Neuronal variability and tuning are balanced to optimize naturalistic self-motion coding in primate vestibular pathways

Noisy galvanic vestibular stimulation induces stochastic resonance in vestibular perceptual thresholds assessed efficiently using confidence reports

In sensory perception, stochastic resonance (SR) refers to the application of noise to enhance information transfer, allowing for the sensing of lower-level stimuli. Previously, subjective-assessments identified SR in vestibular perceptual thresholds, assessed using a standard two alternative (i.e., binary), forced-choice task, when applying noisy Galvanic Vestibular Stimulation (nGVS). However, this required extensive testing of at least 100 binary trials to yield sufficiently precise thresholds at each of several nGVS amplitudes, leading to confounds of fatigue, sleepiness, learning, etc. stalling the study of vestibular SR. To mitigate this, we explore confidence reporting, which via a confidence signal detection (CSD) model may much more efficiently identify SR (i.e., with fewer trials), if SR exists in CSD thresholds. To test this, Y-translation thresholds were tested with 100 trials at each nGVS amplitude (0 or sham, 0.1, 0.2, 0.3 and 0.4 mA peak-to-peak). To objectively identify SR, we applied a machine learning classification algorithm trained on simulated datasets. We found significant evidence of SR exhibition using CSD thresholds (p = 0.0025), with six of 10 subjects classified as exhibiting SR. Next, we considered fewer trials, finding the false positive rate of SR identification to be better using CSD thresholds with as few as 50 trials, when compared to 100 binary trials. Applying the CSD model to our subject's data with a subset of their trials found similar classifications of SR exhibition as with 100 binary trials. We demonstrate CSD thresholds exhibit SR, proving a means of better and much more efficiently identifying SR.

Neural populations within macaque early vestibular pathways are adapted to encode natural self-motion

How the activities of large neural populations are integrated in the brain to ensure accurate perception and behavior remains a central problem in systems neuroscience. Here, we investigated population coding of naturalistic self-motion by neurons within early vestibular pathways in rhesus macaques (Macacca mulatta). While vestibular neurons displayed similar dynamic tuning to self-motion, inspection of their spike trains revealed significant heterogeneity. Further analysis revealed that, during natural but not artificial stimulation, heterogeneity resulted primarily from variability across neurons as opposed to trial-to-trial variability. Interestingly, vestibular neurons displayed different correlation structures during naturalistic and artificial self-motion. Specifically, while correlations due to the stimulus (i.e., signal correlations) did not differ, correlations between the trial-to-trial variabilities of neural responses (i.e., noise correlations) were instead significantly positive during naturalistic but not artificial stimulation. Using computational modeling, we show that positive noise correlations during naturalistic stimulation benefits information transmission by heterogeneous vestibular neural populations. Taken together, our results provide evidence that neurons within early vestibular pathways are adapted to the statistics of natural self-motion stimuli at the population level. We suggest that similar adaptations will be found in other systems and species.

Serotonin increases population coding of behaviorally relevant stimuli by enhancing responses of ON but not OFF-type sensory neurons

How neural populations encode sensory input to generate behavioral responses remains a central problem in systems neuroscience. Here we investigated how neuromodulation influences population coding of behaviorally relevant stimuli to give rise to behavior in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus. We performed multi-unit recordings from ON and OFF sensory pyramidal cells in response to stimuli whose amplitude (i.e., envelope) varied in time, before and after electrical stimulation of the raphe nuclei. Overall, raphe stimulation increased population coding by ON- but not by OFF-type cells, despite both cell types showing similar sensitivities to the stimulus at the single neuron level. Surprisingly, only changes in population coding by ON-type cells were correlated with changes in behavioral responses. Taken together, our results show that neuromodulation differentially affects ON vs. OFF-type cells in order to enhance perception of behaviorally relevant sensory input.

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.

Coding of object location by heterogeneous neural populations with spatially dependent correlations in weakly electric fish

Understanding how neural populations encode sensory stimuli remains a central problem in neuroscience. Here we performed multi-unit recordings from sensory neural populations in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus in response to stimuli located at different positions along the rostro-caudal axis. Our results reveal that the spatial dependence of correlated activity along receptive fields can help mitigate the deleterious effects that these correlations would otherwise have if they were spatially independent. Moreover, using mathematical modeling, we show that experimentally observed heterogeneities in the receptive fields of neurons help optimize information transmission as to object location. Taken together, our results have important implications for understanding how sensory neurons whose receptive fields display antagonistic center-surround organization encode location. Important similarities between the electrosensory system and other sensory systems suggest that our results will be applicable elsewhere.

Enhancement of Vestibular Motion Discrimination by Small Stochastic Whole-body Perturbations in Young Healthy Humans

Noisy galvanic vestibular stimulation has been shown to improve vestibular perception in healthy subjects. Here, we sought to obtain similar results using more natural stimuli consisting of small-amplitude motion perturbations of the whole body. Thirty participants were asked to report the perceived direction of antero-posterior sinusoidal motion on a MOOG platform. We compared the baseline perceptual thresholds with those obtained by applying small, stochastic perturbations at different power levels along the antero-posterior axis, symmetrically distributed around a zero-mean. At the population level, we found that the thresholds for all but the highest level of noise were significantly lower than the baseline threshold. At the individual level, the threshold was lower with at least one noise level than the threshold without noise in 87% of participants. Thus, small, stochastic oscillations of the whole body can increase the probability of recognizing the direction of motion from low, normally subthreshold vestibular signals, possibly due to stochastic resonance mechanisms. We suggest that, just as the external noise of the present experiments, also the spontaneous random oscillations of the head and body associated with standing posture are beneficial by enhancing vestibular thresholds with a mechanism similar to stochastic resonance.

Neural substrates of perception in the vestibular thalamus during natural self-motion: A review

Accumulating evidence across multiple sensory modalities suggests that the thalamus does not simply relay information from the periphery to the cortex. Here we review recent findings showing that vestibular neurons within the ventral posteriolateral area of the thalamus perform nonlinear transformations on their afferent input that determine our subjective awareness of motion. Specifically, these neurons provide a substrate for previous psychophysical observations that perceptual discrimination thresholds are much better than predictions from Weber's law. This is because neural discrimination thresholds, which are determined from both variability and sensitivity, initially increase but then saturate with increasing stimulus amplitude, thereby matching the previously observed dependency of perceptual self-motion discrimination thresholds. Moreover, neural response dynamics give rise to unambiguous and optimized encoding of natural but not artificial stimuli. Finally, vestibular thalamic neurons selectively encode passively applied motion when occurring concurrently with voluntary (i.e., active) movements. Taken together, these results show that the vestibular thalamus plays an essential role towards generating motion perception as well as shaping our vestibular sense of agency that is not simply inherited from afferent input.

Natural statistics of head roll: implications for Bayesian inference in spatial orientation

We previously proposed a Bayesian model of multisensory integration in spatial orientation (Clemens IAH, de Vrijer M, Selen LPJ, van Gisbergen JAM, Medendorp WP. J Neurosci 31: 5365-5377, 2011). Using a Gaussian prior, centered on an upright head orientation, this model could explain various perceptual observations in roll-tilted participants, such as the subjective visual vertical, the subjective body tilt (Clemens IAH, de Vrijer M, Selen LPJ, van Gisbergen JAM, Medendorp WP. J Neurosci 31: 5365-5377, 2011), the rod-and-frame effect (Alberts BBGT, de Brouwer AJ, Selen LPJ, Medendorp WP. eNeuro 3: ENEURO.0093-16.2016, 2016), as well as their clinical (Alberts BBGT, Selen LPJ, Verhagen WIM, Medendorp WP. Physiol Rep 3: e12385, 2015) and age-related deficits (Alberts BBGT, Selen LPJ, Medendorp WP. J Neurophysiol 121: 1279-1288, 2019). Because it is generally assumed that the prior reflects an accumulated history of previous head orientations, and recent work on natural head motion suggests non-Gaussian statistics, we examined how the model would perform with a non-Gaussian prior. In the present study, we first experimentally generalized the previous observations in showing that also the natural statistics of head orientation are characterized by long tails, best quantified as a t-location-scale distribution. Next, we compared the performance of the Bayesian model and various model variants using such a t-distributed prior to the original model with the Gaussian prior on their accounts of previously published data of the subjective visual vertical and subjective body tilt tasks. All of these variants performed substantially worse than the original model, suggesting a special value of the Gaussian prior. We provide computational and neurophysiological reasons for the implementation of such a prior, in terms of its associated precision-accuracy trade-off in vertical perception across the tilt range.NEW & NOTEWORTHY It has been argued that the brain uses Bayesian computations to process multiple sensory cues in vertical perception, including a prior centered on upright head orientation which is usually taken to be Gaussian. Here, we show that non-Gaussian prior distributions, although more akin to the statistics of head orientation during natural activities, provide a much worse explanation of such perceptual observations than a Gaussian prior.

Sensory adaptation mediates efficient and unambiguous encoding of natural stimuli by vestibular thalamocortical pathways

Sensory systems must continuously adapt to optimally encode stimuli encountered within the natural environment. The prevailing view is that such optimal coding comes at the cost of increased ambiguity, yet to date, prior studies have focused on artificial stimuli. Accordingly, here we investigated whether such a trade-off between optimality and ambiguity exists in the encoding of natural stimuli in the vestibular system. We recorded vestibular nuclei and their target vestibular thalamocortical neurons during naturalistic and artificial self-motion stimulation. Surprisingly, we found no trade-off between optimality and ambiguity. Using computational methods, we demonstrate that thalamocortical neural adaptation in the form of contrast gain control actually reduces coding ambiguity without compromising the optimality of coding under naturalistic but not artificial stimulation. Thus, taken together, our results challenge the common wisdom that adaptation leads to ambiguity and instead suggest an essential role in underlying unambiguous optimized encoding of natural stimuli.

The neural basis for violations of Weber's law in self-motion perception

A prevailing view is that Weber's law constitutes a fundamental principle of perception. This widely accepted psychophysical law states that the minimal change in a given stimulus that can be perceived increases proportionally with amplitude and has been observed across systems and species in hundreds of studies. Importantly, however, Weber's law is actually an oversimplification. Notably, there exist violations of Weber's law that have been consistently observed across sensory modalities. Specifically, perceptual performance is better than that predicted from Weber's law for the higher stimulus amplitudes commonly found in natural sensory stimuli. To date, the neural mechanisms mediating such violations of Weber's law in the form of improved perceptual performance remain unknown. Here, we recorded from vestibular thalamocortical neurons in rhesus monkeys during self-motion stimulation. Strikingly, we found that neural discrimination thresholds initially increased but saturated for higher stimulus amplitudes, thereby causing the improved neural discrimination performance required to explain perception. Theory predicts that stimulus-dependent neural variability and/or response nonlinearities will determine discrimination threshold values. Using computational methods, we thus investigated the mechanisms mediating this improved performance. We found that the structure of neural variability, which initially increased but saturated for higher amplitudes, caused improved discrimination performance rather than response nonlinearities. Taken together, our results reveal the neural basis for violations of Weber's law and further provide insight as to how variability contributes to the adaptive encoding of natural stimuli with continually varying statistics.

Vestibular Precision at the Level of Perception, Eye Movements, Posture, and Neurons

Precision and accuracy are two fundamental properties of any system, including the nervous system. Reduced precision (i.e., imprecision) results from the presence of neural noise at each level of sensory, motor, and perceptual processing. This review has three objectives: (1) to show the importance of studying vestibular precision, and specifically that studying accuracy without studying precision ignores fundamental aspects of the vestibular system; (2) to synthesize key hypotheses about precision in vestibular perception, the vestibulo-ocular reflex, posture, and neurons; and (3) to show that groups of studies that are thoughts to be distinct (e.g., perceptual thresholds, subjective visual vertical variability, neuronal variability) are actually "two sides of the same coin" - because the methods used allow results to be related to the standard deviation of a Gaussian distribution describing the underlying neural noise. Vestibular precision varies with age, stimulus amplitude, stimulus frequency, body orientation, motion direction, pathology, medication, and electrical/mechanical vestibular stimulation, but does not vary with sex. The brain optimizes precision during integration of vestibular cues with visual, auditory, and/or somatosensory cues. Since a common concern with precision metrics is time required for testing, we describe approaches to optimize data collection and provide evidence that fatigue and session effects are minimal. Finally, we summarize how precision is an individual trait that is correlated with clinical outcomes in patients as well as with performance in functional tasks like balance. These findings highlight the importance of studying vestibular precision and accuracy, and that knowledge gaps remain.

Efficient and robust coding in heterogeneous recurrent networks

Cortical networks show a large heterogeneity of neuronal properties. However, traditional coding models have focused on homogeneous populations of excitatory and inhibitory neurons. Here, we analytically derive a class of recurrent networks of spiking neurons that close to optimally track a continuously varying input online, based on two assumptions: 1) every spike is decoded linearly and 2) the network aims to reduce the mean-squared error between the input and the estimate. From this we derive a class of predictive coding networks, that unifies encoding and decoding and in which we can investigate the difference between homogeneous networks and heterogeneous networks, in which each neurons represents different features and has different spike-generating properties. We find that in this framework, 'type 1' and 'type 2' neurons arise naturally and networks consisting of a heterogeneous population of different neuron types are both more efficient and more robust against correlated noise. We make two experimental predictions: 1) we predict that integrators show strong correlations with other integrators and resonators are correlated with resonators, whereas the correlations are much weaker between neurons with different coding properties and 2) that 'type 2' neurons are more coherent with the overall network activity than 'type 1' neurons.

Lower Baseline Variability Gives Rise to Lower Detection Thresholds in Midbrain than Hindbrain Electrosensory Neurons

Understanding how the brain decodes sensory information to give rise to behaviour remains an important problem in systems neuroscience. Across various sensory modalities (e.g. auditory, visual), the time-varying contrast of natural stimuli has been shown to carry behaviourally relevant information. However, it is unclear how such information is actually decoded by the brain to evoke perception and behaviour. Here we investigated how midbrain electrosensory neurons respond to weak contrasts in the electrosensory system of the weakly electric fish Apteronotus leptorhynchus. We found that these neurons displayed lower detection thresholds than their afferent hindbrain electrosensory neurons. Further analysis revealed that the lower detection thresholds of midbrain neurons were not due to increased sensitivity to the stimulus. Rather, these were due to the fact that midbrain neurons displayed lower variability in their firing activities in the absence of stimulation, which is due to lower firing rates. Our results suggest that midbrain neurons play an active role towards enabling the detection of weak stimulus contrasts, which in turn leads to perception and behavioral responses.

Neural variability determines coding strategies for natural self-motion in macaque monkeys

We have previously reported that central neurons mediating vestibulo-spinal reflexes and self-motion perception optimally encode natural self-motion (Mitchell et al., 2018). Importantly however, the vestibular nuclei also comprise other neuronal classes that mediate essential functions such as the vestibulo-ocular reflex (VOR) and its adaptation. Here we show that heterogeneities in resting discharge variability mediate a trade-off between faithful encoding and optimal coding via temporal whitening. Specifically, neurons displaying lower variability did not whiten naturalistic self-motion but instead faithfully represented the stimulus' detailed time course, while neurons displaying higher variability displayed temporal whitening. Using a well-established model of VOR pathways, we demonstrate that faithful stimulus encoding is necessary to generate the compensatory eye movements found experimentally during naturalistic self-motion. Our findings suggest a novel functional role for variability toward establishing different coding strategies: (1) faithful stimulus encoding for generating the VOR; (2) optimized coding via temporal whitening for other vestibular functions.

Neural Mechanisms Underlying High-Frequency Vestibulocollic Reflexes In Humans And Monkeys

The vestibulocollic reflex is a compensatory response that stabilizes the head in space. During everyday activities, this stabilizing response is evoked by head movements that typically span frequencies from 0 to 30 Hz. Transient head impacts, however, can elicit head movements with frequency content up to 300-400 Hz, raising the question whether vestibular pathways contribute to head stabilization at such high frequencies. Here, we first established that electrical vestibular stimulation modulates human neck motor unit (MU) activity at sinusoidal frequencies up to 300 Hz, but that sensitivity increases with frequency up to a low-pass cutoff of ∼70-80 Hz. To examine the neural substrates underlying the low-pass dynamics of vestibulocollic reflexes, we then recorded vestibular afferent responses to the same electrical stimuli in monkeys. Vestibular afferents also responded to electrical stimuli up to 300 Hz, but in contrast to MUs their sensitivity increased with frequency up to the afferent resting firing rate (∼100-150 Hz) and at higher frequencies afferents tended to phase-lock to the vestibular stimulus. This latter nonlinearity, however, was not transmitted to neck motoneurons, which instead showed minimal phase-locking that decreased at frequencies >75 Hz. Similar to human data, we validated that monkey muscle activity also exhibited low-pass filtered vestibulocollic reflex dynamics. Together, our results show that neck MUs are activated by high-frequency signals encoded by primary vestibular afferents, but undergo low-pass filtering at intermediate stages in the vestibulocollic reflex. These high-frequency contributions to vestibular-evoked neck muscle responses could stabilize the head during unexpected head transients.SIGNIFICANCE STATEMENT Vestibular-evoked neck muscle responses rely on accurate encoding and transmission of head movement information to stabilize the head in space. Unexpected transient events, such as head impacts, are likely to push the limits of these neural pathways since their high-frequency features (0-300 Hz) extend beyond the frequency bandwidth of head movements experienced during everyday activities (0-30 Hz). Here, we demonstrate that vestibular primary afferents encode high-frequency stimuli through frequency-dependent increases in sensitivity and phase-locking. When transmitted to neck motoneurons, these signals undergo low-pass filtering that limits neck motoneuron phase-locking in response to stimuli >75 Hz. This study provides insight into the neural dynamics producing vestibulocollic reflexes, which may respond to high-frequency transient events to stabilize the head.

Cortical circuits for integration of self-motion and visual-motion signals

The cerebral cortex contains cells which respond to movement of the head, and these cells are thought to be involved in the perception of self-motion. In particular, studies in the primary visual cortex of mice show that both running speed and passive whole-body rotation modulates neuronal activity, and modern genetically targeted viral tracing approaches have begun to identify previously unknown circuits that underlie these responses. Here we review recent experimental findings and provide a road map for future work in mice to elucidate the functional architecture and emergent properties of a cortical network potentially involved in the generation of egocentric-based visual representations for navigation.

Asymmetric Unilateral Vestibular Perception in Adolescents With Idiopathic Scoliosis

The cause of Adolescent Idiopathic Scoliosis (AIS) remains unclear, but one proposed cause of AIS is asymmetric vestibular function and the related descending drive to the spine musculature. The objective of this study was to determine if asymmetric vestibular function is present in individuals with AIS. Ten individuals with AIS (8F, 2M) and 10 healthy age- and sex-matched controls were exposed to 10s-long virtual rotations induced by monaural or binaural electrical vestibular stimulation (EVS), and 10s-long real rotations delivered by a rotating chair. Using a forced-choice paradigm, participants indicated their perceived rotation direction (right or left) to stimuli of varying intensity. A Bayesian adaptive algorithm adjusted the stimulus intensity and direction to identify a stimulus level, which we called the direction recognition threshold, at which participants correctly identified the rotation direction 69% of the time. For unilateral vestibular stimuli (monaural EVS), the direction recognition thresholds were more asymmetric in all participants with AIS compared to control participants [(0.22-1.00 mA) vs. (0.01-0.21 mA); p < 0.001]. For bilateral vestibular stimuli, however, the direction recognition thresholds did not differ between groups for either the real or virtual rotations (multiple p > 0.05). Previous reports of semicircular canal orientation asymmetry in individuals with AIS could not explain the magnitude of the vestibular function asymmetry we observed, suggesting a functional cause to the observed vestibular asymmetry. Thus, the present results suggest that a unilateral vestibular dysfunction is linked to AIS, potentially revealing a new path for the screening and monitoring of scoliosis in adolescents.

Descending pathways mediate adaptive optimized coding of natural stimuli in weakly electric fish

Biological systems must be flexible to environmental changes to survive. This is exemplified by the fact that sensory systems continuously adapt to changes in the environment to optimize coding and behavioral responses. However, the nature of the underlying mechanisms remains poorly understood in general. Here, we investigated the mechanisms mediating adaptive optimized coding of naturalistic stimuli with varying statistics depending on the animal's velocity during movement. We found that central neurons adapted their responses to stimuli with different power spectral densities such as to optimally encode them, thereby ensuring that behavioral responses are, in turn, better matched to the new stimulus statistics. Sensory adaptation further required descending inputs from the forebrain as well as the raphe nuclei. Our findings thus reveal a previously unknown functional role for descending pathways in mediating adaptive optimized coding of natural stimuli that is likely generally applicable across sensory systems and species.

Neural substrates, dynamics and thresholds of galvanic vestibular stimulation in the behaving primate

Galvanic vestibular stimulation (GVS) uses the external application of electrical current to selectively target the vestibular system in humans. Despite its recent popularity for the assessment/treatment of clinical conditions, exactly how this non-invasive tool activates the vestibular system remains an open question. Here we directly investigate single vestibular afferent responses to GVS applied to the mastoid processes of awake-behaving monkeys. Transmastoid GVS produces robust and parallel activation of both canal and otolith afferents. Notably, afferent activation increases with intrinsic neuronal variability resulting in constant GVS-evoked neuronal detection thresholds across all afferents. Additionally, afferent tuning differs for GVS versus natural self-motion stimulation. Using a stochastic model of repetitive activity in afferents, we largely explain the main features of GVS-evoked vestibular afferent dynamics. Taken together, our results reveal the neural substrate underlying transmastoid GVS-evoked perceptual, ocular and postural responses-information that is essential to advance GVS applicability for biomedical uses in humans.

Neuronal variability and tuning are balanced to optimize naturalistic self-motion coding in primate vestibular pathways

It is commonly assumed that the brain's neural coding strategies are adapted to the statistics of natural stimuli. Specifically, to maximize information transmission, a sensory neuron's tuning function should effectively oppose the decaying stimulus spectral power, such that the neural response is temporally decorrelated (i.e. 'whitened'). However, theory predicts that the structure of neuronal variability also plays an essential role in determining how coding is optimized. Here, we provide experimental evidence supporting this view by recording from neurons in early vestibular pathways during naturalistic self-motion. We found that central vestibular neurons displayed temporally whitened responses that could not be explained by their tuning alone. Rather, computational modeling and analysis revealed that neuronal variability and tuning were matched to effectively complement natural stimulus statistics, thereby achieving temporal decorrelation and optimizing information transmission. Taken together, our findings reveal a novel strategy by which neural variability contributes to optimized processing of naturalistic stimuli.