Suprathreshold Stochastic Resonance in Mechanoelectrical Transduction of Hair Cells

Hair cell, the sound signal sensor in the auditory system, works in an environment full of noise. This noise has been demonstrated before to be a factor beneficial to the transfer of subthreshold weak signal. We further theoretically demonstrate that in suprathreshold signal situation, noise can still be a beneficial factor and enhance the haircell nonlinear transfer of suprathreshoM signal. This reveals an additional constructive function of noise in hearing and provides theoretic foundation for relevant applications.     

Stochastic resonance of a periodically driven neuron under non-Gaussian noise

We investigate the first-passage-time statistics of the integrate-fire neuron model driven by a sub-threshold harmonic signal superposed with a non-Gaussian noise. Here, we considered the noise as the result of a random multiplicative process displaced from the origin by an additive term. Such a mechanism generates a power-law distributed noise whose characteristic decay exponent can be finely tuned. We performed numerical simulations to analyze the influence of the noise non-Gaussian character on the stochastic resonance condition. We found that when the noise deviates from Gaussian statistics, the resonance condition occurs at weaker noise intensities, achieving a minimum at a finite value of the distribution function decay exponent. We discuss the possible relevance of this feature to the efficiency of the firing dynamics of biological neurons, as the present result indicates that neurons would require a lower noise level to detect a sub-threshold signal when its statistics departs from Gaussian.     

Entropic Stochastic Resonance Driven by Colored Noise

The phenomenon of entropic stochastic resonance （ESR） in a two-dimensional confined system driven by a transverse periodic force is investigated when the colored fluctuation is included in the system. Applying the method of unified colored noise approximation, the approximate Fokker-Planck equation can be derived in the absence of the periodic force. Through the escaping rate of the Brownian particle from one well to the other, the power spectral amplification can be obtained. It is found that increasing the values of the noise correlation time and the signal frequency can suppress the ESR of the system.     

From Autonomous Coherence Resonance to Periodically Driven Stochastic Resonance

In periodically driven nonlinear stochastic systems, noise may play a role of enhancing the output periodic signal （termed as stochastic resonance or SR）. While in autonomous excitable systems, noise may play a role of increasing coherent motion （termed as coherence resonance or CR）. So far the topics of SR and CR have been investigated separately as two major fields of studying the active roles of noise in nonlinear systems. We find that these two topics are closely related to each other. Specifically, SR occurs in such periodically driven systems that the corresponding autonomous systems show CR. The SR with sensitive frequency dependence can be observed when the corresponding autonomous system shows CR with finite characteristic frequency. Moreover, ‘resonant noise＇ and ‘resonant frequency＇ of SR coincide with those of CR.     

New Evidence of Active Tuning in Cochlea

The wonderful performance of hearing systems is mainly attributed to the tuning tiltering of basilar membrane （BM）. Although theory of the cochlear mechanism has been greatly developed since the 1970s and the amplification or sensitivity of the cochlea has been concluded due to the out hair cells, the mechanics underlying the sharp-tuning or frequency selectivity of cochlea remains a puzzle. We use the cochlear translation function derived from the data of an experiment of the BM in vivo to calculate basilar responses to tone bursts, and find that there are resonant peaks with the characteristic frequency at the corresponding place in the initial and terminal part of the responses. However, when the translation function is shallower, there will be no resonant peaks in the responses. The result indicates that the sharp tuning is due to existence of the active resonant tuning mechanism.     

Stochastic Resonance in Neural Systems with Small-World Connections

We study the stochastic resonance （SR） in Hodgkin-Huxley （HH） neural systems with small-world （SW） connections under the noise synaptic current and periodic stimulus, focusing on the dependence of properties of SR on coupling strength c. It is found that there exists a critical coupling strength c^＊ such that if c 〈 c^＊, then the SR can appear on the SW neural network. Especially, dependence of the critical coupling strength c^＊ on the number of neurons N shows the monotonic even almost linear increase of c^＊ as N increases and c^＊ on the SW network is smaller than that on the random network. For the effect of the SW network on the phenomenon of SR, we show that decreasing the connection-rewiring probability p of the network topology leads to an enhancement of SR. This indicates that the SR on the SW network is more prominent than that on the random network （p = 1.0）. In addition, it is noted that the effect becomes remarkable as coupling strength increases. Moreover, it is found that the SR weakens but resonance range becomes wider with the increase of c on the SW neural network.     

Frequency Selectivity Behaviour in the Auditory Midbrain： Implications of Model Study

By numerical simulations on frequency dependence of the spiking threshold, i.e. on the critical amplitude of periodic stimulus, for a neuron to fire, we find that bushy cells in the cochlear nuclear exhibit frequency selec- tivity behaviour. However, the selective frequency band of a bushy cell is far away from that of the preferred spectral range in human and mammal auditory perception. The mechanism underlying this neural activity is also discussed. Further studies show that the ion channel densities have little impact on the selective frequency band of bushy cells. These findings suggest that the neuronal behaviour of frequency selectivity in bushy cells at both the single cell and population levels may be not functionally relevant to frequency discrimination. Our results may reveal a neural hint to the reconsideration on the busily cell functional role in auditory information processing of sound frequency.     

Stochastic resonance and heat fluctuations in a driven double-well system

We study a periodically driven (symmetric as well as asymmetric) double-well potential system at finite temperature. We show that mean heat loss by the system to the environment (bath) per period of the applied field is a good quantifier of stochastic resonance. It is found that the heat fluctuations over a single period are always larger than the work fluctuations. The observed distributions of work and heat exhibit pronounced asymmetry near resonance. The heat loss over a large number of periods satisfies the conventional steady-state fluctuation theorem.     

Phononic band structure in a two-dimensional hybrid triangular graphite lattice

The propagation of acoustic wave in a two-dimensional phononic crystal of a hybrid triangular graphite array is investigated by the plane wave expansion (PWE) method. Our numerical results show that the location and width of the band gaps can be tuned by altering the radii of scatters at different positions.     

Long-Time Dynamic Response and Stochastic Resonance of Subdiffusive Overdamped Bistable Fractional Fokker--Planck Systems

To explore the influence of anomalous diffusion on stochastic resonance （SR） more deeply and effectively, the method of moments is extended to subdiffusive overdamped bistable fractional Fokker-Planck systems for calculating the long-time linear dynamic response. It is found that the method of moments attains high accuracy with the truncation order N = 10, and in normal diffusion such obtained spectral amplification factor （SAF） of the first-order harmonic is also confirmed by stochastic simulation. Observing the SAF of the odd-order harmonics we find some interesting results, i.e. for smaller driving frequency the decrease of subdiffusion exponent inhibits the stochastic resonance （S.R）, while for larger driving frequency＂ the decrease of subdiffusion exponent enhances the second SR peak, but the first one vanishes and a double SR is induced in the third-order harmonic at the same time. These observations suggest that the anomalous diffusion has important influence on the bistable dynamics.     

Measurement of noise associated with model transformer cores

The performance of a transformer core may be considered in terms of power loss and by the noise generated by the core, both of which should be minimised. This paper discusses the setting up of a suitable system for evaluation of noise in a large model transformer core (500 kV A) and issues associated with noise measurement. The equivalent continuous sound pressure level (LAeq) was used as a measure of the A-weighted sound level and measurements were made in the range 16 Hz–25 kHz for various step lap core configurations. The selection of optimum sound insulation materials between core and ground support and for enclosing the transformer is essential for minimisation of background noise. Core clamping pressure must be optimised in order to minimise noise. The use of two laminations per layer instead of one leads to an increase in noise arising from the core. Provided care is taken in building the core, good reproducibility of results can be obtained for analysis.     

Effect of atomic environment on the Fe hyperfine structure and the thermal stability of magnetic order in L10 ordered Fe-Pt alloys

The ⁵⁷Fe Mössbauer effect measurements were made for the L1₀ ordered Fe-Pt alloys with 39-62 at% Pt and the effect of local atomic environment on the hyperfine structure was investigated. Furthermore, the thermal stability of magnetic order was investigated for the alloys with high Pt concentration. From the analyses of the observed Mössbauer spectra, we found that dipole-field-like anisotropic transferred hyperfine fields are mainly responsible for the large difference in hyperfine field between Fe-site and Pt-site in the Fe-rich alloys. In the Pt-rich region far from stoichiometry, the existence of many Fe-sites occupied by excess Pt atoms causes a distribution of exchange fields. Therefore, the iron atoms in different local environments may have their several hyperfine fields with different temperature dependence. The anomalous temperature dependence of the averaged hyperfine field and line broadening observed for the 61, 62 at% Pt alloys can be understood from the co-existence of various sub-spectra with different temperature dependence. As a result, the thermal stability of magnetic order is largely reduced as the Pt concentration exceeds 60 at%.     

Stochastic resonance in the FitzHugh-Nagumo model from a dynamic mutual information point of view

Stochastic resonance(SR) in a FitzHugh-Nagumo neuron model is investigated based on a dynamic mutual information (DMI) between the input and the corresponding output signals. The DMI is expressed in terms of the (cross)power spectra of the input and output time series. Both stochastic-periodic and aperiodic SR are treated based on the DMI and our results are in good accord with the SR measured by the signal to noise ratio(SNR) for the case of the stochastic-periodic input and the power norm for the case of the aperiodic input.     

Effects of Nonlinear Time-Delay on a Stochastic Asymmetric System

We numerically investigate the effects of nonlinear time-delay on the stochastic system. With the delay time increasing, it is found that the peak of probability distribution in low steady states is decreased, and the peak of probability distribution in high steady states is increased. The mean of state variable, the normalized variance, and the normalized autocorrelation function which quantifies the concentrated degree are slowly varied for small delay time. However, the mean of state variable is rapidly increased, and the normalized variance and the normalized autocorrelation function is rapidly decreased for large delay time.     

Stochastic resonance in FitzHugh-Nagumo system with time-delayed feedback

The dynamics of a periodically driven FitzHugh-Nagumo system with time-delayed feedback and Gaussian white noise is investigated. The stochastic resonance which is characterized by the Fourier coefficient Q is numerically calculated. It is found that the stochastic resonance of the system is a non-monotonic function of the noise strength and the signal period. The variation of the time-delayed feedback can induce periodic stochastic resonance in the system.     

Stochastic Resonance in the Tumour Cell Growth Model

The phenomenon of stochastic resonance （SR） in the tumour cell growth model subjected cross-correlated noises is investigated. When a weakly periodic signal is added to the system, the signal-to-noise ratio RSNR is derived by the quasi-steady-state probability distribution function and the adiabatic elimination method. Based on the derived RSNR, the effects of these parameters （the cross-correlated strength λ and the cross-correlated time τ） are analysed by numerical calculation. It is found that the existence of a maximum in RSNR is the identifying characteristic of the SR phenomenon. The maximum of RsNR decreases with the increase of λ and increases with the increase of τ.     

Particle Transport with Asymmetric Unbiased Forces and Entropic Barrier

Transport of a Brownian particle moving along the axis of a three-dimensional （313） symmetric and periodic tube is investigated in the presence of asymmetric unbiased forces. It is found that in the presence of entropic barrier, the asymmetry of the unbiased forces is a way of inducing a net particle current. The particle current is a peaked function of temperature, which indicates that the thermal noise may facilitate the transport even in the presence of entropic barrier. There exists an optimized radius at the bottleneck at which the particle current takes its maximum value. The current can be influenced by the slope of tube walls and there exists an optimized slope for which the particle current takes its maximum value.     

Comparison of the small-world topology between anatomical and functional connectivity in the human brain

We applied graph analysis to both anatomical and functional connectivity in the human brain. Anatomical connectivity was acquired from diffusion tensor imaging data by probabilistic fiber tracking, and functional connectivity was extracted from resting-state functional magnetic resonance imaging data by calculating correlation maps of time series. For the same subject, anatomical networks seemed to be disassortative, while functional networks were significantly assortative. Anatomical networks showed higher efficiency and smaller diameters than functional networks. It can be proposed that anatomical connectivity, as a major constraint of functional connectivity, has a relatively stable and efficient structure to support functional connectivity that is more changeable and flexible.     

Stochastic resonance in time-delayed bistable systems driven by weak periodic signal

We study theoretically a bistable system with time-delayed feedback driven by a weak periodic force. The effective potential function and the steady-state probability density are derived. The delay time and the strength of its feedback can change the shapes of the potential wells. In the adiabatic approximation, the signal-to-noise ratio (SNR) of the system with a weak periodic force is obtained. The time-delayed feedback modulates the magnitude of SNR by changing the shape of the potential and the effective strength of the signal. The maximum of SNR decreases with increasing the feedback intensity ?. When ? is negative (or positive), the time delay can suppress (or promote) the stochastic resonance phenomenon.     

Multiresolution information measures applied to speech recognition

Considerable advances in automatic speech recognition have been made in the last decades, thanks specially to the use of hidden Markov models. In the field of speech signal analysis, different techniques have been developed. However, deterioration in the performance of the speech recognizers has been observed when they are trained with clean signal and tested with noisy signals. This is still an open problem in this field. Continuous multiresolution entropy has been shown to be robust to additive noise in applications to different physiological signals. In previous works we have included Shannon and Tsallis entropies, and their corresponding divergences, in different speech analysis and recognition systems. In this paper we present an extension of the continuous multiresolution entropy to different divergences and we propose them as new dimensions for the pre-processing stage of a speech recognition system. This approach takes into account information about changes in the dynamics of speech signal at different scales. The methods proposed here are tested with speech signals corrupted with babble and white noise. Their performance is compared with classical mel cepstral parametrization. The results suggest that these continuous multiresolution entropy related measures provide valuable information to the speech recognition system and that they could be considered to be included as an extra component in the pre-processing stage.