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Glickman M, Sela T, Usher M, Levy DJ. The effect of perceptual organization on numerical and preference-based decisions shows inter-subject correlation. Psychon Bull Rev 2023; 30:1410-1421. [PMID: 36625990 PMCID: PMC10482786 DOI: 10.3758/s13423-022-02234-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/04/2022] [Indexed: 01/11/2023]
Abstract
Individual differences in cognitive processing have been the subject of intensive research. One important type of such individual differences is the tendency for global versus local processing, which was shown to correlate with a wide range of processing differences in fields such as decision making, social judgments and creativity. Yet, whether these global/local processing tendencies are correlated within a subject across different domains is still an open question. To address this question, we develop and test a novel method to quantify global/local processing tendencies, in which we directly set in opposition the local and global information instead of instructing subjects to specifically attend to one processing level. We apply our novel method to two different domains: (1) a numerical cognition task, and (2) a preference task. Using computational modeling, we accounted for classical effects in choice and numerical-cognition. Global/local tendencies in both tasks were quantified using a salience parameter. Critically, the salience parameters extracted from the numerical cognition and preference tasks were highly correlated, providing support for robust perceptual organization tendencies within an individual.
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Affiliation(s)
- Moshe Glickman
- Department of Experimental Psychology, University College London, London, UK
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
| | - Tal Sela
- Department of Behavioral Sciences, Kinneret Academic College, Tzemach, Israel
| | - Marius Usher
- The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Dino J. Levy
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Coller School of Management, Tel Aviv University, Tel Aviv, Israel
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2
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Glickman M, Moran R, Usher M. Evidence integration and decision confidence are modulated by stimulus consistency. Nat Hum Behav 2022; 6:988-999. [PMID: 35379981 DOI: 10.1038/s41562-022-01318-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/11/2022] [Indexed: 11/09/2022]
Abstract
Evidence integration is a normative algorithm for choosing between alternatives with noisy evidence, which has been successful in accounting for vast amounts of behavioural and neural data. However, this mechanism has been challenged by non-integration heuristics, and tracking decision boundaries has proven elusive. Here we first show that the decision boundaries can be extracted using a model-free behavioural method termed decision classification boundary, which optimizes choice classification based on the accumulated evidence. Using this method, we provide direct support for evidence integration over non-integration heuristics, show that the decision boundaries collapse across time and identify an integration bias whereby incoming evidence is modulated based on its consistency with preceding information. This consistency bias, which is a form of pre-decision confirmation bias, was supported in four cross-domain experiments, showing that choice accuracy and decision confidence are modulated by stimulus consistency. Strikingly, despite its seeming sub-optimality, the consistency bias fosters performance by enhancing robustness to integration noise.
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Affiliation(s)
- Moshe Glickman
- Department of Experimental Psychology, University College London, London, UK. .,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
| | - Rani Moran
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.,Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Marius Usher
- School of Psychology, University of Tel Aviv, Tel Aviv, Israel. .,Sagol School of Neuroscience, University of Tel Aviv, Tel Aviv, Israel.
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3
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Abstract
Integration to boundary is an optimal decision algorithm that accumulates evidence until the posterior reaches a decision boundary, resulting in the fastest decisions for a target accuracy. Here, we demonstrated that this advantage incurs a cost in metacognitive accuracy (confidence), generating a cognition/metacognition trade-off. Using computational modeling, we found that integration to a fixed boundary results in less variability in evidence integration and thus reduces metacognitive accuracy, compared with a collapsing-boundary or a random-timer strategy. We examined how decision strategy affects metacognitive accuracy in three cross-domain experiments, in which 102 university students completed a free-response session (evidence terminated by the participant's response) and an interrogation session (fixed number of evidence samples controlled by the experimenter). In both sessions, participants observed a sequence of evidence and reported their choice and confidence. As predicted, the interrogation protocol (preventing integration to boundary) enhanced metacognitive accuracy. We also found that in the free-response sessions, participants integrated evidence to a collapsing boundary-a strategy that achieves an efficient compromise between optimizing choice and metacognitive accuracy.
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Affiliation(s)
| | - Moshe Glickman
- Department of Experimental Psychology, University College London.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, United Kingdom
| | - Stephen M Fleming
- Department of Experimental Psychology, University College London.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, United Kingdom.,Wellcome Centre for Human Neuroimaging, University College London
| | - Marius Usher
- School of Psychological Sciences, Tel Aviv University
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4
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Appelhoff S, Hertwig R, Spitzer B. Control over sampling boosts numerical evidence processing in human decisions from experience. Cereb Cortex 2022; 33:207-221. [PMID: 35266973 PMCID: PMC9758588 DOI: 10.1093/cercor/bhac062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 01/30/2022] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
When acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does control over information acquisition affect the quality of sample-based decisions? Here, combining variants of a numerical sampling task with neural recordings, we show that control over when to stop sampling can enhance (i) behavioral choice accuracy, (ii) the build-up of parietal decision signals, and (iii) the encoding of numerical sample information in multivariate electroencephalogram patterns. None of these effects were observed when participants could only control which alternatives to sample, but not when to stop sampling. Furthermore, levels of control had no effect on early sensory signals or on the extent to which sample information leaked from memory. The results indicate that freedom to stop sampling can amplify decisional evidence processing from the outset of information acquisition and lead to more accurate choices.
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Affiliation(s)
- Stefan Appelhoff
- Corresponding author: Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany.
| | - Ralph Hertwig
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Bernhard Spitzer
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany,Research Group Adaptive Memory and Decision Making, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
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5
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Fosco WD, Meisel SN, Weigard A, White CN, Colder CR. Computational modeling reveals strategic and developmental differences in the behavioral impact of reward across adolescence. Dev Sci 2022; 25:e13159. [PMID: 34240533 PMCID: PMC8741886 DOI: 10.1111/desc.13159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 06/30/2021] [Accepted: 07/05/2021] [Indexed: 11/27/2022]
Abstract
Studies of reward effects on behavior in adolescence typically rely on performance metrics that confound myriad cognitive and non-cognitive processes, making it challenging to determine which process is impacted by reward. The present longitudinal study applied the diffusion decision model to a reward task to isolate the influence of reward on response caution from influences of processing and motor speed. Participants completed three annual assessments from early to middle adolescence (N = 387, 55% female, Mage = 12.1 at Wave 1; Mage = 13.1 at Wave 2, Mage = 14.1 at Wave 3) and three annual assessments in late adolescence (Mages = 17.8, 18.9, 19.9). At each assessment, participants completed a two-choice reaction time task under conditions of no-reward and a block in which points were awarded for speeded accuracy. Reward reduced response caution at all waves, as expected, but had a greater impact as teens moved from early to middle adolescence. Simulations to identify optimal response caution showed that teens were overly cautious in early adolescence but became too focused on speed over accuracy by middle adolescence. By late adolescence, participants adopted response styles that maximized reward. Further, response style was associated with both internalizing and externalizing symptoms in early-to-middle adolescence, providing evidence for the construct validity of a diffusion model approach in this developmental period.
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Affiliation(s)
- Whitney D. Fosco
- Department of Psychiatry and Behavioral Health, Penn State Health Milton S. Hershey Medical Center,Penn State College of Medicine
| | - Samuel N. Meisel
- Center for Alcohol and Addiction Studies, Brown University,E. P. Bradley Hospital
| | | | - Corey N. White
- Department of Psychology, Missouri Western State University
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6
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Kang Z, Spitzer B. Concurrent visual working memory bias in sequential integration of approximate number. Sci Rep 2021; 11:5348. [PMID: 33674642 PMCID: PMC7935854 DOI: 10.1038/s41598-021-84232-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 02/01/2021] [Indexed: 11/29/2022] Open
Abstract
Previous work has shown bidirectional crosstalk between Working Memory (WM) and perception such that the contents of WM can alter concurrent percepts and vice versa. Here, we examine WM-perception interactions in a new task setting. Participants judged the proportion of colored dots in a stream of visual displays while concurrently holding location- and color information in memory. Spatiotemporally resolved psychometrics disclosed a modulation of perceptual sensitivity consistent with a bias of visual spatial attention towards the memorized location. However, this effect was short-lived, suggesting that the visuospatial WM information was rapidly deprioritized during processing of new perceptual information. Independently, we observed robust bidirectional biases of categorical color judgments, in that perceptual decisions and mnemonic reports were attracted to each other. These biases occurred without reductions in overall perceptual sensitivity compared to control conditions without a concurrent WM load. The results conceptually replicate and extend previous findings in visual search and suggest that crosstalk between WM and perception can arise at multiple levels, from sensory-perceptual to decisional processing.
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Affiliation(s)
- Zhiqi Kang
- Center for Adaptive Rationality, Max Planck Institute for Human Development, 14195, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität Zu Berlin, 10099, Berlin, Germany
| | - Bernhard Spitzer
- Center for Adaptive Rationality, Max Planck Institute for Human Development, 14195, Berlin, Germany.
- Berlin School of Mind and Brain, Humboldt-Universität Zu Berlin, 10099, Berlin, Germany.
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Stine GM, Zylberberg A, Ditterich J, Shadlen MN. Differentiating between integration and non-integration strategies in perceptual decision making. eLife 2020; 9:55365. [PMID: 32338595 PMCID: PMC7217695 DOI: 10.7554/elife.55365] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 04/24/2020] [Indexed: 01/26/2023] Open
Abstract
Many tasks used to study decision-making encourage subjects to integrate evidence over time. Such tasks are useful to understand how the brain operates on multiple samples of information over prolonged timescales, but only if subjects actually integrate evidence to form their decisions. We explored the behavioral observations that corroborate evidence-integration in a number of task-designs. Several commonly accepted signs of integration were also predicted by non-integration strategies. Furthermore, an integration model could fit data generated by non-integration models. We identified the features of non-integration models that allowed them to mimic integration and used these insights to design a motion discrimination task that disentangled the models. In human subjects performing the task, we falsified a non-integration strategy in each and confirmed prolonged integration in all but one subject. The findings illustrate the difficulty of identifying a decision-maker’s strategy and support solutions to achieve this goal.
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Affiliation(s)
- Gabriel M Stine
- Department of Neuroscience, Columbia University, New York, United States
| | - Ariel Zylberberg
- Mortimer B. Zuckerman Mind Brain Behavior Institute and The Kavli Institute for Brain Science, Columbia University, New York, United States.,Department of Brain and Cognitive Sciences, University of Rochester, Rochester, United States
| | - Jochen Ditterich
- Center for Neuroscience and Department of Neurobiology, Physiology & Behavior, University of California, Davis, United States
| | - Michael N Shadlen
- Department of Neuroscience, Columbia University, New York, United States.,Mortimer B. Zuckerman Mind Brain Behavior Institute and The Kavli Institute for Brain Science, Columbia University, New York, United States.,Howard Hughes Medical Institute, Columbia University, New York, United States
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8
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Glickman M, Sharoni O, Levy DJ, Niebur E, Stuphorn V, Usher M. The formation of preference in risky choice. PLoS Comput Biol 2019; 15:e1007201. [PMID: 31465438 PMCID: PMC6738658 DOI: 10.1371/journal.pcbi.1007201] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2018] [Revised: 09/11/2019] [Accepted: 06/20/2019] [Indexed: 12/01/2022] Open
Abstract
A key question in decision-making is how people integrate amounts and probabilities to form preferences between risky alternatives. Here we rely on the general principle of integration-to-boundary to develop several biologically plausible process models of risky-choice, which account for both choices and response-times. These models allowed us to contrast two influential competing theories: i) within-alternative evaluations, based on multiplicative interaction between amounts and probabilities, ii) within-attribute comparisons across alternatives. To constrain the preference formation process, we monitored eye-fixations during decisions between pairs of simple lotteries, designed to systematically span the decision-space. The behavioral results indicate that the participants' eye-scanning patterns were associated with risk-preferences and expected-value maximization. Crucially, model comparisons showed that within-alternative process models decisively outperformed within-attribute ones, in accounting for choices and response-times. These findings elucidate the psychological processes underlying preference formation when making risky-choices, and suggest that compensatory, within-alternative integration is an adaptive mechanism employed in human decision-making.
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Affiliation(s)
- Moshe Glickman
- The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Orian Sharoni
- The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Dino J. Levy
- Coller School of Management, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Ernst Niebur
- Department of Neuroscience and Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Veit Stuphorn
- Department of Neuroscience and Krieger Mind/Brain Institute, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Marius Usher
- The School of Psychological Sciences, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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