Serial dependence does not originate from low-level visual processing

Ceylan, Gizay; Herzog, Michael H.; Pascucci, David

doi:10.1016/j.cognition.2021.104709

Cited by 74 publications

(158 citation statements)

References 34 publications

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“…In this view, SD in perceptual biases is a sequential effect of decisions on a specific dimension of sensory input, which may be independent of all other aspects of stimuli 17 . Interestingly, this would even predict SD for completely different stimuli, provided that they share a common task-relevant dimension 29 .…”

Section: Discussionmentioning

confidence: 99%

Serial dependence and representational momentum in single-trial perceptual decisions

Pascucci

Plomp

2021

Sci Rep

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The human brain has evolved to predict and anticipate environmental events from their temporal dynamics. Predictions can bias perception toward the recent past, particularly when the environment contains no foreseeable changes, but can also push perception toward future states of sensory input, like when anticipating the trajectory of moving objects. Here, we show that perceptual decisions are simultaneously influenced by both past and future states of sensory signals. Using an orientation adjustment task, we demonstrate that single-trial errors are displaced toward previous features of behaviorally relevant stimuli and, at the same time, toward future states of dynamic sensory signals. These opposing tendencies, consistent with decisional serial dependence and representational momentum, involve different types of processing: serial dependence occurs beyond objecthood whereas representational momentum requires the representation of a single object with coherent dynamics in time and space. The coexistence of these two phenomena supports the independent binding of stimuli and decisions over time.

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Section: Discussionmentioning

confidence: 99%

Serial dependence and representational momentum in single-trial perceptual decisions

Pascucci

Plomp

2021

Sci Rep

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“…In support of this view, it has been shown that higher confidence levels on the previous trial response increase the serial dependence effect even when the previous trial stimulus uncertainty is the same (Samaha et al, 2019). In addition, manipulating the uncertainty of the stimulus in the previous trial does not affect serial dependence (Ceylan et al, 2021). This is an interesting topic and it remains an open question how much the uncertainty stored in implicit memory relies on the uncertainty of the previous trial sensory information.…”

Section: Discussionmentioning

confidence: 96%

“…There is a growing interest in the serial dependence literature to identify the source of serial dependence: whether it comes from sensory signals (Cicchini et al, 2017;, biased percepts (Cicchini et al, 2021;Collins, 2020;Fornaciai & Park, 2020), decision processes (Ceylan et al, 2021;Fischer et al, 2020;Fritsche et al, 2017;Pascucci et al, 2019;Roseboom, 2019) or motor responses (St. John-Saaltink et al, 2016). A limitation of the present work is that speed, time-to-contact, and motor responses are correlated, preventing us from pinpointing the source of serial dependence in the coincident timing task.…”

Section: Discussionmentioning

confidence: 99%

Temporal dynamics of implicit memory underlying serial dependence

et al. 2021

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Serial dependence is the effect in which the immediately preceding trial influences participants' responses to the current stimulus. But for how long does this bias last in the absence of interference from other stimuli? Here, we had 20 healthy young adult participants (12 women) perform a coincident timing task using different inter-trial intervals to characterize the serial dependence effect as the time between trials increases. Our results show that serial dependence abruptly decreases from 0.1 s to 1 s inter-trial interval, but it remains pronounced after that for up to 8 s. In addition, participants' response variability slightly decreases over longer intervals. We discuss these results in light of recent models suggesting that serial dependence might rely on a short-term memory trace kept through changes in synaptic weights, which might explain its long duration and apparent stability over time.

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“…The amplitude parameter a was taken as the strength of the serial dependence bias, indicating the degree to which participants' judgments of each facial trait were biased towards the direction of the previous faces ( Liberman et al, 2014 ; Manassi et al, 2017 ; Fritsche et al, 2020 ). Here, we averaged the ratings of all participants for each facial trait and fitted the DoG function, which is a default protocol used by previous studies ( Bliss et al, 2017 ; Fritsche et al, 2020 ; Ceylan et al, 2021 ) because it can systematically test serial dependence effect by measuring how the group average of response errors changes as a function of the difference between the previous and current facial trait value ( Bliss et al, 2017 ; Fritsche et al, 2020 ; Ceylan et al, 2021 ). The value of parameter a of the DoG can reveal the level of serial dependence effect.…”

Section: Discussionmentioning

confidence: 99%

“…All of them were naïve to the purpose of the experiment and provided informed consent, with ethics approved by the Ethics Committee at Soochow University, China. At the beginning, we chose 30 as the sample size (considering the dramatic different in experimental design and the purpose of the current study, we adapted the sample size of previous studies; Fritsche et al, 2020 ; Ceylan, Herzog, & Pascucci, 2021 ). However, two more subjects signed in before we closed the registration, so we still tested them.…”

Section: Methodsmentioning

confidence: 99%

A general serial dependence among various facial traits: Evidence from Markov Chain and derivative of Gaussian

Ying

2021

Journal of Vision

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The human vision system can extract a stable representation of the always-changing visual world. However, the mechanism underlying such perceptual continuity remains unclear. A possible candidate is the serial dependence: visual perception of an object is positively biased toward the visual input from the recent past. Does the visual system use one pattern of serial dependence for general purposes? Or different patterns of serial dependence for different visual tasks? Because different social facial traits (e.g., trustworthiness and dominance) are dissociable, it is reasonable to assume that the perception of different facial characteristics would require different patterns of serial dependences. In this study, we examine the existence and the similarities of the serial dependence(s) in the evaluation of seven facial characteristics (i.e., attractiveness, trustworthiness, confidence, dominance, intelligence, age, and aggressiveness). The convergent evidence from conventional Derivative of Gaussian fitting and Markov Chain modeling demonstrated that (1) serial dependence exists in judgments of all seven social facial characteristic, (2) the serial dependences of them are highly similar, and (3) the serial dependence follows the efficient coding. Thus it is highly possible that there exists a general serial dependence mechanism for (at least high-level) vision processing. Moreover, we used the Markov Chain modeling to better describe the transitional pattern of serial dependence, which is a kind of Markov process. These findings may shed light on future works regarding serial dependence, as well as face perception.

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Serial dependence does not originate from low-level visual processing

Cited by 74 publications

References 34 publications

Serial dependence and representational momentum in single-trial perceptual decisions

Serial dependence and representational momentum in single-trial perceptual decisions

Temporal dynamics of implicit memory underlying serial dependence

A general serial dependence among various facial traits: Evidence from Markov Chain and derivative of Gaussian

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