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Cited by 678Neural and Behavioral Psychology StudiesNeural dynamics and brain functionMotor Control and Adaptation

Changes of mind in decision-making

Open access
Resulaj, Arbora, Kiani, Roozbeh, Wolpert, Daniel M., Shadlen, Michael N.·2009·Nature
DOI 10.1038/nature08275PMC PMC2875179
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Abstract

A decision is a commitment to a proposition or plan of action based on evidence and the expected costs and benefits associated with the outcome. Progress in a variety of fields has led to a quantitative understanding of the mechanisms that evaluate evidence and reach a decision. Several formalisms propose that a representation of noisy evidence is evaluated against a criterion to produce a decision. Without additional evidence, however, these formalisms fail to explain why a decision-maker would change their mind. Here we extend a model, developed to account for both the timing and the accuracy of the initial decision, to explain subsequent changes of mind. Subjects made decisions about a noisy visual stimulus, which they indicated by moving a handle. Although they received no additional information after initiating their movement, their hand trajectories betrayed a change of mind in some trials. We propose that noisy evidence is accumulated over time until it reaches a criterion level, or bound, which determines the initial decision, and that the brain exploits information that is in the processing pipeline when the initial decision is made to subsequently either reverse or reaffirm the initial decision. The model explains both the frequency of changes of mind as well as their dependence on both task difficulty and whether the initial decision was accurate or erroneous. The theoretical and experimental findings advance the understanding of decision-making to the highly flexible and cognitive acts of vacillation and self-correction.

AI snapshot

Written from the paper’s full text.

TL;DR

The paper shows that subjects can change their mind after initiating a perceptual decision even though no new visual evidence is available, because late-arriving evidence in the processing pipeline can revise the initial choice. It extends bounded drift-diffusion models with a post-initiation change-of-mind bound and deadline to explain when and how often these reversals occur.

Key findings

  • Changes of mind were reflected in curved hand trajectories and reliably improved accuracy for all three subjects by improving sensitivity to motion (p<0.006 for each subject).
  • The initial choice depended on early stimulus fluctuations (average over first 150 ms positive, p<0.0001), while later fluctuations had little bearing on the initial choice; on change-of-mind trials, later motion energy supported the final, changed decision (p<0.0001).
  • Non-decision time was estimated at 300–400 ms, and the model’s change bound required reversal of the accumulated evidence; the amount of evidence needed to change mind (BΔ) differed by ~30% across subjects.
  • A model with a post-initiation change bound fit better than using all available information (p<0.003 for all subjects), capturing changes to correct and incorrect choices with R² = 0.63–0.85 and 0.76–0.99, respectively; changes were most frequent at intermediate motion strengths when the initial choice was erroneous.

Methods

  • Three naïve participants judged left/right motion of a dynamic random dot stimulus and indicated choices by moving a handle to left/right targets; the motion stimulus was extinguished at movement initiation, so no new visual evidence was available during the movement.
  • Subjects completed at least 500 training trials followed by 1500 test trials; hand trajectories were recorded at 1000 Hz, and a change of mind was detected if the area carved out by the hand opposite the final chosen target exceeded 0.1 cm².
  • Analyses used bounded drift-diffusion modeling, motion-energy residuals to test which stimulus epochs supported initial versus changed choices, and fits of post-initiation change-bound/deadline parameters; a control experiment used an auditory beep to time movement initiation, with stimulus motion beginning 200–2000 ms before the beep (mean 440 ms).

Limitations

  • Stated in the paper: the proposed mechanism cannot explain all changes of mind, such as corrections arising from confusion about stimulus-response associations, or changes requiring memory retrieval or incorporation of a new decision policy.
  • Stated in the paper: the model is specific to situations with time pressure and an arm movement; ballistic actions such as eye movements preclude this kind of change-of-mind mechanism.
  • Evident from the text: the main experiment used only three naïve subjects, and some supporting results (e.g., slower-instruction effects) are reported as “data not shown,” limiting generalizability and independent verification.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1038/nature08275

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 24 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Although subjects received no additional information after initiating their movement, their hand trajectories betrayed a change of mind on some trials.

    “Although they received no additional information after initiating their movement, their hand trajectories betrayed a change of mind on some trials.”
    Quote in the paperSubstantial claim
  • Findingown data

    Although no further visual information was available after movement initiation, the hand trajectories gave a clear indication that on some trials observers changed their mind.

    “Although no further visual information was available after movement initiation, the hand trajectories (Fig. 1c) gave a clear indication that on some trials observers changed their mind.”
    Quote in the paperSubstantial claim
  • Findingown data

    The choice at initiation and reaction times as a function of task difficulty (coherence of dot motion) were explained by a bounded drift-diffusion model consistent with previous studies in humans and monkeys.

    “The choice at initiation (initial hand trajectory) and reaction times as a function of task difficulty (coherence of dot motion) were explained by a bounded drift-diffusion model (Fig. 2, black curves) consistent with previous studies in humans and monkeys1,9,14.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [1] Gold, J. I. & Shadlen, M. N. The neural basis of decision making. Annu. Rev. Neurosci. 30, 535–574 (2007) source

      Not checked in the free run.

    • cites [9] Palmer, J., Huk, A. C. & Shadlen, M. N. The effect of stimulus strength on the speed and accuracy of a perceptual decision. J. Vis. 5, 376–404 (2005) source

      Not checked in the free run.

    • cites [14] Smith, P. L. & Ratcliff, R. Psychology and neurobiology of simple decisions. Trends Neurosci. 27, 161–168 (2004) source

      Not checked in the free run.

  • Findingown data

    Normally hand movements for easy trials (high coherence) were straight to the target.

    “Normally hand movements for easy trials (high coherence) were straight to the target.”
    Quote in the paperSubstantial claim
  • Findingown data

    For all three subjects, the model fits imply that upon termination of the initial decision, the subjects set a new bound at a level that would necessitate a reversal of the sign of the accumulated evidence.

    “For all three subjects, the model fits imply that upon termination of the initial decision, the subjects set a new bound at a level that would necessitate a reversal of the sign of the accumulated evidence.”
    Quote in the paperSubstantial claim
  • May combine two claims. 15
  • The quote only partly states this claim. 1
  • Classified as probably not a substantial claim. 9

  • May combine two claims.

    Findingown data

    Changes of mind reliably improved accuracy for all three subjects by improving sensitivity to motion (p<0.006 for each subject).

    “Changes of mind reliably improved accuracy (Fig. 2 top row, black and red circles for the initial and final choice, respectively) for all three subjects by improving sensitivity to motion (p<0.006 for each subject).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The amount of evidence required for a subject to change their mind (Table 1, BΔ) differed by ~30% across subjects, which explains the variation in the pattern of their changes.

    “The amount of evidence required for a subject to change their mind (Table 1, BΔ) differed by ~30% across subjects, which explains the variation in the pattern of their changes.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    This optimal solution fails to explain the findings: it predicts too many changes and would defer them to the end of the evidence stream.

    “This idea fails to explain our findings: it predicts too many changes and it would defer them to the end of the evidence stream, which is clearly not the case (Fig 1c).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The results of the experiment with an exogenous cue confirm that subjects base their initial choice on early evidence but can avail themselves of additional evidence in the processing pipeline to revise this choice.

    “The results of this experiment, which are summarized in Supplementary Figures 1-3, confirm the finding that subjects base their initial choice on early evidence but can avail themselves of additional evidence in the processing pipeline to revise this choice.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In a control experiment with 100% coherent motion, the criterion detected no change-of-mind trials, suggesting that the detection strategy is conservative.

    “In a control experiment with 100% coherent motion, this criterion detected no change-of-mind trials, suggesting that our detection strategy is conservative.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The stimulus fluctuations immediately after stimulus onset supported the initial choice (average over first 150 ms is positive, p<0.0001), whereas the fluctuations in the final few hundred ms had little bearing on the choice.

    “The stimulus fluctuations immediately after stimulus onset supported the initial choice (Fig. 3a, left blue curve; average over first 150 ms is positive, p<0.0001), whereas the fluctuations in the final few hundred ms had little bearing on the choice.”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Findingown data

    An analysis of the motion evidence leading to the subjects' choices supports the hypothesis that unused information could be processed after the brain has committed to an initial choice.

    “An analysis of the motion evidence leading to the subjects’ choices supports this hypothesis.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Although some changes of mind resulted in errors, the majority corrected an initial error.

    “Although some changes of mind resulted in errors, the majority corrected an initial error.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    When two subjects were instructed to perform the reaction time experiment more slowly, their initial decisions were more accurate and there were fewer changes of mind.

    “When two of our subjects were instructed to perform the reaction time experiment more slowly, their initial decisions were more accurate and there were fewer changes of mind (data not shown).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The early information from the stimulus provided weaker support for the initial choice and exhibited a negative trend near the time of initiation, in support of the final, changed decision.

    “The early information from the stimulus provided weaker support for the initial choice (left red trace) and exhibited a negative trend near the time of initiation (right red trace), in support of the final, changed decision.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Such an accumulation process explains both the choice and accuracy of decisions over a range of difficulty levels as well as the time required to make the decision.

    “Such an accumulation process explains both the choice and accuracy of decisions over a range of difficulty levels as well as the time required to make the decision9.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [9] Palmer, J., Huk, A. C. & Shadlen, M. N. The effect of stimulus strength on the speed and accuracy of a perceptual decision. J. Vis. 5, 376–404 (2005) source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    These models are naturally viewed as an extension of signal detection theory and Bayesian inference to streams of data over time.

    “They are naturally viewed as an extension of signal detection theory and Bayesian inference to streams of data over time4,11.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [4] Green, D. M. & Swets, J. A. Signal Detection Theory and Psychophysics (Wiley, 1966)

      Not checked in the free run.

    • cites [11] Beck, J. M. et al. Probabilistic population codes for Bayesian decision making. Neuron 60, 1142–1152 (2008) source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductown data

    The moving dots were extinguished as soon as the subjects initiated their movement, and hence subjects could not acquire new evidence during their movement.

    “Critically, the moving dots were extinguished as soon as the subjects initiated their movement (Fig. 1b) and hence subjects could not acquire new evidence during their movement.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    Several formalisms propose that a representation of noisy evidence is evaluated against a criterion to produce a decision.

    “Several formalisms propose that a representation of noisy evidence is evaluated against a criterion to produce a decision4-8.”
    Quote in the paperSubstantial claim0 of 5 sources checked
    • cites [4] Green, D. M. & Swets, J. A. Signal Detection Theory and Psychophysics (Wiley, 1966)

      Not checked in the free run.

    • cites [5] Laming, D. R. J. Information Theory of Choice-Reaction Times (Wiley, 1968)

      Not checked in the free run.

    • cites [6] Ratcliff, R. & Rouder, J. N. Modelling response times for two-choice decisions. Psychol. Sci. 9, 347–356 (1998) source

      Not checked in the free run.

    • cites [7] Link, S. W. The relative judgment theory of two choice response time. J. Math. Psychol. 12, 114–135 (1975) source

      Not checked in the free run.

    • cites [8] Smith, P. L. & Vickers, D. The accumulator model of two-choice discrimination. J. Math. Psychol. 32, 135–168 (1988) source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Premisenone given

    One important limitation of these models is that they fail to explain why a decision-maker might change their mind after an initial decision has been taken.

    “One important limitation of these models is that they fail to explain why a decision-maker might change their mind after an initial decision has been taken.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The observation provides evidence against two main alternatives to post-initiation processing: (1) change of decision based on recall and/or reconsideration of evidence acquired before initiation, and (2) a correction of an initial motor error perhaps owing to confusion about the stimulus-response mapping.

    “The observation provides evidence against two main alternatives to post-initiation processing: (1) change of decision based on recall and/or reconsideration of evidence acquired before initiation18, and (2) a correction of an initial motor error perhaps owing to confusion about the stimulus-response mapping12.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [18] Romo, R., Hernandez, A., Zainos, A., Lemus, L. & Brody, C. D. Neuronal correlates of decision-making in secondary somatosensory cortex. Nature Neurosci. 5, 1217–1225 (2002) source

      Not checked in the free run.

    • cites [12] Rabbitt, P. & Vyas, S. Processing a display even after you make a response to it. How perceptual errors can be corrected. Q. J. Exp. Psychol. A 33, 223–239 (1981) source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationreasoning

    Such strong evidence ought to arrive when the initial choice is an error and when the motion is strong.

    “Such strong evidence ought to arrive when the initial choice is an error and when the motion is strong.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Taking the motion energy filtering delay into account, the initial choices depend on the earliest information in the stimulus, but ignore an epoch on the order of tnd.

    “Taking this into account, the initial choices depend on the earliest information in the stimulus, but ignore an epoch on the order of tnd.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationreasoning

    Because in our study the subject must complete an arm movement, the optimal solution is likely to trade-off accuracy against motor costs (energy) associated with larger corrections nearer the end of the movement.

    “Also, because in our study the subject must complete an arm movement, the optimal solution is likely to trade-off accuracy against motor costs (energy) associated with larger corrections nearer the end of the movement.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationreasoning

    A change that depends on retrieval of information from memory or incorporation of a new decision policy (e.g., values) would require elaboration of the model.

    “Further, a change that depends on retrieval of information from memory or incorporation of a new decision policy (e.g., values) would require elaboration of the model.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    It is well known that the initiation and final specification of a movement can be dissociated in time.

    “It is well known that the initiation and final specification of a movement can be dissociated in time30.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [30] Ghez, C., Hening, W. & Favilla, M. Gradual specification of response amplitude in human tracking performance. Brain Behav. Evol. 33, 69–74 (1989) source

      Not checked in the free run.

  • May combine two claims.

    Interpretationnone given

    The decision rule is to change only if the accumulated evidence reaches the change bound and to reaffirm otherwise.

    “The decision rule is to change only if the accumulated evidence reaches the change bound and to reaffirm otherwise.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S1 (asserted), S4 (based).

    Interpretationreasoning

    An optimal solution to maximize the percentage of correct final choices would be to continue to accumulate evidence about direction until there is no more to be had (i.e., tnd) and to decide in favor of the more likely direction.

    “Suppose the subject wishes to use changes of mind to maximize the percentage of correct final choices. Then the subject ought to continue to accumulate evidence about direction until there is no more to be had (i.e., tnd) and to decide in favor of the more likely direction.”
    Quote in the paperNot a substantial claim
23 of 23

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Variation in post-decision confidence predicts how likely the decision is to be revised if an opportunity arises.

    “Variation in post-decision confidence predicts how likely the decision is to be revised if an opportunity arises,9”

    From Two prefrontal-subcortical circuits estimate controllability and reflect its impact on learning (2026) · cites this paper as [9]

    The paper’s Abstract reports that changes of mind depend on task difficulty and whether the initial decision was correct, and its model explains revision using evidence accumulated after the initial decision. It does not report measuring post-decision confidence or show that variation in confidence predicts revision. (LLM, conf=0.78)

    Experimental — accuracy not yet measured

  • Evidence accumulation may continue after a decision has been made, informing estimates of decision confidence and potentially leading to changes of mind.

    “Pleskac & Busemeyer (2010) additionally proposed that this evidence accumulation process may continue after a decision has been made, informing estimates of decision confidence and potentially leading to changes of mind (Resulaj et al. 2009, van den Berg et al. 2016a).”

    From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Resulaj et al. 2009

    The passage describing the model (section labeled “Changing your mind: a computational mechanism of vacillation > Abstract”; page unavailable) says evidence continues to accumulate after the initial decision and can reach a change-of-mind bound. Our copy does not say that this post-decision accumulation informs estimates of decision confidence. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Evidence for a process of post-decision evidence accumulation was adduced to explain reversals of perceptual decisions in humans and monkeys.

    “Evidence for such a process was adduced to explain reversals of perceptual decisions in humans and monkeys (Rabbitt, 1966; Rabbitt and Vyas, 1981; McPeek et al., 2000; Caspi and Beutter, 2004; Van Zandt and Maldonado-Molina, 2004; Resulaj et al., 2009; Burk et al., 2014; Kiani et al., 2014b; Moher and Song, 2014).”

    From A common mechanism underlies changes of mind about decisions and confidence (2016) · cites this paper as Resulaj et al., 2009

  • In previous studies, the motor system receives a continuous updating of the state of the evidence leading to a choice and can utilize late arriving information to revise an initial choice by continuing the process of deliberation.

    “In previous studies, we showed that the motor system receives a continuous updating of the state of the evidence leading to a choice (Gold and Shadlen, 2000; Selen et al., 2012) and can utilize the late arriving information to revise an initial choice by continuing the process of deliberation (Resulaj et al., 2009; Burk et al., 2014).”

    From A common mechanism underlies changes of mind about decisions and confidence (2016) · cites this paper as Resulaj et al., 2009

  • For three of the four subjects, changes of decision corrected an initial error more often than they spoiled an initially correct choice.

    “For three of the four subjects, changes of decision corrected an initial error more often than they spoiled an initially correct choice (P<0.001, P<0.001, P = 0.084, P<0.001), consistent with previous reports (Resulaj et al., 2009; Burk et al., 2014).”

    From A common mechanism underlies changes of mind about decisions and confidence (2016) · cites this paper as Resulaj et al., 2009

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Related

Authors
Resulaj, A., Kiani, R., Wolpert, D. M., & Shadlen, M. N.
Affiliations
  • University of Cambridge (GB)
  • Howard Hughes Medical Institute (US)
Corresponding author
Shadlen, Michael N.
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2009-08-19
Volume
461
Issue
7261
Pages
263-266
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/nature08275
PMC
PMC2875179
OpenAlex
W2070029806
Cited by
678
References
39
Citations by year
2026: 27 · 2025: 46 · 2024: 65 · 2023: 33 · 2022: 45 · 2021: 67 · 2020: 58 · 2019: 44 · 2018: 42 · 2017: 31 · 2016: 43 · 2015: 46 · 2014: 41 · 2013: 26 · 2012: 35
FWCI
10.05
Type
journal article
Language
en
Open access
Licence
www.springer.com/tdm (tdm)
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Cambridge University Engineering Department Publications Database (submittedVersion)
Funders
  • Howard Hughes Medical Institute
  • Wellcome Trust (077730, 028056)
  • National Eye Institute (EY11378, R01EY011378)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
Keywords
decision-making, change of mind, vacillation, self-correction, evidence accumulation, drift-diffusion model, decision reversal, decision accuracy, task difficulty, hand trajectory
MeSH terms
Computers, Cues, Decision Making, Female, Hand, Humans, Male, Models, Neurological, Models, Psychological, Motion, Movement, Photic Stimulation, Psychomotor Performance, Reaction Time, Time Factors

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