Statistics of neuronal identification with open- and closed-loop measures of intrinsic excitability

Frontiers in Neural Circuits

Volumn , Issue APRIL2012, 2012, Pages 1-17

  Brookings, Ted ^a   Grashow, Rachel ^b   Marder, Eve ^a  

^a BRANDEIS UNIVERSITY   (United States)

^b HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Clustering algorithms; Dynamic clamp; Feature selection; Half center oscillator; Identified neurons; Morris Lecar model; Multiple correlations; Stomatogastric ganglion

Indexed keywords

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; BOOTSTRAPPING; BRAIN ELECTROPHYSIOLOGY; CANCER BOREALIS; CELL ACTIVITY; CELL ASSAY; CELL SELECTION; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; CRAB; DATA MINING; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; NERVE CELL EXCITABILITY; NERVE CELL MEMBRANE POTENTIAL; NERVE CELL NETWORK; NEUROPHYSIOLOGY; NONHUMAN; STATISTICAL ANALYSIS; SYNAPTIC INHIBITION;

EID: 84863618294     PISSN: 16625110     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncir.2012.00019     Document Type: Article

References (63)

1. Aickin, M., and Gensler, H. (1996). Adjusting for multiple testing when reporting research results: the Bonferroni vs Holm methods. Am. J. Public Health 86, 726-728.
2. Andreopoulos, B., An, A., Wang, X., and Schroeder, M. (2009). A roadmap of clustering algorithms: finding a match for a biomedical application. Brief. Bioinformatics 10, 297-314.
3. Arthur, D., and Vassilvitskii, S. (2007). "k-Means++: the advantages of careful seeding, " in Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms. (New Orleans, LA: Society for Industrial and Applied Mathematics), 1027-1035.
4. Beyer, K., Goldstein, J., Ramakrishnan, R., and Shaft, U. (1999). When is "nearest neighbor" meaningful?" in Database Theory-ICDT'99, eds C. Beeri and P. Buneman (Berlin: Springer), 217-235.
5. Bishop, C. M. (1996). Neural Networks for Pattern Recognition. Oxford: Oxford University Press.
6. Bohm, C., Railing, K., Kriegel, H. P., and Kroger, P. (2004). "Density connected clustering with local sub-space preferences, " in ICDM '04. Fourth IEEE International Conference on Data Mining, 2004, Piscat-away, 27-34.
7. Borodinsky, L. N., Root, C. M., Cronin, J. A., Sann, S. B., Gu, X., and Spitzer, N. C. (2004). Activity-dependent homeostatic specification of transmitter expression in embryonic neurons. Nature 429, 523-530.
8. Buchholtz, F., Golowasch, J., Epstein, I. R., and Marder, E. (1992). Mathematical model of an identified stomatogastric ganglion neuron. J. Neurophysiol. 67, 332-340.
9. Calabrese, R. L., Norris, B. J., Wenning, A., and Wright, T. M. (2011). Coping with variability in small neuronal networks. Integr. Comp. Biol. 51,845-855.
10. Dickinson, P. S., Mecsas, C., and Marder, E. (1990). Neuropeptide fusion of two motor pattern generator circuits. Nature 344, 155-158.
11. Dorval, A. D., Christini, D. J., and White, J. A. (2001). Real-time linux dynamic clamp: a fast and flexible way to construct virtual ion channels in living cells. Ann. Biomed. Eng. 29, 897-907.
12. Ertoz, L., Steinbach, M., and Kumar, V. (2003). "Finding clusters of different sizes, shapes, and densities in noisy, high dimensional data, " in Proceedings of the Third SIAM International Conference on Data Mining, eds D. Barbara and C. Kamath (San Francisco: Society for Industrial and Applied Mathematics), 12.
13. Getting, P. A. (1981). Mechanisms of pattern generation underlying swimming in Tritonia. I. Neuronal network formed by monosynaptic connections. J. Neurophysiol. 46, 65-79.
14. Getting, P. A. (1989). Emerging principles governing the operation of neural networks. Annu. Rev. Neurosci. 12, 185-204.
15. Getting, P. A., and Dekin, M. S. (1985). Mechanisms of pattern generation underlying swimming in TRITONIA. IV. Gating of central pattern generator. J. Neurophysiol. 53, 466-480.
16. Getting, P. A., Lennard, P. R., and Hume, R. I. (1980). Central pattern generator mediating swimming in tritonia. I. Identification and synaptic interactions. J. Neurophysiol. 44, 151-164.
17. Goaillard, J. M., Taylor, A. L., Schulz, D.J., and Marder, E. (2009). Functional consequences of animal-to-animal variation in circuit parameters. Nat. Neurosci. 12, 1424-1430.
18. Grashow, R., Brookings, T., and Marder, E. (2010). Compensation for variable intrinsic neuronal excitability by circuit-synaptic interactions. J. Neurosci. 30, 9145-9156.
19. Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Learning: Data Mining Inference, and Prediction. New York: Springer Verlag, 515-520.
20. Hinneburg, A., Aggarwal, C. C., and Keim, D. A. (2000). "What is the nearest neighbor in high dimensional spaces?" in Proceedings of the 26th International Conference on Very Large Data Bases (San Francisco: Morgan Kaufmann Publishers Inc.) 671675, 506-515.
21. Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6, 65-70.
22. Houle, M., Kriegel, H.-P., Kroger, P., Schubert, E., and Zimek, A. (2010). "Can shared-neighbor distances defeat the curse of dimensionality?" in ScientificandStatistical Database Management, eds M. Gertz and B. Ludascher (Berlin: Springer), 482-500.
23. Hume, R. I., and Getting, P. A. (1982). Motor organization of tritonia swimming. II. Synaptic drive to flexion neurons from premotor interneurons. J. Neurophysiol. 47, 75-90.
24. Hume, R. I., Getting, P. A., and Del Beccaro, M. A. (1982). Motor organization of tritonia swimming. I. Quantitative analysis of swim behavior and flexion neuron firing patterns. J. Neurophysiol. 47, 60-74.
25. Jonas, P., Bischofberger, J., Fricker, D., and Miles, R. (2004). Interneuron diversity series: fast in, fast out-temporal and spatial signal processing in hippocampal interneurons. Trends Neurosci. 27, 30-40.
26. Katz, P. S. (1996). Neurons, networks, and motor behavior. Neuron 16, 245-253.
27. Kriegel, H.-P., Kroger, P., Sander, J., and Zimek, A. (2011). Density-based clustering. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 1, 231-240.
28. Kriegel, H.-P., Kroger, P., Schubert, E., and Zimek, A. (2008). "A general framework for increasing the robustness of PCA-based correlation clustering algorithms, " in Scientific and Statistical Database Management, eds B. Ludascher and N. Mamoulis (Berlin: Springer), 418-435.
29. Kristan, W. B. Jr., Calabrese, R. L., and Friesen, W. O. (2005). Neuronal control of leech behavior. Prog. Neurobiol. 76, 279-327.
30. Marder, E., and Bucher, D. (2001). Central pattern generators and the control of rhythmic movements. Curr. Biol. 11, R986-R996.
31. Marder, E., and Bucher, D. (2007). Understanding circuit dynamics using the stomatogastric nervous system of lobsters and crabs. Annu. Rev. Physiol. 69, 291-316.
32. Marder, E., and Calabrese, R. L. (1996). Principles of rhythmic motor pattern generation. Physiol. Rev. 76, 687-717.
33. Meyrand, P., Simmers, J., and Moulins, M. (1991). Construction of a pattern-generating circuit with neurons of different networks. Nature 351, 60-63.
34. Miller, J. P., and Selverston, A. I. (1982a). Mechanisms underlying pattern generation in lobster stom-atogastric ganglion as determined by selective inactivation ofidentified neurons. II. Oscillatoryproperties of pyloric neurons. J. Neurophysiol. 48, 1378-1391.
35. Miller, J. P., and Selverston, A. I. (1982b). Mechanisms underlying pattern generation in lobster stom-atogastric ganglion as determined by selective inactivation ofidentified neurons. IV. Network properties of pyloric system. J. Neurophysiol. 48, 1416-1432.
36. Miller, M. N., Okaty, B. W., and Nelson, S. B. (2008). Region-specific spike-frequency acceleration in layer 5 pyramidal neurons mediated by Kv1 subunits. J. Neurosci. 28, 13716-13726.
37. Morris, C., and Lecar, H. (1981). Voltage oscillations in the barnacle giant muscle fiber. Biophys. J. 35, 193-213.
38. Mulloney, B., and Selverston, A. I. (1974a). Organization of the stom-atogastric ganglion in the spiny lobster. I. Neurons driving the lateral teeth. J. Comp. Physiol. 91, 1-32.
39. Mulloney, B., and Selverston, A. I. (1974b). Organization of the stom-atogastric ganglion in the spiny lobster. III. Coordination of the two subsets of the gastric system. J. Comp. Physiol. 91, 53-78.
40. Okaty, B. W., Sugino, K., and Nelson, S.A. (2011a). Cell type-specific transcriptomics in the brain. J. Neurosci. 31, 6939-6943.
41. Okaty, B. W., Sugino, K., and Nelson, S. B. (2011b). A quantitative comparison of cell-type-specific microarray gene expression profiling methods in the mouse brain. PLoS ONE 6, e16493. doi:10.1371/journal.pone.0016493
42. Pearson, K. G., Reye, D. N., Parsons, D.W., and Bicker, G. (1985). Flight-initiating interneurons in the locust. J. Neurophysiol. 53, 910-925.
43. Pei, T., Zhu, A. X., Zhou, C., Li, B., and Qin, C. (2009). Detecting feature from spatial point processes using collective nearest neighbor. Comput. Environ. Urban Syst. 33, 435-447.
44. Perrins, R., and Weiss, K. R. (1996). A cerebral central pattern generator in Aplysia and its connections with buccal feeding circuitry. J. Neurosci. 16, 7030-7045.
45. Sander, J., Ester, M., Kriegel, H.-P., and Xu, X. (1998). Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications. Data Min. Knowl. Discov. 2, 169-194.
46. Sasaki, K., Due, M. R., Jing, J., and Weiss, K. R. (2007). Feeding CPG in Aplysia directly controls two distinct outputs of a compartmentalized interneuron that functions as a CPG element. J. Neurophysiol. 98, 3796-3801.
47. Schmidt, J., Fischer, H., and Buschges, A. (2001). Pattern generation for walking and searching movements of a stick insect leg. II. Control of motoneuronal activity. J. Neurophysiol. 85, 354-361.
48. Schulz, D. J., Goaillard, J. M., and Marder, E. (2006). Variable channel expression in identified single and electrically coupled neurons in different animals. Nat. Neurosci. 9, 356-362.
49. Schulz, D. J., Goaillard, J. M., and Marder, E. E. (2007). Quantitative expression profiling of identified neurons reveals cell-specific constraints on highly variable levels of gene expression. Proc. Natl. Acad. Sci. U.S.A. 104, 13187-13191.
50. Selverston, A. I., and Miller, J. P. (1980). Mechanisms underlying pattern generation in the lobster stomatogastric ganglion as determined by selective inactivation of identified neurons. I. Pyloric neurons. J. Neurophysiol. 44, 1102-1121.
51. Selverston, A. I., Russell, D. F., Miller, J. P., and King, D. G. (1976). The stomatogastric nervous system: structure and function of a small neural network. Prog. Neurobiol. 7, 215-290.
52. Sharp, A. A., Skinner, F. K., and Marder, E. (1996). Mechanisms of oscillation in dynamic clamp constructed two-cell half-center circuits. J. Neurophysiol. 76, 867-883.
53. Sugino, K., Hempel, C. M., Miller, M. N., Hattox, A. M., Shapiro, P., Wu, C., Huang, Z. J., and Nelson, S. B. (2006). Molecular taxonomy of major neuronal classes in the adult mouse forebrain. Nat. Neurosci. 9, 99-107.
54. Swensen, A. M., and Bean, B. P. (2005). Robustness of burst firing in dissociated Purkinje neurons with acute or long-term reductions in sodium conductance. J. Neurosci. 25, 3509-3520.
55. Taylor, A. L., Hickey, T. J., Prinz, A. A., and Marder, E. (2006). Structure and visualization of high-dimensional conductance spaces. J. Neurophysiol. 96, 891-905.
56. Tobin, A. E., Cruz-Bermudez, N. D., Marder, E., and Schulz, D. J. (2009). Correlations in ion channel mRNA in rhythmically active neurons. PLoS ONE 4, e6742. doi:10.1371/journal.pone.0006742
57. Toledo-Rodriguez, M., and Markram, H. (2007). Single-cell RT-PCR, a technique to decipher the electrical, anatomical, and genetic determinants of neuronal diversity. Methods Mol. Biol. 403, 123-139.
58. Vinh, N. X., Epps, J., and Bailey, J. (2009). "Information theoretic measures for clusterings comparison: is a correction for chance necessary?" in Proceedings of the 26th Annual International Conference on Machine Learning (Montreal, QC: ACM), 1073-1080.
59. Weimann, J. M., and Marder, E. (1994). Switching neurons are integral members of multiple oscillatory networks. Curr. Biol. 4, 896-902.
60. Weimann, J. M., Meyrand, P., and Marder, E. (1991). Neurons that form multiple pattern generators: identification and multiple activity patterns of gastric/pyloric neurons in the crab stomatogastric system. J. Neurophysiol. 65, 111-122.
61. Wienecke, J., Westerdahl, A. C., Hultborn, H., Kiehn, O., and Ryge, J. (2010). Global gene expression analysis of rodent motor neurons following spinal cord injury associates molecular mechanisms with development of postinjury spasticity. J. Neurophysiol. 103, 761-778.
62. William, C. M., Tanabe, Y., and Jessell, T. M. (2003). Regulation of motor neuron subtype identity by repressor activity of Mnx class homeodomain proteins. Development 130, 1523-1536.
63. Zagoraiou, L., Akay, T., Martin, J. F., Brownstone, R. M., Jessell, T. M., and Miles, G. B. (2009). A cluster of cholinergic premotor interneurons modulates mouse locomotor activity. Neuron 64, 645-662.