Synchronization of the Noisy Electrosensitive Cells in the Paddlefish

Abstract

Synchronization of electrosensitive cells of the paddlefish is studied by means of electrophysiological experiments. Different types of noisy phase locked regimes are observed. The experimental data are compared with computer simulations of a noise-mediated modified Hodgkin-Huxley neuron model and of a stochastic circle map. [S0031-9007(98) Since the historical work of Huygens [1], synchronization has attracted much attention. It occurs when a nonlinear oscillator, showing a stable limit cycle [2], is subjected to an external time-dependent force or is coupled with another oscillator. Synchronization has been observed in a wide variety of natural and man-made systems [3]. It is also important in various biological systems, including, most recently, the human heart-respiratory system, as well as certain brain functions revealed by magnetoencephalography [4].In this Letter we study experimentally the synchronization of electroreceptors of the paddlefish, Polydon spathula, which feeds on zooplankton, e.g., the water flea, Daphnia [5]. While adult fishes filter feed almost entirely on clouds of zooplankton, small paddlefish are particulate feeders, selecting and capturing zooplankton individually [6,7]. The paddlefish is named for its large rostrum, or "paddle," which is covered with an array of thousands of electrosensory organs (see Fig. 1). Recently it has been demonstrated that paddlefish are sensitive to weak electric fields, which they use for sensing prey electrically in the dark [8]. Both natural zooplankton and artificial electric dipoles were used to stimulate feeding [8].Each of the electrosensory organs on the rostrum ( Fig. 1) consists of a patch of ampullary-type cells, which synapse onto primary afferent (sensory) neurons sending long axons to the brain. The latter will be referred to as "electroreceptor cells" because their spike trains can be recorded, and are modulated by weak electric fields near the rostrum. We present here the first direct evidence that each cell contains a noise-mediated oscillator by showing that it can be synchronized with an external signal. In the absence of external stimuli, the cells generate noisy nearly periodic spike sequences. Noise mediated oscillators were previously studied in the electroreceptive cells of the dogfish (a kind of shark) and catfish [9] only indirectly by means of spike interval histograms. They have never been shown to exist in the primitive species of the order acipenseriformes (sturgeons and paddlefish).Extracellular recordings were obtained in vivo from single cells. In our experiments (for details see [8]) a cell was stimulated by a weak electric and/or magnetic field generated by a dipole or a small coil located near the rostrum. The electric field strengths (a few tens of mV ͞cm) were comparable in magnitude to those generated by the zooplankton. Recordings of the spike train from the cell and periodic signal from the dipole were digitized and analyzed by computer. An example recording is shown in Fig. 1. The synchronized 1:5 mode locking (5 s...

Anticipated synchronization in a biologically plausible model of neuronal motifs

“…Including effects from microcircuit dynamics (such as the ones we have presented here) in models of synaptic plasticity is a natural next step, one which we are currently pursuing. Once we have verified AS in a biologically plausible model, one could consider using simplified models [35,36] (e.g., by replacing the HH equations and/or the synaptic kinetics) and the influence of noise [10,20]. We are also investigating whether the structure of the phase diagram can be qualitatively reproduced via a phase-response-curve analysis [37,38] of the neuronal motifs studied here.…”

Complex networks: Structure and dynamics

“…The natural continuation of these pioneering works was to investigate synchronization phenomena in spatially extended or infinite-dimensional systems [404][405][406][407][408][409], to test synchronization in experiments or natural systems [410][411][412][413][414][415][416][417][418][419][420][421], to study the mechanisms leading to de-synchronization [422,423], and to define unifying formal approaches that could encompass within the same framework the different synchronization phenomena [424]. A full account of the different synchronization states studied so far for chaotic systems and space-extended fields can be found in Ref.…”

Real-time interaction between a neuromorphic electronic circuit and the spinal cord

“…Thus, we denoted the moments of time at which the moving averaged ventral root activity increased above a fixed threshold as t k , k = 0, 1, 2, …, N and, similarly, we denoted the times at which a neuron of the aVLSI circuit crosses a preset threshold to be τ i , i = 0, 1, 2, …, M. Then, in the unidirectional open-loop mode with the circuit neuron (E neuron) driving the spinal activity (or in the closed-loop mode), the phase of the kth cycle of the ventral root activity was calculated as [34] Defined in this way, the phase varied between 0 and 1 and was defined at discrete moments of time.…”