Inconsistent effects of stochastic resonance on human auditory processing

Stochastic resonance in the sensory systems and its applications in neural prosthetics

Noise is generally considered to be detrimental. In the right conditions, however, noise can improve signal detection or information transmission. This counterintuitive phenomenon is called stochastic resonance (SR). SR has generated significant interdisciplinary interest, particularly in physics, engineering, and medical and environmental sciences. In this review, we discuss a growing empirical literature that suggests that noise at the right intensity may improve the detection and processing of auditory, sensorimotor, and visual stimuli. We focus particularly on applications of SR in sensory biology and investigate whether SR-based technologies present a pathway to improve outcomes for individuals living with sensory impairments. We conclude that there is considerable evidence supporting the application of SR in developing sensory prosthetics. However, the progression of SR-based technologies is variable across the sensory modalities. We suggest opportunities for further advancements in each modality, considering the best approaches to maximise benefits and capitalise on progress already made. Overall, SR can offer opportunities to improve existing technologies or to motivate innovations.

Multi-Type Stochastic Resonances for Noise-Enhanced Mechanical, Optical, and Acoustic Sensing

Stochastic resonance (SR) typically manifests in nonlinear systems, wherein the detection of a weak signal is bolstered by the addition of noise. Since its first discovery in a study of ice ages on Earth, various types of SRs have been observed in biological and physical systems and have been implemented in sensors to benefit from noise. However, a universally designed sensor architecture capable of accommodating different types of SRs has not been proposed, and the widespread applications of SRs in daily environments have not yet been demonstrated. Here, we propose a sensor architecture to simultaneously realize multi-type SRs and demonstrate their wide applications in mechanical, optical, and acoustic sensing domains. In particular, we find the coexistence of excitable SR and bistable SR in a sensor architecture composed of wirelessly coupled inductor-capacitor resonators connected to a nonlinearly saturable amplifier. In both types of SRs, adding noise to the system leads to a characteristic noise-enhanced signal-to-noise ratio (SNR). We further validate our findings through mechanical, optical, and acoustic sensing experiments and obtain noise-enhanced SNR by 9 dB, 3 dB, and 7 dB, respectively, compared to the standard methods devoid of SR integration. Our findings provide a general strategy to design various types of SRs and pave the way for the development of a distinctive class of sensors leveraging environmental noise, with potential applications ranging from biomedical devices to ambient sensing.

Subtractive adaptation is a more effective and general mechanism in binocular rivalry than divisive adaptation

The activity of neurons is influenced by random fluctuations and can be strongly modulated by firing rate adaptation, particularly in sensory systems. Still, there is ongoing debate about the characteristics of neuronal noise and the mechanisms of adaptation, and even less is known about how exactly they affect perception. Noise and adaptation are critical in binocular rivalry, a visual phenomenon where two images compete for perceptual dominance. Here, we investigated the effects of different noise processes and adaptation mechanisms on visual perception by simulating a model of binocular rivalry with Gaussian white noise, Ornstein-Uhlenbeck noise, and pink noise, in variants with divisive adaptation, subtractive adaptation, and without adaptation. By simulating the nine models in parameter space, we find that white noise only produces rivalry when paired with subtractive adaptation and that subtractive adaptation reduces the influence of noise intensity on rivalry strength and introduces convergence of the mean percept duration, an important metric of binocular rivalry, across all noise processes. In sum, our results show that white noise is an insufficient description of background activity in the brain and that subtractive adaptation is a stronger and more general switching mechanism in binocular rivalry than divisive adaptation, with important noise-filtering properties.

Using noise for the better: The effects of transcranial random noise stimulation on the brain and behavior

Van der Groen, O., Potok, W., Wenderoth, N., Edwards, G., Mattingley, J.B. and Edwards, D. Using noise for the better: The effects of transcranial random noise stimulation on the brain and behavior. NEUROSCI BIOBEHAV REV X (X) XXX-XXX 2021.- Transcranial random noise stimulation (tRNS) is a non-invasive electrical brain stimulation method that is increasingly employed in studies of human brain function and behavior, in health and disease. tRNS is effective in modulating perception acutely and can improve learning. By contrast, its effectiveness for modulating higher cognitive processes is variable. Prolonged stimulation with tRNS, either as one longer application, or multiple shorter applications, may engage plasticity mechanisms that can result in long-term benefits. Here we provide an overview of the current understanding of the effects of tRNS on the brain and behavior and provide some specific recommendations for future research.

Auditory brainstem responses to high-resolution audio sounds: Effects of anti-alias filters

Despite the superior technical specifications of high-resolution audio in comparison to conventional compact discs (CDs) and digital versatile discs (DVDs), whether and how high-resolution audio leads to an improved subjective listening experience remains unclear. The sound quality of conventional digital formats is deteriorated by temporal blur, which is caused by a high-cut filter applied to avoid aliasing of a digital sound source, resulting in spurious artificial sound energy before and after the actual sound onset. Using sound materials of high-resolution audio grade, this study investigated the effects of filter-induced temporal blur on the auditory neural pathway from the cochlea through the rostral brainstem by measuring the auditory brainstem responses (ABRs) of participants with normal hearing. The participants (N = 24) listened to 0.1-ms clicks, with and without a high-cut filter of 22 kHz or 11 kHz applied to them. The amplitudes and latencies of five ABR waves (<10 ms) revealed no significant effects caused by filtering. The participants could not distinguish between the original and the 22-kHz filtered click sounds, while they could distinguish between the original and the 11-kHz filtered sounds. These results indicate that a CD-level anti-alias filter does not affect initial auditory processing and the sound difference is not discernible, at least for artificial sounds with a simple acoustic structure.