Transient Information Flow in a Network of Excitatory and Inhibitory Model Neurons: Role of Noise and Signal Autocorrelation

We investigate the performance of sparsely-connected networks of integrate-and-fire neurons for ultra-short term information processing. We exploit the fact that the population activity of networks with balanced excitation and inhibition can switch from an oscillatory firing regime to a state of asynchronous irregular firing or quiescence depending on the rate of external background spikes. We find that in terms of information buffering the network performs best for a moderate, non-zero, amount of noise. Analogous to the phenomenon of stochastic resonance the performance decreases for higher and lower noise levels. The optimal amount of noise corresponds to the transition zone between a quiescent state and a regime of stochastic dynamics. This provides a potential explanation on the role of non-oscillatory population activity in a simplified model of cortical micro-circuits.Comment: 27 pages, 7 figures, to appear in J. Physiology (Paris) Vol. 9

Inconsistent effects of stochastic resonance on human auditory processing

It has been demonstrated that, while otherwise detrimental, noise can improve sensory perception under optimal conditions. The mechanism underlying this improvement is stochastic resonance. An inverted U-shaped relationship between noise level and task performance is considered as the signature of stochastic resonance. Previous studies have proposed the existence of stochastic resonance also in the human auditory system. However, the reported beneficial effects of noise are small, based on a small sample, and do not confirm the proposed inverted U-shaped function. Here, we investigated in two separate studies whether stochastic resonance may be present in the human auditory system by applying noise of different levels, either acoustically or electrically via transcranial random noise stimulation, while participants had to detect acoustic stimuli adjusted to their individual hearing threshold. We find no evidence for behaviorally relevant effects of stochastic resonance. Although detection rate for near-threshold acoustic stimuli appears to vary in an inverted U-shaped manner for some subjects, it varies in a U-shaped manner or in other manners for other subjects. Our results show that subjects do not benefit from noise, irrespective of its modality. In conclusion, our results question the existence of stochastic resonance in the human auditory system

Emotional agents at the square lattice

We introduce and investigate by numerical simulations a number of models of emotional agents at the square lattice. Our models describe the most general features of emotions such as the spontaneous emotional arousal, emotional relaxation, and transfers of emotions between different agents. Group emotions in the considered models are periodically fluctuating between two opposite valency levels and as result the mean value of such group emotions is zero. The oscillations amplitude depends strongly on probability ps of the individual spontaneous arousal. For small values of relaxation times tau we observed a stochastic resonance, i.e. the signal to noise ratio SNR is maximal for a non-zero ps parameter. The amplitude increases with the probability p of local affective interactions while the mean oscillations period increases with the relaxation time tau and is only weakly dependent on other system parameters. Presence of emotional antenna can enhance positive or negative emotions and for the optimal transition probability the antenna can change agents emotions at longer distances. The stochastic resonance was also observed for the influence of emotions on task execution efficiency.Comment: 28 pages, 19 figures, 3 table

Diversity and noise effects in a model of homeostatic regulation of the sleep-wake cycle

Recent advances in sleep neurobiology have allowed development of physiologically based mathematical models of sleep regulation that account for the neuronal dynamics responsible for the regulation of sleep-wake cycles and allow detailed examination of the underlying mechanisms. Neuronal systems in general, and those involved in sleep regulation in particular, are noisy and heterogeneous by their nature. It has been shown in various systems that certain levels of noise and diversity can significantly improve signal encoding. However, these phenomena, especially the effects of diversity, are rarely considered in the models of sleep regulation. The present paper is focused on a neuron-based physiologically motivated model of sleep-wake cycles that proposes a novel mechanism of the homeostatic regulation of sleep based on the dynamics of a wake-promoting neuropeptide orexin. Here this model is generalized by the introduction of intrinsic diversity and noise in the orexin-producing neurons in order to study the effect of their presence on the sleep-wake cycle. A quantitative measure of the quality of a sleep-wake cycle is introduced and used to systematically study the generalized model for different levels of noise and diversity. The model is shown to exhibit a clear diversity-induced resonance: that is, the best wake-sleep cycle turns out to correspond to an intermediate level of diversity at the synapses of the orexin-producing neurons. On the other hand only a mild evidence of stochastic resonance is found when the level of noise is varied. These results show that disorder, especially in the form of quenched diversity, can be a key-element for an efficient or optimal functioning of the homeostatic regulation of the sleep-wake cycle. Furthermore, this study provides an example of constructive role of diversity in a neuronal system that can be extended beyond the system studied here.Comment: 18 pages, 12 figures, 1 tabl

Estimation of an Optimal Stimulus Amplitude for Using Vestibular Stochastic Stimulation to Improve Balance Function

Sensorimotor changes such as postural and gait instabilities can affect the functional performance of astronauts when they transition across different gravity environments. We are developing a method, based on stochastic resonance (SR), to enhance information transfer by applying non-zero levels of external noise on the vestibular system (vestibular stochastic resonance, VSR). The goal of this project was to determine optimal levels of stimulation for SR applications by using a defined vestibular threshold of motion detection

Experimental Observation of Coherence and Stochastic Resonances in an Electronic Chua Circuit

Stochastic and coherence resonances appear in nonlinear systems subjected to an external source of noise and are characterized by a maximum response at the optimal value of the noise intensity. This paper shows experimentally that it is possible to observe them in a chaotic system. To this end we have analysed an electronic Chua circuit running in the chaotic regime and added noise to its dynamics. In the case of coherence resonance, we observe an optimal periodicity for the jumps between chaotic attractors, whereas in the case of stochastic resonance we observe a maximum in the signal-to-noise ratio at the frequency of an external sinusoidal perturbation.Comment: 6 page

Stochastic resonance in electrical circuits—II: Nonconventional stochastic resonance.

Stochastic resonance (SR), in which a periodic signal in a nonlinear system can be amplified by added noise, is discussed. The application of circuit modeling techniques to the conventional form of SR, which occurs in static bistable potentials, was considered in a companion paper. Here, the investigation of nonconventional forms of SR in part using similar electronic techniques is described. In the small-signal limit, the results are well described in terms of linear response theory. Some other phenomena of topical interest, closely related to SR, are also treate