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Xie T, Adamek M, Cho H, Adamo MA, Ritaccio AL, Willie JT, Brunner P, Kubanek J. Graded decisions in the human brain. Nat Commun 2024; 15:4308. [PMID: 38773117 PMCID: PMC11109249 DOI: 10.1038/s41467-024-48342-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 04/26/2024] [Indexed: 05/23/2024] Open
Abstract
Decision-makers objectively commit to a definitive choice, yet at the subjective level, human decisions appear to be associated with a degree of uncertainty. Whether decisions are definitive (i.e., concluding in all-or-none choices), or whether the underlying representations are graded, remains unclear. To answer this question, we recorded intracranial neural signals directly from the brain while human subjects made perceptual decisions. The recordings revealed that broadband gamma activity reflecting each individual's decision-making process, ramped up gradually while being graded by the accumulated decision evidence. Crucially, this grading effect persisted throughout the decision process without ever reaching a definite bound at the time of choice. This effect was most prominent in the parietal cortex, a brain region traditionally implicated in decision-making. These results provide neural evidence for a graded decision process in humans and an analog framework for flexible choice behavior.
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Affiliation(s)
- Tao Xie
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- National Center for Adaptive Neurotechnologies, St. Louis, MO, 63110, USA
| | - Markus Adamek
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- National Center for Adaptive Neurotechnologies, St. Louis, MO, 63110, USA
| | - Hohyun Cho
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- National Center for Adaptive Neurotechnologies, St. Louis, MO, 63110, USA
| | - Matthew A Adamo
- Department of Neurosurgery, Albany Medical College, Albany, NY, 12208, USA
| | - Anthony L Ritaccio
- Department of Neurology, Albany Medical College, Albany, NY, 12208, USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Jon T Willie
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA
- National Center for Adaptive Neurotechnologies, St. Louis, MO, 63110, USA
| | - Peter Brunner
- Department of Neurological Surgery, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- National Center for Adaptive Neurotechnologies, St. Louis, MO, 63110, USA.
- Department of Neurology, Albany Medical College, Albany, NY, 12208, USA.
| | - Jan Kubanek
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, 84112, USA.
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Kira S, Zylberberg A, Shadlen MN. Incorporation of a cost of deliberation time in perceptual decision making. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578067. [PMID: 38352612 PMCID: PMC10862799 DOI: 10.1101/2024.01.31.578067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
Many decisions benefit from the accumulation of evidence obtained sequentially over time. In such circumstances, the decision maker must balance speed against accuracy, and the nature of this tradeoff mediates competing desiderata and costs, especially those associated with the passage of time. A neural mechanism to achieve this balance is to accumulate evidence in suitable units and to terminate the deliberation when enough evidence has accrued. To accommodate time costs, it has been hypothesized that the criterion to terminate a decision may become lax as a function of time. Here we tested this hypothesis by manipulating the cost of time in a perceptual choice-reaction time task. Participants discriminated the direction of motion in a dynamic random-dot display, which varied in difficulty across trials. After each trial, they received feedback in the form of points based on whether they made a correct or erroneous choice. They were instructed to maximize their points per unit of time. Unbeknownst to the participants, halfway through the experiment, we increased the time pressure by canceling a small fraction of trials if they had not made a decision by a provisional deadline. Although the manipulation canceled less than 5% of trials, it induced the participants to make faster decisions while lowering their decision accuracy. The pattern of choices and reaction times were explained by bounded drift-diffusion. In all phases of the experiment, stopping bounds were found to decline as a function of time, consistent with the optimal solution, and this decline was exaggerated in response to the time-cost manipulation.
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Affiliation(s)
- Shinichiro Kira
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
- Zuckerman Mind Brain Behavior Institute, Columbia University, NY, USA
| | - Ariel Zylberberg
- Zuckerman Mind Brain Behavior Institute, Columbia University, NY, USA
| | - Michael N Shadlen
- Zuckerman Mind Brain Behavior Institute, Columbia University, NY, USA
- Kavli Institute for Brain Science, Columbia University, NY, USA
- Howard Hughes Medical Institute, Columbia University, NY, USA
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3
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Olschewski S, Luckman A, Mason A, Ludvig EA, Konstantinidis E. The Future of Decisions From Experience: Connecting Real-World Decision Problems to Cognitive Processes. PERSPECTIVES ON PSYCHOLOGICAL SCIENCE 2024; 19:82-102. [PMID: 37390328 PMCID: PMC10790535 DOI: 10.1177/17456916231179138] [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] [Indexed: 07/02/2023]
Abstract
In many important real-world decision domains, such as finance, the environment, and health, behavior is strongly influenced by experience. Renewed interest in studying this influence led to important advancements in the understanding of these decisions from experience (DfE) in the last 20 years. Building on this literature, we suggest ways the standard experimental design should be extended to better approach important real-world DfE. These extensions include, for example, introducing more complex choice situations, delaying feedback, and including social interactions. When acting upon experiences in these richer and more complicated environments, extensive cognitive processes go into making a decision. Therefore, we argue for integrating cognitive processes more explicitly into experimental research in DfE. These cognitive processes include attention to and perception of numeric and nonnumeric experiences, the influence of episodic and semantic memory, and the mental models involved in learning processes. Understanding these basic cognitive processes can advance the modeling, understanding and prediction of DfE in the laboratory and in the real world. We highlight the potential of experimental research in DfE for theory integration across the behavioral, decision, and cognitive sciences. Furthermore, this research could lead to new methodology that better informs decision-making and policy interventions.
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Affiliation(s)
- Sebastian Olschewski
- Department of Psychology, University of Basel
- Warwick Business School, University of Warwick
| | - Ashley Luckman
- Warwick Business School, University of Warwick
- University of Exeter Business School, University of Exeter
| | - Alice Mason
- Department of Psychology, University of Bath
- Department of Psychology, University of Warwick
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Cerracchio E, Miletić S, Forstmann BU. Modelling decision-making biases. Front Comput Neurosci 2023; 17:1222924. [PMID: 37927545 PMCID: PMC10622807 DOI: 10.3389/fncom.2023.1222924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
Biases are a fundamental aspect of everyday life decision-making. A variety of modelling approaches have been suggested to capture decision-making biases. Statistical models are a means to describe the data, but the results are usually interpreted according to a verbal theory. This can lead to an ambiguous interpretation of the data. Mathematical cognitive models of decision-making outline the structure of the decision process with formal assumptions, providing advantages in terms of prediction, simulation, and interpretability compared to statistical models. We compare studies that used both signal detection theory and evidence accumulation models as models of decision-making biases, concluding that the latter provides a more comprehensive account of the decision-making phenomena by including response time behavior. We conclude by reviewing recent studies investigating attention and expectation biases with evidence accumulation models. Previous findings, reporting an exclusive influence of attention on the speed of evidence accumulation and prior probability on starting point, are challenged by novel results suggesting an additional effect of attention on non-decision time and prior probability on drift rate.
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Affiliation(s)
- Ettore Cerracchio
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Steven Miletić
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - Birte U Forstmann
- Department of Psychology, University of Amsterdam, Amsterdam, Netherlands
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Ackerman R, Binah-Pollak A, Lauterman T. Metacognitive Effort Regulation across Cultures. J Intell 2023; 11:171. [PMID: 37754900 PMCID: PMC10532471 DOI: 10.3390/jintelligence11090171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/11/2023] [Accepted: 08/20/2023] [Indexed: 09/28/2023] Open
Abstract
Success in cognitive tasks is associated with effort regulation and motivation. We employed the meta-reasoning approach to investigate metacognitive monitoring accuracy and effort regulation in problem solving across cultures. Adults from China, from Israel, and from Europe and North America (for simplicity: "Western countries") solved nonverbal problems and rated their confidence in their answers. The task involved identifying geometric shapes within silhouettes and, thus, required overcoming interference from holistic processing. The Western group displayed the worst monitoring accuracy, with both the highest overconfidence and poorest resolution (discrimination in confidence between the correct and wrong solutions). The Israeli group resembled the Western group in many respects but exhibited better monitoring accuracy. The Chinese group invested the most time and achieved the best success rates, demonstrating exceptional motivation and determination to succeed. However, their efficiency suffered as they correctly solved the fewest problems per minute of work. Effort regulation analysis based on the Diminishing Criterion Model revealed distinct patterns: the Western participants invested the least amount of time regardless of item difficulty and the Israelis invested more time only when addressing the hardest items. The Chinese group allocated more time throughout but particularly in moderate to difficult items, hinting at their strategic determination to overcome the challenge. Understanding cultural differences in metacognitive processes carries implications for theory (e.g., motivational factors) and practice (e.g., international teams, education). The present findings can serve as a foundation for future research in these and other domains.
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Affiliation(s)
- Rakefet Ackerman
- Technion—Israel Institute of Technology, Haifa 3200003, Israel; (A.B.-P.); (T.L.)
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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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7
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Balsdon T, Verdonck S, Loossens T, Philiastides MG. Secondary motor integration as a final arbiter in sensorimotor decision-making. PLoS Biol 2023; 21:e3002200. [PMID: 37459392 PMCID: PMC10393169 DOI: 10.1371/journal.pbio.3002200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 08/01/2023] [Accepted: 06/15/2023] [Indexed: 08/02/2023] Open
Abstract
Sensorimotor decision-making is believed to involve a process of accumulating sensory evidence over time. While current theories posit a single accumulation process prior to planning an overt motor response, here, we propose an active role of motor processes in decision formation via a secondary leaky motor accumulation stage. The motor leak adapts the "memory" with which this secondary accumulator reintegrates the primary accumulated sensory evidence, thus adjusting the temporal smoothing in the motor evidence and, correspondingly, the lag between the primary and motor accumulators. We compare this framework against different single accumulator variants using formal model comparison, fitting choice, and response times in a task where human observers made categorical decisions about a noisy sequence of images, under different speed-accuracy trade-off instructions. We show that, rather than boundary adjustments (controlling the amount of evidence accumulated for decision commitment), adjustment of the leak in the secondary motor accumulator provides the better description of behavior across conditions. Importantly, we derive neural correlates of these 2 integration processes from electroencephalography data recorded during the same task and show that these neural correlates adhere to the neural response profiles predicted by the model. This framework thus provides a neurobiologically plausible description of sensorimotor decision-making that captures emerging evidence of the active role of motor processes in choice behavior.
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Affiliation(s)
- Tarryn Balsdon
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, United Kingdom
| | - Stijn Verdonck
- Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Tim Loossens
- Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Marios G Philiastides
- School of Psychology and Neuroscience, University of Glasgow, Glasgow, United Kingdom
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Drevet J, Drugowitsch J, Wyart V. Efficient stabilization of imprecise statistical inference through conditional belief updating. Nat Hum Behav 2022; 6:1691-1704. [PMID: 36138224 DOI: 10.1038/s41562-022-01445-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 08/11/2022] [Indexed: 01/14/2023]
Abstract
Statistical inference is the optimal process for forming and maintaining accurate beliefs about uncertain environments. However, human inference comes with costs due to its associated biases and limited precision. Indeed, biased or imprecise inference can trigger variable beliefs and unwarranted changes in behaviour. Here, by studying decisions in a sequential categorization task based on noisy visual stimuli, we obtained converging evidence that humans reduce the variability of their beliefs by updating them only when the reliability of incoming sensory information is judged as sufficiently strong. Instead of integrating the evidence provided by all stimuli, participants actively discarded as much as a third of stimuli. This conditional belief updating strategy shows good test-retest reliability, correlates with perceptual confidence and explains human behaviour better than previously described strategies. This seemingly suboptimal strategy not only reduces the costs of imprecise computations but also, counterintuitively, increases the accuracy of resulting decisions.
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Affiliation(s)
- Julie Drevet
- Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale (Inserm), Paris, France.
- Département d'Études Cognitives, École Normale Supérieure, Université PSL, Paris, France.
| | - Jan Drugowitsch
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Valentin Wyart
- Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale (Inserm), Paris, France.
- Département d'Études Cognitives, École Normale Supérieure, Université PSL, Paris, France.
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9
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Barendregt NW, Gold JI, Josić K, Kilpatrick ZP. Normative decision rules in changing environments. eLife 2022; 11:e79824. [PMID: 36282065 PMCID: PMC9754630 DOI: 10.7554/elife.79824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 10/20/2022] [Indexed: 11/13/2022] Open
Abstract
Models based on normative principles have played a major role in our understanding of how the brain forms decisions. However, these models have typically been derived for simple, stable conditions, and their relevance to decisions formed under more naturalistic, dynamic conditions is unclear. We previously derived a normative decision model in which evidence accumulation is adapted to fluctuations in the evidence-generating process that occur during a single decision (Glaze et al., 2015), but the evolution of commitment rules (e.g. thresholds on the accumulated evidence) under dynamic conditions is not fully understood. Here, we derive a normative model for decisions based on changing contexts, which we define as changes in evidence quality or reward, over the course of a single decision. In these cases, performance (reward rate) is maximized using decision thresholds that respond to and even anticipate these changes, in contrast to the static thresholds used in many decision models. We show that these adaptive thresholds exhibit several distinct temporal motifs that depend on the specific predicted and experienced context changes and that adaptive models perform robustly even when implemented imperfectly (noisily). We further show that decision models with adaptive thresholds outperform those with constant or urgency-gated thresholds in accounting for human response times on a task with time-varying evidence quality and average reward. These results further link normative and neural decision-making while expanding our view of both as dynamic, adaptive processes that update and use expectations to govern both deliberation and commitment.
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Affiliation(s)
- Nicholas W Barendregt
- Department of Applied Mathematics, University of Colorado BoulderBoulderUnited States
| | - Joshua I Gold
- Department of Neuroscience, University of PennsylvaniaPhiladelphiaUnited States
| | - Krešimir Josić
- Department of Mathematics, University of HoustonHoustonUnited States
| | - Zachary P Kilpatrick
- Department of Applied Mathematics, University of Colorado BoulderBoulderUnited States
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Zilker V, Pachur T. Toward an attentional turn in research on risky choice. Front Psychol 2022; 13:953008. [PMID: 36148098 PMCID: PMC9487305 DOI: 10.3389/fpsyg.2022.953008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/08/2022] [Indexed: 11/16/2022] Open
Abstract
For a long time, the dominant approach to studying decision making under risk has been to use psychoeconomic functions to account for how behavior deviates from the normative prescriptions of expected value maximization. While this neo-Bernoullian tradition has advanced the field in various ways—such as identifying seminal phenomena of risky choice (e.g., Allais paradox, fourfold pattern)—it contains a major shortcoming: Psychoeconomic curves are mute with regard to the cognitive mechanisms underlying risky choice. This neglect of the mechanisms both limits the explanatory value of neo-Bernoullian models and fails to provide guidance for designing effective interventions to improve decision making. Here we showcase a recent “attentional turn” in research on risk choice that elaborates how deviations from normative prescriptions can result from imbalances in attention allocation (rather than distortions in the representation or processing of probability and outcome information) and that thus promises to overcome the challenges of the neo-Bernoullian tradition. We argue that a comprehensive understanding of preference formation in risky choice must provide an account on a mechanistic level, and we delineate directions in which existing theories that rely on attentional processes may be extended to achieve this objective.
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Affiliation(s)
- Veronika Zilker
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
- TUM School of Management, Technical University of Munich, Munich, Germany
- *Correspondence: Veronika Zilker
| | - Thorsten Pachur
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
- TUM School of Management, Technical University of Munich, Munich, Germany
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