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  • 1.
    Bhardwaj, Manisha
    et al.
    University of Houston.
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Ma, Wei Ji
    New York University.
    Josić, Krešimir
    University of Houston.
    Do people take stimulus correlations into account in visual search?2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 3, article id e0149402Article in journal (Refereed)
    Abstract [en]

    In laboratory visual search experiments, distractors are often statistically independent of each other. However, stimuli in more naturalistic settings are often correlated and rarely independent. Here, we examine whether human observers take stimulus correlations into account in orientation target detection. We find that they do, although probably not optimally. In particular, it seems that low distractor correlations are overestimated. Our results might contribute to bridging the gap between artificial and natural visual search tasks.

  • 2. Hannus, Aave
    et al.
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Bekkering, Harold
    Roerdink, Jos B T M
    Cornelissen, Frans W
    Visual search near threshold: Some features are more equal than others.2006In: Journal of Vision, ISSN 1534-7362, E-ISSN 1534-7362, Vol. 6, no 4Article in journal (Refereed)
    Abstract [en]

    While searching for objects, we combine information from multiple visual modalities. Classical theories of visual search assume that features are processed independently prior to an integration stage. Based on this, one would predict that features that are equally discriminable in single feature search should remain so in conjunction search. We test this hypothesis by examining whether search accuracy in feature search predicts accuracy in conjunction search. Subjects searched for objects combining color and orientation or size; eye movements were recorded. Prior to the main experiment, we matched feature discriminability, making sure that in feature search, 70% of saccades were likely to go to the correct target stimulus. In contrast to this symmetric single feature discrimination performance, the conjunction search task showed an asymmetry in feature discrimination performance: In conjunction search, a similar percentage of saccades went to the correct color as in feature search but much less often to correct orientation or size. Therefore, accuracy in feature search is a good predictor of accuracy in conjunction search for color but not for size and orientation. We propose two explanations for the presence of such asymmetries in conjunction search: the use of conjunctively tuned channels and differential crowding effects for different features.

  • 3.
    Keshvari, Shaiyan
    et al.
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Van den Berg, Ronald
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Ma, Wei Ji
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    No evidence for an item limit in change detection2013In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 9, no 2, article id e1002927Article in journal (Refereed)
    Abstract [en]

    Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items (“item-limit models”). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size (“continuous-resource models”). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

  • 4.
    Keshvari, Shaiyan
    et al.
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Van den Berg, Ronald
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Ma, Wei Ji
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    No evidence for an item limit in change detection2013In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 9, no 2Article in journal (Refereed)
    Abstract [en]

    Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models"). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models"). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

  • 5.
    Keshvari, Shaiyan
    et al.
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Van den Berg, Ronald
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Ma, Wei Ji
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Probabilistic computation in human perception under variability in encoding precision2012In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 7, no 6, article id e40216Article in journal (Refereed)
    Abstract [en]

    A key function of the brain is to interpret noisy sensory information. To do so optimally, observers must, in many tasks, take into account knowledge of the precision with which stimuli are encoded. In an orientation change detection task, we find that encoding precision does not only depend on an experimentally controlled reliability parameter (shape), but also exhibits additional variability. In spite of variability in precision, human subjects seem to take into account precision near-optimally on a trial-to-trial and item-to-item basis. Our results offer a new conceptualization of the encoding of sensory information and highlight the brain's remarkable ability to incorporate knowledge of uncertainty during complex perceptual decision-making.

  • 6. Ma, Wei Ji
    et al.
    Navalpakkam, Vidhya
    Beck, Jeffrey M
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Pouget, Alexandre
    Behavior and neural basis of near-optimal visual search.2011In: Nature Neuroscience, ISSN 1097-6256, E-ISSN 1546-1726, Vol. 14, no 6Article in journal (Refereed)
    Abstract [en]

    The ability to search efficiently for a target in a cluttered environment is one of the most remarkable functions of the nervous system. This task is difficult under natural circumstances, as the reliability of sensory information can vary greatly across space and time and is typically a priori unknown to the observer. In contrast, visual-search experiments commonly use stimuli of equal and known reliability. In a target detection task, we randomly assigned high or low reliability to each item on a trial-by-trial basis. An optimal observer would weight the observations by their trial-to-trial reliability and combine them using a specific nonlinear integration rule. We found that humans were near-optimal, regardless of whether distractors were homogeneous or heterogeneous and whether reliability was manipulated through contrast or shape. We present a neural-network implementation of near-optimal visual search based on probabilistic population coding. The network matched human performance.

  • 7. Ma, Wei Ji
    et al.
    Shen, Shan
    Dziugaite, Gintare
    van den Berg, Ronald
    Baylor College of Medicine, Houston, TX, United States; University of Cambridge, Cambridge, UK.
    Requiem for the max rule?2015In: Vision Research, ISSN 0042-6989, E-ISSN 1878-5646, Vol. 116, no Pt B, p. 179-193Article in journal (Refereed)
    Abstract [en]

    In tasks such as visual search and change detection, a key question is how observers integrate noisy measurements from multiple locations to make a decision. Decision rules proposed to model this process have fallen into two categories: Bayes-optimal (ideal observer) rules and ad-hoc rules. Among the latter, the maximum-of-outputs (max) rule has been the most prominent. Reviewing recent work and performing new model comparisons across a range of paradigms, we find that in all cases except for one, the optimal rule describes human data as well as or better than every max rule either previously proposed or newly introduced here. This casts doubt on the utility of the max rule for understanding perceptual decision-making.

  • 8.
    Mazyar, Helga
    et al.
    Baylor Coll Med, Houston, TX 77030 USA.
    Van den Berg, Ronald
    Baylor Coll Med, Houston, TX 77030 USA.
    Ma, Wei Ji
    Baylor Coll Med, Houston, TX 77030 USA.
    Does precision decrease with set size?2012In: Journal of Vision, ISSN 1534-7362, E-ISSN 1534-7362, Vol. 12, no 6, article id 10Article in journal (Refereed)
    Abstract [en]

    The brain encodes visual information with limited precision. Contradictory evidence exists as to whether the precision with which an item is encoded depends on the number of stimuli in a display (set size). Some studies have found evidence that precision decreases with set size, but others have reported constant precision. These groups of studies differed in two ways. The studies that reported a decrease used displays with heterogeneous stimuli and tasks with a short-term memory component, while the ones that reported constancy used homogeneous stimuli and tasks that did not require short-term memory. To disentangle the effects of heterogeneity and short-memory involvement, we conducted two main experiments. In Experiment 1, stimuli were heterogeneous, and we compared a condition in which target identity was revealed before the stimulus display with one in which it was revealed afterward. In Experiment 2, target identity was fixed, and we compared heterogeneous and homogeneous distractor conditions. In both experiments, we compared an optimal-observer model in which precision is constant with set size with one in which it depends on set size. We found that precision decreases with set size when the distractors are heterogeneous, regardless of whether short-term memory is involved, but not when it is homogeneous. This suggests that heterogeneity, not short-term memory, is the critical factor. In addition, we found that precision exhibits variability across items and trials, which may partly be caused by attentional fluctuations.

  • 9.
    Mazyar, Helga
    et al.
    Baylor Coll Med, Houston, TX 77030 USA.
    Van den Berg, Ronald
    Baylor Coll Med, Houston, TX 77030 USA.
    Seilheimer, Robert L.
    Baylor Coll Med, Houston, TX 77030 USA.
    Ma, Wei Ji
    Baylor Coll Med, Houston, TX 77030 USA.
    Independence is elusive: set size effects on encoding precision in visual search2013In: Journal of Vision, ISSN 1534-7362, E-ISSN 1534-7362, Vol. 13, no 5, article id 8Article in journal (Refereed)
    Abstract [en]

    Looking for a target in a visual scene becomes more difficult as the number of stimuli increases. In a signal detection theory view, this is due to the cumulative effect of noise in the encoding of the distractors, and potentially on top of that, to an increase of the noise (i.e., a decrease of precision) per stimulus with set size, reflecting divided attention. It has long been argued that human visual search behavior can be accounted for by the first factor alone. While such an account seems to be adequate for search tasks in which all distractors have the same, known feature value (i.e., are maximally predictable), we recently found a clear effect of set size on encoding precision when distractors are drawn from a uniform distribution (i.e., when they are maximally unpredictable). Here we interpolate between these two extreme cases to examine which of both conclusions holds more generally as distractor statistics are varied. In one experiment, we vary the level of distractor heterogeneity; in another we dissociate distractor homogeneity from predictability. In all conditions in both experiments, we found a strong decrease of precision with increasing set size, suggesting that precision being independent of set size is the exception rather than the rule.

  • 10.
    Poom, Leo
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Lindskog, Marcus
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Winman, Anders
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Grouping effects in numerosity perception under prolonged viewing conditions2019In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 14, no 2, article id e0207502Article in journal (Refereed)
    Abstract [en]

    Humans can estimate numerosities–such as the number sheep in a flock–without deliberate counting. A number of biases have been identified in these estimates, which seem primarily rooted in the spatial organization of objects (grouping, symmetry, etc). Most previous studies on the number sense used static stimuli with extremely brief exposure times. However, outside the laboratory, visual scenes are often dynamic and freely viewed for prolonged durations (e.g., a flock of moving sheep). The purpose of the present study is to examine grouping-induced numerosity biases in stimuli that more closely mimic these conditions. To this end, we designed two experiments with limited-dot-lifetime displays (LDDs), in which each dot is visible for a brief period of time and replaced by a new dot elsewhere after its disappearance. The dynamic nature of LDDs prevents subjects from counting even when they are free-viewing a stimulus under prolonged presentation. Subjects estimated the number of dots in arrays that were presented either as a single group or were segregated into two groups by spatial clustering, dot size, dot color, or dot motion. Grouping by color and motion reduced perceived numerosity compared to viewing them as a single group. Moreover, the grouping effect sizes between these two features were correlated, which suggests that the effects may share a common, feature-invariant mechanism. Finally, we find that dot size and total stimulus area directly affect perceived numerosity, which makes it difficult to draw reliable conclusions about grouping effects induced by spatial clustering and dot size. Our results provide new insights into biases in numerosity estimation and they demonstrate that the use of LDDs is an effective method to study the human number sense under prolonged viewing.

  • 11.
    Stengård, Elina
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Imperfect Bayesian inference in visual perception2019In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 15, no 4, article id e1006465Article in journal (Refereed)
    Abstract [en]

    The main task of perceptual systems is to make truthful inferences about the environment. The sensory input to these systems is often astonishingly imprecise, which makes human perception prone to error. Nevertheless, numerous studies have reported that humans often perform as accurately as is possible given these sensory imprecisions. This suggests that the brain makes optimal use of the sensory input and computes without error. The validity of this claim has recently been questioned for two reasons. First, it has been argued that a lot of the evidence for optimality comes from studies that used overly flexible models. Second, optimality in human perception is implausible due to limitations inherent to neural systems. In this study, we reconsider optimality in a standard visual perception task by devising a research method that addresses both concerns. In contrast to previous studies, we find clear indications of suboptimalities. Our data are best explained by a model that is based on the optimal decision strategy, but with imperfections in its execution.

  • 12.
    Stengård, Elina
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Optimality of visual search under ambiguous stimuli2017In: CogSci 2017: Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017Conference paper (Other academic)
    Abstract [en]

    A hallmark of optimal decision making is that cues are weighted by their reliability. Previous studies have reported evidence for reliability weighting in several human perceptual decision-making tasks in which sensory noise was the only possible source of errors. Here we use a target detection task to test whether optimality generalizes to situations where stimulus ambiguity is an additional source of uncertainty. Target and distractor orientations were drawn from distributions with different means and the level of ambiguity was varied through the amount of overlap between the two distributions. In line with previous studies, we found clear evidence for sensory reliability-weighting, regardless of the level of ambiguity. However, using a richer set of models than before, we also found that the estimated weights deviated from the optimal ones. Finally, we found no effect of ambiguity level on task efficiency, which suggests that subjects optimally accounted for this source of uncertainty.

  • 13.
    Thibault, Louis
    et al.
    Université Paris Descartes.
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Cavanagh, Patrick
    Université Paris Descartes.
    Claire, Sergent
    Université Paris Descartes.
    Retrospective Attention Gates Discrete Conscious Access to Past Sensory Stimuli2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 2, article id e0148504Article in journal (Refereed)
    Abstract [en]

    Cueing attention after the disappearance of visual stimuli biases which items will be remembered best. This observation has historically been attributed to the influence of attention on memory as opposed to subjective visual experience. We recently challenged this view by showing that cueing attention after the stimulus can improve the perception of a single Gabor patch at threshold levels of contrast. Here, we test whether this retro-perception actually increases one's chance of consciously perceiving the stimulus, or simply allows for a more precise recall of its features. We used retro-cues in an orientation-matching task and performed mixture-model analysis to independently estimate the proportion of guesses and the precision of non-guess responses. We find that the improvements in performance conferred by retrospective attention are overwhelmingly carried by a reduction in the proportion of guesses, providing strong evidence that attracting attention to the target’s location after its disappearance increases the likelihood of perceiving it consciously.

  • 14.
    Thibault, Louis
    et al.
    Université Paris Descartes.
    Van den Berg, Ronald
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Cavanagh, Patrick
    Université Paris Descartes.
    Sergent, Claire
    Université Paris Descartes.
    Retrospective Attention Gates Discrete Conscious Access to Past Sensory Stimuli2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 2, article id e0148504Article in journal (Refereed)
    Abstract [en]

    Cueing attention after the disappearance of visual stimuli biases which items will be remembered best. This observation has historically been attributed to the influence of attention on memory as opposed to subjective visual experience. We recently challenged this view by showing that cueing attention after the stimulus can improve the perception of a single Gabor patch at threshold levels of contrast. Here, we test whether this retro-perception actually increases the frequency of consciously perceiving the stimulus, or simply allows for a more precise recall of its features. We used retro-cues in an orientation-matching task and performed mixture-model analysis to independently estimate the proportion of guesses and the precision of non-guess responses. We find that the improvements in performance conferred by retrospective attention are overwhelmingly determined by a reduction in the proportion of guesses, providing strong evidence that attracting attention to the target’s location after its disappearance increases the likelihood of perceiving it consciously.

  • 15.
    Van den Berg, Ronald
    et al.
    Cambridge University.
    Anandalingam, Kavi
    Cambridge University.
    Zylberberg, Ariel
    Columbia University.
    Kiani, Roozbeh
    New York University.
    Shadlen, Michael
    Columbia University.
    Wolpert, Daniel
    Cambridge University.
    A common mechanism underlies changes of mind about decisions and confidence2016In: eLIFE, E-ISSN 2050-084XArticle in journal (Refereed)
    Abstract [en]

    Decisions are accompanied by a degree of confidence that a selected option is correct. A sequential sampling framework explains the speed and accuracy of decisions and extends naturally to the confidence that the decision rendered is likely to be correct. However, discrepancies between confidence and accuracy suggest that confidence might be supported by mechanisms dissociated from the decision process. Here we show that this discrepancy can arise naturally because of simple processing delays. When participants were asked to report choice and confidence simultaneously, their confidence, reaction time and a perceptual decision about motion were explained by bounded evidence accumulation. However, we also observed revisions of the initial choice and/or confidence. These changes of mind were explained by a continuation of the mechanism that led to the initial choice. Our findings extend the sequential sampling framework to vacillation about confidence and invites caution in interpreting dissociations between confidence and accuracy.

  • 16.
    van den Berg, Ronald
    et al.
    University of Cambridge; Baylor College of Medicine.
    Awh, Edward
    Ma, Wei Ji
    Factorial comparison of working memory models2014In: Psychological review, ISSN 0033-295X, E-ISSN 1939-1471, Vol. 121, no 1, p. 124-149Article in journal (Refereed)
    Abstract [en]

    Three questions have been prominent in the study of visual working memory limitations: (a) What is the nature of mnemonic precision (e.g., quantized or continuous)? (b) How many items are remembered? (c) To what extent do spatial binding errors account for working memory failures? Modeling studies have typically focused on comparing possible answers to a single one of these questions, even though the result of such a comparison might depend on the assumed answers to both others. Here, we consider every possible combination of previously proposed answers to the individual questions. Each model is then a point in a 3-factor model space containing a total of 32 models, of which only 6 have been tested previously. We compare all models on data from 10 delayed-estimation experiments from 6 laboratories (for a total of 164 subjects and 131,452 trials). Consistently across experiments, we find that (a) mnemonic precision is not quantized but continuous and not equal but variable across items and trials; (b) the number of remembered items is likely to be variable across trials, with a mean of 6.4 in the best model (median across subjects); (c) spatial binding errors occur but explain only a small fraction of responses (16.5% at set size 8 in the best model). We find strong evidence against all 6 documented models. Our results demonstrate the value of factorial model comparison in working memory.

  • 17.
    Van den Berg, Ronald
    et al.
    Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Inst Math & Comp Sci, NL-9713 AW Groningen, Netherlands.
    Cornelissen, Frans W.
    Laboratory for Experimental Ophthalmology, School of Behavioral and Cognitive Neurosciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
    Roerdink, Jos B. T. M.
    Institute of Mathematics and Computing Science and School of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, The Netherlands.
    A crowding model of visual clutter2009In: Journal of Vision, ISSN 1534-7362, E-ISSN 1534-7362, Vol. 9, no 4, article id 24Article in journal (Refereed)
    Abstract [en]

    Visual information is difficult to search and interpret when the density of the displayed information is high or the layout is chaotic. Visual information that exhibits such properties is generally referred to as being "cluttered." Clutter should be avoided in information visualizations and interface design in general because it can severely degrade task performance. Although previous studies have identified computable correlates of clutter (such as local feature variance and edge density), understanding of why humans perceive some scenes as being more cluttered than others remains limited. Here, we explore an account of clutter that is inspired by findings from visual perception studies. Specifically, we test the hypothesis that the so-called "crowding" phenomenon is an important constituent of clutter. We constructed an algorithm to predict visual clutter in arbitrary images by estimating the perceptual impairment due to crowding. After verifying that this model can reproduce crowding data we tested whether it can also predict clutter. We found that its predictions correlate well with both subjective clutter assessments and search performance in cluttered scenes. These results suggest that crowding and clutter may indeed be closely related concepts and suggest avenues for further research.

  • 18.
    Van den Berg, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Cornelissen, FW
    Roerdink, JBTM
    Perceptual dependencies in information visualization assessed by complex visual search2008In: ACM Transactions on Applied Perception, ISSN 1544-3558, E-ISSN 1544-3965Article in journal (Refereed)
    Abstract [en]

    A common approach for visualizing data sets is to map them to images in which distinct data dimensions are mapped to distinct visual features, such as color, size and orientation. Here, we consider visualizations in which different data dimensions should receive equal weight and attention. Many of the end-user tasks performed on these images involve a form of visual search. Often, it is simply assumed that features can be judged independently of each other in such tasks. However, there is evidence for perceptual dependencies when simultaneously presenting multiple features. Such dependencies could potentially affect information visualizations that contain combinations of features for encoding information and, thereby, bias subjects into unequally weighting the relevance of different data dimensions. We experimentally assess (1) the presence of judgment dependencies in a visualization task (searching for a target node in a node-link diagram) and (2) how feature contrast relates to salience. From a visualization point of view, our most relevant findings are that (a) to equalize saliency (and thus bottom-up weighting) of size and color, color contrasts have to become very low. Moreover, orientation is less suitable for representing information that consists of a large range of data values, because it does not show a clear relationship between contrast and salience; (b) color and size are features that can be used independently to represent information, at least as far as the range of colors that were used in our study are concerned; (c) the concept of (static) feature salience hierarchies is wrong; how salient a feature is compared to another is not fixed, but a function of feature contrasts; (d) final decisions appear to be as good an indicator of perceptual performance as indicators based on measures obtained from individual fixations. Eye tracking, therefore, does not necessarily present a benefit for user studies that aim at evaluating performance in search tasks.

  • 19.
    Van den Berg, Ronald
    et al.
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA; Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands.
    Johnson, Addie
    Univ Groningen, Dept Psychol, NL-9712 TS Groningen, Netherlands.
    Martinez Anton, Angela
    Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands; Univ Groningen, Dept Psychol, NL-9712 TS Groningen, Netherlands.
    Schepers, Anne L.
    Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands; Univ Groningen, Dept Psychol, NL-9712 TS Groningen, Netherlands.
    Cornelissen, Frans W.
    Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands; Univ Groningen, Dept Psychol, NL-9712 TS Groningen, Netherlands.
    Comparing crowding in human and ideal observers2012In: Journal of Vision, ISSN 1534-7362, E-ISSN 1534-7362, Vol. 12, no 6, article id 13Article in journal (Refereed)
    Abstract [en]

    A visual target is more difficult to recognize when it is surrounded by other, similar objects. This breakdown in object recognition is known as crowding. Despite a long history of experimental work, computational models of crowding are still sparse. Specifically, few studies have examined crowding using an ideal-observer approach. Here, we compare crowding in ideal observers with crowding in humans. We derived an ideal-observer model for target identification under conditions of position and identity uncertainty. Simulations showed that this model reproduces the hallmark of crowding, namely a critical spacing that scales with viewing eccentricity. To examine how well the model fits quantitatively to human data, we performed three experiments. In Experiments 1 and 2, we measured observers' perceptual uncertainty about stimulus positions and identities, respectively, for a target in isolation. In Experiment 3, observers identified a target that was flanked by two distractors. We found that about half of the errors in Experiment 3 could be accounted for by the perceptual uncertainty measured in Experiments 1 and 2. The remainder of the errors could be accounted for by assuming that uncertainty (i.e., the width of internal noise distribution) about stimulus positions and identities depends on flanker proximity. Our results provide a mathematical restatement of the crowding problem and support the hypothesis that crowding behavior is a sign of optimality rather than a perceptual defect.

  • 20.
    Van den Berg, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Lindskog, Marcus
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Poom, Leo
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Winman, Anders
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Recent Is More: A Negative Time-Order Effect in Nonsymbolic Numerical Judgment.2017In: Journal of Experimental Psychology: Human Perception and Performance, ISSN 0096-1523Print, Vol. 43, no 6, p. 1084-1097Article in journal (Refereed)
    Abstract [en]

    Humans as well as some nonhuman animals can estimate object numerosities—such as the number of sheep in a flock—without explicit counting. Here, we report on a negative time-order effect (TOE) in this type of judgment: When nonsymbolic numerical stimuli are presented sequentially, the second stimulus is overestimated compared to the first. We examined this “recent is more” effect in two comparative judgment tasks: larger–smaller discrimination and same–different discrimination. Ideal-observer modeling revealed evidence for a TOE in 88.2% of the individual data sets. Despite large individual differences in effect size, there was strong consistency in effect direction: 87.3% of the identified TOEs were negative. The average effect size was largely independent of task but did strongly depend on both stimulus magnitude and interstimulus interval. Finally, we used an estimation task to obtain insight into the origin of the effect. We found that subjects tend to overestimate both stimuli but the second one more strongly than the first one. Overall, our findings are highly consistent with findings from studies on TOEs in nonnumerical judgments, which suggests a common underlying mechanism.

  • 21.
    Van den Berg, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Ma, Wei Ji
    A resource-rational theory of set size effects in human visual working memory2018In: eLIFE, E-ISSN 2050-084X, Vol. 7, article id e34963Article in journal (Refereed)
    Abstract [en]

    Encoding precision in visual working memory decreases with the number of encoded items. Here, we propose a normative theory for such set size effects: the brain minimizes a weighted sum of an error-based behavioral cost and a neural encoding cost. We construct a model from this theory and find that it predicts set size effects. Notably, these effects are mediated by probing probability, which aligns with previous empirical findings. The model accounts well for effects of both set size and probing probability on encoding precision in nine delayed-estimation experiments. Moreover, we find support for the prediction that the total amount of invested resource can vary non-monotonically with set size. Finally, we show that it is sometimes optimal to encode only a subset or even none of the relevant items in a task. Our findings raise the possibility that cognitive 'limitations' arise from rational cost minimization rather than from constraints.

  • 22.
    Van den Berg, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Ma, Wei Ji
    Robust averaging during perceptual judgment is not optimal.2012In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 109, no 13Article in journal (Refereed)
  • 23.
    Van den Berg, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Ma, WJ
    "Plateau"-related summary statistics are uninformative for comparing working memory models.2014In: Attention, Perception & Psychophysics, ISSN 1943-3921, E-ISSN 1943-393XArticle in journal (Refereed)
    Abstract [en]

    Performance on visual working memory tasks decreases as more items need to be remembered. Over the past decade, a debate has unfolded between proponents of slot models and slotless models of this phenomenon (Ma, Husain, Bays (Nature Neuroscience 17, 347-356, 2014). Zhang and Luck (Nature 453, (7192), 233-235, 2008) and Anderson, Vogel, and Awh (Attention, Perception, Psychophys 74, (5), 891-910, 2011) noticed that as more items need to be remembered, "memory noise" seems to first increase and then reach a "stable plateau." They argued that three summary statistics characterizing this plateau are consistent with slot models, but not with slotless models. Here, we assess the validity of their methods. We generated synthetic data both from a leading slot model and from a recent slotless model and quantified model evidence using log Bayes factors. We found that the summary statistics provided at most 0.15 % of the expected model evidence in the raw data. In a model recovery analysis, a total of more than a million trials were required to achieve 99 % correct recovery when models were compared on the basis of summary statistics, whereas fewer than 1,000 trials were sufficient when raw data were used. Therefore, at realistic numbers of trials, plateau-related summary statistics are highly unreliable for model comparison. Applying the same analyses to subject data from Anderson et al. (Attention, Perception, Psychophys 74, (5), 891-910, 2011), we found that the evidence in the summary statistics was at most 0.12 % of the evidence in the raw data and far too weak to warrant any conclusions. The evidence in the raw data, in fact, strongly favored the slotless model. These findings call into question claims about working memory that are based on summary statistics.

  • 24.
    Van den Berg, Ronald
    et al.
    Univ Groningen, Inst Math & Comp Sci, Groningen, Netherlands; Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands; Univ Groningen, Sch Behav & Cognit Neurosci, Groningen, Netherlands.
    Roerdink, Jos B. T. M.
    Univ Groningen, Inst Math & Comp Sci, Groningen, Netherlands; .
    Cornelissen, Frans W.
    Univ Groningen, Univ Med Ctr Groningen, Lab Expt Ophthalmol, Groningen, Netherlands; Univ Groningen, Sch Behav & Cognit Neurosci, Groningen, Netherlands.
    A neurophysiologically plausible population code model for feature integration explains visual crowding2010In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 6, no 1, article id e1000646Article in journal (Refereed)
    Abstract [en]

    An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

  • 25.
    Van den Berg, Ronald
    et al.
    Department of Mathematics and Computing Science and School of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, The Netherlands..
    Roerdink, Jos B. T. M.
    Department of Mathematics and Computing Science and School of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, The Netherlands..
    Cornelissen, Frans W.
    Department of Mathematics and Computing Science and School of Behavioral and Cognitive Neurosciences, University of Groningen, Groningen, The Netherlands..
    On the generality of crowding: visual crowding in size, saturation, and hue compared to orientation2007In: Journal of Vision, ISSN 1534-7362, E-ISSN 1534-7362, Vol. 7, no 2Article in journal (Refereed)
    Abstract [en]

    Perception of peripherally viewed shapes is impaired when surrounded by similar shapes. This phenomenon is commonly referred to as "crowding". Although studied extensively for perception of characters (mainly letters) and, to a lesser extent, for orientation, little is known about whether and how crowding affects perception of other features. Nevertheless, current crowding models suggest that the effect should be rather general and thus not restricted to letters and orientation. Here, we report on a series of experiments investigating crowding in the following elementary feature dimensions: size, hue, and saturation. Crowding effects in these dimensions were benchmarked against those in the orientation domain. Our primary finding is that all features studied show clear signs of crowding. First, identification thresholds increase with decreasing mask spacing. Second, for all tested features, critical spacing appears to be roughly half the viewing eccentricity and independent of stimulus size, a property previously proposed as the hallmark of crowding. Interestingly, although critical spacings are highly comparable, crowding magnitude differs across features: Size crowding is almost as strong as orientation crowding, whereas the effect is much weaker for saturation and hue. We suggest that future theories and models of crowding should be able to accommodate these differences in crowding effects.

  • 26.
    Van den Berg, Ronald
    et al.
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Shin, Hongsup
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Chou, Wen-Chuang
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    George, Ryan
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA; Rice Univ, Dept Computat & Appl Math, Houston, TX 77005 USA.
    Ma, Wei Ji
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Variability in encoding precision accounts for visual short-term memory limitations2012In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 109, no 22, p. 8780-8785Article in journal (Refereed)
    Abstract [en]

    It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of "slots" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.

  • 27.
    Van den Berg, Ronald
    et al.
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Vogel, Michael
    Univ Houston, Dept Math, Houston, TX 77204 USA.
    Josic, Kresimir
    Univ Houston, Dept Math, Houston, TX 77204 USA; Univ Houston, Dept Biol & Biochem, Houston, TX 77204 USA.
    Ma, Wei Ji
    Baylor Coll Med, Dept Neurosci, Houston, TX 77030 USA.
    Optimal inference of sameness2012In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 109, no 8, p. 3178-3183Article in journal (Refereed)
    Abstract [en]

    Deciding whether a set of objects are the same or different is a cornerstone of perception and cognition. Surprisingly, no principled quantitative model of sameness judgment exists. We tested whether human sameness judgment under sensory noise can be modeled as a form of probabilistically optimal inference. An optimal observer would compare the reliability-weighted variance of the sensory measurements with a set size-dependent criterion. We conducted two experiments, in which we varied set size and individual stimulus reliabilities. We found that the optimal-observer model accurately describes human behavior, outperforms plausible alternatives in a rigorous model comparison, and accounts for three key findings in the animal cognition literature. Our results provide a normative footing for the study of sameness judgment and indicate that the notion of perception as near-optimal inference extends to abstract relations.

  • 28.
    Van den Berg, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Yoo, Aspen H.
    NYU, Ctr Neural Sci, New York, NY 10003 USA.; NYU, Dept Psychol, New York, NY 10003 USA.
    Ma, Wei Ji
    NYU, Ctr Neural Sci, New York, NY 10003 USA.; NYU, Dept Psychol, New York, NY 10003 USA.
    Fechner’s law in metacognition: A quantitative model of visual working memory confidence.2017In: Psychological Review, ISSN 0033-295XPrint, Vol. 124, no 2, p. 197-214Article in journal (Refereed)
    Abstract [en]

    Although visual working memory (VWM) has been studied extensively, it is unknown how people form confidence judgments about their memories. Peirce (1878) speculated that Fechner’s law—which states that sensation is proportional to the logarithm of stimulus intensity—might apply to confidence reports. Based on this idea, we hypothesize that humans map the precision of their VWM contents to a confidence rating through Fechner’s law. We incorporate this hypothesis into the best available model of VWM encoding and fit it to data from a delayed-estimation experiment. The model provides an excellent account of human confidence rating distributions as well as the relation between performance and confidence. Moreover, the best-fitting mapping in a model with a highly flexible mapping closely resembles the logarithmic mapping, suggesting that no alternative mapping exists that accounts better for the data than Fechner’s law. We propose a neural implementation of the model and find that this model also fits the behavioral data well. Furthermore, we find that jointly fitting memory errors and confidence ratings boosts the power to distinguish previously proposed VWM encoding models by a factor of 5.99 compared to fitting only memory errors. Finally, we show that Fechner’s law also accounts for metacognitive judgments in a word recognition memory task, which is a first indication that it may be a general law in metacognition. Our work presents the first model to jointly account for errors and confidence ratings in VWM and could lay the groundwork for understanding the computational mechanisms of metacognition.

  • 29.
    Van den Berg, Ronald
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Zylberberg, Ariel
    Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Kavli Institute of Brain Science, and Howard Hughes Medical Institute, Columbia University, New York, NY 10032, USA.
    Kiani, Roozbeh
    Center for Neural Science, New York University, New York, NY 10003, USA.
    Shadlen, Michael N.
    Department of Neuroscience, Zuckerman Mind Brain Behavior Institute, Kavli Institute of Brain Science, and Howard Hughes Medical Institute, Columbia University, New York, NY 10032, USA.
    Wolpert, Daniel M.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
    Confidence Is the Bridge between Multi-stage Decisions2016In: Current Biology, ISSN 0960-9822, E-ISSN 1879-0445Article in journal (Refereed)
    Abstract [en]

    Demanding tasks often require a series of decisions to reach a goal. Recent progress in perceptual decision-making has served to unite decision accuracy, speed, and confidence in a common framework of bounded evidence accumulation, furnishing a platform for the study of such multi-stage decisions. In many instances, the strategy applied to each decision, such as the speed-accuracy trade-off, ought to depend on the accuracy of the previous decisions. However, as the accuracy of each decision is often unknown to the decision maker, we hypothesized that subjects may carry forward a level of confidence in previous decisions to affect subsequent decisions. Subjects made two perceptual decisions sequentially and were rewarded only if they made both correctly. The speed and accuracy of individual decisions were explained by noisy evidence accumulation to a terminating bound. We found that subjects adjusted their speed-accuracy setting by elevating the termination bound on the second decision in proportion to their confidence in the first. The findings reveal a novel role for confidence and a degree of flexibility, hitherto unknown, in the brain’s ability to rapidly and precisely modify the mechanisms that control the termination of a decision.

1 - 29 of 29
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