Neuronal thresholds and choice-related activity of otolith afferent fibers during heading perception

Protocol for behavioral and neural recording in macaques during a novelty detection task

The neural mechanisms of novelty detection, especially in relation to behavior, are currently poorly understood. Here, we present a protocol for recording neuronal activity in macaque auditory cortex during novelty detection tasks. We describe steps for behavioral training, surgical headpost implantation, MRI-based electrode targeting, and electrophysiological recording. These steps allow direct assessment of the correlation between novelty detection behavior and neuronal activity. For complete details on the use and execution of this protocol, please refer to Gong et al.1.

Neural correlates of novelty detection in the primary auditory cortex of behaving monkeys

The neural mechanisms underlying novelty detection are not well understood, especially in relation to behavior. Here, we present single-unit responses from the primary auditory cortex (A1) from two monkeys trained to detect deviant tones amid repetitive ones. Results show that monkeys can detect deviant sounds, and there is a strong correlation between late neuronal responses (250-350 ms after deviant onset) and the monkeys' perceptual decisions. The magnitude and timing of both neuronal and behavioral responses are increased by larger frequency differences between the deviant and standard tones and by increasing the number of standard tones preceding the deviant. This suggests that A1 neurons encode novelty detection in behaving monkeys, influenced by stimulus relevance and expectations. This study provides evidence supporting aspects of predictive coding in the sensory cortex.

Temporal and spatial properties of vestibular signals for perception of self-motion

It is well recognized that the vestibular system is involved in numerous important cognitive functions, including self-motion perception, spatial orientation, locomotion, and vector-based navigation, in addition to basic reflexes, such as oculomotor or body postural control. Consistent with this rationale, vestibular signals exist broadly in the brain, including several regions of the cerebral cortex, potentially allowing tight coordination with other sensory systems to improve the accuracy and precision of perception or action during self-motion. Recent neurophysiological studies in animal models based on single-cell resolution indicate that vestibular signals exhibit complex spatiotemporal dynamics, producing challenges in identifying their exact functions and how they are integrated with other modality signals. For example, vestibular and optic flow could provide congruent and incongruent signals regarding spatial tuning functions, reference frames, and temporal dynamics. Comprehensive studies, including behavioral tasks, neural recording across sensory and sensory-motor association areas, and causal link manipulations, have provided some insights into the neural mechanisms underlying multisensory self-motion perception.

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.

Joint representation of working memory and uncertainty in human cortex

Neural representations of visual working memory (VWM) are noisy, and thus, decisions based on VWM are inevitably subject to uncertainty. However, the mechanisms by which the brain simultaneously represents the content and uncertainty of memory remain largely unknown. Here, inspired by the theory of probabilistic population codes, we test the hypothesis that the human brain represents an item maintained in VWM as a probability distribution over stimulus feature space, thereby capturing both its content and uncertainty. We used a neural generative model to decode probability distributions over memorized locations from fMRI activation patterns. We found that the mean of the probability distribution decoded from retinotopic cortical areas predicted memory reports on a trial-by-trial basis. Moreover, in several of the same mid-dorsal stream areas, the spread of the distribution predicted subjective trial-by-trial uncertainty judgments. These results provide evidence that VWM content and uncertainty are jointly represented by probabilistic neural codes.

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.

Differences in the Structure and Function of the Vestibular Efferent System Among Vertebrates

The role of the mammalian vestibular efferent system in everyday life has been a long-standing mystery. In contrast to what has been reported in lower vertebrate classes, the mammalian vestibular efferent system does not appear to relay inputs from other sensory modalities to the vestibular periphery. Furthermore, to date, the available evidence indicates that the mammalian vestibular efferent system does not relay motor-related signals to the vestibular periphery to modulate sensory coding of the voluntary self-motion generated during natural behaviors. Indeed, our recent neurophysiological studies have provided insight into how the peripheral vestibular system transmits head movement-related information to the brain in a context independent manner. The integration of vestibular and extra-vestibular information instead only occurs at next stage of the mammalian vestibular system, at the level of the vestibular nuclei. The question thus arises: what is the physiological role of the vestibular efferent system in mammals? We suggest that the mammalian vestibular efferent system does not play a significant role in short-term modulation of afferent coding, but instead plays a vital role over a longer time course, for example in calibrating and protecting the functional efficacy of vestibular circuits during development and aging in a role analogous the auditory efferent system.

Stimulus-dependent relationships between behavioral choice and sensory neural responses

Understanding perceptual decision-making requires linking sensory neural responses to behavioral choices. In two-choice tasks, activity-choice covariations are commonly quantified with a single measure of choice probability (CP), without characterizing their changes across stimulus levels. We provide theoretical conditions for stimulus dependencies of activity-choice covariations. Assuming a general decision-threshold model, which comprises both feedforward and feedback processing and allows for a stimulus-modulated neural population covariance, we analytically predict a very general and previously unreported stimulus dependence of CPs. We develop new tools, including refined analyses of CPs and generalized linear models with stimulus-choice interactions, which accurately assess the stimulus- or choice-driven signals of each neuron, characterizing stimulus-dependent patterns of choice-related signals. With these tools, we analyze CPs of macaque MT neurons during a motion discrimination task. Our analysis provides preliminary empirical evidence for the promise of studying stimulus dependencies of choice-related signals, encouraging further assessment in wider data sets.

Coding strategies in the otolith system differ for translational head motion vs. static orientation relative to gravity

The detection of gravito-inertial forces by the otolith system is essential for our sense of balance and accurate perception. To date, however, how this system encodes the self-motion stimuli that are experienced during everyday activities remains unknown. Here, we addressed this fundamental question directly by recording from single otolith afferents in monkeys during naturalistic translational self-motion and changes in static head orientation. Otolith afferents with higher intrinsic variability transmitted more information overall about translational self-motion than their regular counterparts, owing to stronger nonlinearities that enabled precise spike timing including phase locking. By contrast, more regular afferents better discriminated between different static head orientations relative to gravity. Using computational methods, we further demonstrated that coupled increases in intrinsic variability and sensitivity accounted for the observed functional differences between afferent classes. Together, our results indicate that irregular and regular otolith afferents use different strategies to encode naturalistic self-motion and static head orientation relative to gravity.

Vestibular processing during natural self-motion: implications for perception and action

How the brain computes accurate estimates of our self-motion relative to the world and our orientation relative to gravity in order to ensure accurate perception and motor control is a fundamental neuroscientific question. Recent experiments have revealed that the vestibular system encodes this information during everyday activities using pathway-specific neural representations. Furthermore, new findings have established that vestibular signals are selectively combined with extravestibular information at the earliest stages of central vestibular processing in a manner that depends on the current behavioural goal. These findings have important implications for our understanding of the brain mechanisms that ensure accurate perception and behaviour during everyday activities and for our understanding of disorders of vestibular processing.

Objective Estimation of Sensory Thresholds Based on Neurophysiological Parameters

Reliable determination of sensory thresholds is the holy grail of signal detection theory. However, there exists no assumption-independent gold standard for the estimation of thresholds based on neurophysiological parameters, although a reliable estimation method is crucial for both scientific investigations and clinical diagnosis. Whenever it is impossible to communicate with the subjects, as in studies with animals or neonates, thresholds have to be derived from neural recordings or by indirect behavioral tests. Whenever the threshold is estimated based on such measures, the standard approach until now is the subjective setting-either by eye or by statistical means-of the threshold to the value where at least a "clear" signal is detectable. These measures are highly subjective, strongly depend on the noise, and fluctuate due to the low signal-to-noise ratio near the threshold. Here we show a novel method to reliably estimate physiological thresholds based on neurophysiological parameters. Using surrogate data we demonstrate that fitting the responses to different stimulus intensities with a hard sigmoid function, in combination with subsampling, provides a robust threshold value as well as an accurate uncertainty estimate. This method has no systematic dependence on the noise and does not even require samples in the full dynamic range of the sensory system. We prove that this method is universally applicable to all types of sensory systems, ranging from somatosensory stimulus processing in the cortex to auditory processing in the brain stem.

Probing Sensory Readout via Combined Choice-Correlation Measures and Microstimulation Perturbation

It is controversial whether covariation between neuronal activity and perceptual choice (i.e., choice correlation) reflects the functional readout of sensory signals. Here, we combined choice-correlation measures and electrical microstimulation on a site-to-site basis in the medial superior temporal area (MST), middle temporal area (MT), and ventral intraparietal area (VIP) when macaques discriminated between motion directions in both fine and coarse tasks. Microstimulation generated comparable effects between tasks but heterogeneous effects across and within brain regions. Within the MST and MT, microstimulation significantly biased an animal's choice toward the sensory preference instead of choice-related signals of the stimulated units. This was particularly evident for sites with conflict preference of sensory and choice-related signals. In the VIP, microstimulation failed to produce significant effects in either task despite strong choice correlations presented in this area. Our results suggest that sensory readout may not be inferred from choice-related signals during perceptual decision-making tasks.

When uncertain, does human self-motion decision-making fully utilize complete information?

When forced to choose humans often feel uncertain. Investigations of human perceptual decision-making often employ signal detection theory, which assumes that even when uncertain all available information is fully utilized. However, other studies have suggested or assumed that, when uncertain, human subjects guess totally at random, ignoring available information. When uncertain, do humans simply guess totally at random? Or do humans fully utilize complete information? Or does behavior fall between these two extremes yielding "above chance" performance without fully utilizing complete information? While it is often assumed complete information is fully utilized, even when uncertain, to our knowledge this has never been experimentally confirmed. To answer this question, we combined numerical simulations, theoretical analyses, and human studies performed using a self-motion direction-recognition perceptual decision-making task (did I rotate left or right?). Subjects were instructed to make forced-choice binary (left/right) and trinary (left/right/uncertain) decisions when cued following each stimulus. Our results show that humans 1) do not guess at random when uncertain and 2) make binary and trinary decisions equally well. These findings show that humans fully utilize complete information when uncertain for our perceptual decision-making task. This helps unify signal detection theory and other models of forced-choice decision-making which allow for uncertain responses. NEW & NOTEWORTHY Humans make many perceptual decisions every day. But what if we are uncertain? While many studies assume that humans fully utilize complete information, other studies have suggested and/or assumed that when we're uncertain and forced to decide, information is not fully utilized. While humans tend to perform above chance when uncertain, no earlier study has tested whether available information is fully utilized. Our results show that humans make fully informed decisions even when uncertain.

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal "noise" correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks.

SIGNIFICANCE STATEMENT

Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain.

Dissociation of Choice Formation and Choice-Correlated Activity in Macaque Visual Cortex

Responses of individual task-relevant sensory neurons can predict monkeys' trial-by-trial choices in perceptual decision-making tasks. Choice-correlated activity has been interpreted as evidence that the responses of these neurons are causally linked to perceptual judgments. To further test this hypothesis, we studied responses of orientation-selective neurons in V1 and V2 while two macaque monkeys performed a fine orientation discrimination task. Although both animals exhibited a high level of neuronal and behavioral sensitivity, only one exhibited choice-correlated activity. Surprisingly, this correlation was negative: when a neuron fired more vigorously, the animal was less likely to choose the orientation preferred by that neuron. Moreover, choice-correlated activity emerged late in the trial, earlier in V2 than in V1, and was correlated with anticipatory signals. Together, these results suggest that choice-correlated activity in task-relevant sensory neurons can reflect postdecision modulatory signals.SIGNIFICANCE STATEMENT When observers perform a difficult sensory discrimination, repeated presentations of the same stimulus can elicit different perceptual judgments. This behavioral variability often correlates with variability in the activity of sensory neurons driven by the stimulus. Traditionally, this correlation has been interpreted as suggesting a causal link between the activity of sensory neurons and perceptual judgments. More recently, it has been argued that the correlation instead may originate in recurrent input from other brain areas involved in the interpretation of sensory signals. Here, we call both hypotheses into question. We show that choice-related activity in sensory neurons can be highly variable across observers and can reflect modulatory processes that are dissociated from perceptual decision-making.

Transformation of spatiotemporal dynamics in the macaque vestibular system from otolith afferents to cortex

Sensory signals undergo substantial recoding when neural activity is relayed from sensors through pre-thalamic and thalamic nuclei to cortex. To explore how temporal dynamics and directional tuning are sculpted in hierarchical vestibular circuits, we compared responses of macaque otolith afferents with neurons in the vestibular and cerebellar nuclei, as well as five cortical areas, to identical three-dimensional translational motion. We demonstrate a remarkable spatio-temporal transformation: otolith afferents carry spatially aligned cosine-tuned translational acceleration and jerk signals. In contrast, brainstem and cerebellar neurons exhibit non-linear, mixed selectivity for translational velocity, acceleration, jerk and position. Furthermore, these components often show dissimilar spatial tuning. Moderate further transformation of translation signals occurs in the cortex, such that similar spatio-temporal properties are found in multiple cortical areas. These results suggest that the first synapse represents a key processing element in vestibular pathways, robustly shaping how self-motion is represented in central vestibular circuits and cortical areas.

Self-motion evokes precise spike timing in the primate vestibular system

The accurate representation of self-motion requires the efficient processing of sensory input by the vestibular system. Conventional wisdom is that vestibular information is exclusively transmitted through changes in firing rate, yet under this assumption vestibular neurons display relatively poor detection and information transmission. Here, we carry out an analysis of the system's coding capabilities by recording neuronal responses to repeated presentations of naturalistic stimuli. We find that afferents with greater intrinsic variability reliably discriminate between different stimulus waveforms through differential patterns of precise (∼6 ms) spike timing, while those with minimal intrinsic variability do not. A simple mathematical model provides an explanation for this result. Postsynaptic central neurons also demonstrate precise spike timing, suggesting that higher brain areas also represent self-motion using temporally precise firing. These findings demonstrate that two distinct sensory channels represent vestibular information: one using rate coding and the other that takes advantage of precise spike timing.

Early vestibular pathways are thought to code sensory inputs regarding self-motion via changes in firing rate. Here, the authors record from both regular and irregular afferents in macaques, and find both irregular afferents and central neurons also represent self-motion via temporally precise spike timing.

Feedforward and feedback sources of choice probability in neural population responses

How the processing of signals carried by sensory neurons supports perceptual decisions is a long-standing question in neuroscience. The ability to record neuronal activity in awake animals while they perform psychophysical tasks near threshold has been a key advance in studying these questions. Trial-to-trial correlations between the activity of sensory neurons and the decisions reported by animals ('choice probabilities'), even when measured across repeated presentations of an identical stimulus provide insights into this problem. But understanding the sources of such co-variability between sensory neurons and behavior has proven more difficult than it initially appeared. Below, we discuss our current understanding of what gives rise to these correlations.

Origins of choice-related activity in mouse somatosensory cortex

During perceptual decisions about faint or ambiguous sensory stimuli, even identical stimuli can produce different choices. Spike trains from sensory cortex neurons can predict trial-to-trial variability in choice. Choice-related spiking is widely studied to link cortical activity to perception, but its origins remain unclear. Using imaging and electrophysiology, we found that mouse primary somatosensory cortex neurons showed robust choice-related activity during a tactile detection task. Spike trains from primary mechanoreceptive neurons did not predict choices about identical stimuli. Spike trains from thalamic relay neurons showed highly transient, weak choice-related activity. Intracellular recordings in cortex revealed a prolonged choice-related depolarization in most neurons that was not accounted for by feedforward thalamic input. Top-down axons projecting from secondary to primary somatosensory cortex signaled choice. An intracellular measure of stimulus sensitivity determined which neurons converted choice-related depolarization into spiking. Our results reveal how choice-related spiking emerges across neural circuits and within single neurons.