Single synapse information coding in intraburst spike patterns of central pattern generator motor neurons

Journal of Neuroscience

Volumn 31, Issue 34, 2011, Pages 12297-12306

  Brochini, Ludmila ^a   Carelli, Pedro V ^a,b   Pinto, Reynaldo D ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b FEDERAL UNIVERSITY OF PERNAMBUCO   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTIC METHOD; ANIMAL CELL; ANIMAL EXPERIMENT; ANIMAL TISSUE; ARTICLE; BRAIN NERVE CELL; CELL FUNCTION; COMPUTER MODEL; CONTROLLED STUDY; CRAB; ELECTROPHYSIOLOGY; FEMALE; INTRABURST SPIKE PATTERN; MALE; MOTONEURON; MUSCLE CONTRACTION; NERVE CELL NETWORK; NONHUMAN; PRIORITY JOURNAL; SPIKE; SYNAPSE;

ACTION POTENTIALS; ANIMALS; BRACHYURA; COMPUTER SIMULATION; FEMALE; GANGLIA, INVERTEBRATE; INHIBITORY POSTSYNAPTIC POTENTIALS; MALE; MODELS, NEUROLOGICAL; MOTOR NEURONS; MUSCLE CONTRACTION; NEURAL PATHWAYS; PALINURIDAE; PERIODICITY; REACTION TIME; SIGNAL PROCESSING, COMPUTER-ASSISTED; SYNAPTIC TRANSMISSION;

EID: 80052145184     PISSN: 02706474     EISSN: 15292401     Source Type: Journal    
DOI: 10.1523/JNEUROSCI.1568-11.2011     Document Type: Article

References (49)

1. Ayers J, Selverston AI (1984) Synaptic perturbation and entrainment of gastric mill rhythm of the spiny lobster. J Neurophysiol 51:113-125.
2. Bair W, Koch C (1996) Temporal precision of spike trains in extrastriate cortex of the behaving macaque monkey. Neural Comput 8:1185-1202.
3. Böhm H, Dybek E, Heizel HG (2001) Anatomy and in vivo activity of neurons connecting the crustacean stomatogastric nervous system to the brain. J Comp Physiol A 187:392-403.
4. Borst A, Theunissen FE (1999) Information theory and neural coding. Nat Neurosci 2:947-957.
5. Brocard F, Tazerart S, Vinay L (2010) Do pacemakers drive the central pattern generator for locomotion in mammals? Neuroscientist 16:139-155.
6. Butts DA, Weng C, Jin J, Yeh CI, Lesica NA, Alonso JM, Stanley GB (2007) Temporal precision in the neural code and the timescales of natural vision. Naure 449:92-95.
7. Campos D, Aguirre C, Serrano E, Rodriguez Ortiz FD, De Polavieja GG, Varona P (2007) Temporal structure in the bursting activity of the leech heartbeat CPG neurons. Neurocomputing 70:1792-1796.
8. Canavier CC, Achuthan S (2010) Pulse coupled oscillators and the phase resetting curve. Math Biosci 226:77-96.
9. Carelli PV, Reyes MB, Sartorelli JC, Pinto RD (2005) Whole cell stochastic model reproduces the irregularities found in the membrane potential of bursting neurons. J Neurophysiol 94:1169-1179.
10. Chacron MJ, Longtin A, Maler L (2004) To burst or not to burst? J Comput Neurosci 17:127-136.
11. Clarac F, Pearlstein E (2007) Invertebrate preparations and their contribution to neurobiology in the second half of the 20th century. Brain Res Rev 54:113-161.
12. Ermentrout GB, Galán RF, Urban NN (2007) Relating neural dynamics to neural coding. Phys Rev Lett 99:248103.
13. Eyherabide HG, Samengo I (2010) Time and category information in pattern-based codes. Front Comput Neurosci 4:145.
14. Eyherabide HG, Rokem A, Herz AV, Samengo I (2008) Burst firing is a neural code in an insect auditory system. Front Comput Neurosci 2:3-7.
15. Galán RF, Ermentrout GB, Urban NN (2005) Efficient estimation of phaseresetting curves in real neurons and its significance for neural-network modeling. Phys Rev Lett 94:158101.
16. Goaillard JM, Taylor AL, Schulz DJ, Marder E (2009) Functional consequences of animal-to-animal variation in circuit parameters. Nat Neurosci 12:1424-1430.
17. Grashow R, Brookings T, Marder E (2010) Compensation for variable intrinsic neuronal excitability by circuit-synaptic interactions. J Neurosci 30:9145-9156.
18. Hooper SL, Guschlbauer C, von Uckermann G, Büschges A (2007) Different motor neuron spike patterns produce contractions with very similar rises in graded slow muscles. J Neurophysiol 97:1428-1444.
19. Kayser C, Montemurro MA, Logothetis NK, Panzeri S (2009) Spike-phase coding boosts and stabilizes information carried by spatial and temporal spike patterns. Neuron 61:597-608.
20. Kreuz T, Chicharro D, Greschner M, Andrzejak RG (2011) Time-resolved and time-scale adaptive measures of spike train synchrony. J Neurosci Methods 195:92-106.
21. Kumar A, Rotter S, Aertsen A (2010) Spiking activity propagation in neuronal networks: reconciling different perspectives on neural coding. Nat Rev Neurosci 11:615-627.
22. Latorre R, Rodríguez FB, Varona P (2006) Neural signatures: multiple coding in spiking bursting cells. Biol Cybern 95:169-183.
23. MacKay DJC (2003) Information theory, inference, and learning algorithms. Cambridge, UK: Cambridge UP.
24. Marder E, Bucher D (2007) Understanding circuit dynamics using the stomatogastric nervous system of lobsters and crabs. Annu Rev Physiol 69:291-316.
25. Marder E, Prinz AA (2002) Modeling stability in neuron and network function: the role of activity in homeostasis. Bioessays 24:1145-1154.
26. Middleton JW, Yu N, Longtin A, Maler L (2011) Routing the flow of sensorysignals using plastic responses to bursts and isolated spikes: experiment and theory. J Neurosci 31:2461-2473.
27. Morris LG, Hooper SL (1997) Muscle response to changing neuronal input in the lobster (Panulirus interruptus) stomatogastric system: spike number-versus spike frequency-dependent domains. J Neurosci 17:5956-5971.
28. Moulins M, Vedel JP, Nagy F (1979) Complex motor neurone in crustacea: three axonal spike initiating zones in three different ganglia. Neurosci Lett 13:231-236.
29. Nowotny T, Szücs A, Pinto RD, Selverston AI (2006) StdpC: a modern dynamic clamp. J Neurosci Methods 158:287-299.
30. Oprisan SA, Prinz AA, Canavier CC (2004) Phase resetting and phase locking in hybrid circuits of one model and one biological neuron. Biophys J 87:2283-2298.
31. Panzeri S, Brunel N, Logothetis NK, Kayser C (2010) Sensory neural codes using multiplexed temporal scales. Trends Neurosci 33:111-120.
32. Pinto RD, Elson RC, Szücs A, Rabinovich MI, Selverston AI, Abarbanel HD (2001) Extended dynamic clamp: controlling up to four neurons using a single desktop computer and interface. J Neurosci Methods 108:39-48.
33. Reinagel P, Godwin D, Sherman SM, Koch C (1999) Encoding of visual information by LGN bursts. J Neurophysiol 81:2558-2569.
34. Russell DF, Hartline DK (1984) Synaptic regulation of cellular properties and burst oscillations of neurons in gastric mill system of spiny lobsters, Panulirus interruptus. J Neurophysiol 52:54-73.
35. Sabourin P, Pollack GS (2009) Behaviorally relevant burst coding in primary sensory neurons. J Neurophysiol 102:1086-1091.
36. Schleimer JH, Stemmler M (2009) Coding of information in limit cycle oscillators. Phys Rev Lett 103:248105.
37. Segundo JP, Sugihara G, Dixon P, Stiber M, Bersier LF (1998) The spike trains of inhibited pacemaker neurons seen through the magnifying glass of nonlinear analyses. Neuroscience 87:741-766.
38. Selverston AI (2010) Invertebrate central pattern generator circuits. Philos Trans R Soc Lond B Biol Sci 365:2329-2345.
39. Selverston AI, Russell DF, Miller JP (1976) The stomatogastric nervous system: structure and function of a small neural network. Prog Neurobiol 7:215-290.
40. Selverston AI, Rabinovich MI, Abarbanel HD, Elson R, Szücs A, Pinto RD, Huerta R, Varona P (2000) Reliable circuits form irregular neurons: a dynamical approach to understanding central pattern generators. J Physiol Paris 94:357-374.
41. Shannon CE (1948) A mathematical theory of communication. Bell Systems Tech J 27:379-423.
42. Sherman SM (2001) Tonic and burst firing: dual modes of thalamocortical relay. Trends Neurosci 24:122-126.
43. Steriade M, McCormick DA, Sejnowski TJ (1993) Thalamocortical oscillations in the sleeping and aroused brain. Science 262:679-685.
44. Szücs A, Pinto RD, Rabinovich MI, Abarbanel HD, Selverston AI (2003) Synaptic modulation of the interspike interval signatures of bursting pyloric neurons. J Neurophysiol 89:1363-1377.
45. Szücs A, Abarbanel HD, Rabinovich MI, Selverston AI (2005) Dopamine modulation of spike dynamics in bursting neurons. Eur J Neurosci 21:763-772.
46. Theiler J, Eubank S, Longtin A, Galdrikian B, Farmer JD (1992) Testing for nonlinearity in time series: the method of surrogate data. Physica D 58:77-94.
47. Tiesinga P, Fellous JM, Sejnowski TJ (2008) Regulation of spike timing in visual cortical circuits. Nat Rev Neurosci 9:97-107.
48. de Ruyter van Steveninck RR, Lewen GD, Strong SP, Köberle R, Bialek W (1997) Reproducibility and variability in neural spike trains. Science 275:1805-1808.
49. Zhurov Y, Brezina V (2006) Variability of motor neuron spike timing maintains and shapes contractions of the accessory radula closer muscle of Aplysia. J Neurosci 26:7056-7070.