Serial Dependence Research Articles

Dynamic predictive templates in perception

Hallucinations are vivid and transient experiences of objects, such as images or sounds, that occur in the absence of a corresponding stimulus.1,2,3,4,5,6,7,8,9 To understand the neurocomputational mechanisms of hallucinations, cognitive neuroscience has focused on experiments that induce false alarms (FAs) in healthy participants,1,2,3,4,5,9 psychosis-prone individuals,1,3,4 and patients diagnosed with schizophrenia.5 FAs occur when participants make decisions about difficult-to-detect stimuli and indicate the presence of a signal that was, in fact, not presented. Since FAs are, at heart, reports, they must meet two criteria to serve as an experimental proxy for hallucinations: first, FAs should reflect perceptual states that are characterized by specific contents10,11,12 (criterion 1). Second, FAs should occur on a timescale compatible with the temporal dynamics of hallucinations13,14 (criterion 2). In this work, we combined a classification image approach15 with hidden Markov models16 to show that FAs can match the perceptual and temporal characteristics of hallucinations. We asked healthy human participants to discriminate visual stimuli from noise and found that FAs were more likely to occur during an internal mode of sensory processing, a minute-long state of the brain during which perception is strongly biased toward previous experiences17 (serial dependency). Our results suggest that hallucinations are driven by dynamic predictive templates that transform noise into transient, coherent, and meaningful perceptual experiences.

Super recognizers: Increased sensitivity or reduced biases? Insights from serial dependence.

Super recognizers (SRs) are people that exhibit a naturally occurring superiority for processing facial identity. Despite the increase of SR research, the mechanisms underlying their exceptional abilities remain unclear. Here, we investigated whether the enhanced facial identity processing of SRs could be attributed to the lack of sequential effects, such as serial dependence. In serial dependence, perception of stimulus features is assimilated toward stimuli presented in previous trials. This constant error in visual perception has been proposed as a mechanism that promotes perceptual stability in everyday life. We hypothesized that an absence of this constant source of error in SRs could account for their superior processing-potentially in a domain-general fashion. We tested SRs (n = 17) identified via a recently proposed diagnostic framework (Ramon, 2021) and age-matched controls (n = 20) with two experiments probing serial dependence in the face and shape domains. In each experiment, observers were presented with randomly morphed face identities or shapes and were asked to adjust a face's identity or a shape to match the stimulus they saw. We found serial dependence in controls and SRs alike, with no difference in its magnitude across groups. Interestingly, we found that serial dependence impacted the performance of SRs more than that of controls. Taken together, our results show that enhanced face identity processing skills in SRs cannot be attributed to the lack of serial dependence. Rather, serial dependence, a beneficial nested error in our visual system, may in fact further stabilize the perception of SRs and thus enhance their visual processing proficiency.

Visual continuum in non-human animals: serial dependence revealed in dogs.

Serial dependence is a recently described phenomenon by which the perceptual evaluation of a stimulus is biased by a previously attended one. By integrating stimuli over time, serial dependence is believed to ensure a stable conscious experience. Despite increasing studies in humans, it is unknown if the process occurs also in other species. Here, we assessed whether serial dependence occurs in dogs. To this aim, dogs were trained on a quantity discrimination task before being presented with a discrimination where one of the discriminanda was preceded by a task-irrelevant stimulus. If dogs are susceptible to serial dependence, the task-irrelevant stimulus was hypothesized to influence the perception of the subsequently presented quantity. Our results revealed that dogs perceived the currently presented quantity to be closer to the one presented briefly before, in accordance with serial dependence. The direction and strength of the effect were comparable to those observed in humans. Data regarding dogs' attention during the task suggest that dogs used two different quantity estimation mechanisms, an indication of a higher cognitive mechanism involved in the process. The present results are the first empirical evidence that serial dependence extends beyond humans, suggesting that the mechanism is shared by phylogenetically distant mammals.

The neural representation of stereotype content

Judgments about social groups are characterized by their position in a representational space defined by two axes, warmth and competence. We examined serial dependence (SD) in evaluations of warmth and competence while measuring participants’ electroencephalographic (EEG) activity, as a means to address the independence between these two psychological axes. SD is the attraction of perceptual reports towards things seen in the recent past and has recently been intensely investigated in vision. SD occurs at multiple levels of visual processing, from basic features to meaningful objects. The current study aims to (1) measure whether SD occurs between non-visual objects, in particular social groups and (2) uncover the neural correlates of social group evaluation and SD using EEG. Participants’ judgments about social groups such as “nurses” or “accountants” were serially dependent, but only when the two successive groups were close in representational space. The pattern of results argues in favor of a non-separability between the two axes, because groups nearby on one dimension but far on the other were not subject to SD, even though that other dimension was irrelevant to the task at hand. Using representational similarity analysis, we found a brain signature that differentiated social groups as a function of their position in the representational space. Our results thus argue that SD may be a ubiquitous cognitive phenomenon, that social evaluations are serially dependent, and that reproducible neural signatures of social evaluations can be uncovered.

Serial dependence: A matter of memory load

In serial dependence, perceptual decisions are biased towards stimuli encountered in the recent past. Here, we investigate whether and how serial dependence is affected by the availability of visual working memory (VWM) resources. In two experiments, participants reproduced the orientation of a series of stimuli. On alternating trials, we included an additional VWM task with randomly varying levels of load. Serial dependence was not only affected by the additional load task but also clearly modulated by the level of load: a high load in the previous trial reduced serial dependence while a high load in the present increased it. These results were independent of the effects of VWM load on the precision of reproduction responses. Our findings provide new insights into the mechanisms that may regulate serial dependence, revealing its intimate link with VWM resources. Significance statementOur perception, thoughts, and behavior are continuously influenced by recent events. For instance, the way we process and understand current visual information depends on what we have seen in the preceding seconds, a phenomenon known as serial dependence. The precise mechanisms and factors involved in serial dependence are still unclear. Here, we demonstrated that working memory resources are a crucial component. Specifically, when we are currently experiencing a heavy memory load, the influence of prior stimuli becomes stronger. Conversely, when prior stimuli were shown under a high memory load, their influence was reduced. These findings highlight the importance of working memory resources in shaping our interpretation of the present based on the recent past.

Stochastic hyperplane-based ranks and their use in multivariate portmanteau tests

The article proposes and justifies an optimal rank-based portmanteau test of multivariate elliptical strict white noise against multivariate serial dependence. It is based on new stochastic hyperplane-based ranks that are simpler and easier to compute than other usable hyperplane-based competitors and still share with them many good properties such as their distribution-free nature, affine invariance, efficiency, robustness and weak moment assumptions. The finite-sample performance of the portmanteau test is illustrated empirically in a small Monte Carlo simulation study.

Intact Serial Dependence in Schizophrenia: Evidence from an Orientation Adjustment Task

Abstract Background and Hypothesis For a long time, it was proposed that schizophrenia (SCZ) patients rely more on sensory input and less on prior information, potentially leading to reduced serial dependence—ie, a reduced influence of prior stimuli in perceptual tasks. However, existing evidence is constrained to a few paradigms, and whether reduced serial dependence reflects a general characteristic of the disease remains unclear. Study Design We investigated serial dependence in 26 SCZ patients and 27 healthy controls (CNT) to evaluate the influence of prior stimuli in a classic visual orientation adjustment task, a paradigm not previously tested in this context. Study Results As expected, the CNT group exhibited clear serial dependence, with systematic biases toward the orientation of stimuli shown in the preceding trials. Serial dependence in SCZ patients was largely comparable to that in the CNT group. Conclusions These findings challenge the prevailing notion of reduced serial dependence in SCZ, suggesting that observed differences between healthy CNT and patients may depend on aspects of perceptual or cognitive processing that are currently not understood.

Integration of history information Drives Serial Dependence and Stabilizes Working Memory Representations.

Serial dependence has shown seemingly contradictory effects on visual perception and working memory. While serial dependence promotes perpetual and mnemonic stability, it biases behavioral reports toward prior information. The neural mechanisms that drive both biasing and adaptive stabilizing effects are not well understood. We proposed and tested a reactivation and integration mechanism that can account for these contradictory effects. We used multivariate pattern analyses of EEG data (26 human participants, 17 females, 9 males) to examine the reactivation of prior reported orientation during the delay period of a visual working memory task. The reactivation strength of prior reports, but not prior sensory items, was predictive of the magnitude of serial dependency biases. These reactivated representations integrated with the representation of the current memory item and improved the ability to decode the current contents of memory. Overall, our data provide convergent evidence suggesting that prior reports in a visual working memory task are reactivated on the subsequent trial and become integrated with current memory representations. This similarity-dependent reactivation mechanism drives both report biasing and stabilization effects attributed to serial dependence in working memory.

Model selection for generalized linear models with weak factors

AbstractThe literature has witnessed an upsurge of interest in model selection in diverse fields and optimization applications. Despite the substantial progress, model selection remains a significant challenge when covariates are highly correlated, particularly within economic and financial datasets that exhibit cross‐sectional and serial dependency. In this paper, we introduce a novel methodology named factor augmented regularized model selection with weak factors (WeakFARM) for generalized linear models in the presence of correlated covariates with weak latent factor structure. By identifying weak latent factors and idiosyncratic components and employing them as predictors, WeakFARM converts the challenge from model selection with highly correlated covariates to that with weakly correlated ones. Furthermore, we develop a variable screening method based on the proposed WeakFARM method. Comprehensive theoretical guarantees including estimation consistency, model selection consistency and sure screening property are also provided. We demonstrate the effectiveness of our approach by extensive simulation studies and a real data application in economic forecasting.

Serial dependence requires visual awareness: Evidence from continuous flash suppression.

The visual system often undergoes a relatively stable perception even in a noisy visual environment. This crucial function was reflected in a visual perception phenomenon-serial dependence, in which recent stimulus history systematically biases current visual decisions. Although serial dependence effects have been revealed in numerous studies, few studies examined whether serial dependence would require visual awareness. By using the continuous flash suppression (CFS) technique to render grating stimuli invisible, we investigated whether serial dependence effects could emerge at the unconscious levels. In an orientation adjustment task, subjects viewed a randomly oriented grating and reported their orientation perception via an adjustment response. Subjects performed a series of three type trial pairs. The first two trial pairs, in which subjects were instructed to make a response or no response toward the first trial of the pairs, respectively, were used to measure serial dependence at the conscious levels; the third trial pair, in which the grating stimulus in the first trial of the pair was masked by a CFS stimulus, was used to measure the serial dependence at the unconscious levels. One-back serial dependence effects for the second trial of the pairs were evaluated. We found significant serial dependence effects at the conscious levels, whether absence (Experiment 1) or presence (Experiment 2) of CFS stimuli, but failed to find the effects at the unconscious levels, corroborating the view that serial dependence requires visual awareness.

Markov switching stereotype logit models for longitudinal ordinal data affected by unobserved heterogeneity in responding behavior

AbstractWhen asked to assess their opinion about attitudes or perceptions on Likert-scale, respondents often endorse the midpoint or extremes of the scale and agree or disagree regardless of the content. These responding behaviors are known in the psychometric literature as middle, extremes, aquiescence and disacquiescence response styles that generally introduce bias in the results. One of the key motivations behind our approach is to account for these attitudes and how they evolve over time. The novelty of our proposal, in the context of longitudinal ordered categorical data, is in considering simultaneously the temporal dynamics of the responses (observable ordinal variables) and unobservable answering behaviors, possibly influenced by response styles, through a Markov switching logit model with two latent components. One component accommodates serial dependence and respondent’s unobserved heterogeneity, the other component determines the responding attitude (due to response styles or not). The dependence of the responses on covariates is modelled by a stereotype logit model with parameters varying according to the two latent components. The stereotype logit model is adopted because it is a flexible extension of the proportional odds logit model that retains the advantage of using a single parameter to describe a regressor effect. In the paper, a new interpretation of the parameters of the stereotype model is given by defining the allocation sets as intervals of values of the linear predictor that identify the most probable response. Unobserved heterogeneity, serial dependence and tendency to response style are modelled through our approach on longitudinal data, collected by the Bank of Italy.

Tactile adaptation to orientation produces a robust tilt aftereffect and exhibits crossmodal transfer when tested in vision

Orientation processing is one of the most fundamental functions in both visual and somatosensory perception. Converging findings suggest that orientation processing in both modalities is closely linked: somatosensory neurons share a similar orientation organisation as visual neurons, and the visual cortex has been found to be heavily involved in tactile orientation perception. Hence, we hypothesized that somatosensation would exhibit a similar orientation adaptation effect, and this adaptation effect would be transferable between the two modalities, considering the above-mentioned connection. The tilt aftereffect (TAE) is a demonstration of orientation adaptation and is used widely in behavioural experiments to investigate orientation mechanisms in vision. By testing the classic TAE paradigm in both tactile and crossmodal orientation tasks between vision and touch, we were able to show that tactile perception of orientation shows a very robust TAE, similar to its visual counterpart. We further show that orientation adaptation in touch transfers to produce a TAE when tested in vision, but not vice versa. Additionally, when examining the test sequence following adaptation for serial effects, we observed another asymmetry between the two conditions where the visual test sequence displayed a repulsive intramodal serial dependence effect while the tactile test sequence exhibited an attractive serial dependence. These findings provide concrete evidence that vision and touch engage a similar orientation processing mechanism. However, the asymmetry in the crossmodal transfer of TAE and serial dependence points to a non-reciprocal connection between the two modalities, providing further insights into the underlying processing mechanism.

Dynamic connectedness between FinTech and energy markets: Evidence from fat tails, serial dependence, and Bayesian approach

In a complex global environment, modeling the relationships among several markets and asset classes has become more challenging. Literature strives to provide conclusive evidence due to system complexities. Therefore, we investigate the dynamic relationship between Fintech and energy sectors using fat tails, serial dependence, and the Bayesian approach from May 1, 2019, to October 28, 2022. Results unveil significant temporal variations in network interconnections, with an evident increase in interlinkages across short, medium, and long durations due to transient market events. The COVID-19 pandemic and the onset of the Russia-Ukraine conflict have substantially altered the long-term relational dynamics within these networks. An analysis of net directional linkages reveals a pivotal shift in market roles—from being predominantly shock recipients to becoming shock transmitters—highlighted during the COVID-19 pandemic and the initial phase of the Russia-Ukraine War. Initial observations indicate that, amid the global impact of COVID-19, Fintech markets absorbed shocks through investments in green bonds and renewable energy sources like wind, solar, and clean energy. These findings suggest that while Fintech consistently acts as a shock absorber in long-term scenarios, it assumes the role of a shock transmitter during adverse economic states.

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.

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.

Continuity fields enhance visual perception through positive serial dependence

Continuity fields enhance visual perception through positive serial dependence

Temporal integration of target features across and within trials in the attentional blink.

Attentional blink research has typically investigated attentional limitations in multiple target processing. The current study investigated the temporal integration of target features in the attentional blink. Across two experiments, we demonstrated that the orientation estimations of individual target items in the attentional blink paradigm were systematically biased. Specifically, there was evidence for both within- and across-trial biases, revealing a general bias towards previously presented stimuli. Moreover, both biases were found to be more salient for targets suffering from the attentional blink. The current study is the first to demonstrate an across-trial bias in responses in the attentional blink paradigm. This set of findings is in line with the literature, suggesting that the human visual system can implicitly summarize information presented over time, which may lead to biases. By investigating temporal integration in the attentional blink, we have been able to address the modulatory role of attention on biases imposed by the implicit temporal effects in estimation tasks. Our findings may inform future research on attentional blink, serial dependence, and ensemble perception.

Estimating the size of a closed population by modeling latent and observed heterogeneity.

The paper extends the empirical likelihood (EL) approach of Liu etal. to a new and very flexible family of latent class models for capture-recapture data also allowing for serial dependence on previous capture history, conditionally on latent type and covariates. The EL approach allows to estimate the overall population size directly rather than by adding estimates conditional to covariate configurations. A Fisher-scoring algorithm for maximum likelihood estimation is proposed and a more efficient alternative to the traditional EL approach for estimating the non-parametric component is introduced; this allows us to show that the mapping between the non-parametric distribution of the covariates and the probabilities of being never captured is one-to-one and strictly increasing. Asymptotic results are outlined, and a procedure for constructing profile likelihood confidence intervals for the population size is presented. Two examples based on real data are used to illustrate the proposed approach and a simulation study indicates that, when estimating the overall undercount, the method proposed here is substantially more efficient than the one based on conditional maximum likelihood estimation, especially when the sample size is not sufficiently large.

Opposing serial dependencies revealed for sequences of auditory emotional stimuli.

Our percept of the world is not solely determined by what we perceive and process at a given moment in time, but also depends on what we processed recently. In the present study, we investigate whether the perceived emotion of a spoken sentence is contingent upon the emotion of an auditory stimulus on the preceding trial (i.e., serial dependence). Thereto, participants were exposed to spoken sentences that varied in emotional affect by changing the prosody that ranged from 'happy' to 'fearful'. Participants were instructed to rate the emotion. We found a positive serial dependence for emotion processing whereby the perceived emotion was biased towards the emotion on the preceding trial. When we introduced 'no-go' trials (i.e., no rating was required), we found a negative serial dependence when participants knew in advance to withhold their response on a given trial (Experiment 2) and a positive serial dependence when participants received the information to withhold their response after the stimulus presentation (Experiment 3). We therefore established a robust serial dependence for emotion processing in speech and introduce a methodology to disentangle perceptual from post-perceptual processes. This approach can be applied to the vast majority of studies investigating sequential dependencies to separate positive from negative serial dependence.

Conflicts between short- and long-term experiences affect visual perception through modulating sensory or motor response systems: Evidence from Bayesian inference models

The independent effects of short- and long-term experiences on visual perception have been discussed for decades. However, no study has investigated whether and how these experiences simultaneously affect our visual perception. To address this question, we asked participants to estimate their self-motion directions (i.e., headings) simulated from optic flow, in which a long-term experience learned in everyday life (i.e., straight-forward motion being more common than lateral motion) plays an important role. The headings were selected from three distributions that resembled a peak, a hill, and a flat line, creating different short-term experiences. Importantly, the proportions of headings deviating from the straight-forward motion gradually increased in the peak, hill, and flat distributions, leading to a greater conflict between long- and short-term experiences. The results showed that participants biased their heading estimates towards the straight-ahead direction and previously seen headings, which increased with the growing experience conflict. This suggests that both long- and short-term experiences simultaneously affect visual perception. Finally, we developed two Bayesian models (Model 1 vs. Model 2) based on two assumptions that the experience conflict altered the likelihood distribution of sensory representation or the motor response system. The results showed that both models accurately predicted participants' estimation biases. However, Model 1 predicted a higher variance of serial dependence compared to Model 2, while Model 2 predicted a higher variance of the bias towards the straight-ahead direction compared to Model 1. This suggests that the experience conflict can influence visual perception by affecting both sensory and motor response systems. Taken together, the current study systematically revealed the effects of long- and short-term experiences on visual perception and the underlying Bayesian processing mechanisms.