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.

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.

The effect of velocity on auditory representational momentum.

"Representational Momentum" (RM) is a mislocalization of the endpoint of a moving target in the direction of motion. In vision, RM has been shown to increase with target velocity. In audition, however, the effect of target velocity is unclear. Using a perceptual paradigm with moving broadband noise targets in Virtual Auditory Space resulted in a linear increase in RM from 0.9° to 2.3° for an increase in target velocity from 25°/s to 100°/s. Accounting for the effect of eye position also reduced variance. These results suggest that RM may be the result of similar underlying mechanisms in both modalities.

Reward Sensitivity and Noise Contribute to Negative Affective Bias: A Learning Signal Detection Theory Approach in Decision-Making.

In patients with mood disorders, negative affective biases - systematically prioritising and interpreting information negatively - are common. A translational cognitive task testing this bias has shown that depressed patients have a reduced preference for a high reward under ambiguous decision-making conditions. The precise mechanisms underscoring this bias are, however, not yet understood. We therefore developed a set of measures to probe the underlying source of the behavioural bias by testing its relationship to a participant's reward sensitivity, value sensitivity and reward learning rate. One-hundred-forty-eight participants completed three online behavioural tasks: the original ambiguous-cue decision-making task probing negative affective bias, a probabilistic reward learning task probing reward sensitivity and reward learning rate, and a gambling task probing value sensitivity. We modelled the learning task through a dynamic signal detection theory model and the gambling task through an expectation-maximisation prospect theory model. Reward sensitivity from the probabilistic reward task (ß = 0.131, p = 0.024) and setting noise from the probabilistic reward task (ß = -0.187, p = 0.028) both predicted the affective bias score in a logistic regression. Increased negative affective bias, at least on this specific task, may therefore be driven in part by a combination of reduced sensitivity to rewards and more variable responses.

Consensus Goals in the Field of Visual Metacognition.

Despite the tangible progress in psychological and cognitive sciences over the last several years, these disciplines still trail other more mature sciences in identifying the most important questions that need to be solved. Reaching such consensus could lead to greater synergy across different laboratories, faster progress, and increased focus on solving important problems rather than pursuing isolated, niche efforts. Here, 26 researchers from the field of visual metacognition reached consensus on four long-term and two medium-term common goals. We describe the process that we followed, the goals themselves, and our plans for accomplishing these goals. If this effort proves successful within the next few years, such consensus building around common goals could be adopted more widely in psychological science.

Affective Bias Through the Lens of Signal Detection Theory.

Affective bias - a propensity to focus on negative information at the expense of positive information - is a core feature of many mental health problems. However, it can be caused by wide range of possible underlying cognitive mechanisms. Here we illustrate this by focusing on one particular behavioural signature of affective bias - increased tendency of anxious/depressed individuals to predict lower rewards - in the context of the Signal Detection Theory (SDT) modelling framework. Specifically, we show how to apply this framework to measure affective bias and compare it to the behaviour of an optimal observer. We also show how to extend the framework to make predictions about bias when the individual holds incorrect assumptions about the decision context. Building on this theoretical foundation, we propose five experiments to test five hypothetical sources of this affective bias: beliefs about prior probabilities, beliefs about performance, subjective value of reward, learning differences, and need for accuracy differences. We argue that greater precision about the mechanisms driving affective bias may eventually enable us to better understand the mechanisms underlying mood and anxiety disorders.

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.

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.

Sensitivity to Auditory Velocity Contrast.

A natural auditory scene often contains sound moving at varying velocities. Using a velocity contrast paradigm, we compared sensitivity to velocity changes between continuous and discontinuous trajectories. Subjects compared the velocities of two stimulus intervals that moved along a single trajectory, with and without a 1 second inter stimulus interval (ISI). We found thresholds were threefold larger for velocity increases in the instantaneous velocity change condition, as compared to instantaneous velocity decreases or thresholds for the delayed velocity transition condition. This result cannot be explained by the current static "snapshot" model of auditory motion perception and suggest a continuous process where the percept of velocity is influenced by previous history of stimulation.

No attentional capture from invisible flicker.

We tested whether fast flicker can capture attention using eight flicker frequencies from 20-96 Hz, including several too high to be perceived (>50 Hz). Using a 480 Hz visual display rate, we presented smoothly sampled sinusoidal temporal modulations at: 20, 30, 40, 48, 60, 69, 80, and 96 Hz. We first established flicker detection rates for each frequency. Performance was at or near ceiling until 48 Hz and dropped sharply to chance level at 60 Hz and above. We then presented the same flickering stimuli as pre-cues in a visual search task containing five elements. Flicker location varied randomly and was therefore congruent with target location on 20% of trials. Comparing congruent and incongruent trials revealed a very strong congruency effect (faster search for cued targets) for all detectable frequencies (20-48 Hz) but no effect for faster flicker rates that were detected at chance. This pattern of results (obtained with brief flicker cues: 58 ms) was replicated for long flicker cues (1000 ms) intended to allow for entrainment to the flicker frequency. These results indicate that only visible flicker serves as an exogenous attentional cue and that flicker rates too high to be perceived are completely ineffective.