Contrast detection is enhanced by deterministic, high-frequency transcranial alternating current stimulation with triangle and sine waveform

Stochastic Resonance (SR) describes a phenomenon where an additive noise (stochastic carrier-wave) enhances the signal transmission in a nonlinear system. In the nervous system, nonlinear properties are present from the level of single ion channels all the way to perception and appear to support the emergence of SR. For example, SR has been repeatedly demonstrated for visual detection tasks, also by adding noise directly to cortical areas via transcranial random noise stimulation (tRNS). When dealing with nonlinear physical systems, it has been suggested that resonance can be induced not only by adding stochastic signals (i.e., noise) but also by adding a large class of signals that are not stochastic in nature which cause "deterministic amplitude resonance" (DAR). Here we mathematically show that high-frequency, deterministic, periodic signals can yield resonance-like effects with linear transfer and infinite signal-to-noise ratio at the output. We tested this prediction empirically and investigated whether non-random, high-frequency, transcranial alternating current stimulation applied to visual cortex could induce resonance-like effects and enhance performance of a visual detection task. We demonstrated in 28 participants that applying 80 Hz triangular-waves or sine-waves with tACS reduced visual contrast detection threshold for optimal brain stimulation intensities. The influence of tACS on contrast sensitivity was equally effective to tRNS-induced modulation, demonstrating that both tACS and tRNS can reduce contrast detection thresholds. Our findings suggest that a resonance-like mechanism can also emerge when deterministic electrical waveforms are applied via tACS.Comment: accepted for publication in J. Neurophysiolog

Motion processing deficits in migraine are related to contrast sensitivity

Background: There are conflicting reports concerning the ability of people with migraine to detect and discriminate visual motion. Previous studies used different displays and none adequately assessed other parameters that could affect performance, such as those that could indicate precortical dysfunction. Methods: Motion-direction detection, discrimination and relative motion thresholds were compared from participants with and without migraine. Potentially relevant visual covariates were included (contrast sensitivity; acuity; stereopsis; visual discomfort, stress, triggers; dyslexia). Results: For each task, migraine participants were less accurate than a control group and had impaired contrast sensitivity, greater visual discomfort, visual stress and visual triggers. Only contrast sensitivity correlated with performance on each motion task; it also mediated performance. Conclusions: Impaired performance on certain motion tasks can be attributed to impaired contrast sensitivity early in the visual system rather than a deficit in cortical motion processing per se. There were, however, additional differences for global and relative motion thresholds embedded in noise, suggesting changes in extrastriate cortex in migraine. Tasks to study the effects of noise on performance at different levels of the visual system and across modalities are recommended. A battery of standard visual tests should be included in any future work on the visual system and migraine

Noise-enhanced computation in a model of a cortical column

Varied sensory systems use noise in order to enhance detection of weak signals. It has been conjectured in the literature that this effect, known as stochastic resonance, may take place in central cognitive processes such as the memory retrieval of arithmetical multiplication. We show in a simplified model of cortical tissue, that complex arithmetical calculations can be carried out and are enhanced in the presence of a stochastic background. The performance is shown to be positively correlated to the susceptibility of the network, defined as its sensitivity to a variation of the mean of its inputs. For nontrivial arithmetic tasks such as multiplication, stochastic resonance is an emergent property of the microcircuitry of the model network

Ubiquitous Crossmodal Stochastic Resonance in Humans: Auditory Noise Facilitates Tactile, Visual and Proprioceptive Sensations

BACKGROUND: Stochastic resonance is a nonlinear phenomenon whereby the addition of noise can improve the detection of weak stimuli. An optimal amount of added noise results in the maximum enhancement, whereas further increases in noise intensity only degrade detection or information content. The phenomenon does not occur in linear systems, where the addition of noise to either the system or the stimulus only degrades the signal quality. Stochastic Resonance (SR) has been extensively studied in different physical systems. It has been extended to human sensory systems where it can be classified as unimodal, central, behavioral and recently crossmodal. However what has not been explored is the extension of this crossmodal SR in humans. For instance, if under the same auditory noise conditions the crossmodal SR persists among different sensory systems. METHODOLOGY/PRINCIPAL FINDINGS: Using physiological and psychophysical techniques we demonstrate that the same auditory noise can enhance the sensitivity of tactile, visual and propioceptive system responses to weak signals. Specifically, we show that the effective auditory noise significantly increased tactile sensations of the finger, decreased luminance and contrast visual thresholds and significantly changed EMG recordings of the leg muscles during posture maintenance. CONCLUSIONS/SIGNIFICANCE: We conclude that crossmodal SR is a ubiquitous phenomenon in humans that can be interpreted within an energy and frequency model of multisensory neurons spontaneous activity. Initially the energy and frequency content of the multisensory neurons' activity (supplied by the weak signals) is not enough to be detected but when the auditory noise enters the brain, it generates a general activation among multisensory neurons of different regions, modifying their original activity. The result is an integrated activation that promotes sensitivity transitions and the signals are then perceived. A physiologically plausible model for crossmodal stochastic resonance is presented

Different effects of adding white noise on cognitive performance of sub-, normal and super-attentive school children

Objectives: Noise often has detrimental effects on performance. However, because of the phenomenon of stochastic resonance (SR), auditory white noise (WN) can alter the "signal to noise'' ratio and improve performance. The Moderate Brain Arousal (MBA) model postulates different levels of internal "neural noise'' in individuals with different attentional capacities. This in turn determines the particular WN level most beneficial in each individual case-with one level of WN facilitating poor attenders but hindering super-attentive children. The objective of the present study is to find out if added WN affects cognitive performance differently in children that differ in attention ability. Methods: Participants were teacher-rated super-(N = 25); normal-(N = 29) and sub-attentive (N = 36) children (aged 8 to 10 years). Two non-executive function (EF) tasks (a verbal episodic recall task and a delayed verbal recognition task) and two EF tasks (a visuo-spatial working memory test and a Go-NoGo task) were performed under three WN levels. The non-WN condition was only used to control for potential differences in background noise in the group testing situations. Results: There were different effects of WN on performance in the three groups-adding moderate WN worsened the performance of super-attentive children for both task types and improved EF performance in sub-attentive children. The normal-attentive children's performance was unaffected by WN exposure. The shift from moderate to high levels of WN had little further effect on performance in any group. Significance: The predicted differential effect of WN on performance was confirmed. However, the failure to find evidence for an inverted U function challenges current theories. Alternative explanations are discussed. We propose that WN therapy should be further investigated as a possible non-pharmacological treatment for inattention

Electrical stimulation of visual cortex can immediately improve spatial vision

Published in final edited form as:Curr Biol. 2016 July 25; 26(14): 1867–1872. doi:10.1016/j.cub.2016.05.019.SUMMARY We can improve human vision by correcting the optics of our lenses [1, 2, 3]. However, after the eye transduces the light, visual cortex has its own limitations that are challenging to correct [4]. Overcoming these limitations has typically involved innovative training regimes that improve vision across many days [5, 6]. In the present study, we wanted to determine whether it is possible to immediately improve the precision of spatial vision with noninvasive direct-current stimulation. Previous work suggested that visual processing could be modulated with such stimulation [7, 8, 9]. However, the short duration and variability of such effects made it seem unlikely that spatial vision could be improved for more than several minutes [7, 10]. Here we show that visual acuity in the parafoveal belt can be immediately improved by delivering noninvasive direct current to visual cortex. Twenty minutes of anodal stimulation improved subjects’ vernier acuity by approximately 15% and increased the amplitude of the earliest visually evoked potentials in lockstep with the behavioral effects. When we reversed the orientation of the electric field, we impaired resolution and reduced the amplitude of visually evoked potentials. Next, we found that anodal stimulation improved acuity enough to be measurable with the relatively coarse Snellen test and that subjects with the poorest acuity benefited the most from stimulation. Finally, we found that stimulation-induced acuity improvements were accompanied by changes in contrast sensitivity at high spatial frequencies.This work was supported by grants from the NIH (R01-EY019882, R01-EY025275, P30-EY08126, T32-EY007135, F31-MH102042). We thank the reviewers and Randolph Blake for helpful comments. We thank Kevin Dieter for technical assistance in designing the psychophysical procedure for experiment 5. Subjects gave informed written consent to procedures approved by the Vanderbilt University Institutional Review Board and were compensated at a rate of $10/hr for their time. (R01-EY019882 - NIH; R01-EY025275 - NIH; P30-EY08126 - NIH; T32-EY007135 - NIH; F31-MH102042 - NIH)Accepted manuscrip

Experimental evidence of stochastic resonance without tuning due to non Gaussian noises

In order to test theoretical predictions, we have studied the phenomenon of stochastic resonance in an electronic experimental system driven by white non Gaussian noise. In agreement with the theoretical predictions our main findings are: an enhancement of the sensibility of the system together with a remarkable widening of the response (robustness). This implies that even a single resonant unit can reach a marked reduction in the need of noise tuning.Comment: 4 pages, 3 figure

Analysis of noise-induced transitions from regular to chaotic oscillations in the Chen system

The stochastically perturbed Chen system is studied within the parameter region which permits both regular and chaotic oscillations. As noise intensity increases and passes some threshold value, noise-induced hopping between close portions of the stochastic cycle can be observed. Through these transitions, the stochastic cycle is deformed to be a stochastic attractor that looks like chaotic. In this paper for investigation of these transitions, a constructive method based on the stochastic sensitivity function technique with confidence ellipses is suggested and discussed in detail. Analyzing a mutual arrangement of these ellipses, we estimate the threshold noise intensity corresponding to chaotization of the stochastic attractor. Capabilities of this geometric method for detailed analysis of the noise-induced hopping which generates chaos are demonstrated on the stochastic Chen system. © 2012 American Institute of Physics