Closure of ionic channels in turtle cones

Recent observations from turtle cones on the kinetics of the light response and the variance and power spectrum of spontaneous noise are discussed in terms of the behaviour of membrane ionic channels.Presented at the EMBO-Workshop on Transduction Mechanism of Photoreceptors, Jülich, Germany, October 4–8, 1976     

Feedback-induced gain control in stochastic spiking networks

The joint influence of recurrent feedback and noise on gain control in a network of globally coupled spiking leaky integrate-and-fire neurons is studied theoretically and numerically. The context of our work is the origin of divisive versus subtractive gain control, as mixtures of these effects are seen in a variety of experimental systems. We focus on changes in the slope of the mean firing frequency-versus-input bias (f –I) curve when the gain control signal to the cells comes from the cells’ output spikes. Feedback spikes are modeled as alpha functions that produce an additive current in the current balance equation. For generality, they occur after a fixed minimum delay. We show that purely divisive gain control, i.e. changes in the slope of the f –I curve, arises naturally with this additive negative or positive feedback, due to a linearizing actions of feedback. Negative feedback alone lowers the gain, accounting in particular for gain changes in weakly electric fish upon pharmacological opening of the feedback loop as reported by Bastian (J Neurosci 6:553–562, 1986). When negative feedback is sufficiently strong it further causes oscillatory firing patterns which produce irregularities in the f –I curve. Small positive feedback alone increases the gain, but larger amounts cause abrupt jumps to higher firing frequencies. On the other hand, noise alone in open loop linearizes the f –I curve around threshold, and produces mixtures of divisive and subtractive gain control. With both noise and feedback, the combined gain control schemes produce a primarily divisive gain control shift, indicating the robustness of feedback gain control in stochastic networks. Similar results are found when the “input” parameter is the contrast of a time-varying signal rather than the bias current. Theoretical results are derived relating the slope of the f –I curve to feedback gain and noise strength. Good agreement with simulation results are found for inhibitory and excitatory feedback. Finally, divisive feedback is also found for conductance-based feedback (shunting or excitatory) with and without noise. This article is part of a special issue on Neuronal Dynamics of Sensory Coding.     

Lognormal distribution of firing time and rate from a single neuron?

Even a single neuron may be able to produce significant lognormal features in its firing statistics due to noise in the charging ion current. A mathematical scheme introduced in advanced nanotechnology is relevant for the analysis of this mechanism in the simplest case, the integrate-and-fire model with white noise in the charging ion current.     

Noise analysis and relaxation experiments of transport of hydrophobic anions across lipid membranes at equilibrium and nonequilibrium

Under equilibrium and nonequilibnum steady-stale conditions the spectral intensity of current noise S_J(f) generated by the transport of hydrophobic unions across lipid bilayer membranes was investigated. The experimental results were compared with different reaction models S_J(f) showed a characteristic increase proportional to f² between frequency-independent tails at low and high frequencies. This gradient was found to be independent of applied voltage which indicates the contribution of a single voltage-dependent reaction step of ion translocation across the membrane From the shape of S_J(f) at low frequencies the rate constant of ion desorption from the membrane into the aqueous phase could be estimated. Unambiguous evidence for the application of a general model, which includes the coupling of slow ion diffusion in the aqueous phase to ion adsorption/desorption at the membrane interface, could not be obtained from the low-frequency shape of S_J(f). The shot noise of this ion transport determines the amplitude of S_J(f) at high frequencies which decreases with increasing voltage applied. Analysis of voltage-jump current-relaxation experiments and of current noise carried cut on one membrane yielded significant differences of the derived ion partition coefficient. This deviation is qualitatively described on the basis of incomplete reaction steps.     

Improving noise resistance of intrinsic rhythms in a square-wave burster model

The square-wave burster (Wang and Rinzel, 2003) is a class of autonomous bursting cells that share a bifurcation structure. It is known that this class of cells is involved in the generation of various life-supporting rhythms. In our research to realize an electronic circuit that mimics the rhythm generating mechanism in the square-wave burster, our circuit experimentally exhibited severe fluctuations in its rhythmic activity. We have found a noise-sensitive region in the phase portrait of the ideal model and have proposed modifications of the model that can reduce this fluctuation. A possible modification to ionic-conductance neuron models (Kohno and Aihara, 2011) was inspired by them. This modification, however, cannot be applied to a group of square-wave bursters, including the Butera–Rinzel–Smith model (0010 and 0050), which is a model of the pre-Bötzinger complex bursting neuron that plays a crucial role in the generation of respiration rhythms, because this modification premises that the slow dynamics originates from an activation gate variable of a hyperpolarizing ionic current. However, in some square-wave bursters, they are controlled by an inactivation gate variable of a depolarizing ionic current. In this study, we proposed a similar modification with a completely different mechanism that can be applied to this group of square-wave bursters. In the presence of noises, the modified Butera–Rinzel–Smith model can generate rhythmic activity that is more stable and similar to biological observations than the original model. The mechanisms underlying this modification are explained with noisy bifurcation diagrams.     

Noise filtering in the auditory system of Locusta migratoria L

Many acoustically communicating grasshoppers live in crowded populations where sound of many individuals may cause permanent noise. Tympanic receptors and first-order auditory interneurons of Locusta migratoria code such noise tonically, whereas many higher order interneurons react only weakly. In response to simultaneously presented sound they exhibit a better signal-to-noise ratio than their presynaptic elements. Two possible filter mechanisms are suggested for noise reduction in higher-order interneurons: (i) high-pass filtering of receptor spike frequencies and (ii) filtering due to synchronization of receptor spikes. Different receptor spike frequencies were elicited by series of short noise pulses with variable repetition rates. Receptor activities differing in their degree of synchronization were elicited by sound stimuli with variable rising times. In contrast to the first order interneurons some higher order interneurons responded best to receptor spike frequencies above 150–200 Hz, thus showing the postulated filtering. Only one higher order interneuron (AN4) distinguished between synchronous and asynchronous receptor activities. It is suggested that high-pass filtering of receptor spike frequencies is responsible for the noise filtering observed in these interneurons. The synchronization selectivity of AN4 is proposed to be responsible for temporal pattern detection of conspecific sounds.