Noise and vestibular perception of passive self-motion

Noise defined as random disturbances is ubiquitous in both the external environment and the nervous system. Depending on the context, noise can degrade or improve information processing and performance. In all cases, it contributes to neural systems dynamics. We review some effects of various sources of noise on the neural processing of self-motion signals at different stages of the vestibular pathways and the resulting perceptual responses. Hair cells in the inner ear reduce the impact of noise by means of mechanical and neural filtering. Hair cells synapse on regular and irregular afferents. Variability of discharge (noise) is low in regular afferents and high in irregular units. The high variability of irregular units provides information about the envelope of naturalistic head motion stimuli. A subset of neurons in the vestibular nuclei and thalamus are optimally tuned to noisy motion stimuli that reproduce the statistics of naturalistic head movements. In the thalamus, variability of neural discharge increases with increasing motion amplitude but saturates at high amplitudes, accounting for behavioral violation of Weber’s law. In general, the precision of individual vestibular neurons in encoding head motion is worse than the perceptual precision measured behaviorally. However, the global precision predicted by neural population codes matches the high behavioral precision. The latter is estimated by means of psychometric functions for detection or discrimination of whole-body displacements. Vestibular motion thresholds (inverse of precision) reflect the contribution of intrinsic and extrinsic noise to perception. Vestibular motion thresholds tend to deteriorate progressively after the age of 40 years, possibly due to oxidative stress resulting from high discharge rates and metabolic loads of vestibular afferents. In the elderly, vestibular thresholds correlate with postural stability: the higher the threshold, the greater is the postural imbalance and risk of falling. Experimental application of optimal levels of either galvanic noise or whole-body oscillations can ameliorate vestibular function with a mechanism reminiscent of stochastic resonance. Assessment of vestibular thresholds is diagnostic in several types of vestibulopathies, and vestibular stimulation might be useful in vestibular rehabilitation

Modulatory mechanisms underlying high-frequency transcranial random noise stimulation (hf-tRNS): A combined stochastic resonance and equivalent noise approach.

BACKGROUND: High-frequency transcranial random noise stimulation (hf-tRNS) is a neuromodulatory technique consisting of the application of alternating current at random intensities and frequencies. hf-tRNS induces random neural activity in the system that may boost the sensitivity of neurons to weak inputs. Stochastic resonance is a nonlinear phenomenon whereby the addition of an optimal amount of noise results in performance enhancement, whereas further noise increments impair signal detection or discrimination. OBJECTIVE: The aim of the study was to assess whether modulatory effects of hf-tRNS rely on the stochastic resonance phenomenon, and what is the specific neural mechanism producing stochastic resonance. METHOD: Observers performed a two-interval forced choice motion direction discrimination task in which they had to report whether two moving patches presented in two temporal intervals had the same or different motion directions. hf-tRNS was administered at five intensity levels (0.5, 0.75, 1.0, 1.5, and 2.25 mA). RESULTS: The results showed a significant improvement in performance when hf-tRNS was applied at 1.5 mA, representing the optimal level of external noise. However, stimulation intensity at 2.25 mA significantly impaired direction discrimination performance. An equivalent noise (EN) analysis, used to assess how hf-tRNS modulates the mechanisms underlying global motion processing, showed an increment in motion signal integration with the optimal current intensity, but reduced motion signal integration at 2.25 mA. CONCLUSION: These results indicate that hf-tRNS-induced noise modulates neural signal-to-noise ratio in a way that is compatible with the stochastic resonance phenomenon

Unbewusste Modulatoren der somatosensorischen Wahrnehmung

It is intriguing that perception of the same stimulus can vary profoundly from trial to trial. For example, it has been shown in many studies that weak, so-called “near-threshold stimuli” are sometimes consciously perceived and sometimes not. In my thesis, I have been investigating factors which underlie this profound perceptual variability in the somatosensory domain. Together with my colleagues, I performed three studies in which we tested three different types of presumed non-conscious modulators of somatosensory perception. In the first – behavioral - study, we investigated how the presence of subliminal noise during a peripheral somatosensory stimulation influences perception. Counter-intuitively, we found that peripheral noise can even improve perception of weak somatosensory stimuli. In our interpretation, this occurs most likely due to “stochastic resonance” effects (Study I: Iliopoulos et al. 2014). In the second – behavioral and EEG - study, we tested the effect of different forms of pulsed subliminal stimulation (single pulses versus pulse trains) on brain rhythms and somatosensory perception. Following-up on previous results of our group, we tested the hypothesis that subliminal pulsed stimulation impairs perception of subsequent stimuli via centrally enhanced Mu rhythm. Interestingly, the main result of this study was that trains of subliminal stimuli indeed inhibited subsequent somatosensory detection, however, - in contrast to our previous findings for single pulses – trains were associated with decreased Mu rhythm. We conclude that central rhythms most likely play a role in mediating the perceptual modulation of peripheral subliminal stimuli, however, the relationship is more complex than previously assumed (Study II: Iliopoulos et al. 2020). In the third study, we examined the influence of interoceptive signaling, especially from the heart, on somatosensory perception. The hypothesis was that the cardiac phase (systole versus diastole) and the so-called heart-evoked potential (HEP) would modulate somatosensory perception. Indeed, our study showed that somatosensory perception was better during diastole than during systole and detection performance declined as the amplitude of the HEP increased. Our interpretation of the former effect assumes that all events which occur simultaneously with the “pulse” are assumed by the brain to be pulse-synchronous peripheral noise and therefore suppressed. Our interpretation of the latter effect (HEP) assumes that HEP is a marker of the relative balance between interoception and exteroception (Study III: Al et al. 2020). In conclusion, in the studies which form the basis for my thesis, we have shown that somatosensory perception is modulated by peripheral effects (modes of peripheral stimulation, peripheral noise), central effects (Mu rhythm) and interoceptive signals from the heart. The precise interplay between these modulators is an exciting research topic for future studies.Interessanterweise kann die Wahrnehmung desselben Reizes von Augenblick zu Augenblick so stark variieren, dass dieser manchmal bewusst wahrgenommen wird und manchmal nicht. In meiner Dissertation habe ich Faktoren untersucht, die dieser Wahrnehmungsvariabilität im somatosensorischen (SS) System zugrunde liegen. Mit meinen Kollegen habe ich drei Studien durchgeführt, in denen wir verschiedene mutmaßlich unbewusste Modulatoren der SS-Wahrnehmung untersuchten. In der ersten Studie untersuchten wir, wie die Wahrnehmung peripherer SS-Reize durch unterschwelliges Rauschen beeinflusst wird. Wir konnten zeigen, dass peripheres Rauschen die Wahrnehmung schwacher Reize verbessert. Dies ist ein Hinweis auf das Vorliegen von "stochastischen Resonanzeffekten" (Studie I: Iliopoulos et al. 2014). In der zweiten Studie, die neben behavioralen Messungen auch elektroencephalographische (EEG) Messungen umfasste, testeten wir die Auswirkung verschiedener Formen gepulster unterschwelliger elektrischer Fingerstimulationen (Einzelpulse gegen Pulsserien) auf die Wahrnehmung und auf Hirn-rhythmen. Ausgehend von früheren Ergebnissen unserer Arbeitsgruppe überprüften wir, ob repetitive subliminale Stimulationen die Wahrnehmung nachfolgender Reize über einen zentral verstärkten Mu-Rhythmus beeinträchtigen. Das Ergebnis dieser Studie war, dass Serien unterschwelliger Reize tatsächlich die nachfolgende SS-Wahrnehmung hemmten, jedoch - im Gegensatz zu früheren Ergebnissen für Einzelimpulse – die Reizserien mit einem verringerten Mu-Rhythmus verbunden waren. Daraus schließen wir, dass zentrale Rhythmen höchstwahrscheinlich eine Rolle bei der Wahrnehmungsmodulation durch periphere unterschwellige Reize spielen, dass aber der Zusammenhang zwischen beiden komplexer ist als bisher vermutet (Studie II: Iliopoulos et al. 2020). In der dritten Studie untersuchten wir den Einfluss interozeptiver Signale aus dem Herzen auf die SS-Wahrnehmung. Die Hypothese war, dass die Herzphase und das so genannte Herz-evozierte Potenzial (HEP) die SS-Wahrnehmung modulieren. Wir zeigten, dass die SS-Wahrnehmung während der Diastole besser war als während der Systole und dass die Wahrnehmung in umgekehrtem Verhältnis zur Amplitude des vorausgehenden HEP stand. Für den ersten Effekt legen unsere Daten nahe, dass alle Ereignisse, die zusammen mit der Pulswelle auftreten, vom Gehirn als puls-synchrones peripheres Rauschen angenommen und daher unterdrückt werden. Der zweite Befund wird in Übereinstimmung mit der Literatur am besten dadurch erklärt, dass das HEP ein Marker für das relative Gleichgewicht zwischen Interozeption und Exterozeption darstellt (Studie III: Al et al. 2020). Zusammenfassend zeigen die Ergebnisse dieser Arbeit, wie die SS-Wahrnehmung durch periphere Effekte (Art der Stimulation, Rauschen), zentrale Effekte (Mu-Rhythmus) und interozeptive Signale des Herzens moduliert wird. Das genaue Zusammenspiel zwischen diesen Modulatoren ist ein spannendes Forschungsthema für zukünftige Studien

Pupil-linked Phasic Arousal Predicts a Reduction of Choice Bias Across Species and Decision Domains

Decisions are often made by accumulating ambiguous evidence over time. The brain's arousal systems are activated during such decisions. In previous work in humans, we found that evoked responses of arousal systems during decisions are reported by rapid dilations of the pupil and track a suppression of biases in the accumulation of decision-relevant evidence (de Gee et al., 2017). Here, we show that this arousal-related suppression in decision bias acts on both conservative and liberal biases, and generalizes from humans to mice, and from perceptual to memory-based decisions. In challenging sound-detection tasks, the impact of spontaneous or experimentally induced choice biases was reduced under high phasic arousal. Similar bias suppression occurred when evidence was drawn from memory. All of these behavioral effects were explained by reduced evidence accumulation biases. Our results point to a general principle of interplay between phasic arousal and decision-making

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

Analytical methods and experimental approaches for electrophysiological studies of brain oscillations

Brain oscillations are increasingly the subject of electrophysiological studies probing their role in the functioning and dysfunction of the human brain. In recent years this research area has seen rapid and significant changes in the experimental approaches and analysis methods. This article reviews these developments and provides a structured overview of experimental approaches, spectral analysis techniques and methods to establish relationships between brain oscillations and behaviour

Modelling decision-making biases

Biases are a fundamental aspect of everyday life decision-making. A variety of modelling approaches have been suggested to capture decision-making biases. Statistical models are a means to describe the data, but the results are usually interpreted according to a verbal theory. This can lead to an ambiguous interpretation of the data. Mathematical cognitive models of decision-making outline the structure of the decision process with formal assumptions, providing advantages in terms of prediction, simulation, and interpretability compared to statistical models. We compare studies that used both signal detection theory and evidence accumulation models as models of decision-making biases, concluding that the latter provides a more comprehensive account of the decision-making phenomena by including response time behavior. We conclude by reviewing recent studies investigating attention and expectation biases with evidence accumulation models. Previous findings, reporting an exclusive influence of attention on the speed of evidence accumulation and prior probability on starting point, are challenged by novel results suggesting an additional effect of attention on non-decision time and prior probability on drift rate