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Psychological and neuroscientific research over the past two decades has shown that the Bayesian causal inference (BCI) is a potential unifying theory that can account for a wide range of perceptual and sensorimotor processes in humans. Therefore, we introduce the BCI Toolbox, a statistical and analytical tool in Python, enabling researchers to conveniently perform quantitative modeling and analysis of behavioral data. Additionally, we describe the algorithm of the BCI model and test its stability and reliability via parameter recovery. The present BCI toolbox offers a robust platform for BCI model implementation as well as a hands-on tool for learning and understanding the model, facilitating its widespread use and enabling researchers to delve into the data to uncover underlying cognitive mechanisms., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Zhu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The now-classic goal-gradient hypothesis posits that organisms increase effort expenditure as a function of their proximity to a goal. Despite nearly a century having passed since its original formulation, goal-gradient-like behavior in human cognitive performance remains poorly understood: Are we more willing to engage in costly cognitive processing when we are near, versus far, from a goal state? Moreover, the computational mechanisms underpinning these potential goal-gradient effects-for example, whether goal proximity affects fidelity of stimulus encoding, response caution, or other identifiable mechanisms governing speed and accuracy-are unclear. Here, in two experiments, we examine the effect of goal proximity, operationalized as progress toward the completion of a rewarded task block, upon task performance in an attentionally demanding oddball task. Supporting the goal-gradient hypothesis, we found that participants responded more quickly, but not less accurately, when rewards were proximal than when they were distal. Critically, this effect was only observed when participants were given information about goal proximity. Using hierarchical drift diffusion modeling, we found that these apparent goal-gradient performance effects were best explained by a collapsing bound model, in which proximity to a goal reduced response caution and increased information processing. Taken together, these results suggest that goal gradients could help explain the oft-observed fluctuations in engagement of cognitively effortful processing, extending the scope of the goal-gradient hypothesis to the domain of cognitive tasks. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Efficient decision-making requires accounting for sources of uncertainty (noise, or variability). Many studies have shown how the nervous system is able to account for perceptual uncertainty (noise, variability) that arises from limitations in its own abilities to encode perceptual stimuli. However, many other sources of uncertainty exist, reflecting for example variability in the behaviour of other agents or physical processes. Here we review previous studies on decision making under uncertainty as a function of the different types of uncertainty that the nervous system encounters, showing that noise that is intrinsic to the perceptual system can often be accounted for near-optimally (i.e. not statistically different from optimally), whereas accounting for other types of uncertainty can be much more challenging. As an example, we present a study in which participants made decisions about multisensory stimuli with both intrinsic (perceptual) and extrinsic (environmental) uncertainty and show that the nervous system accounts for these differently when making decisions: they account for internal uncertainty but under-account for external. Human perceptual systems may be well equipped to account for intrinsic (perceptual) uncertainty because, in principle, they have access to this. Accounting for external uncertainty is more challenging because this uncertainty must be learned. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Saccadic eye movements are preceded by profound changes in visual perception. These changes have been linked to the phenomenon of 'forward remapping', in which cells begin to respond to stimuli that appear in their post-saccadic receptive field before the eye has moved. Few studies have examined the perceptual consequences of remapping of areas of impaired sensory acuity, such as the blindspot. Understanding the perceptual consequences of remapping of scotomas may produce important insights into why some neurovisual deficits, such as hemianopia are so intractable for rehabilitation. The current study took advantage of a naturally occurring scotoma in healthy participants (the blindspot) to examine pre-saccadic perception at the upcoming location of the blindspot. Participants viewed stimuli monocularly and were required to make stimulus-driven vertical eye-movements. At a variable latency between the onset of saccade target (ST) and saccade execution a discrimination target (DT) was presented at one of 4 possible locations; within the blindspot, contralateral to the blindspot, in post-saccadic location of the blindspot and contralateral to the post-saccadic location of the blindspot. There was a significant perceptual impairment at the post-saccadic location of the blindspot relative to the contralateral post-saccadic location of the blindspot and the post-saccadic location of the blindspot in a no-saccade control condition. These data are consistent with the idea that the visual system includes a representation of the blindspot which is remapped prior to saccade onset., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Smith et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

When the illumination falling on a surface change, so does the reflected light. Despite this, adult observers are good at perceiving surfaces as relatively unchanging-an ability termed colour constancy. Very few studies have investigated colour constancy in infants, and even fewer in children. Here we asked whether there is a difference in colour constancy between children and adults; what the developmental trajectory is between six and 11 years; and whether the pattern of constancy across illuminations and reflectances differs between adults and children. To this end, we developed a novel, child-friendly computer-based object selection task. In this, observers saw a dragon's favourite sweet under a neutral illumination and picked the matching sweet from an array of eight seen under a different illumination (blue, yellow, red, or green). This set contained a reflectance match (colour constant; perfect performance) and a tristimulus match (colour inconstant). We ran two experiments, with two-dimensional scenes in one and three-dimensional renderings in the other. Twenty-six adults and 33 children took part in the first experiment; 26 adults and 40 children took part in the second. Children performed better than adults on this task, and their performance decreased with age in both experiments. We found differences across illuminations and sweets, but a similar pattern across both age groups. This unexpected finding might reflect a real decrease in colour constancy from childhood to adulthood, explained by developmental changes in the perceptual and cognitive mechanisms underpinning colour constancy, or differences in task strategies between children and adults. HIGHLIGHTS: Six- to 11-year-old children demonstrated better performance than adults on a colour constancy object selection task. Performance decreased with age over childhood. These findings may indicate development of cognitive strategies used to overcome automatic colour constancy mechanisms., (© 2022 The Authors. Developmental Science published by John Wiley & Sons Ltd.)

Reliability-weighted averaging of multiple perceptual estimates (or cues) can improve precision. Research suggests that newly learned statistical associations can be rapidly integrated in this way for efficient decision-making. Yet, it remains unclear if the integration of newly learned statistics into decision-making can directly influence perception, rather than taking place only at the decision stage. In two experiments, we implicitly taught observers novel associations between shape and color. Observers made color matches by adjusting the color of an oval to match a simultaneously presented reference. As the color of the oval changed across trials, so did its shape according to a novel mapping of axis ratio to color. Observers showed signatures of reliability-weighted averaging-a precision improvement in both experiments and reweighting of the newly learned shape cue with changes in uncertainty in Experiment 2. To ask whether this was accompanied by perceptual effects, Experiment 1 tested for forced fusion by measuring color discrimination thresholds with and without incongruent novel cues. Experiment 2 tested for a memory color effect, observers adjusting the color of ovals with different axis ratios until they appeared gray. There was no evidence for forced fusion and the opposite of a memory color effect. Overall, our results suggest that the ability to quickly learn novel cues and integrate them with familiar cues is not immediately (within the short duration of our experiments and in the domain of color and shape) accompanied by common perceptual effects.

Vigor reflects how motivated people are to respond to stimuli. We previously showed that, on average, humans are more vigorous when a higher rate of reward is available, and that this relationship is modulated by the dopamine precursor levodopa. Dopamine signaling and probabilistic reward learning deteriorate across the adult life span, and thus, the relationship between vigor and reward may also change in aging. We tested this assertion and assessed whether it correlates with D1 dopamine receptor availability, measured using Positron Emission Tomography. We registered response times of 30 older and 30 younger participants during an oddball discrimination task where rewards varied systematically between trials. The average reward rate had a similar impact on vigor in both age groups. There was a weak positive association between ventral striatal dopamine receptor availability and the effect of average reward rate on response time. Overall, the effect of reward on response vigor was similar in younger and older adults, and weakly correlated with dopamine D1 receptor availability., Competing Interests: Declaration of Competing Interest None., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Mature perceptual systems can learn new arbitrary sensory signals (novel cues) to properties of the environment, but little is known about the extent to which novel cues are integrated into normal perception. In normal perception, multiple uncertain familiar cues are combined, often near-optimally (reliability-weighted averaging), to increase perceptual precision. We trained observers to use abstract novel cues to estimate horizontal locations of hidden objects on a monitor. In experiment 1, 4 groups of observers each learned to use a different novel cue. All groups benefited from a suboptimal but significant gain in precision using novel and familiar cues together after short-term training (3 ∼1.5 hr sessions), extending previous reports of novel-familiar cue combination. In experiment 2, we tested whether 2 novel cues may also be combined with each other. One pair of novel cues could be combined to improve precision but the other could not, at least not after 3 sessions of repeated training. Overall, our results provide extensive evidence that novel cues can be learned and combined with familiar cues to enhance perception, but mixed evidence for whether perceptual and decision-making systems can extend this ability to the combination of multiple novel cues with only short-term training. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Understanding of the brain and the principles governing neural processing requires theories that are parsimonious, can account for a diverse set of phenomena, and can make testable predictions. Here, we review the theory of Bayesian causal inference, which has been tested, refined, and extended in a variety of tasks in humans and other primates by several research groups. Bayesian causal inference is normative and has explained human behavior in a vast number of tasks including unisensory and multisensory perceptual tasks, sensorimotor, and motor tasks, and has accounted for counter-intuitive findings. The theory has made novel predictions that have been tested and confirmed empirically, and recent studies have started to map its algorithms and neural implementation in the human brain. The parsimony, the diversity of the phenomena that the theory has explained, and its illuminating brain function at all three of Marr's levels of analysis make Bayesian causal inference a strong neuroscience theory. This also highlights the importance of collaborative and multi-disciplinary research for the development of new theories in neuroscience., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Observers in perceptual tasks are often reported to combine multiple sensory cues in a weighted average that improves precision-in some studies, approaching statistically optimal (Bayesian) weighting, but in others departing from optimality, or not benefitting from combined cues at all. To correctly conclude which combination rules observers use, it is crucial to have accurate measures of their sensory precision and cue weighting. Here, we present a new approach for accurately recovering these parameters in perceptual tasks with continuous responses. Continuous responses have many advantages, but are susceptible to a central tendency bias, where responses are biased towards the central stimulus value. We show that such biases lead to inaccuracies in estimating both precision gains and cue weightings, two key measures used to assess sensory cue combination. We introduce a method that estimates sensory precision by regressing continuous responses on targets and dividing the variance of the residuals by the squared slope of the regression line, "correcting-out" the error introduced by the central bias and increasing statistical power. We also suggest a complementary analysis that recovers the sensory cue weights. Using both simulations and empirical data, we show that the proposed methods can accurately estimate sensory precision and cue weightings in the presence of central tendency biases. We conclude that central tendency biases should be (and can easily be) accounted for to consistently capture Bayesian cue combination in continuous response data., (© 2021. The Author(s).)

Human observers recognize the faces of people they know efficiently and without apparent effort. Consequently, recognizing a familiar face is often assumed to be an automatic process beyond voluntary control. However, there are circumstances in which a person might seek to hide their recognition of a particular face. The present study therefore used event-related potentials (ERPs) and a classifier based on logistic regression to determine if it is possible to detect whether a viewer is familiar with a particular face, regardless of whether the participant is willing to acknowledge it or not. In three experiments, participants were presented with highly variable "ambient" images of personally familiar and unfamiliar faces, while performing an incidental butterfly detection task (Experiment 1), an explicit familiarity judgment task (Experiment 2), and a concealed familiarity task in which they were asked to deny familiarity with one truly known facial identity while acknowledging familiarity with a second known identity (Experiment 3). In all three experiments, we observed substantially more negative ERP amplitudes at occipito-temporal electrodes for familiar relative to unfamiliar faces starting approximately 200 ms after stimulus onset. Both the earlier N250 familiarity effect, reflecting visual recognition of a known face, and the later sustained familiarity effect, reflecting the integration of visual with additional identity-specific information, were similar across experiments and thus independent of task demands. These results were further supported by the classifier analysis. We conclude that ERP correlates of familiar face recognition are largely independent of voluntary control and discuss potential applications in forensic settings., (© 2021 Society for Psychophysiological Research.)

To form a more reliable percept of the environment, the brain needs to estimate its own sensory uncertainty. Current theories of perceptual inference assume that the brain computes sensory uncertainty instantaneously and independently for each stimulus. We evaluated this assumption in four psychophysical experiments, in which human observers localized auditory signals that were presented synchronously with spatially disparate visual signals. Critically, the visual noise changed dynamically over time continuously or with intermittent jumps. Our results show that observers integrate audiovisual inputs weighted by sensory uncertainty estimates that combine information from past and current signals consistent with an optimal Bayesian learner that can be approximated by exponential discounting. Our results challenge leading models of perceptual inference where sensory uncertainty estimates depend only on the current stimulus. They demonstrate that the brain capitalizes on the temporal dynamics of the external world and estimates sensory uncertainty by combining past experiences with new incoming sensory signals., Competing Interests: UB, TR, AF, OS, UN No competing interests declared, (© 2020, Beierholm et al.)

Previous studies suggest that to achieve color constancy, the human visual system makes use of multiple cues, including a priori assumptions about the illumination ("daylight priors"). Specular highlights have been proposed to aid constancy, but the evidence for their usefulness is mixed. Here, we used a novel cue-combination approach to test whether the presence of specular highlights or the validity of a daylight prior improves illumination chromaticity estimates, inferred from achromatic settings, to determine whether and under which conditions either cue contributes to color constancy. Observers made achromatic settings within three-dimensional rendered scenes containing matte or glossy shapes, illuminated by either daylight or nondaylight illuminations. We assessed both the variability of these settings and their accuracy, in terms of the standard color constancy index (CCI). When a spectrally uniform background was present, neither CCIs nor variability improved with specular highlights or daylight illuminants (Experiment 1). When a Mondrian background was introduced, CCIs decreased overall but were higher for scenes containing glossy, as opposed to matte, shapes (Experiments 2 and 3). There was no overall reduction in variability of settings and no benefit for scenes illuminated by daylights. Taken together, these results suggest that the human visual system indeed uses specular highlights to improve color constancy but only when other cues, such as from the local surround, are weakened.

Aging has been shown to impact multisensory perception, but the underlying computational mechanisms are unclear. For effective interactions with the environment, observers should integrate signals that share a common source, weighted by their reliabilities, and segregate those from separate sources. Observers are thought to accumulate evidence about the world's causal structure over time until a decisional threshold is reached. Combining psychophysics and Bayesian modeling, we investigated how aging affects audiovisual perception of spatial signals. Older and younger adults were comparable in their final localization and common-source judgment responses under both speeded and unspeeded conditions, but were disproportionately slower for audiovisually incongruent trials. Bayesian modeling showed that aging did not affect the ability to arbitrate between integration and segregation under either unspeeded or speeded conditions. However, modeling the within-trial dynamics of evidence accumulation under speeded conditions revealed that older observers accumulate noisier auditory representations for longer, set higher decisional thresholds, and have impaired motor speed. Older observers preserve audiovisual localization performance, despite noisier sensory representations, by sacrificing response speed., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Results in the recent literature suggest that multisensory integration in the brain follows the rules of Bayesian inference. However, how neural circuits can realize such inference and how it can be learned from experience is still the subject of active research. The aim of this work is to use a recent neurocomputational model to investigate how the likelihood and prior can be encoded in synapses, and how they affect audio-visual perception, in a variety of conditions characterized by different experience, different cue reliabilities and temporal asynchrony. The model considers two unisensory networks (auditory and visual) with plastic receptive fields and plastic crossmodal synapses, trained during a learning period. During training visual and auditory stimuli are more frequent and more tuned close to the fovea. Model simulations after training have been performed in crossmodal conditions to assess the auditory and visual perception bias: visual stimuli were positioned at different azimuth (±10° from the fovea) coupled with an auditory stimulus at various audio-visual distances (±20°). The cue reliability has been altered by using visual stimuli with two different contrast levels. Model predictions are compared with behavioral data. Results show that model predictions agree with behavioral data, in a variety of conditions characterized by a different role of prior and likelihood. Finally, the effect of a different unimodal or crossmodal prior, re-learning, temporal correlation among input stimuli, and visual damage (hemianopia) are tested, to reveal the possible use of the model in the clarification of important multisensory problems.

Cooperation and competition are vital for human survival and for social progress. In this study we examine the impact of external (environmental) and internal (individual differences) factors on the tendency to cooperate or compete in social conflicts. To this end, 53 young adults played blocks of the repeated Prisoner's Dilemma Game with each other or with a computer. The environmental context was manipulated across blocks, by introducing uncertainty, randomly losing or gaining money. Individual differences were assessed by participants' attachment style. We found that participants cooperated more when randomly losing money compared to when randomly winning or in the neutral condition. Moreover, in a negative uncertain environment, individuals with higher anxious and avoidant attachment styles cooperated less. The above effects were only observed when playing against a human and not a computer. Overall, the findings highlight the dependency of cooperative behavior on the context as driven by external and internal factors., Competing Interests: The authors have declared that no competing interests exist.

Television consumption influences perceptions of attractive female body size. However, cross-cultural research examining media influence on body ideals is typically confounded by differences in the availability of reliable and diverse foodstuffs. 112 participants were recruited from 3 Nicaraguan villages that differed in television consumption and nutritional status, such that the contribution of both factors could be revealed. Participants completed a female figure preference task, reported their television consumption, and responded to several measures assessing nutritional status. Communities with higher television consumption and/or higher nutritional status preferred thinner female bodies than communities with lower television consumption and/or lower nutritional status. Bayesian mixed models estimated the plausible range of effects for television consumption, nutritional status, and other relevant variables on individual preferences. The model explained all meaningful differences between our low-nutrition villages, and television consumption, after sex, was the most likely of these predictors to contribute to variation in preferences (probability mass >95% when modelling only variables with zero-order associations with preferences, but only 90% when modelling all possible predictors). In contrast, we found no likely link with nutritional status. We thus found evidence that where media access and nutritional status are confounded, media is the more likely predictor of body ideals.

Subjects routinely control the vigor with which they emit motoric responses. However, the bulk of formal treatments of decision-making ignores this dimension of choice. A recent theoretical study suggested that action vigor should be influenced by experienced average reward rate and that this rate is encoded by tonic dopamine in the brain. We previously examined how average reward rate modulates vigor as exemplified by response times and found a measure of agreement with the first suggestion. In the current study, we examined the second suggestion, namely the potential influence of dopamine signaling on vigor. Ninety healthy subjects participated in a double-blind experiment in which they received one of the following: placebo, L-DOPA (which increases dopamine levels in the brain), or citalopram (which has a selective, if complex, effect on serotonin levels). Subjects performed multiple trials of a rewarded odd-ball discrimination task in which we varied the potential reward over time in order to exercise the putative link between vigor and average reward rate. Replicating our previous findings, we found that a significant fraction of the variance in subjects' responses could be explained by our experimentally manipulated changes in average reward rate. Crucially, this relationship was significantly stronger under L-Dopa than under Placebo, suggesting that the impact of average reward levels on action vigor is indeed subject to a dopaminergic influence.

Perceptual events derive their significance to an animal from their meaning about the world, that is from the information they carry about their causes. The brain should thus be able to efficiently infer the causes underlying our sensory events. Here we use multisensory cue combination to study causal inference in perception. We formulate an ideal-observer model that infers whether two sensory cues originate from the same location and that also estimates their location(s). This model accurately predicts the nonlinear integration of cues by human subjects in two auditory-visual localization tasks. The results show that indeed humans can efficiently infer the causal structure as well as the location of causes. By combining insights from the study of causal inference with the ideal-observer approach to sensory cue combination, we show that the capacity to infer causal structure is not limited to conscious, high-level cognition; it is also performed continually and effortlessly in perception.

Recently, it has been shown that visual perception can be radically altered by signals of other modalities. For example, when a single flash is accompanied by multiple auditory beeps, it is often perceived as multiple flashes. This effect is known as the sound-induced flash illusion. In order to investigate the principles underlying this illusion, we developed an ideal observer (derived using Bayes' rule), and compared human judgements with those of the ideal observer for this task. The human observer's performance was highly consistent with that of the ideal observer in all conditions ranging from no interaction, to partial integration, to complete integration, suggesting that the rule used by the nervous system to decide when and how to combine auditory and visual signals is statistically optimal. Our findings show that the sound-induced flash illusion is an epiphenomenon of this general, statistically optimal strategy.

Vascular damage induced by acute hypertension is preceded by a peculiar pattern where blood vessels show alternating regions of constrictions and dilations ("sausages on a string"). The pattern occurs in the smaller blood vessels, and it plays a central role in causing the vascular damage. A related vascular pattern has been observed in larger vessels from several organs during angiography. In the larger vessels the occurrence of the pattern does not appear to be related to acute hypertension. A unifying feature between the phenomenon in large and small vessels seems to be an increase in vascular wall tension. Despite much research, the mechanisms underlying the sausage pattern have remained unknown. Here we present an anisotropic model of the vessel wall and show that the sausage pattern can arise because of an instability of the vessel wall. The model reproduces many of the key features observed experimentally. Most importantly, it suggests that the "sausaging" phenomenon is neither caused by a mechanical failure of the vessel wall due to a high blood pressure nor is it due to standing pressure waves caused by the beating of the heart. Rather, it is the expression of a general instability phenomenon. Experimental data suggest that the structural changes induced by the instability may cause secondary damage to the wall of small arteries and arterioles in the form of endothelial hyperpermeability followed by local fibrinoid necrosis of the vascular wall.

The spike timing in rhythmically active interneurons in the mammalian spinal locomotor network varies from cycle to cycle. We tested the contribution from passive membrane properties to this variable firing pattern, by measuring the reliability of spike timing, P, in interneurons in the isolated neonatal rat spinal cord, using intracellular injection of sinusoidal command currents of different frequencies (0.325-31.25 Hz). P is a measure of the precision of spike timing. In general, P was low at low frequencies and amplitudes (P = 0-0.6; 0-1.875 Hz; 0-30 pA), and high at high frequencies and amplitudes (P = 0.8-1; 3.125-31.25 Hz; 30-200 pA). The exact relationship between P and amplitude was difficult to describe because of the well-known low-pass properties of the membrane, which resulted in amplitude attenuation of high-frequency compared with low-frequency command currents. To formalize the analysis we used a leaky integrate and fire (LIF) model with a noise term added. The LIF model was able to reproduce the experimentally observed properties of P as well as the low-pass properties of the membrane. The LIF model enabled us to use the mathematical theory of nonlinear oscillators to analyze the relationship between amplitude, frequency, and P. This was done by systematically calculating the rotational number, N, defined as the number of spikes divided by the number of periods of the command current, for a large number of frequencies and amplitudes. These calculations led to a phase portrait based on the amplitude of the command current versus the frequency-containing areas [Arnold tongues (ATs)] with the same rotational number. The largest ATs in the phase portrait were those where N was a whole integer, and the largest areas in the ATs were seen for middle to high (>3 Hz) frequencies and middle to high amplitudes (50-120 pA). This corresponded to the amplitude- and frequency-evoked increase in P. The model predicted that P would be high when a cell responded with an integer and constant N. This prediction was confirmed by comparing N and P in real experiments. Fitting the result of the LIF model to the experimental data enabled us to estimate the standard deviation of the internal neuronal noise and to use these data to simulate the relationship between N and P in the model. This simulation demonstrated a good correspondence between the theoretical and experimental values. Our data demonstrate that interneurons can respond with a high reliability of spike timing, but only by combining fast and slow oscillations is it possible to obtain a high reliability of firing during rhythmic locomotor movements. Theoretical analysis of the rotation number provided new insights into the mechanism for obtaining reliable spike timing.