No Access Submitted: 01 December 2011 Published Online: 29 December 2011
Chaos 21, 047501 (2011); https://doi.org/10.1063/1.3671647
Frank Moss was a leading figure in the study of nonlinear and stochastic processes in biological systems. His work, particularly in the area of stochastic resonance, has been highly influential to the interdisciplinary scientific community. This Focus Issue pays tribute to Moss with articles that describe the most recent advances in the field he helped to create. In this Introduction, we review Moss’s seminal scientific contributions and introduce the articles that make up this Focus Issue.
  1. 1. H. Hoch, L. Busse, and F. Moss, “Noise from vortex-line turbulence in He-II,” Phys. Rev. Lett. 34, 384 (1975). https://doi.org/10.1103/PhysRevLett.34.384 , Google ScholarCrossref
  2. 2. F. Moss and G. V. Welland, “Multiplicative noise in the Vinen equation for turbulent superfluid He-4,” Phys. Rev. A 25, 3389 (1982). https://doi.org/10.1103/PhysRevA.25.3389 , Google ScholarCrossref
  3. 3. J. Smythe, F. Moss, and P. V. E. McClintock, “Observation of a noise-induced phase-transition with an analog simulator,” Phys. Rev. Lett. 51, 1062 (1983). https://doi.org/10.1103/PhysRevLett.51.1062 , Google ScholarCrossref
  4. 4. P. Hänggi, T. J. Mroczkowski, F. Moss and P. V. E. McClintock, “Bistability driven by colored noise—Theory and experiment,” Phys. Rev. A 32, 695 (1985). https://doi.org/10.1103/PhysRevA.32.695 , Google ScholarCrossref
  5. 5. L. Fronzoni, R. Mannella, P. V. E. McClintock, and F. Moss, “Postponement of Hopf bifurcations by multiplicative colored noise,” Phys. Rev. A 36, 834 (1987). https://doi.org/10.1103/PhysRevA.36.834 , Google ScholarCrossref
  6. 6. F. Moss, P. Hänggi, R. Mannella and P. V. E. McClintock, “Stochastic phase portraits of a damped bistable oscillator driven by colored noise,” Phys. Rev. A 33, 4459 (1986). https://doi.org/10.1103/PhysRevA.33.4459 , Google ScholarCrossref
  7. 7. G. Debnath, F. Moss, T. Leiber, H. Risken, and F. Marchesoni, “Holes in the 2-dimensional probability density of bistable systems driven by strongly colored noise,” Phys. Rev. A 42, 703 (1990). https://doi.org/10.1103/PhysRevA.42.703 , Google ScholarCrossref
  8. 8. F. Moss and P. V. E. McClintock, Noise in Nonlinear Dynamical Systems. Theory of Continuous Fokker-Planck Systems (Cambridge University Press, Cambridge, 1989). Google Scholar
  9. 9. F. Moss and P. V. E. McClintock, Noise in Nonlinear Dynamical Systems. Theory of Noise-Induced Processes in Special Applications (Cambridge University Press, Cambridge, 1989). Google Scholar
  10. 10. F. Moss and P. V. E. McClintock, Noise in Nonlinear Dynamical Systems. Experiments and Simulations (Cambridge University Press, Cambridge, 1989). Google Scholar
  11. 11. C. Nicolis, “Stochastic aspects of climatic transitions—response to a periodic forcing,” Tellus 34(1), 1 (1982). https://doi.org/10.1111/j.2153-3490.1982.tb01786.x , Google ScholarCrossref
  12. 12. R. Benzi, G. Parisi, A. Sutera, and A. Vulpiani, “Stochastic resonance in climatic change,” Tellus 34(1), 10 (1982). https://doi.org/10.1111/j.2153-3490.1982.tb01787.x , Google ScholarCrossref
  13. 13. B. McNamara, K. Wiesenfeld, and R. Roy, “Observation of stochastic resonance in a ring laser,” Phys. Rev. Lett. 60, 2626 (1988). https://doi.org/10.1103/PhysRevLett.60.2626 , Google ScholarCrossref
  14. 14. L. Gammaitoni, M. Martinelli, L. Pardi, and S. Santucci, “Observation of stochastic resonance in bistable electron-paramagnetic-resonance systems,” Phys. Rev. Lett. 67, 1799 (1991). https://doi.org/10.1103/PhysRevLett.67.1799 , Google ScholarCrossref
  15. 15. R. N. Mantegna and B. Spagnolo, “Stochastic resonance in a tunnel-diode,” Phys. Rev. E 49, R1792 (1994). https://doi.org/10.1103/PhysRevE.49.R1792 , Google ScholarCrossref
  16. 16. A. Longtin, A. Bulsara, and F. Moss, “Time-interval sequences in bistable systems and the noise-induced transmission of information by sensory neurons,” Phys. Rev. Lett. 67, 656 (1991). https://doi.org/10.1103/PhysRevLett.67.656 , Google ScholarCrossref
  17. 17. A. Bulsara, E. W. Jacobs, T. Zhou, F. Moss, and L. Kiss, “Stochastic resonance in a single neuron model—theory and analog simulation,” J. Theor. Biol. 152, 531 (1991). https://doi.org/10.1016/S0022-5193(05)80396-0 , Google ScholarCrossref
  18. 18. F. Moss, J. K. Douglass, L. Wilkens, D. Pierson, and E. Pantazelou, “Stochastic resonance in an electronic FitzHugh-Nagumo model,” Ann. N.Y. Acad. Sci. 706(1), 26 (1993). Google Scholar
  19. 19. D. Pierson, J. K. Douglass, E. Pantazelou, and F. Moss, “Using an electronic FitzHugh-Nagumo simulator to mimic noisy electrophysiological data from stimulated crayfish mechanoreceptor cells,” AIP Conf. Proc. 285, 731 (1993). Google ScholarScitation
  20. 20. A. Longtin, A. Bulsara, D. Pierson, and F. Moss, “Bistability and the dynamics of periodically forced sensory neurons,” Biol. Cybern. 70, 569 (1994). https://doi.org/10.1007/BF00198810 , Google ScholarCrossref
  21. 21. J. K. Douglass, L. Wilkens, E. Pantazelou, and F. Moss, “Noise enhancement of information-transfer in crayfish mechanoreceptors by stochastic resonance,” Nature 365, 337 (1993). https://doi.org/10.1038/365337a0 , Google ScholarCrossref
  22. 22. X. Pei, L. A. Wilkens, and F. Moss, “Light enhances hydrodynamic signaling in the multimodal caudal photoreceptor interneurons of the crayfish,” J. Neurophysiol. 76, 3002 (1996). Google ScholarCrossref
  23. 23. S. Bahar, A. Neiman, L. A. Wilkens, and F. Moss, “Phase synchronization and stochastic resonance effects in the crayfish caudal photoreceptor,” Phys. Rev. E 65, 050901–R (2002). https://doi.org/10.1103/PhysRevE.65.050901 , Google ScholarCrossref
  24. 24. S. Bahar and F. Moss, “Stochastic phase synchronization in the crayfish mechanoreceptor/photoreceptor system,” Chaos 13, 138 (2003). https://doi.org/10.1063/1.1501899 , Google ScholarScitation
  25. 25. Z. Gingl, L. B. Kiss, and F. Moss, “Non-dynamical stochastic resonance—Theory and experiments with white and arbitrarily colored noise,” Europhys. Lett. 29, 191 (1995). https://doi.org/10.1209/0295-5075/29/3/001 , Google ScholarCrossref
  26. 26. P. Jung, “Threshold devices—Fractal noise and neural talk,” Phys. Rev. E 50, 2513 (1994). https://doi.org/10.1103/PhysRevE.50.2513 , Google ScholarCrossref
  27. 27. P. Jung, “Stochastic resonance and optimal design of threshold detectors,” Phys. Lett. A 207, 93 (1995). https://doi.org/10.1016/0375-9601(95)00636-H , Google ScholarCrossref
  28. 28. D. F. Russell, L. A. Wilkens, and F. Moss, “Use of behavioural stochastic resonance by paddle fish for feeding,” Nature 402, 291 (1999). https://doi.org/10.1038/46279 , Google ScholarCrossref
  29. 29. E. Simonotto, M. Riani, C. Seife, M. Roberts, J. Twitty, and F. Moss, “Visual perception of stochastic resonance,” Phys. Rev. Lett. 78, 1186 (1997). https://doi.org/10.1103/PhysRevLett.78.1186 , Google ScholarCrossref
  30. 30. X. Pei and F. Moss, “Characterization of low-dimensional dynamics in the crayfish caudal photoreceptor,” Nature 379, 618 (1996). https://doi.org/10.1038/379618a0 , Google ScholarCrossref
  31. 31. X. Pei and F. Moss, “Detecting low dimensional dynamics in biological experiments,” Int. J. Neural Syst. 7, 429 (1996). https://doi.org/10.1142/S0129065796000403 , Google ScholarCrossref
  32. 32. H. A. Braun, K. Schafer, K. Voigt, R. Peters, F. Bretschneider, X. Pei, L. Wilkens, and F. Moss, “Low-dimensional dynamics in sensory biology 1: Thermally sensitive electroreceptors of the catfish,” J. Comput. Neurosci. 4, 335 (1997). https://doi.org/10.1023/A:1008852000496 , Google ScholarCrossref
  33. 33. H. A. Braun, M. Dewald, K. Schafer, K. Voigt, X. Pei, K. Dolan, and F. Moss, “Low-dimensional dynamics in sensory biology 2: Facial cold receptors of the rat,” J. Comput. Neurosci. 7, 17 (1999). https://doi.org/10.1023/A:1008911409355 , Google ScholarCrossref
  34. 34. F. Moss, D. Pierson, and D. Ogorman, “Stochastic resonance—Tutorial and update,” Int. J. Bifurcation Chaos 4, 1383 (1994). https://doi.org/10.1142/S0218127494001118 , Google ScholarCrossref
  35. 35. K. Wiesenfeld and F. Moss, “Stochastic resonance and the benefits of noise—From ice ages to crayfish and SQUIDs,” Nature 373, 33 (1995). https://doi.org/10.1038/373033a0 , Google ScholarCrossref
  36. 36. R. D. Astumian and F. Moss, “Overview: the constructive role of noise in fluctuation driven transport and stochastic resonance,” Chaos 8, 533 (1998). https://doi.org/10.1063/1.166334 , Google ScholarScitation
  37. 37. F. Moss, L. M. Ward, and W. G. Sannita, “Stochastic resonance and sensory information processing: A tutorial and review of applications,” Clin. Neurophysiol. 115, 267 (2004). https://doi.org/10.1016/j.clinph.2003.09.014 , Google ScholarCrossref
  38. 38. V. S. Anishchenko, A. B. Neiman, F. Moss, and L. Schimansky-Geier, “Stochastic resonance: noise enhanced order,” Usp. Fiz. Nauk 169, 7 (1999). https://doi.org/10.3367/UFNr.0169.199901c.0007 , Google ScholarCrossref
  39. 39. F. Moss, “Chaos under control,” Nature 370, 596 (1994). https://doi.org/10.1038/370596a0 , Google ScholarCrossref
  40. 40. F. Moss and X. Pei, “Neurons in parallel,” Nature 376, 211 (1995). https://doi.org/10.1038/376211a0 , Google ScholarCrossref
  41. 41. F. Moss and K. Wiesenfeld, “The benefits of background noise,” Sci. Am. 273, 66 (1995). https://doi.org/10.1038/scientificamerican0895-66 , Google ScholarCrossref
  42. 42. F. Moss, F. C. Tan, and R. Klinke, “Will there be noise in their ears?,” Nat. Med. 2, 860 (1996). https://doi.org/10.1038/nm0896-860 , Google ScholarCrossref
  43. 43. F. Moss, “Stochastic resonance at the molecular level,” Biophys. J. 73, 2249 (1997). https://doi.org/10.1016/S0006-3495(97)78256-0 , Google ScholarCrossref
  44. 44. F. Moss, “Noisy waves,” Nature 391, 743 (1998). https://doi.org/10.1038/35745 , Google ScholarCrossref
  45. 45. F. Moss and J. G. Milton, “Balancing the unbalanced,” Nature 425, 911 (2003). https://doi.org/10.1038/425911a , Google ScholarCrossref
  46. 46. W. Garver and F. Moss, “Electronic fireflies,” Sci. Am. 269, 128 (1993). https://doi.org/10.1038/scientificamerican1293-128 , Google ScholarCrossref
  47. 47. W. Garver and F. Moss, “The amateur scientist,” Sci. Am. 273, 100 (1995). https://doi.org/10.1038/scientificamerican0895-100 , Google ScholarCrossref
  48. 48. J. A. Freund, L. Schimansky-Geier, B. Beisner, A. Neiman, D. F. Russell, T. Yakusheva, and F. Moss, “Behavioral stochastic resonance: How the noise from a Daphnia swarm enhances individual prey capture by juvenile paddlefish,” J. Theor. Biol. 214, 71 (2002). https://doi.org/10.1006/jtbi.2001.2445 , Google ScholarCrossref
  49. 49. J. A. Freund, J. Kienert, L. Schimansky-Geier, B. Beisner, A. Neiman, D. F. Russell, T. Yakusheva, and F. Moss, “Behavioral stochastic resonance: How a noisy army betrays its outpost,” Phys. Rev. E 63, 031910 (2001). https://doi.org/10.1103/PhysRevE.63.031910 , Google ScholarCrossref
  50. 50. R. Garcia, F. Moss, A. Nihongi, J. R. Strickler, S. Göller, U. Erdmann, L. Schimansky-Geier, and I. M. Sokolov, “Optimal foraging by zooplankton within patches: The case of Daphnia ,” Math. Biosci. 207, 165 (2007). https://doi.org/10.1016/j.mbs.2006.11.014 , Google ScholarCrossref
  51. 51. N. D. Dees, S. Bahar, R. Garcia, and F. Moss, “Patch exploitation in two dimensions: From Daphnia to simulated foragers,” J. Theor. Biol. 252(1), 69 (2008). https://doi.org/10.1016/j.jtbi.2008.01.026 , Google ScholarCrossref
  52. 52. N. D. Dees, S. Bahar, and F. Moss, “Stochastic resonance and the evolution of Daphnia foraging strategy,” Phys Biol. 5(4), 044001 (2008). https://doi.org/10.1088/1478-3975/5/4/044001 , Google ScholarCrossref
  53. 53. H. Yu, J. Wang, C. Liu, B. Deng, and X. Wei, “Stochastic resonance on a modular neuronal network of small-world subnetworks with a subthreshold pacemaker,” Chaos 21, 047502 (2011). Google ScholarScitation
  54. 54. J. L. Mateos and F. R. Alatriste, “Brownian motors and stochastic resonance,” Chaos 21, 047503 (2011). Google ScholarScitation
  55. 55. M. H. Hofmann and L. A. Wilkens, “Nonlinear dynamics of skin potentials in the electrosensory paddlefish,” Chaos 21, 047504 (2011). Google ScholarScitation
  56. 56. A. B. Neiman and D. F. Russell, “Sensory coding in oscillatory electroreceptors of paddlefish,” Chaos 21, 047505 (2011). Google ScholarScitation
  57. 57. D. Takeshita and S. Bahar, “Synchronization analysis of voltage-sensitive dye imaging during focal seizures in the rat neocortex,” Chaos 21, 047506 (2011). Google ScholarScitation
  58. 58. N. Yu and A. Longtin, “Coherence depression in stochastic excitable systems with two-frequency forcing,” Chaos 21, 047507 (2011). Google ScholarScitation
  59. 59. J. L. van Hemmen, A. Longtin, and A. N. Vollmayr, “Testing resonating vector strength: Auditory system, electric fish, and noise,” Chaos 21, 047508 (2011). Google ScholarScitation
  60. 60. H. A. Braun, J. Schwabedal, M. Dewald, C. Finke, S. Postnova, M. T. Huber, B. Wollweber, H. Schneider, M. C. Hirsch, K. Voight, U. Feudel, and F. Moss, “Noise induced precursors of tonic-to-bursting transitions in hypothalamic neurons and in a conductance-based model,” Chaos 21, 047509 (2011). Google ScholarScitation
  61. 61. C. Finke, J. A. Freund, E. Rosa, Jr., P. H. Bryant, H. A. Braun, and U. Feudel, “Temperature-dependent stochastic dynamics of the Huber-Braun neuron model,” Chaos 21, 047510 (2011). Google ScholarScitation
  62. 62. S. Yanchuk, P. Perlikowski, O. V. Popovych, and P. A. Tass, “Variability of spatio-temporal patterns in non-homogeneous rings of spiking neurons,” Chaos 21, 047511 (2011). Google ScholarScitation
  63. 63. A. Quan, I. Osorio, T. Ohira, and J. Milton, “Vulnerability to paroxysmal oscillations in delayed neural networks: A basis for nocturnal frontal lobe epilepsy?,” Chaos 21, 047512 (2011). Google ScholarScitation
  64. 64. S. Astakhov, A. Feoktistov, V. S. Anishchenko, and J. Kurths, “Synchronization of multi-frequency noise-induced oscillations,” Chaos 21, 047513 (2011). Google ScholarScitation
  65. 65. I. Bashkirtseva and L. Ryashko, “Sensitivity analysis of stochastic attractors and noise-induced transitions for population model with Allee effect,” Chaos 21, 047514 (2011). Google ScholarScitation
  66. 66. K. Wiesenfeld and D. Borrero-Echeverry, “Huygens (and others) revisited,” Chaos 21, 047515 (2011). Google ScholarScitation
  67. 67. P. Jung and F. Marchesoni, “Energetics of stochastic resonance,” Chaos 21, 047516 (2011). Google ScholarScitation
  68. 68. P. Romanczuk, W. Ebeling, U. Erdmann, and L. Schimansky-Geier, “Active particles with broken symmetry,” Chaos 21, 047517 (2011). Google ScholarScitation
  69. 69. S. Martens, G. Schmid, L. Schimansky-Geier, and P. Hänggi, “Biased Brownian motion in extreme corrugated tubes,” Chaos 21, 047518 (2011). Google ScholarScitation
  70. 70. A. M. Berezhkovskii and S. M. Bezrukov, “Surface area of the domain visited by a spherical Brownian particle,” Chaos 21, 047519 (2011). Google ScholarScitation
  71. 71. B. Kia, A. Dari, W. L. Ditto, and M. L. Spano, “Unstable periodic orbits and noise in chaos computing,” Chaos 21, 047520 (2011). Google ScholarScitation
  72. 72. A. Dari, B. Kia, A. R. Bulsara, and W. L. Ditto, “Logical stochastic resonance with correlated internal and external noises in a synthetic biological logic block,” Chaos 21, 047521 (2011). Google ScholarScitation
  73. 73. X. L. Yang, D. V. Senthilkumar, Z. K. Sun, and J. Kurths, “Key role of time-delay and connection topology in shaping the dynamics of noisy genetic regulatory networks,” Chaos 21, 047522 (2011). Google ScholarScitation
  74. 74. M. Stamatakis, R. M. Adams, and G. Balázsi, “A common repressor pool results in indeterminacy of extrinsic noise,” Chaos 21, 047523 (2011). Google ScholarScitation
  1. © 2011 American Institute of Physics.
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