Low-Dimensional Dynamics in Sensory Biology 1: Thermally Sensitive Electroreceptors of the Catfish

We report the results of a search for evidence of periodic unstableorbits in the electroreceptors of the catfish. The function of thesereceptor organs is to sense weak external electric fields. Inaddition, they respond to the ambient temperature and to the ioniccomposition of the water. These quantities are encoded by receptorsthat make use of an internal oscillator operating at the level of themembrane potential. If such oscillators have three or more degreesof freedom, and at least one of which also exhibits a nonlinearity,they are potentially capable of chaotic dynamics. By detecting theexistence of stable and unstable periodic orbits, we demonstratebifurcations between noisy stable and chaotic behavior using theambient temperature as a parameter. We suggest that the techniquedeveloped herein be regarded as an additional tool for the analysisof data in sensory biology and thus can be potentially useful instudies of functional responses to external stimuli. We speculatethat the appearance of unstable orbits may be indicative of a stateof heightened sensory awareness by the animal.

[1]  E. Hunt Stabilizing high-period orbits in a chaotic system: The diode resonator. , 1991 .

[2]  P. Cvitanović,et al.  Periodic orbits as the skeleton classical and quantum chaos , 1991 .

[3]  Frank Moss,et al.  Characterization of low-dimensional dynamics in the crayfish caudal photoreceptor , 1996, Nature.

[4]  Grebogi,et al.  Detecting unstable periodic orbits in chaotic experimental data. , 1996, Physical review letters.

[5]  A Garfinkel,et al.  Controlling cardiac chaos. , 1992, Science.

[6]  Erik Aurell,et al.  Recycling of strange sets: II. Applications , 1990 .

[7]  F Moss,et al.  Light enhances hydrodynamic signaling in the multimodal caudal photoreceptor interneurons of the crayfish. , 1996, Journal of neurophysiology.

[8]  P. Grassberger,et al.  Characterization of Strange Attractors , 1983 .

[9]  S J Schiff,et al.  Stochastic versus deterministic variability in simple neuronal circuits: II. Hippocampal slice. , 1994, Biophysical journal.

[10]  Hunt Stabilizing high-period orbits in a chaotic system: The diode resonator. , 1991, Physical review letters.

[11]  Steven H. Strogatz,et al.  Nonlinear Dynamics and Chaos , 2024 .

[12]  S J Schiff,et al.  Stochastic versus deterministic variability in simple neuronal circuits: I. Monosynaptic spinal cord reflexes. , 1994, Biophysical journal.

[13]  K. Schäfer,et al.  Periodic firing pattern in afferent discharges from electroreceptor organs of catfish , 2004, Pflügers Archiv.

[14]  Adi R. Bulsara,et al.  Bistability and the dynamics of periodically forced sensory neurons , 1994, Biological Cybernetics.

[15]  Celso Grebogi,et al.  Using small perturbations to control chaos , 1993, Nature.

[16]  Bruce J. West,et al.  Chaos and fractals in human physiology. , 1990, Scientific American.

[17]  A Garfinkel,et al.  Chaos and chaos control in biology. , 1994, The Journal of clinical investigation.

[18]  D. T. Kaplan,et al.  Exceptional events as evidence for determinism , 1994 .

[19]  Edward Ott,et al.  Controlling chaos , 2006, Scholarpedia.

[20]  Rollins,et al.  Controlling chaos in highly dissipative systems: A simple recursive algorithm. , 1993, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[21]  K. Schäfer,et al.  Oscillation and noise determine signal transduction in shark multimodal sensory cells , 1994, Nature.

[22]  Moss,et al.  Detecting periodic unstable points in noisy chaotic and limit cycle attractors with applications to biology. , 1995, Physical review letters.

[23]  P. F. M. Teunis,et al.  Ampullary electroreceptors in catfish (Teleostei): temperature dependence of stimulus transduction , 1990, Pflügers Archiv.

[24]  Ying-Cheng Lai,et al.  Controlling chaos , 1994 .

[25]  Valery Petrov,et al.  Controlling chaos in the Belousov—Zhabotinsky reaction , 1993, Nature.

[26]  Ditto,et al.  Experimental control of chaos. , 1990, Physical review letters.

[27]  Roy,et al.  Dynamical control of a chaotic laser: Experimental stabilization of a globally coupled system. , 1992, Physical review letters.

[28]  George Sugihara,et al.  Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series , 1990, Nature.

[29]  Collins,et al.  Controlling nonchaotic neuronal noise using chaos control techniques. , 1995, Physical review letters.

[30]  Los AlamOs Nallon Testing for nonlinearity in time series: the method of surrogate data — Source link , 2005 .

[31]  B Grier Experimental control. , 1979, Research in nursing & health.

[32]  W. Ditto,et al.  Controlling chaos in the brain , 1994, Nature.

[33]  Cvitanovic,et al.  Invariant measurement of strange sets in terms of cycles. , 1988, Physical review letters.

[34]  A. Wolf,et al.  Determining Lyapunov exponents from a time series , 1985 .

[35]  Bulsara,et al.  Time-interval sequences in bistable systems and the noise-induced transmission of information by sensory neurons. , 1991, Physical review letters.

[36]  Erik Aurell,et al.  Recycling of strange sets: I. Cycle expansions , 1990 .

[37]  James Theiler,et al.  Testing for nonlinearity in time series: the method of surrogate data , 1992 .

[38]  Karin Hinzer,et al.  Encoding with Bursting, Subthreshold Oscillations, and Noise in Mammalian Cold Receptors , 1996, Neural Computation.

[39]  Ditto,et al.  Evidence for determinism in ventricular fibrillation. , 1995, Physical review letters.

[40]  S J Schiff,et al.  Predictability of EEG interictal spikes. , 1995, Biophysical journal.

[41]  L. Olsen,et al.  Chaos versus noisy periodicity: alternative hypotheses for childhood epidemics. , 1990, Science.