How recent history affects perception: the normative approach and its heuristic approximation

Emergent perceptual biases from state-space geometry in trained spiking recurrent neural networks

A stimulus held in working memory is perceived as contracted toward the average stimulus. This contraction bias has been extensively studied in psychophysics, but little is known about its origin from neural activity. By training recurrent networks of spiking neurons to discriminate temporal intervals, we explored the causes of this bias and how behavior relates to population firing activity. We found that the trained networks exhibited animal-like behavior. Various geometric features of neural trajectories in state space encoded warped representations of the durations of the first interval modulated by sensory history. Formulating a normative model, we showed that these representations conveyed a Bayesian estimate of the interval durations, thus relating activity and behavior. Importantly, our findings demonstrate that Bayesian computations already occur during the sensory phase of the first stimulus and persist throughout its maintenance in working memory, until the time of stimulus comparison.

Decoding contextual influences on auditory perception from primary auditory cortex

Perception can be highly dependent on stimulus context, but whether and how sensory areas encode the context remains uncertain. We used an ambiguous auditory stimulus - a tritone pair - to investigate the neural activity associated with a preceding contextual stimulus that strongly influenced the tritone pair's perception: either as an ascending or a descending step in pitch. We recorded single-unit responses from a population of auditory cortical cells in awake ferrets listening to the tritone pairs preceded by the contextual stimulus. We find that the responses adapt locally to the contextual stimulus, consistent with human MEG recordings from the auditory cortex under the same conditions. Decoding the population responses demonstrates that cells responding to pitch-class-changes are able to predict well the context-sensitive percept of the tritone pairs. Conversely, decoding the individual pitch-class representations and taking their distance in the circular Shepard tone space predicts the opposite of the percept. The various percepts can be readily captured and explained by a neural model of cortical activity based on populations of adapting, pitch-class and pitch-class-direction cells, aligned with the neurophysiological responses. Together, these decoding and model results suggest that contextual influences on perception may well be already encoded at the level of the primary sensory cortices, reflecting basic neural response properties commonly found in these areas.

Location- and feature-based selection histories make independent, qualitatively distinct contributions to urgent visuomotor performance

Attention mechanisms that guide visuomotor behaviors are classified into three broad types according to their reliance on stimulus salience, current goals, and selection histories (i.e., recent experience with events of many sorts). These forms of attentional control are clearly distinct and multifaceted, but what is largely unresolved is how they interact dynamically to determine impending visuomotor choices. To investigate this, we trained two macaque monkeys to perform an urgent version of an oddball search task in which a red target appears among three green distracters, or vice versa. By imposing urgency, performance can be tracked continuously as it transitions from uninformed guesses to informed choices, and this, in turn, permits assessment of attentional control as a function of time. We found that the probability of making a correct choice was strongly modulated by the histories of preceding target colors and target locations. Crucially, although both effects were gated by success (or reward), the two variables played dynamically distinct roles: whereas location history promoted an early motor bias, color history modulated the later perceptual evaluation. Furthermore, target color and location influenced performance independently of each other. The results show that, when combined, selection histories can give rise to enormous swings in visuomotor performance even in simple tasks with highly discriminable stimuli.

Is she still angry? Intact learning but no updating of facial expressions priors in autism

Autistic people exhibit atypical use of prior information when processing simple perceptual stimuli; yet, it remains unclear whether and how these difficulties in using priors extend to complex social stimuli. Here, we compared autistic people without accompanying intellectual disability and nonautistic people in their ability to acquire an "emotional prior" of a facial expression and update this prior to a different facial expression of the same identity. Participants performed a two-interval same/different discrimination task between two facial expressions. To study the acquisition of the prior, we examined how discrimination was modified by the contraction of the perceived facial expressions toward the average of presented stimuli (i.e., regression to the mean). At first, facial expressions surrounded one average emotional prior (mostly sad or angry), and then the average switched (to mostly angry or sad, accordingly). Autistic people exhibited challenges in facial discrimination, and yet acquired the first prior, demonstrating typical regression-to-the-mean effects. However, unlike nonautistic people, autistic people did not update their perception to the second prior, suggesting they are less flexible in updating an acquired prior of emotional expressions. Our findings shed light on the perception of emotional expressions, one of the most pressing challenges in autism.

Unifying network model links recency and central tendency biases in working memory

The central tendency bias, or contraction bias, is a phenomenon where the judgment of the magnitude of items held in working memory appears to be biased toward the average of past observations. It is assumed to be an optimal strategy by the brain and commonly thought of as an expression of the brain's ability to learn the statistical structure of sensory input. On the other hand, recency biases such as serial dependence are also commonly observed and are thought to reflect the content of working memory. Recent results from an auditory delayed comparison task in rats suggest that both biases may be more related than previously thought: when the posterior parietal cortex (PPC) was silenced, both short-term and contraction biases were reduced. By proposing a model of the circuit that may be involved in generating the behavior, we show that a volatile working memory content susceptible to shifting to the past sensory experience - producing short-term sensory history biases - naturally leads to contraction bias. The errors, occurring at the level of individual trials, are sampled from the full distribution of the stimuli and are not due to a gradual shift of the memory toward the sensory distribution's mean. Our results are consistent with a broad set of behavioral findings and provide predictions of performance across different stimulus distributions and timings, delay intervals, as well as neuronal dynamics in putative working memory areas. Finally, we validate our model by performing a set of human psychophysics experiments of an auditory parametric working memory task.

Reinforcement Learning during Locomotion

When learning a new motor skill, people often must use trial and error to discover which movement is best. In the reinforcement learning framework, this concept is known as exploration and has been linked to increased movement variability in motor tasks. For locomotor tasks, however, increased variability decreases upright stability. As such, exploration during gait may jeopardize balance and safety, making reinforcement learning less effective. Therefore, we set out to determine if humans could acquire and retain a novel locomotor pattern using reinforcement learning alone. Young healthy male and female participants walked on a treadmill and were provided with binary reward feedback (indicated by a green checkmark on the screen) that was tied to a fixed monetary bonus, to learn a novel stepping pattern. We also recruited a comparison group who walked with the same novel stepping pattern but did so by correcting for target error, induced by providing real-time veridical visual feedback of steps and a target. In two experiments, we compared learning, motor variability, and two forms of motor memories between the groups. We found that individuals in the binary reward group did, in fact, acquire the new walking pattern by exploring (increasing motor variability). Additionally, while reinforcement learning did not increase implicit motor memories, it resulted in more accurate explicit motor memories compared with the target error group. Overall, these results demonstrate that humans can acquire new walking patterns with reinforcement learning and retain much of the learning over 24 h.

Direct contribution of the sensory cortex to the judgment of stimulus duration

Decision making frequently depends on monitoring the duration of sensory events. To determine whether, and how, the perception of elapsed time derives from the neuronal representation of the stimulus itself, we recorded and optogenetically modulated vibrissal somatosensory cortical activity as male rats judged vibration duration. Perceived duration was dilated by optogenetic excitation. A second set of rats judged vibration intensity; here, optogenetic excitation amplified the intensity percept, demonstrating sensory cortex to be the common gateway both to time and to stimulus feature processing. A model beginning with the membrane currents evoked by vibrissal and optogenetic drive and culminating in the representation of perceived time successfully replicated rats' choices. Time perception is thus as deeply intermeshed within the sensory processing pathway as is the sense of touch itself, suggesting that the experience of time may be further investigated with the toolbox of sensory coding.

Frequency-specific contributions to auditory perceptual priors: Testing the predictive-coding hypothesis

Perceptual priors formed by recent stimuli bias our immediate percept. These priors, expressing our implicit expectations, affect both high- and low-level processing stages. Yet, the nature of the inter-level interaction is unknown. Do priors operate top-down and bias low-level features toward recently experienced objects (predictive-coding hypothesis), or are low-level biases bottom-up driven and formed by local memory circuits? To decipher between these options in auditory perception, we used the "missing fundamental illusion", enabling the dissociation of low-level components from the high-level pitch. Surprisingly, in contrast to predictive coding, when the fundamental frequency was missing, pitch contraction across timbre categories was not found to the previously perceived high-level pitch, but to the physically present frequency. This bottom-up contribution of low-level memory components to perceptual priors, operating independently of recent high-level percepts, may stabilize the perceptual organization and underlie continuity between similar low-level features belonging to different object categories in the auditory modality.

Refinement of face representations by exposure reveals different time scales of biases in face processing

Experience modulates face processing abilities so that face discrimination and recognition improve with development, especially for more frequently experienced faces (e.g., own-race faces). Although advanced models describe how experience generally modulates perception, the mechanism by which exposure refines internal perceptual representations of faces is unknown. To address this issue, we investigated the effect of short- and long-term experienced stimulus history on face processing. Participants performed same-different judgments in a serial discrimination task where two consecutive faces were drawn from a distribution of morphed faces. Use of stimulus statistics was measured by testing the gravitation of face representations towards the mean of a range of morphed faces around which they were sampled (regression-to-the-mean). The results demonstrated regression of face representations towards the experienced mean and the retention of stimulus statistics over days. In trials where regression facilitated discrimination, the bias diminished the otherwise disadvantage of other-race over own-races faces. The dynamics of the perceptual bias, probed by trial-by-trial performance, further indicated different timescales of the bias, depending on perceptual expertise: people with weak face-recognition skills showed the use of a stable reference, built on long-term statistics accumulated over many trials, along with an updating of this reference by recent trials. In contrast, the strong face recognizers showed a different pattern where sequential effects mostly contributed to discrimination, with relatively minimal reliance on the long-term average for other-race faces. The findings suggest a mechanism by which exposure refines face representations and reveal, for the first time in adults, associations between levels of specialization of perceptual representations and the extent to which these representations become narrowly tuned.

The Influence of Memory on Visual Perception in Infants, Children, and Adults

Perception is not an independent, in-the-moment event. Instead, perceiving involves integrating prior expectations with current observations. How does this ability develop from infancy through adulthood? We examined how prior visual experience shapes visual perception in infants, children, and adults. Using an identical task across age groups, we exposed participants to pairs of colorful stimuli and implicitly measured their ability to discriminate relative saturation levels. Results showed that adult participants were biased by previously experienced exemplars, and exhibited weakened in-the-moment discrimination between different levels of saturation. In contrast, infants and children showed less influence of memory in their perception, and they actually outperformed adults in discriminating between current levels of saturation. Our findings suggest that as humans develop, their perception relies more on prior experience and less on current observation.

Independent short- and long-term dependencies in perception

Perception is biased by stimulus history. Both long-term effects such as the central-tendency bias (CTB) and short-term effects such as serial dependence (SD) have been described, but research into the two has remained largely separate. The sources of these effects, however, are highly correlated in stimulus statistics, which can result in a misinterpretation of experimental data. We compared CTB and SD in the perception of color and line length. Observers judged the relative hue or length of consecutive stimuli in a delayed-matching task. Two interstimulus intervals were used to investigate whether elapsed time or the number of stimulus occurrences was more important for SD. We estimated biases by fitting psychometric functions to the data split based on the history features, and we also fit generalized linear mixed models with either CTB, SD, or both included as regressors. We found biases to both recent stimulus history and the cumulative average of stimulus values for both color and line length judgments. The strength and pattern of each of the biases depended on whether all sources of bias were included in the analysis. Within the range of interstimulus intervals tested, the number of intervening stimuli was more important than elapsed time for SD. We conclude that both SD and CTB independently affect perceptual judgments, and that one effect is not an artifact caused by the other. Failing to consider both effects in data analysis can give an erroneous picture of the phenomenon under study.

Effects of contraction bias on the decision process in the macaque prefrontal cortex

Our representation of magnitudes such as time, distance, and size is not always veridical because it is affected by multiple biases. From a Bayesian perspective, estimation errors are considered to be the result of an optimization mechanism for the behavior in a noisy environment by integrating previous experience with the incoming sensory information. One influence of the distribution of past stimuli on perceptual decisions is represented by the regression toward the mean, a type of contraction bias. Using a spatial discrimination task with 2 stimuli presented sequentially at different distances from the center, we show that this bias is also present in macaques when comparing the magnitude of 2 distances. We found that the contraction of the first stimulus magnitude toward the center of the distribution accounted for some of the changes in performance, even more so than the effect of difficulty related to the ratio between stimulus magnitudes. At the neural level in the dorsolateral prefrontal cortex, the coding of the decision after the presentation of the second stimulus reflected the effect of the contraction bias on the discriminability of the stimuli at the behavioral level.

Perceptual history biases in serial ensemble representation

Ensemble perception refers to the visual system's ability to efficiently represent groups of similar objects as a unified percept using their summary statistical information. Most studies focused on extraction of current trial averages, giving little attention to prior experience effects, although a few recent studies found that ensemble mean estimations contract toward previously presented stimuli, with most of these focusing on explicit perceptual averaging of simultaneously presented item ensembles. Yet, the time element is crucial in real dynamic environments, where we encounter ensemble items over time, aggregating information until reaching summary representations. Moreover, statistical information of objects and scenes is learned over time and often implicitly and then used for predictions that shape perception, promoting environmental stability. Therefore, we now focus on temporal aspects of ensemble statistics and test whether prior information, beyond the current trial, biases implicit perceptual decisions. We designed methods to separate current trial biases from those of previously seen trial ensembles. In each trial, six circles of different sizes were presented serially, followed by two test items. Participants were asked to choose which was present in the sequence. Participants unconsciously rely on ensemble statistics, choosing stimuli closer to the ensemble mean. To isolate the influence of earlier trials, the two test items were sometimes equidistant from the current trial mean. Results showed membership judgment biases toward current trial mean, when informative (largest effect). On equidistant trials, judgments were biased toward previously experienced stimulus statistics. Comparison of similar conditions with a shifted stimulus distribution ruled out a bias toward an earlier, presession, prototypical diameter. We conclude that ensemble perception, even for temporally experienced ensembles, is influenced not only by current trial mean but also by means of recently seen ensembles and that these influences are somewhat correlated on a participant-by-participant basis.

Priming of probabilistic attentional templates

Attentional priming has a dominating influence on vision, speeding visual search, releasing items from crowding, reducing masking effects, and during free-choice, primed targets are chosen over unprimed ones. Many accounts postulate that templates stored in working memory control what we attend to and mediate the priming. But what is the nature of these templates (or representations)? Analyses of real-world visual scenes suggest that tuning templates to exact color or luminance values would be impractical since those can vary greatly because of changes in environmental circumstances and perceptual interpretation. Tuning templates to a range of the most probable values would be more efficient. Recent evidence does indeed suggest that the visual system represents such probability, gradually encoding statistical variation in the environment through repeated exposure to input statistics. This is consistent with evidence from neurophysiology and theoretical neuroscience as well as computational evidence of probabilistic representations in visual perception. I argue that such probabilistic representations are the unit of attentional priming and that priming of, say, a repeated single-color value simply involves priming of a distribution with no variance. This "priming of probability" view can be modelled within a Bayesian framework where priming provides contextual priors. Priming can therefore be thought of as learning of the underlying probability density function of the target or distractor sets in a given continuous task.

Duration discrimination: A diffusion decision modeling approach

The human ability to discriminate the duration of two subsequently presented stimuli is often studied with tasks that involve a comparison between a standard stimulus (with fixed duration) and comparison stimuli (with varying durations). The performance in such tasks is influenced by the presentation order of these successively presented stimuli. The so-called Type A effect refers to the impact of presentation order on the point of subjective equality. The Type B effect describes effects of presentation order on the just-noticeable-difference. Cognitive models that account for these context effects assume that participants' duration estimation is influenced by the history of previously encountered stimuli. For example, the internal reference model assumes that the magnitude of a "typical" stimulus is represented by an internal reference. This internal reference evolves throughout an experiment and is updated on every trial. Different recent models have in common that they describe how the internal reference is computed but are agnostic to the decision process itself. In this study, we develop a new model that incorporates the mechanisms of perceptual discrimination models into a diffusion model. The diffusion model focuses on the dynamics of the decision process itself and accounts for choice and response times based on a set of latent cognitive variables. We show that our model accurately predicts the accuracy and response time distribution in a classical duration discrimination task. Further, model parameters were sensitive to the Type A and B effect. The proposed model opens up new opportunities for studying human discrimination performance (e.g., individual differences).

A quantum-like cognitive approach to modeling human biased selection behavior

Cognitive biases of the human mind significantly influence the human decision-making process. However, they are often neglected in modeling selection behaviors and hence deemed irrational. Here, we introduce a cognitive quantum-like approach for modeling human biases by simulating society as a quantum system and using a Quantum-like Bayesian network (QBN) structure. More specifically, we take inspiration from the electric field to improve our recent entangled QBN approach to model the initial bias due to unequal probabilities in parent nodes. Entangled QBN structure is particularly suitable for modeling bias behavior due to changing the state of systems with each observation and considering every decision-maker an integral part of society rather than an isolated agent. Hence, biases caused by emotions between agents or past personal experiences are also modeled by the social entanglement concept motivated by entanglement in quantum physics. In this regard, we propose a bias potential function and a new quantum-like entanglement witness in Hilbert space to introduce a biased variant of the entangled QBN (BEQBN) model based on quantum probability. The predictive BEQBN is evaluated on two well-known empirical tasks. Results indicate the superiority of the BEQBN by achieving the first rank compared to classical BN and six QBN approaches and presenting more realistic predictions of human behaviors.

A perceptual glitch in serial perception generates temporal distortions

Precisely estimating event timing is essential for survival, yet temporal distortions are ubiquitous in our daily sensory experience. Here, we tested whether the relative position, duration, and distance in time of two sequentially-organized events-standard S, with constant duration, and comparison C, with duration varying trial-by-trial-are causal factors in generating temporal distortions. We found that temporal distortions emerge when the first event is shorter than the second event. Importantly, a significant interaction suggests that a longer inter-stimulus interval (ISI) helps to counteract such serial distortion effect only when the constant S is in the first position, but not if the unpredictable C is in the first position. These results imply the existence of a perceptual bias in perceiving ordered event durations, mechanistically contributing to distortion in time perception. We simulated our behavioral results with a Bayesian model and replicated the finding that participants disproportionately expand first-position dynamic (unpredictable) short events. Our results clarify the mechanisms generating time distortions by identifying a hitherto unknown duration-dependent encoding inefficiency in human serial temporal perception, something akin to a strong prior that can be overridden for highly predictable sensory events but unfolds for unpredictable ones.

Contraction bias in temporal estimation

When asked to compare the perceptual features of two serially presented objects, participants are often biased to over- or under-estimate the difference in magnitude between the stimuli. Overestimation occurs consistently when a) the two stimuli are relatively small in magnitude and the first stimulus is larger in magnitude than the second; or b) the two stimuli are relatively large in magnitude and the first stimulus is smaller in magnitude than the second; underestimation consistently occurs in the complementary cases. This systematic perceptual bias, known as the contraction bias, was demonstrated for a multitude of perceptual features and in various modalities. Here, we tested whether estimation of time-duration is affected by the contraction bias. In each trial of three experiments (n = 20 each), participants compared the duration of two visually presented stimuli. Findings revealed over- and under-estimation effects as predicted by the contraction bias. Here, we discuss this asymmetry and describe how these findings can be explained via a Bayesian inference framework.

Context Sensitivity across Multiple Time scales with a Flexible Frequency Bandwidth

Everyday auditory streams are complex, including spectro-temporal content that varies at multiple timescales. Using EEG, we investigated the sensitivity of human auditory cortex to the content of past stimulation in unattended sequences of equiprobable tones. In 3 experiments including 82 participants overall, we found that neural responses measured at different latencies after stimulus onset were sensitive to frequency intervals computed over distinct timescales. Importantly, early responses were sensitive to a longer history of stimulation than later responses. To account for these results, we tested a model consisting of neural populations with frequency-specific but broad tuning that undergo adaptation with exponential recovery. We found that the coexistence of neural populations with distinct recovery rates can explain our results. Furthermore, the adaptation bandwidth of these populations depended on spectral context-it was wider when the stimulation sequence had a wider frequency range. Our results provide electrophysiological evidence as well as a possible mechanistic explanation for dynamic and multiscale context-dependent auditory processing in the human cortex.

Time coding in rat dorsolateral striatum

To assess the role of dorsolateral striatum (DLS) in time coding, we recorded neuronal activity in rats tasked with comparing the durations of two sequential vibrations. Bayesian decoding of population activity revealed a representation of the unfolding of the trial across time. However, further analyses demonstrated a distinction between the encoding of trial time and perceived time. First, DLS did not show a privileged representation of the stimulus durations compared with other time spans. Second, higher intensity vibrations were perceived as longer; however, time decoded from DLS was unaffected by vibration intensity. Third, DLS did not encode stimulus duration differently on correct versus incorrect trials. Finally, in rats trained to compare the intensities of two sequential vibrations, stimulus duration was encoded even though it was a perceptually irrelevant feature. These findings lead us to posit that temporal information is inherent to DLS activity irrespective of the rat's ongoing percept.

Adaptive auditory brightness perception

Perception adapts to the properties of prior stimulation, as illustrated by phenomena such as visual color constancy or speech context effects. In the auditory domain, only little is known about adaptive processes when it comes to the attribute of auditory brightness. Here, we report an experiment that tests whether listeners adapt to spectral colorations imposed on naturalistic music and speech excerpts. Our results indicate consistent contrastive adaptation of auditory brightness judgments on a trial-by-trial basis. The pattern of results suggests that these effects tend to grow with an increase in the duration of the adaptor context but level off after around 8 trials of 2 s duration. A simple model of the response criterion yields a correlation of r = .97 with the measured data and corroborates the notion that brightness perception adapts on timescales that fall in the range of auditory short-term memory. Effects turn out to be similar for spectral filtering based on linear spectral filter slopes and filtering based on a measured transfer function from a commercially available hearing device. Overall, our findings demonstrate the adaptivity of auditory brightness perception under realistic acoustical conditions.

Choices change the temporal weighting of decision evidence

Many decisions result from the accumulation of decision-relevant information (evidence) over time. Even when maximizing decision accuracy requires weighting all the evidence equally, decision-makers often give stronger weight to evidence occurring early or late in the evidence stream. Here, we show changes in such temporal biases within participants as a function of intermittent judgments about parts of the evidence stream. Human participants performed a decision task that required a continuous estimation of the mean evidence at the end of the stream. The evidence was either perceptual (noisy random dot motion) or symbolic (variable sequences of numbers). Participants also reported a categorical judgment of the preceding evidence half-way through the stream in one condition or executed an evidence-independent motor response in another condition. The relative impact of early versus late evidence on the final estimation flipped between these two conditions. In particular, participants' sensitivity to late evidence after the intermittent judgment, but not the simple motor response, was decreased. Both the intermittent response as well as the final estimation reports were accompanied by nonluminance-mediated increases of pupil diameter. These pupil dilations were bigger during intermittent judgments than simple motor responses and bigger during estimation when the late evidence was consistent than inconsistent with the initial judgment. In sum, decisions activate pupil-linked arousal systems and alter the temporal weighting of decision evidence. Our results are consistent with the idea that categorical choices in the face of uncertainty induce a change in the state of the neural circuits underlying decision-making.NEW & NOTEWORTHY The psychology and neuroscience of decision-making have extensively studied the accumulation of decision-relevant information toward a categorical choice. Much fewer studies have assessed the impact of a choice on the processing of subsequent information. Here, we show that intermittent choices during a protracted stream of input reduce the sensitivity to subsequent decision information and transiently boost arousal. Choices might trigger a state change in the neural machinery for decision-making.

A common dynamic prior for time in duration discrimination

Estimation of time depends heavily on both global and local statistical context. Durations that are short relative to the global distribution are systematically overestimated; durations that are locally preceded by long durations are also overestimated. Context effects are prominent in duration discrimination tasks, where a standard duration and a comparison duration are presented on each trial. In this study, we compare and test two models that posit a dynamically updating internal reference that biases time estimation on global and local scales in duration discrimination tasks. The internal reference model suggests that the internal reference operates during postperceptual stages and only interacts with the first presented duration. In contrast, a Bayesian account of time estimation implies that any perceived duration updates the internal reference and therefore interacts with both the first and second presented duration. We implemented both models and tested their predictions in a duration discrimination task where the standard duration varied from trial to trial. Our results are in line with a Bayesian perspective on time estimation. First, the standard systematically biased estimation of the comparison, such that shorter standards increased the likelihood of reporting that the comparison was shorter. Second, both the previous standard and comparison systematically biased time estimation of subsequent trials in the same direction. Third, more precise observers showed smaller biases. In sum, our findings suggest a common dynamic prior for time that is updated by each perceived duration and where the relative weighting of old and new observations is determined by their relative precision.

Dissecting the Roles of Supervised and Unsupervised Learning in Perceptual Discrimination Judgments

Our ability to compare sensory stimuli is a fundamental cognitive function, which is known to be affected by two biases: choice bias, which reflects a preference for a given response, and contraction bias, which reflects a tendency to perceive stimuli as similar to previous ones. To test whether both reflect supervised processes, we designed feedback protocols aimed to modify them and tested them in human participants. Choice bias was readily modifiable. However, contraction bias was not. To compare these results to those predicted from an optimal supervised process, we studied a noise-matched optimal linear discriminator (Perceptron). In this model, both biases were substantially modified, indicating that the “resilience” of contraction bias to feedback does not maximize performance. These results suggest that perceptual discrimination is a hierarchical, two-stage process. In the first, stimulus statistics are learned and integrated with representations in an unsupervised process that is impenetrable to external feedback. In the second, a binary judgment, learned in a supervised way, is applied to the combined percept.

SIGNIFICANCE STATEMENT The seemingly effortless process of inferring physical reality from the sensory input is highly influenced by previous knowledge, leading to perceptual biases. Two common ones are contraction bias (the tendency to perceive stimuli as similar to previous ones) and choice bias (the tendency to prefer a specific response). Combining human psychophysical experiments with computational modeling we show that they reflect two different learning processes. Contraction bias reflects unsupervised learning of stimuli statistics, whereas choice bias results from supervised or reinforcement learning. This dissociation reveals a hierarchical, two-stage process. The first, where stimuli statistics are learned and integrated with representations, is unsupervised. The second, where a binary judgment is applied to the combined percept, is learned in a supervised way.

Individual difference in serial dependence results from opposite influences of perceptual choices and motor responses

Natural image statistics exhibit temporal regularities of slow changes and short-term correlations and visual perception, too, is biased toward recently seen stimuli, i.e., a positive serial dependence. Some studies report strong individual differences in serial dependence in perceptual decision-making: some observers show positive serial effects, others repulsive effects, and some show no bias. To understand these contrasting results, this study separates the influences of physical stimuli per se, perceptual choices, and motor responses on serial dependence in perceptual decision making. In two experiments, human observers reported which orientation (45° or −45°, at threshold contrast) they perceived. Experiment 1, used a consistent mapping between stimulus and response buttons whereas in Experiment 2, observers did two tasks: one with a consistent stimulus-response mapping, the other with a random stimulus-response mapping (perceptual choice and motor response unrelated). Results show that the stimulus percept (not the physical stimulus per se) affected subsequent perceptual choices in an attractive way and that motor responses produced a repulsive serial effect. When the choice-response mapping was consistent (inseparable choice and response, typical of most experiments), individual differences in the overall serial effect was observed: some were positive, some repulsive, and some were bias-free. The multiple regression analysis revealed that observers’ overall serial effects in the consistent choice-response mapping task could be predicted by their serial effects for choices and motor responses in the random mapping task. These individual differences likely reflect relative weightings of a positive choice bias and a repulsive motor bias.

Priors Bias Perceptual Decisions in Autism, But Are Less Flexibly Adjusted to the Context

According to the predictive coding framework, percepts emerge from combinations of sensory input and prior knowledge, whose relative contributions depend on their reliability. Recent predictive coding theories suggest that Autism Spectrum Disorder (ASD) could be characterized by an atypical weighting of priors. Here, we assessed whether individuals with ASD can flexibly adjust the weight (precision) of the prior to the context. Thirty-one neurotypical adults (NT) and 26 adults with ASD participated in a visual discrimination task designed to elicit a time-order effect (TOE). The TOE reflects the integration of priors with sensory estimates. We used two experimental contexts: a narrow stimulus range (Narrow condition) and a broader range (Broad condition) in order to induce a prior with a higher and lower precision, respectively. Both groups learned a prior that biased their perception, as shown with the TOE. As expected, the NT group had a larger TOE in the Narrow condition than in the Broad condition, revealing a contextual adjustment of the prior precision. In contrast, ASD participants were more inflexible: the extent of the TOE was not modulated by the context. In addition, the accuracy increased when the stimulus range decreased in both group, which may be interpreted as a contextual adjustment of the sensory precision. To conclude, adults with and without ASD implicitly learned a prior mean, but ASD participants failed to flexibly adjust the prior precision to the context. This increased inflexibility in ASD could account for many symptoms, such as their intolerance of uncertainty. LAY SUMMARY: Based on our experience, we have expectations about our environment. Theories suggest that the symptoms encountered in autism could be due to atypical expectations, leading to an impression of an unpredictable world. Using a visual discrimination task, we showed that adults with and without autism were biased by their expectations. Yet, the extent to which expectations biased perception did not depend on the context in autism. This higher inflexibility found in autism may explain symptoms such as resistance to change.

Temporal bisection is influenced by ensemble statistics of the stimulus set

Although humans are well capable of precise time measurement, their duration judgments are nevertheless susceptible to temporal context. Previous research on temporal bisection has shown that duration comparisons are influenced by both stimulus spacing and ensemble statistics. However, theories proposed to account for bisection performance lack a plausible justification of how the effects of stimulus spacing and ensemble statistics are actually combined in temporal judgments. To explain the various contextual effects in temporal bisection, we develop a unified ensemble-distribution account (EDA), which assumes that the mean and variance of the duration set serve as a reference, rather than the short and long standards, in duration comparison. To validate this account, we conducted three experiments that varied the stimulus spacing (Experiment 1), the frequency of the probed durations (Experiment 2), and the variability of the probed durations (Experiment 3). The results revealed significant shifts of the bisection point in Experiments 1 and 2, and a change of the sensitivity of temporal judgments in Experiment 3-which were all well predicted by EDA. In fact, comparison of EDA to the extant prior accounts showed that using ensemble statistics can parsimoniously explain various stimulus set-related factors (e.g., spacing, frequency, variance) that influence temporal judgments.

Perceptual inference is impaired in individuals with ASD and intact in individuals who have lost the autism diagnosis

Beyond the symptoms which characterize their diagnoses, individuals with autism spectrum disorder (ASD) show enhanced performance in simple perceptual discrimination tasks. Often attributed to superior sensory sensitivities, enhanced performance may also reflect a weaker bias towards previously perceived stimuli. This study probes perceptual inference in a group of individuals who have lost the autism diagnosis (LAD); that is, they were diagnosed with ASD in early childhood but have no current ASD symptoms. Groups of LAD, current ASD, and typically developing (TD) participants completed an auditory discrimination task. Individuals with TD showed a bias towards previously perceived stimuli-a perceptual process called "contraction bias"; that is, their representation of a given tone was contracted towards the preceding trial stimulus in a manner that is Bayesian optimal. Similarly, individuals in the LAD group showed a contraction bias. In contrast, individuals with current ASD showed a weaker contraction bias, suggesting reduced perceptual inferencing. These findings suggest that changes that characterize LAD extend beyond the social and communicative symptoms of ASD, impacting perceptual domains. Measuring perceptual processing earlier in development in ASD will tap the causality between changes in perceptual and symptomatological domains. Further, the characterization of perceptual inference could reveal meaningful individual differences in complex high-level behaviors.

Sensation weighting in duration discrimination: A univariate, multivariate, and varied-design study of presentation-order effects

Stimulus discriminability is often assessed by comparisons of two successive stimuli: a fixed standard (St) and a varied comparison stimulus (Co). Hellström's sensation weighting (SW) model describes the subjective difference between St and Co as a difference between two weighted compounds, each comprising a stimulus and its internal reference level (ReL). The presentation order of St and Co has two important effects: Relative overestimation of one stimulus is caused by perceptual time-order errors (TOEs), as well as by judgment biases. Also, sensitivity to changes in Co tends to differ between orders StCo and CoSt: the Type B effect. In three duration discrimination experiments, difference limens (DLs) were estimated by an adaptive staircase method. The SW model was adapted for modeling of DLs generated with this method. In Experiments 1 and 2, St durations were 100, 215, 464, and 1,000 ms in separate blocks. TOEs and Type B effects were assessed with univariate and multivariate analyses, and were well accounted for by the SW model, suggesting that the two effects are closely related, as this model predicts. With short St durations, lower DLs were found with the order CoSt than with StCo, challenging alternative models. In Experiment 3, St durations of 100 and 215 ms, or 464 and 1,000 ms, were intermixed within a block. From the SW model this was predicted to shift the ReL for the first-presented interval, thereby also shifting the TOE. This prediction was confirmed, strengthening the SW model's account of the comparison of stimulus magnitudes.

Neural and Behavioral Evidence for Frequency-Selective Context Effects in Rhythm Processing in Humans

When listening to music, people often perceive and move along with a periodic meter. However, the dynamics of mapping between meter perception and the acoustic cues to meter periodicities in the sensory input remain largely unknown. To capture these dynamics, we recorded the electroencephalography while nonmusician and musician participants listened to nonrepeating rhythmic sequences, where acoustic cues to meter frequencies either gradually decreased (from regular to degraded) or increased (from degraded to regular). The results revealed greater neural activity selectively elicited at meter frequencies when the sequence gradually changed from regular to degraded compared with the opposite. Importantly, this effect was unlikely to arise from overall gain, or low-level auditory processing, as revealed by physiological modeling. Moreover, the context effect was more pronounced in nonmusicians, who also demonstrated facilitated sensory-motor synchronization with the meter for sequences that started as regular. In contrast, musicians showed weaker effects of recent context in their neural responses and robust ability to move along with the meter irrespective of stimulus degradation. Together, our results demonstrate that brain activity elicited by rhythm does not only reflect passive tracking of stimulus features, but represents continuous integration of sensory input with recent context.

Memory integration into visual perception in infancy, childhood, and adulthood

We compared the influence of prior knowledge on visual perception in infants, children, and adults in order to explore the developmental trajectory by which prior knowledge is integrated with new sensory input. Using an identical task across age groups, we tested how participants' accumulated experience affected their ability to judge the relative saturation levels within a pair of sequentially-presented stimuli. We found that infants and children, relative to adults, showed greater influence of the current observation and reduced influence of memory in their perception. In fact, infants and children outperformed adults in discriminating between different levels of saturation, and their performance was less biased by previously-experienced exemplars. Thus, the development of perceptual integration of memory leads to less precise discrimination in the moment, but allows observers to make use of their prior experience in interpreting a complex sensory environment.

Temporal Context affects interval timing at the perceptual level

There is now ample evidence that when observers are asked to estimate features of an object they take into account recent stimulation history and blend the current sensory evidence with the recent stimulus intensity according to their reliability. Most of this evidence has been obtained via estimation or production paradigms both of which entail a conspicuous post-perceptual decision stage. So it is an unsolved question, as to whether the trace of previous stimulation contributes at the decision stage or as early as the perceptual stage. To this aim we focused on duration judgments, which typically exhibit strong central tendency effects and asked a duration comparison between two intervals, one of which characterized by high uncertainty. We found that the perceived duration of this interval regressed toward the average duration, demonstrating a genuine perceptual bias. Regression did not transfer between the visual and the auditory modality, indicating it is modality specific, but generalized across passively observed and actively produced intervals. These findings suggest that temporal central tendency effects modulate how long an interval appears to us and that integration of current sensory evidence can occur as early as in the sensory systems.

Disambiguating serial effects of multiple timescales

What has been previously experienced can systematically affect human perception in the present. We designed a novel psychophysical experiment to measure the perceptual effects of adapting to dynamically changing stimulus statistics. Observers are presented with a series of oriented Gabor patches and are asked occasionally to judge the orientation of highly ambiguous test patches. We developed a computational model to quantify the influence of past stimuli presentations on the observers' perception of test stimuli over multiple timescales and to show that this influence is distinguishable from simple response biases. The experimental results reveal that perception is attracted toward the very recent past and simultaneously repulsed from stimuli presented at short to medium timescales and attracted to presentations further in the past. All effects differ significantly both on their relative strength and their respective duration. Our model provides a structured way of quantifying serial effects in psychophysical experiments, and it could help experimenters in identifying such effects in their data and distinguish them from less interesting response biases.

Grant Report on d-Serine Augmentation of Neuroplasticity-Based Auditory Learning in Schizophrenia †

We report on the rationale and design of an ongoing NIMH sponsored R61-R33 project in schizophrenia/schizoaffective disorder. This project studies augmenting the efficacy of auditory neuroplasticity cognitive remediation (AudRem) with d-serine, an N-methyl-d-aspartate-type glutamate receptor (NMDAR) glycine-site agonist. We operationalize improved (smaller) thresholds in pitch (frequency) between successive auditory stimuli after AudRem as improved plasticity, and mismatch negativity (MMN) and auditory θ as measures of functional target engagement of both NMDAR agonism and plasticity. Previous studies showed that AudRem alone produces significant, but small cognitive improvements, while d-serine alone improves symptoms and MMN. However, the strongest results for plasticity outcomes (improved pitch thresholds, auditory MMN and θ) were found when combining d-serine and AudRem. AudRem improvements correlated with reading and other auditory cognitive tasks, suggesting plasticity improvements are predictive of functionally relevant outcomes. While d-serine appears to be efficacious for acute AudRem enhancement, the optimal dose remains an open question, as does the ability of combined d-serine + AudRem to produce sustained improvement. In the ongoing R61, 45 schizophrenia patients will be randomized to receive three placebo-controlled, double-blind d-serine + AudRem sessions across three separate 15 subject dose cohorts (80/100/120 mg/kg). Successful completion of the R61 is defined by ≥moderate effect size changes in target engagement and correlation with function, without safety issues. During the three-year R33, we will assess the sustained effects of d-serine + AudRem. In addition to testing a potentially viable treatment, this project will develop a methodology to assess the efficacy of novel NMDAR modulators, using d-serine as a "gold-standard".

Generalization of Object Localization From Whiskers to Other Body Parts in Freely Moving Rats

Rats can be trained to associate relative spatial locations of objects with the spatial location of rewards. Here we ask whether rats can localize static silent objects with other body parts in the dark, and if so with what resolution. We addressed these questions in trained rats, whose interactions with the objects were tracked at high-resolution before and after whisker trimming. We found that rats can use other body parts, such as trunk and ears, to localize objects. Localization resolution with non-whisking body parts (henceforth, ‘body’) was poorer than that obtained with whiskers, even when left with a single whisker at each side. Part of the superiority of whiskers was obtained via the use of multiple contacts. Transfer from whisker to body localization occurred within one session, provided that body contacts with the objects occurred before whisker trimming, or in the next session otherwise. This transfer occurred whether temporal cues were used for discrimination or when discrimination was based on spatial cues alone. Rats’ decision in each trial was based on the sensory cues acquired in that trial and on decisions and reward locations in previous trials. When sensory cues were acquired by body contacts, rat decisions relied more on the reward location in previous trials. Overall, the results suggest that rats can generalize the idea of relative object location across different body parts, while preferring to rely on whiskers-based localization, which occurs earlier and conveys higher resolution.

Visual detection of time-varying signals: Opposing biases and their timescales

Human visual perception is a complex, dynamic and fluctuating process. In addition to the incoming visual stimulus, it is affected by many other factors including temporal context, both external and internal to the observer. In this study we investigate the dynamic properties of psychophysical responses to a continuous stream of visual near-threshold detection tasks. We manipulate the incoming signals to have temporal structures with various characteristic timescales. Responses of human observers to these signals are analyzed using tools that highlight their dynamical features as well. Our experiments show two opposing biases that shape perceptual decision making simultaneously: positive recency, biasing towards repeated response; and adaptation, entailing an increased probability of changed response. While both these effects have been reported in previous work, our results shed new light on the timescales involved in these effects, and on their interplay with varying inputs. We find that positive recency is a short-term bias, inversely correlated with response time, suggesting it can be compensated by afterthought. Adaptation, in contrast, reflects trends over longer times possibly including multiple previous trials. Our entire dataset, which includes different input signal temporal structures, is consistent with a simple model with the two biases characterized by a fixed parameter set. These results suggest that perceptual biases are inherent features which are not flexible to tune to input signals.

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.

We demonstrate how people learn and adapt to changes to the probability of occurrence of one of two categories on decision-making under uncertainty. The study combined psychophysical behavioral tasks with computational modeling. We used two behavioral tasks: a typical forced-choice categorization task as well as one in which the observer specified the decision criterion to use on each trial before the stimulus was displayed. We formulated an ideal Bayesian change-point detection model and compared it to several alternative models. We found that the data are explained best by a model that estimates category probability based on recently observed exemplars with a bias towards equal probability. Our results suggest that the brain takes multiple relevant time scales into account when setting category expectations.

Sensorimotor priors are effector dependent

During sensorimotor tasks, subjects use sensory feedback but also prior information. It is often assumed that the sensorimotor prior is just given by the experiment and that the details for acquiring this prior (e.g., the effector) are irrelevant. However, recent research has suggested that the construction of priors is nontrivial. To test if the sensorimotor details matter for the construction of a prior, we designed two tasks that differ only in the effectors that subjects use to indicate their estimate. For both a typical reaching setting and an atypical wrist rotation setting, prior and feedback uncertainty matter as quantitatively predicted by Bayesian statistics. However, in violation of simple Bayesian models, the importance of the prior differs across effectors. Subjects overly rely on their prior in the typical reaching case compared with the wrist case. The brain is not naively Bayesian with a single and veridical prior. NEW & NOTEWORTHY Traditional Bayesian models often assume that we learn statistics of movements and use the information as a prior to guide subsequent movements. The effector is merely a reporting modality for information processing. We asked subjects to perform a visuomotor learning task with different effectors (finger or wrist). Surprisingly, we found that prior information is used differently between the effectors, suggesting that learning of the prior is related to the movement context such as the effector involved or that naive models of Bayesian behavior need to be extended.

Short-Term Influence of Recent Trial History on Perceptual Choice Changes with Stimulus Strength

Perceptual decisions, especially for difficult stimuli, can be influenced by choices and outcomes in previous trials. However, it is not well understood how stimulus strength modulates the temporal characteristics as well as the magnitude of trial history influence. We addressed this question using a contrast detection task in freely moving mice. We found that, at lower as compared to higher stimulus contrast, the current choice of the mice was more influenced by choices and outcomes in the past trials and the influence emerged from a longer history. To examine the neural basis of stimulus strength-dependent history influence, we recorded from the secondary motor cortex (M2), a prefrontal region that plays an important role in cue-guided actions and memory-guided behaviors. We found that more M2 neurons conveyed information about choices on the past two trials at lower than at higher contrast. Furthermore, history-trial activity in M2 was important for decoding upcoming choice at low contrast. Thus, trial history influence of perceptual choice is adaptive to the strength of sensory evidence, which may be important for action selection in a dynamic environment.

Optimality and heuristics in perceptual neuroscience

The foundation for modern understanding of how we make perceptual decisions about what we see or where to look comes from considering the optimal way to perform these behaviors. While statistical computation is useful for deriving the optimal solution to a perceptual problem, optimality requires perfect knowledge of priors and often complex computation. Accumulating evidence, however, suggests that optimal perceptual goals can be achieved or approximated more simply by human observers using heuristic approaches. Perceptual neuroscientists captivated by optimal explanations of sensory behaviors will fail in their search for the neural circuits and cortical processes that implement an optimal computation whenever that behavior is actually achieved through heuristics. This article provides a cross-disciplinary review of decision-making with the aim of building perceptual theory that uses optimality to set the computational goals for perceptual behavior but, through consideration of ecological, computational, and energetic constraints, incorporates how these optimal goals can be achieved through heuristic approximation.

Decay of internal reference information in duration discrimination: Intertrial interval modulates the Type B effect

Psychophysical evidence suggests that human perception of a stimulus is assimilated towards previous stimuli. The internal reference model (IRM) explains such assimilation through an internal reference (IR), which integrates past and present stimulus representations and thus might be conceived as a form of perceptual memory. In this study, we investigated whether the IR decays with time, as previously shown for perceptual memory representations in general. One specific prediction of IRM is higher discrimination sensitivity when a constant standard precedes rather than follows a variable comparison in a two-alternative forced-choice (2AFC) discrimination task. Furthermore, the magnitude of this so-called negative Type B effect should decrease with decreasing weighting of past stimulus information in the integration process. Therefore, decay of the IR should result in a reduced Type B effect. To examine this prediction, we carried out a 2AFC duration discrimination experiment with a short (1,600 ms) and a long (3,200 ms) intertrial interval (ITI). As expected, a reduced negative Type B effect was observed at the long compared with the short ITI, consistent with the idea that humans rely on the immediate past when evaluating current sensory input, however, less so when the IR incorporating the perceptual short-term memory representation of these past stimuli has already decayed.

Context Effects in the Judgment of Visual Relative-Frequency: Trial-by-Trial Adaptation and Non-linear Sequential Effect

Humans' judgment of relative-frequency, similar to their use of probability in decision-making, is often distorted as an inverted-S-shape curve-small relative-frequency overestimated and large relative-frequency underestimated. Here we investigated how the judgment of relative-frequency, despite its natural reference points (0 and 1) and stereotyped distortion, may adapt to the environmental statistics. The task was to report the relative-frequency of black (or white) dots in a visual array of black and white dots. We found that participants' judgment was distorted in the typical inverted-S-shape, but the distortion curve was influenced by both the central tendency and spread of the distribution of objective relative-frequencies: the lower the central tendency, the higher the overall judgment (contrast effect); the higher the spread, the more curved the inverted-S-shape (curvature effect). These context effects are in the spirit of efficient coding but opposite to what would be predicted by Bayesian inference. We further modeled the context effects on the level of individual trials, through which we found not only a trial-by-trial adaptation, but also the non-linear sequential effects that were recently reported mainly in circularly distributed visual stimuli.

Timing in the absence of a clock reset

Prominent models of time perception assume a reset of the timing mechanism with an explicit onset of the interval to be timed. Here we investigated the accuracy and precision of temporal estimations when the duration does not have such an explicit onset. Participants were tracking a disc moving on a circular path with varying speeds, and estimated the duration of one full revolution before the stimulus stopped. The onset of that revolution was either cued (explicit), or undetermined until the stimulus stopped (implicit). Reproduced duration was overestimated for short and underestimated for long durations, and variability of the estimates scaled with the duration in both temporal conditions. However, the bias was more pronounced in the implicit condition. In addition, if the stimulus path was partially occluded, duration of the occluded motion was correctly estimated. In a second experiment, we compared the precision in the explicit and implicit conditions by asking participants to discriminate the duration of one revolution before the stimulus stopped to that of a static stimulus presentation in a forced-choice task. Sensitivity of discrimination was worse in the implicit onset condition, but surprisingly, still comparable to the explicit condition. In summary, the estimates follow principles described in prospective timing paradigms, although not knowing beforehand when to start timing decreases sensitivity of temporal estimations. Since in naturalistic contexts, we often do not know in advance which durations might be relevant to estimate, the simple task presented here could become a valuable tool for testing models of temporal estimation.

Adaptive and Selective Time Averaging of Auditory Scenes

To overcome variability, estimate scene characteristics, and compress sensory input, perceptual systems pool data into statistical summaries. Despite growing evidence for statistical representations in perception, the underlying mechanisms remain poorly understood. One example of such representations occurs in auditory scenes, where background texture appears to be represented with time-averaged sound statistics. We probed the averaging mechanism using "texture steps"-textures containing subtle shifts in stimulus statistics. Although generally imperceptible, steps occurring in the previous several seconds biased texture judgments, indicative of a multi-second averaging window. Listeners seemed unable to willfully extend or restrict this window but showed signatures of longer integration times for temporally variable textures. In all cases the measured timescales were substantially longer than previously reported integration times in the auditory system. Integration also showed signs of being restricted to sound elements attributed to a common source. The results suggest an integration process that depends on stimulus characteristics, integrating over longer extents when it benefits statistical estimation of variable signals and selectively integrating stimulus components likely to have a common cause in the world. Our methodology could be naturally extended to examine statistical representations of other types of sensory signals.

Shorter cortical adaptation in dyslexia is broadly distributed in the superior temporal lobe and includes the primary auditory cortex

Studies of the performance of individuals with dyslexia in perceptual tasks suggest that their implicit inference of sound statistics is impaired. Previously, using two-tone frequency discrimination, we found that the effect of previous trials' frequencies on the judgments of individuals with dyslexia decays faster than the effect on controls' judgments, and that the adaptation (decrease of neural response to repeated stimuli) of their ERP responses to tones is shorter (Jaffe-Dax et al., 2017). Here, we show the cortical distribution of these abnormal dynamics of adaptation using fast-acquisition fMRI. We find that faster decay of adaptation in dyslexia is widespread, although the most significant effects are found in the left superior temporal lobe, including the auditory cortex. This broad distribution suggests that the faster decay of implicit memory of individuals with dyslexia is a general characteristic of their cortical dynamics, which also affects sensory cortices.

Suboptimality in perceptual decision making

Human perceptual decisions are often described as optimal. Critics of this view have argued that claims of optimality are overly flexible and lack explanatory power. Meanwhile, advocates for optimality have countered that such criticisms single out a few selected papers. To elucidate the issue of optimality in perceptual decision making, we review the extensive literature on suboptimal performance in perceptual tasks. We discuss eight different classes of suboptimal perceptual decisions, including improper placement, maintenance, and adjustment of perceptual criteria; inadequate tradeoff between speed and accuracy; inappropriate confidence ratings; misweightings in cue combination; and findings related to various perceptual illusions and biases. In addition, we discuss conceptual shortcomings of a focus on optimality, such as definitional difficulties and the limited value of optimality claims in and of themselves. We therefore advocate that the field drop its emphasis on whether observed behavior is optimal and instead concentrate on building and testing detailed observer models that explain behavior across a wide range of tasks. To facilitate this transition, we compile the proposed hypotheses regarding the origins of suboptimal perceptual decisions reviewed here. We argue that verifying, rejecting, and expanding these explanations for suboptimal behavior - rather than assessing optimality per se - should be among the major goals of the science of perceptual decision making.

A Switching Observer for Human Perceptual Estimation

Human perceptual inference has been fruitfully characterized as a normative Bayesian process in which sensory evidence and priors are multiplicatively combined to form posteriors from which sensory estimates can be optimally read out. We tested whether this basic Bayesian framework could explain human subjects' behavior in two estimation tasks in which we varied the strength of sensory evidence (motion coherence or contrast) and priors (set of directions or orientations). We found that despite excellent agreement of estimates mean and variability with a Basic Bayesian observer model, the estimate distributions were bimodal with unpredicted modes near the prior and the likelihood. We developed a model that switched between prior and sensory evidence rather than integrating the two, which better explained the data than the Basic and several other Bayesian observers. Our data suggest that humans can approximate Bayesian optimality with a switching heuristic that forgoes multiplicative combination of priors and likelihoods.