt K. How computation aids in understanding biological networks. Stein P, Grillner S, Selverston AI, Stuart DG. Neurons, Networks, and Motor Behavior. 1997;139-149 MIT Press, Cambridge, Massachusetts.