Multisensory causal inference is feature-specific, not object-based.

Multisensory integration depends on causal inference about the sensory signals. We tested whether implicit causal-inference judgements pertain to entire objects or focus on task-relevant object features. Participants in our study judged virtual visual, haptic and visual-haptic surfaces with respect to two features-slant and roughness-against an internal standard in a two-alternative forced-choice task. Modelling of participants' responses revealed that the degree to which their perceptual judgements were based on integrated visual-haptic information varied unsystematically across features. For example, a perceived mismatch between visual and haptic roughness would not deter the observer from integrating visual and haptic slant. These results indicate that participants based their perceptual judgements on a feature-specific selection of information, suggesting that multisensory causal inference proceeds not at the object level but at the level of single object features. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Feeling lucky? Prospective and retrospective cues for sensorimotor confidence.

On a daily basis, humans interact with the outside world using judgments of sensorimotor confidence, constantly evaluating our actions for success. We ask, what sensory and motor-execution cues are used in making these judgements and when are they available? Two sources of temporally distinct information are prospective cues, available prior to the action (e.g., knowledge of motor noise and past performance), and retrospective cues specific to the action itself (e.g., proprioceptive measurements). We investigated the use of these two cues in two tasks, a secondary motor-awareness task and a main task in which participants reached toward a visual target with an unseen hand and then made a continuous judgment of confidence about the success of the reach. Confidence was reported by setting the size of a circle centered on the reach-target location, where a larger circle reflects lower confidence. Points were awarded if the confidence circle enclosed the true endpoint, with fewer points returned for larger circles. This incentivized accurate reaches and attentive reporting to maximize the score. We compared three Bayesian-inference models of sensorimotor confidence based on either prospective cues, retrospective cues, or both sources of information to maximize expected gain (i.e., an ideal-performance model). Our findings primarily showed two distinct strategies: participants either performed as ideal observers, using both prospective and retrospective cues to make the confidence judgment, or relied solely on prospective information, ignoring retrospective cues. Thus, participants can make use of retrospective cues, evidenced by the behavior observed in our motor-awareness task, but these cues are not always included in the computation of sensorimotor confidence.

Identifying cortical areas that underlie the transformation from 2D retinal to 3D head-centric motion signals.

Accurate motion perception requires that the visual system integrate the 2D retinal motion signals received by the two eyes into a single representation of 3D motion. However, most experimental paradigms present the same stimulus to the two eyes, signaling motion limited to a 2D fronto-parallel plane. Such paradigms are unable to dissociate the representation of 3D head-centric motion signals (i.e., 3D object motion relative to the observer) from the associated 2D retinal motion signals. Here, we used stereoscopic displays to present separate motion signals to the two eyes and examined their representation in visual cortex using fMRI. Specifically, we presented random-dot motion stimuli that specified various 3D head-centric motion directions. We also presented control stimuli, which matched the motion energy of the retinal signals, but were inconsistent with any 3D motion direction. We decoded motion direction from BOLD activity using a probabilistic decoding algorithm. We found that 3D motion direction signals can be reliably decoded in three major clusters in the human visual system. Critically, in early visual cortex (V1-V3), we found no significant difference in decoding performance between stimuli specifying 3D motion directions and the control stimuli, suggesting that these areas represent the 2D retinal motion signals, rather than 3D head-centric motion itself. In voxels in and surrounding hMT and IPS0 however, decoding performance was consistently superior for stimuli that specified 3D motion directions compared to control stimuli. Our results reveal the parts of the visual processing hierarchy that are critical for the transformation of retinal into 3D head-centric motion signals and suggest a role for IPS0 in their representation, in addition to its sensitivity to 3D object structure and static depth.

Repeated exposure to either consistently spatiotemporally congruent or consistently incongruent audiovisual stimuli modulates the audiovisual common-cause prior.

To estimate an environmental property such as object location from multiple sensory signals, the brain must infer their causal relationship. Only information originating from the same source should be integrated. This inference relies on the characteristics of the measurements, the information the sensory modalities provide on a given trial, as well as on a cross-modal common-cause prior: accumulated knowledge about the probability that cross-modal measurements originate from the same source. We examined the plasticity of this cross-modal common-cause prior. In a learning phase, participants were exposed to a series of audiovisual stimuli that were either consistently spatiotemporally congruent or consistently incongruent; participants' audiovisual spatial integration was measured before and after this exposure. We fitted several Bayesian causal-inference models to the data; the models differed in the plasticity of the common-source prior. Model comparison revealed that, for the majority of the participants, the common-cause prior changed during the learning phase. Our findings reveal that short periods of exposure to audiovisual stimuli with a consistent causal relationship can modify the common-cause prior. In accordance with previous studies, both exposure conditions could either strengthen or weaken the common-cause prior at the participant level. Simulations imply that the direction of the prior-update might be mediated by the degree of sensory noise, the variability of the measurements of the same signal across trials, during the learning phase.

Suprathreshold perceptual decisions constrain models of confidence.

Perceptual confidence is an important internal signal about the certainty of our decisions and there is a substantial debate on how it is computed. We highlight three confidence metric types from the literature: observers either use 1) the full probability distribution to compute probability correct (Probability metrics), 2) point estimates from the perceptual decision process to estimate uncertainty (Evidence-Strength metrics), or 3) heuristic confidence from stimulus-based cues to uncertainty (Heuristic metrics). These metrics are rarely tested against one another, so we examined models of all three types on a suprathreshold spatial discrimination task. Observers were shown a cloud of dots sampled from a dot generating distribution and judged if the mean of the distribution was left or right of centre. In addition to varying the horizontal position of the mean, there were two sensory uncertainty manipulations: the number of dots sampled and the spread of the generating distribution. After every two perceptual decisions, observers made a confidence forced-choice judgement whether they were more confident in the first or second decision. Model results showed that the majority of observers were best-fit by either: 1) the Heuristic model, which used dot cloud position, spread, and number of dots as cues; or 2) an Evidence-Strength model, which computed the distance between the sensory measurement and discrimination criterion, scaled according to sensory uncertainty. An accidental repetition of some sessions also allowed for the measurement of confidence agreement for identical pairs of stimuli. This N-pass analysis revealed that human observers were more consistent than their best-fitting model would predict, indicating there are still aspects of confidence that are not captured by our modelling. As such, we propose confidence agreement as a useful technique for computational studies of confidence. Taken together, these findings highlight the idiosyncratic nature of confidence computations for complex decision contexts and the need to consider different potential metrics and transformations in the confidence computation.

Causal inference regulates audiovisual spatial recalibration via its influence on audiovisual perception.

To obtain a coherent perception of the world, our senses need to be in alignment. When we encounter misaligned cues from two sensory modalities, the brain must infer which cue is faulty and recalibrate the corresponding sense. We examined whether and how the brain uses cue reliability to identify the miscalibrated sense by measuring the audiovisual ventriloquism aftereffect for stimuli of varying visual reliability. To adjust for modality-specific biases, visual stimulus locations were chosen based on perceived alignment with auditory stimulus locations for each participant. During an audiovisual recalibration phase, participants were presented with bimodal stimuli with a fixed perceptual spatial discrepancy; they localized one modality, cued after stimulus presentation. Unimodal auditory and visual localization was measured before and after the audiovisual recalibration phase. We compared participants' behavior to the predictions of three models of recalibration: (a) Reliability-based: each modality is recalibrated based on its relative reliability-less reliable cues are recalibrated more; (b) Fixed-ratio: the degree of recalibration for each modality is fixed; (c) Causal-inference: recalibration is directly determined by the discrepancy between a cue and its estimate, which in turn depends on the reliability of both cues, and inference about how likely the two cues derive from a common source. Vision was hardly recalibrated by audition. Auditory recalibration by vision changed idiosyncratically as visual reliability decreased: the extent of auditory recalibration either decreased monotonically, peaked at medium visual reliability, or increased monotonically. The latter two patterns cannot be explained by either the reliability-based or fixed-ratio models. Only the causal-inference model of recalibration captures the idiosyncratic influences of cue reliability on recalibration. We conclude that cue reliability, causal inference, and modality-specific biases guide cross-modal recalibration indirectly by determining the perception of audiovisual stimuli.

Performance monitoring for sensorimotor confidence: A visuomotor tracking study.

To best interact with the external world, humans are often required to consider the quality of their actions. Sometimes the environment furnishes rewards or punishments to signal action efficacy. However, when such feedback is absent or only partial, we must rely on internally generated signals to evaluate our performance (i.e., metacognition). Yet, very little is known about how humans form such judgements of sensorimotor confidence. Do they monitor their actual performance or do they rely on cues to sensorimotor uncertainty? We investigated sensorimotor metacognition in two visuomotor tracking experiments, where participants followed an unpredictably moving dot cloud with a mouse cursor as it followed a random horizontal trajectory. Their goal was to infer the underlying target generating the dots, track it for several seconds, and then report their confidence in their tracking as better or worse than their average. In Experiment 1, we manipulated task difficulty with two methods: varying the size of the dot cloud and varying the stability of the target's velocity. In Experiment 2, the stimulus statistics were fixed and duration of the stimulus presentation was varied. We found similar levels of metacognitive sensitivity in all experiments, which was evidence against the cue-based strategy. The temporal analysis of metacognitive sensitivity revealed a recency effect, where error later in the trial had a greater influence on the sensorimotor confidence, consistent with a performance-monitoring strategy. From these results, we conclude that humans predominantly monitored their tracking performance, albeit inefficiently, to build a sense of sensorimotor confidence.

Priors and payoffs in confidence judgments.

Priors and payoffs are known to affect perceptual decision-making, but little is understood about how they influence confidence judgments. For optimal perceptual decision-making, both priors and payoffs should be considered when selecting a response. However, for confidence to reflect the probability of being correct in a perceptual decision, priors should affect confidence but payoffs should not. To experimentally test whether human observers follow this normative behavior for natural confidence judgments, we conducted an orientation-discrimination task with varied priors and payoffs that probed both perceptual and metacognitive decision-making. The placement of discrimination and confidence criteria were examined according to several plausible Signal Detection Theory models. In the normative model, observers use the optimal discrimination criterion (i.e., the criterion that maximizes expected gain) and confidence criteria that shift with the discrimination criterion that maximizes accuracy (i.e., are not affected by payoffs). No observer was consistent with this model, with the majority exhibiting non-normative confidence behavior. One subset of observers ignored both priors and payoffs for confidence, always fixing the confidence criteria around the neutral discrimination criterion. The other group of observers incorrectly incorporated payoffs into their confidence by always shifting their confidence criteria with the same gains-maximizing criterion used for discrimination. Such metacognitive mistakes could have negative consequences outside the laboratory setting, particularly when priors or payoffs are not matched for all the possible decision alternatives.

Modality-specific attention attenuates visual-tactile integration and recalibration effects by reducing prior expectations of a common source for vision and touch.

At any moment in time, streams of information reach the brain through the different senses. Given this wealth of noisy information, it is essential that we select information of relevance - a function fulfilled by attention - and infer its causal structure to eventually take advantage of redundancies across the senses. Yet, the role of selective attention during causal inference in cross-modal perception is unknown. We tested experimentally whether the distribution of attention across vision and touch enhances cross-modal spatial integration (visual-tactile ventriloquism effect, Expt. 1) and recalibration (visual-tactile ventriloquism aftereffect, Expt. 2) compared to modality-specific attention, and then used causal-inference modeling to isolate the mechanisms behind the attentional modulation. In both experiments, we found stronger effects of vision on touch under distributed than under modality-specific attention. Model comparison confirmed that participants used Bayes-optimal causal inference to localize visual and tactile stimuli presented as part of a visual-tactile stimulus pair, whereas simultaneously collected unity judgments - indicating whether the visual-tactile pair was perceived as spatially-aligned - relied on a sub-optimal heuristic. The best-fitting model revealed that attention modulated sensory and cognitive components of causal inference. First, distributed attention led to an increase of sensory noise compared to selective attention toward one modality. Second, attending to both modalities strengthened the stimulus-independent expectation that the two signals belong together, the prior probability of a common source for vision and touch. Yet, only the increase in the expectation of vision and touch sharing a common source was able to explain the observed enhancement of visual-tactile integration and recalibration effects with distributed attention. In contrast, the change in sensory noise explained only a fraction of the observed enhancements, as its consequences vary with the overall level of noise and stimulus congruency. Increased sensory noise leads to enhanced integration effects for visual-tactile pairs with a large spatial discrepancy, but reduced integration effects for stimuli with a small or no cross-modal discrepancy. In sum, our study indicates a weak a priori association between visual and tactile spatial signals that can be strengthened by distributing attention across both modalities.

Contingent adaptation in masking and surround suppression.

Adaptation is the process that changes a neuron's response based on recent inputs. In the traditional model, a neuron's state of adaptation depends on the recent input to that neuron alone, whereas in a recently introduced model (Hebbian normalization), adaptation depends on the structure of neural correlated firing. In particular, increased response products between pairs of neurons leads to increased mutual suppression. We test a psychophysical prediction of this model: adaptation should depend on 2nd-order statistics of input stimuli. That is, if two stimuli excite two distinct sub-populations of neurons, then presenting those stimuli simultaneously during adaptation should strengthen mutual suppression between those subpopulations. We confirm this prediction in two experiments. In the first, pairing two gratings synchronously during adaptation (i.e., a plaid) rather than asynchronously (interleaving the two gratings in time) leads to increased effectiveness of one pattern for masking the other. In the second, pairing the gratings in a center-surround configuration results in reduced apparent contrast for the central grating when paired with the same surround (as compared with a condition in which the central grating appears with a different surround at test than during adaptation). These results are consistent with the prediction that an increase in response covariance leads to greater mutual suppression between neurons. This effect is detectable both at threshold (masking) and well above threshold (apparent contrast).

Human online adaptation to changes in prior probability.

Optimal sensory decision-making requires the combination of uncertain sensory signals with prior expectations. The effect of prior probability is often described as a shift in the decision criterion. Can observers track sudden changes in probability? To answer this question, we used a change-point detection paradigm that is frequently used to examine behavior in changing environments. In a pair of orientation-categorization tasks, we investigated the effects of changing probabilities on decision-making. In both tasks, category probability was updated using a sample-and-hold procedure: probability was held constant for a period of time before jumping to another probability state that was randomly selected from a predetermined set of probability states. We developed an ideal Bayesian change-point detection model in which the observer marginalizes over both the current run length (i.e., time since last change) and the current category probability. We compared this model to various alternative models that correspond to different strategies-from approximately Bayesian to simple heuristics-that the observers may have adopted to update their beliefs about probabilities. While a number of models provided decent fits to the data, model comparison favored a model in which probability is estimated following an exponential averaging model with a bias towards equal priors, consistent with a conservative bias, and a flexible variant of the Bayesian change-point detection model with incorrect beliefs. We interpret the former as a simpler, more biologically plausible explanation suggesting that the mechanism underlying change of decision criterion is a combination of on-line estimation of prior probability and a stable, long-term equal-probability prior, thus operating at two very different timescales.

Face perception: A brief journey through recent discoveries and current directions.

Faces are a rich source of information about the people around us. Identity, state of mind, emotions, intentions, age, gender, ethnic background, attractiveness and a host of other attributes about an individual can be gleaned from a face. When face perception fails, dramatic psycho-social consequences can follow at the individual level, as in the case of prosopagnosic parents who are unable to recognize their children at school pick-up. At the species level, social interaction patterns are shaped by human face perception abilities. The computational feat of recognizing faces and facial attributes, and the challenges overcome by the human brain to achieve this feat, have fascinated generations of vision researchers. In this paper, we present a brief overview of some of the milestones of discovery as well as outline a selected set of current directions and open questions on this topic.

Did I do that? Detecting a perturbation to visual feedback in a reaching task.

The motor system executes actions in a highly stereotyped manner despite the high number of degrees of freedom available. Studies of motor adaptation leverage this fact by disrupting, or perturbing, visual feedback to measure how the motor system compensates. To elicit detectable effects, perturbations are often large compared to trial-to-trial reach endpoint variability. However, awareness of large perturbations can elicit qualitatively different compensation processes than unnoticeable ones can. The current experiment measures the perturbation detection threshold, and investigates how humans combine proprioception and vision to decide whether displayed reach endpoint errors are self-generated only, or are due to experimenter-imposed perturbation. We scaled or rotated the position of the visual feedback of center-out reaches to targets and asked subjects to indicate whether visual feedback was perturbed. Subjects detected perturbations when they were at least 1.5 times the standard deviation of trial-to-trial endpoint variability. In contrast to previous studies, subjects suboptimally combined vision and proprioception. Instead of using proprioceptive input, they responded based on the final (possibly perturbed) visual feedback. These results inform methodology in motor system experimentation, and more broadly highlight the ability to attribute errors to one's own motor output and combine visual and proprioceptive feedback to make decisions.

Naturally glossy: Gloss perception, illumination statistics, and tone mapping.

Recognizing materials and understanding their properties is very useful-perhaps critical-in daily life as we encounter objects and plan our interactions with them. Visually derived estimates of material properties guide where and with what force we grasp an object. However, the estimation of material properties, such as glossiness, is a classic ill-posed problem. Image cues that we rely on to estimate gloss are also affected by shape, illumination and, in visual displays, tone-mapping. Here, we focus on the latter two. We define some commonalities present in the structure of natural illumination, and determine whether manipulation of these natural "signatures" impedes gloss constancy. We manipulate the illumination field to violate statistical regularities of natural illumination, such that light comes from below, or the luminance distribution is no longer skewed. These manipulations result in errors in perceived gloss. Similarly, tone mapping has a dramatic effect on perceived gloss. However, when objects are viewed against an informative (rather than plain gray) background that reflects these manipulations, there are some improvements to gloss constancy: in particular, observers are far less susceptible to the effects of tone mapping when judging gloss. We suggest that observers are sensitive to some very simple statistics of the environment when judging gloss.

Temporal Contingencies Determine Whether Adaptation Strengthens or Weakens Normalization.

A fundamental and nearly ubiquitous feature of sensory encoding is that neuronal responses are strongly influenced by recent experience, or adaptation. Theoretical and computational studies have proposed that many adaptation effects may result in part from changes in the strength of normalization signals. Normalization is a "canonical" computation in which a neuron's response is modulated (normalized) by the pooled activity of other neurons. Here, we test whether adaptation can alter the strength of cross-orientation suppression, or masking, a paradigmatic form of normalization evident in primary visual cortex (V1). We made extracellular recordings of V1 neurons in anesthetized male macaques and measured responses to plaid stimuli composed of two overlapping, orthogonal gratings before and after prolonged exposure to two distinct adapters. The first adapter was a plaid consisting of orthogonal gratings and led to stronger masking. The second adapter presented the same orthogonal gratings in an interleaved manner and led to weaker masking. The strength of adaptation's effects on masking depended on the orientation of the test stimuli relative to the orientation of the adapters, but was independent of neuronal orientation preference. Changes in masking could not be explained by altered neuronal responsivity. Our results suggest that normalization signals can be strengthened or weakened by adaptation depending on the temporal contingencies of the adapting stimuli. Our findings reveal an interplay between two widespread computations in cortical circuits, adaptation and normalization, that enables flexible adjustments to the structure of the environment, including the temporal relationships among sensory stimuli.SIGNIFICANCE STATEMENT Two fundamental features of sensory responses are that they are influenced by adaptation and that they are modulated by the activity of other nearby neurons via normalization. Our findings reveal a strong interaction between these two aspects of cortical computation. Specifically, we show that cross-orientation masking, a form of normalization, can be strengthened or weakened by adaptation depending on the temporal contingencies between sensory inputs. Our findings support theoretical proposals that some adaptation effects may involve altered normalization and offer a network-based explanation for how cortex adjusts to current sensory demands.

A spatial frequency spectral peakedness model predicts discrimination performance of regularity in dot patterns.

Subjective assessments of spatial regularity are common in everyday life and also in science, for example in developmental biology. It has recently been shown that regularity is an adaptable visual dimension. It was proposed that regularity is coded via the peakedness of the distribution of neural responses across receptive field size. Here, we test this proposal for jittered square lattices of dots. We examine whether discriminability correlates with a simple peakedness measure across different presentation conditions (dot number, size, and average spacing). Using a filter-rectify-filter model, we determined responses across scale. Consistently, two peaks are present: a lower frequency peak corresponding to the dot spacing of the regular pattern and a higher frequency peak corresponding to the pattern element (dot). We define the "peakedness" of a particular presentation condition as the relative heights of these two peaks for a perfectly regular pattern constructed using the corresponding dot size, number and spacing. We conducted two psychophysical experiments in which observers judged relative regularity in a 2-alternative forced-choice task. In the first experiment we used a single reference pattern of intermediate regularity and, in the second, Thurstonian scaling of patterns covering the entire range of regularity. In both experiments discriminability was highly correlated with peakedness for a wide range of presentation conditions. This supports the hypothesis that regularity is coded via peakedness of the distribution of responses across scale.

Correction: Temporal causal inference with stochastic audiovisual sequences.

[This corrects the article DOI: 10.1371/journal.pone.0183776.].

Temporal causal inference with stochastic audiovisual sequences.

Integration of sensory information across multiple senses is most likely to occur when signals are spatiotemporally coupled. Yet, recent research on audiovisual rate discrimination indicates that random sequences of light flashes and auditory clicks are integrated optimally regardless of temporal correlation. This may be due to 1) temporal averaging rendering temporal cues less effective; 2) difficulty extracting causal-inference cues from rapidly presented stimuli; or 3) task demands prompting integration without concern for the spatiotemporal relationship between the signals. We conducted a rate-discrimination task (Exp 1), using slower, more random sequences than previous studies, and a separate causal-judgement task (Exp 2). Unisensory and multisensory rate-discrimination thresholds were measured in Exp 1 to assess the effects of temporal correlation and spatial congruence on integration. The performance of most subjects was indistinguishable from optimal for spatiotemporally coupled stimuli, and generally sub-optimal in other conditions, suggesting observers used a multisensory mechanism that is sensitive to both temporal and spatial causal-inference cues. In Exp 2, subjects reported whether temporally uncorrelated (but spatially co-located) sequences were perceived as sharing a common source. A unified percept was affected by click-flash pattern similarity and the maximum temporal offset between individual clicks and flashes, but not on the proportion of synchronous click-flash pairs. A simulation analysis revealed that the stimulus-generation algorithms of previous studies is likely responsible for the observed integration of temporally independent sequences. By combining results from Exps 1 and 2, we found better rate-discrimination performance for sequences that are more likely to be integrated than those that are not. Our results support the principle that multisensory stimuli are optimally integrated when spatiotemporally coupled, and provide insight into the temporal features used for coupling in causal inference.