Elapsed Decision Time Affects the Weighting of Prior Probability in a Perceptual Decision Task
Open accessAbstract
Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (1) decisions that linger tend to arise from less reliable evidence, and (2) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed–accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal area (LIP) of rhesus monkeys performing this task.
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The factors that determine when to stop gathering information and commit to a final decision, as well as which options to sample from, remain an active area of investigation.
“the factors that determine when to stop gathering information and commit to a final decision, as well as which options to sample from, remain an active area of investigation1,4,9–11.”
From Interpretable abstractions of artificial neural networks predict behavior and neural activity during human information gathering (2026) · cites this paper as [1]
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Cites
Brainard, D. H. (1997) · Spatial Vision · doi:10.1163/156856897x00357 · Cited by 19,308 · see citing works
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1994) · Cited by 15,411 · see citing works
Jeffreys, H., Moran, P. A. P., & Chatfield, C. (1922) · Nature · doi:10.1038/109132a0 · Cited by 7,837 · see citing works
Probability theory the logic of science
Jaynes, E. T., & Bretthorst, G. L. (2003) · Cited by 4,600 · see citing works
Probability Theory: The Logic of Science
Jaynes, E. T. (2003) · doi:10.1017/cbo9780511790423 · Cited by 4,045 · see citing works
The Neural Basis of Decision Making
Gold, J. I., & Shadlen, M. N. (2007) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113038 · Cited by 3,764 · see citing works
Self-citationSpatiotemporal energy models for the perception of motion
Adelson, E. H., & Bergen, J. R. (1985) · Journal of the Optical Society of America A · doi:10.1364/josaa.2.000284 · Cited by 3,442 · see citing works
The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks
Ratcliff, R., & McKoon, G. (2008) · Neural Computation · doi:10.1162/neco.2008.12-06-420 · Cited by 3,059 · see citing works
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.2307/2291091 · Cited by 2,359 · see citing works
Bogacz, R., Brown, E., Moehlis, J., Holmes, P. J., & Cohen, J. D. (2006) · Psychological Review · doi:10.1037/0033-295x.113.4.700 · Cited by 1,845 · see citing works
Neural Basis of a Perceptual Decision in the Parietal Cortex (Area LIP) of the Rhesus Monkey
Shadlen, M. N., & Newsome, W. T. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.86.4.1916 · Cited by 1,755 · see citing works
Self-citationNeural correlates of decision variables in parietal cortex
Platt, M. L., & Glimcher, P. W. (1999) · Nature · doi:10.1038/22268 · Cited by 1,721 · see citing works
Roitman, J. D., & Shadlen, M. N. (2002) · The Journal of Neuroscience · doi:10.1523/jneurosci.22-21-09475.2002 · Cited by 1,589 · cited 10× · see citing works
“For Tin choices, this decision end point is marked by a common level of firing rate, regardless of motion strength and RT (Roitman and Shadlen, 2002).”
BackgroundMethodResultInfluentialSelf-citationModeling Response Times for Two-Choice Decisions
Ratcliff, R., & Rouder, J. N. (1998) · Psychological Science · doi:10.1111/1467-9280.00067 · Cited by 1,478 · see citing works
Bayesian inference with probabilistic population codes
Ma, W. J., Beck, J. M., Latham, P. E., & Pouget, A. (2006) · Nature Neuroscience · doi:10.1038/nn1790 · Cited by 1,457 · see citing works
A Comparison of Sequential Sampling Models for Two-Choice Reaction Time.
Ratcliff, R., & Smith, P. L. (2004) · Psychological Review · doi:10.1037/0033-295x.111.2.333 · Cited by 1,227 · see citing works
Optimum Character of the Sequential Probability Ratio Test
Wald, A., & Wolfowitz, J. (1948) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177730197 · Cited by 1,162 · see citing works
An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex
Essen, D. C. V., Drury, H. A., Dickson, J., Harwell, J., Hanlon, D., & Anderson, C. H. (2001) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.2001.0080443 · Cited by 1,100 · see citing works
Matching Behavior and the Representation of Value in the Parietal Cortex
Sugrue, L. P., Corrado, G. S., & Newsome, W. T. (2004) · Science · doi:10.1126/science.1094765 · Cited by 1,030 · see citing works
Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex
Kiani, R., & Shadlen, M. N. (2009) · Science · doi:10.1126/science.1169405 · Cited by 1,027 · see citing works
Self-citationSTRUCTURE AND FUNCTION OF VISUAL AREA MT
Born, R. T., & Bradley, D. C. (2005) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131052 · Cited by 1,023 · cited 1× · see citing works
“Unlike SPRT, in which the DV is in units of LLR, the DV of the brain is naturally expressed in units of spike rate, which arise from computations on quantities such as motion energy (Adelson and Bergen, 1985; Born and Bradley, 2005).”
MethodMemory related motor planning activity in posterior parietal cortex of macaque
Gnadt, J. W., & Andersen, R. A. (1988) · Experimental Brain Research · doi:10.1007/bf00271862 · Cited by 998 · see citing works
Information theory of choice-reaction times
Laming, D. (1968) · Medical Entomology and Zoology · Cited by 952 · see citing works
Neural computations that underlie decisions about sensory stimuli
Gold, J. I., & Shadlen, M. N. (2001) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01567-9 · Cited by 881 · see citing works
Self-citationNeural computation of log likelihood in control of saccadic eye movements
Carpenter, R. H. S., & Williams, M. L. L. (1995) · Nature · doi:10.1038/377059a0 · Cited by 823 · see citing works
Hikosaka, O., & Wurtz, R. H. (1983) · Journal of Neurophysiology · doi:10.1152/jn.1983.49.5.1268 · Cited by 697 · see citing works
The effect of stimulus strength on the speed and accuracy of a perceptual decision
Palmer, J., Huk, A. C., & Shadlen, M. N. (2005) · Journal of Vision · doi:10.1167/5.5.1 · Cited by 691 · see citing works
Self-citationDecision-making with multiple alternatives
Churchland, A. K., Kiani, R., & Shadlen, M. N. (2008) · Nature Neuroscience · doi:10.1038/nn.2123 · Cited by 671 · see citing works
Self-citationProbabilistic population codes for Bayesian decision making
Beck, J. M., Ma, W. J., Kiani, R., Hanks, T., Churchland, A. K., Roitman, J., Shadlen, M. N., Latham, P. E., & Pouget, A. (2008) · Neuron · doi:10.1016/j.neuron.2008.09.021 · Cited by 645 · see citing works
Self-citationA role for neural integrators in perceptual decision making
Mazurek, M. E., Roitman, J. D., Ditterich, J., & Shadlen, M. N. (2003) · Cerebral Cortex · doi:10.1093/cercor/bhg097 · Cited by 620 · see citing works
Self-citationA representation of the hazard rate of elapsed time in macaque area LIP
Janssen, P., & Shadlen, M. N. (2005) · Nature Neuroscience · doi:10.1038/nn1386 · Cited by 601 · see citing works
Self-citationResponses of neurons in macaque MT to stochastic motion signals
Britten, K. H., Shadlen, M. N., Newsome, W. T., & Movshon, J. A. (1993) · Visual Neuroscience · doi:10.1017/s0952523800010269 · Cited by 594 · see citing works
Self-citationA practical difference scheme for Fokker-Planck equations
Chang, J., & Cooper, G. (1970) · Journal of Computational Physics · doi:10.1016/0021-9991(70)90001-x · Cited by 556 · see citing works
Risky business: the neuroeconomics of decision making under uncertainty
Platt, M. L., & Huettel, S. A. (2008) · Nature Neuroscience · doi:10.1038/nn2062 · Cited by 556 · see citing works
Gold, J. I., & Shadlen, M. N. (2002) · Neuron · doi:10.1016/s0896-6273(02)00971-6 · Cited by 547 · see citing works
Self-citationHuk, A. C., & Shadlen, M. N. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.4684-04.2005 · Cited by 538 · see citing works
Self-citationOptimal representation of sensory information by neural populations
Jazayeri, M., & Movshon, J. A. (2006) · Nature Neuroscience · doi:10.1038/nn1691 · Cited by 530 · see citing works
Decisions in Changing Conditions: The Urgency-Gating Model
Cisek, P., Puskas, G. A., & El-Murr, S. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1844-09.2009 · Cited by 521 · see citing works
Kiani, R., Hanks, T. D., & Shadlen, M. N. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4761-07.2008 · Cited by 500 · see citing works
Self-citationA Sequential Theory of Psychological Discrimination
Link, S. W., & Heath, R. A. (1975) · Psychometrika · doi:10.1007/bf02291481 · Cited by 492 · see citing works
NEURAL SELECTION AND CONTROL OF VISUALLY GUIDED EYE MOVEMENTS
Schall, J. D., & Thompson, K. G. (1999) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.22.1.241 · Cited by 489 · see citing works
Modulation of Neuronal Activity in Superior Colliculus by Changes in Target Probability
Basso, M. A., & Wurtz, R. H. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-18-07519.1998 · Cited by 474 · see citing works
Good Thinking: The Foundations of Probability and Its Applications.
Berger, J. O., & Good, I. J. (1985) · Journal of the American Statistical Association · doi:10.2307/2288079 · Cited by 390 · see citing works
Microstimulation of macaque area LIP affects decision-making in a motion discrimination task
Hanks, T. D., Ditterich, J., & Shadlen, M. N. (2006) · Nature Neuroscience · doi:10.1038/nn1683 · Cited by 360 · see citing works
Self-citationThe Wave Theory of Difference and Similarity
Link, S. W. (2020) · Routledge eBooks · doi:10.1201/9780429054709 · Cited by 355 · see citing works
Neuronal Correlates of a Perceptual Decision in Ventral Premotor Cortex
Romo, R., Hernández, A., & Zainos, A. (2004) · Neuron · doi:10.1016/s0896-6273(03)00817-1 · Cited by 340 · see citing works
Edwards, W. (1965) · Journal of Mathematical Psychology · doi:10.1016/0022-2496(65)90007-6 · Cited by 335 · see citing works
Probabilistic Interpretation of Population Codes
Zemel, R. S., Dayan, P., & Pouget, A. (1998) · Neural Computation · doi:10.1162/089976698300017818 · Cited by 333 · see citing works
Probabilistic Interpretation of Population Codes
Zemel, R. S., Dayan, P., & Pouget, A. (1999) · The MIT Press eBooks · doi:10.7551/mitpress/4924.003.0011 · Cited by 320 · see citing works
T HE N EUROBIOLOGY OF V ISUAL -S ACCADIC D ECISION M AKING
Glimcher, P. W. (2003) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.010302.081134 · Cited by 291 · see citing works
Bayesian Computation in Recurrent Neural Circuits
Rao, R. P. N. (2004) · Neural Computation · doi:10.1162/08997660460733976 · Cited by 252 · see citing works
Evidence for time‐variant decision making
Ditterich, J. (2006) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2006.05221.x · Cited by 229 · see citing works
Simen, P., Contreras, D., Buck, C. L., Hu, P. T., Holmes, P. J., & Cohen, J. D. (2009) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/a0016926 · Cited by 224 · see citing works
Accuracy, Information, and Response Time in a Saccadic Decision Task
Reddi, B. A. J., Asrress, K. N., & Carpenter, R. H. S. (2003) · Journal of Neurophysiology · doi:10.1152/jn.00689.2002 · Cited by 217 · see citing works
Cohen, M. R., & Newsome, W. T. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.5179-08.2009 · Cited by 214 · see citing works
Rorie, A. E., Gao, J., McClelland, J. L., & Newsome, W. T. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009308 · Cited by 195 · see citing works
A cognitive signal for the proactive timing of action in macaque LIP
Maimon, G., & Assad, J. A. (2006) · Nature Neuroscience · doi:10.1038/nn1716 · Cited by 185 · see citing works
Diederich, A., & Busemeyer, J. (2006) · Perception & Psychophysics · doi:10.3758/bf03193669 · Cited by 143 · see citing works
A Rapid and Precise On-Response in Posterior Parietal Cortex
Bisley, J. W., Krishna, B. S., & Goldberg, M. E. (2004) · Journal of Neuroscience · doi:10.1523/jneurosci.5007-03.2004 · Cited by 140 · see citing works
Gold, J. I., Law, C.-T., Connolly, P. M., & Bennur, S. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90629.2008 · Cited by 123 · see citing works
Can Monkeys Choose Optimally When Faced with Noisy Stimuli and Unequal Rewards?
Feng, S. F., Holmes, P. J., Rorie, A. E., & Newsome, W. T. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000284 · Cited by 105 · see citing works
The Speed and Accuracy of a Simple Perceptual Decision: A Mathematical Primer
Shadlen, M. N., Hanks, T. D., Churchland, A. K., Kiani, R., & Yang, T. (2006) · The MIT Press eBooks · doi:10.7551/mitpress/9780262042383.003.0010 · Cited by 94 · see citing works
Self-citationPATTERN RECOGNITION AND THE RESPONSES OF SENSORY NEURONS*
Barlow, H. B. (1969) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.1969.tb14019.x · Cited by 88 · see citing works
A biased random walk model for two choice reaction times
Ashby, F. G. (1983) · Journal of Mathematical Psychology · doi:10.1016/0022-2496(83)90011-1 · Cited by 85 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- Drugowitsch J Moreno-Bote R Pouget A Computing the cost function in decision making Front Syst Neurosci Conference Abstract: Computational and systems neuroscience 2009 2009
- Jeffreys H Theory of probability 1961 3d Edition Oxford Clarendon Press
- Seidemann E Neural mechanisms mediating conversion of visual signals into perceptual decisions in a direction discrimination task PhD thesis 1998 Stanford, CA Stanford University Neuroscience Program
- Wald A Sequential Analysis 1947 New York Wiley
Cited by
Sorted by citations
Diffusion decision model: Current issues and history
Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2016.01.007 · Cited by 1,630 · see citing works
“Some recent investigations have suggested that the effects of this manipulation for both humans and monkeys can be accounted for better by a bias in drift rate, not starting point [27].”
BackgroundExpectation in perceptual decision making: neural and computational mechanisms
Summerfield, C., & de Lange, F. P. (2014) · Nature Reviews Neuroscience · doi:10.1038/nrn3838 · Cited by 832 · see citing works
The Cost of Accumulating Evidence in Perceptual Decision Making
Drugowitsch, J., Moreno-Bote, R., Churchland, A. K., Shadlen, M. N., & Pouget, A. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.4010-11.2012 · Cited by 577 · see citing works
Self-citationChoice Certainty Is Informed by Both Evidence and Decision Time
Kiani, R., Corthell, L., & Shadlen, M. N. (2014) · Neuron · doi:10.1016/j.neuron.2014.12.015 · Cited by 470 · see citing works
Self-citationSuboptimality in perceptual decision making
Rahnev, D., & Denison, R. N. (2018) · Behavioral and Brain Sciences · doi:10.1017/s0140525x18000936 · Cited by 342 · see citing works
A common mechanism underlies changes of mind about decisions and confidence
van den Berg, R., Anandalingam, K., Zylberberg, A., Kiani, R., Shadlen, M. N., & Wolpert, D. M. (2016) · eLife · doi:10.7554/elife.12192 · Cited by 270 · see citing works
Self-citationTesting theory of mind in large language models and humans
Strachan, J. W. A., Albergo, D., Borghini, G., Pansardi, O., Scaliti, E., Gupta, S., Saxena, K., Rufo, A., Panzeri, S., Manzi, G., et al. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01882-z · Cited by 299 · see citing works
A neural mechanism of speed-accuracy tradeoff in macaque area LIP
Hanks, T., Kiani, R., & Shadlen, M. N. (2014) · eLife · doi:10.7554/elife.02260 · Cited by 222 · see citing works
Self-citationEffects of cortical microstimulation on confidence in a perceptual decision
Fetsch, C. R., Kiani, R., Newsome, W. T., & Shadlen, M. N. (2014) · Neuron · doi:10.1016/j.neuron.2014.07.011 · Cited by 185 · see citing works
Self-citationNeural circuits for evidence accumulation and decision making in larval zebrafish
Bahl, A., & Engert, F. (2020) · Nature Neuroscience · doi:10.1038/s41593-019-0534-9 · Cited by 166 · see citing works
Human Metacognition Across Domains: Insights from Individual Differences and Neuroimaging
Rouault, M., McWilliams, A., Allen, M. G., & Fleming, S. M. (2018) · Personality Neuroscience · doi:10.1017/pen.2018.16 · Cited by 176 · see citing works
Representation of accumulating evidence for a decision in two parietal areas
de Lafuente, V., Jazayeri, M., & Shadlen, M. N. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.2451-14.2015 · Cited by 162 · see citing works
“In particular, LIP is known to represent the accumulated evidence, combined with other factors that affect the decision, such as the previous probability, value, and costs associated with the alternatives (Seo et al., 2009; Rorie et al., 2010; Hanks et al., 2011; Drugowitsch et al., 2012).”
BackgroundSelf-citationAn integrative framework for perceptual disturbances in psychosis
Horga, G., & Abi-Dargham, A. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0234-1 · Cited by 103 · see citing works
A neural mechanism for terminating decisions
Stine, G. M., Trautmann, E. M., Jeurissen, D., & Shadlen, M. N. (2023) · Neuron · doi:10.1016/j.neuron.2023.05.028 · Cited by 83 · see citing works
Self-citationD’Ambrogio, S., Grohn, J., Khalighinejad, N., Mattar, M. G., Hunt, L., & Rushworth, M. F. S. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02342-9 · Cited by 1 · see citing works
- Authors
- Hanks, T. D., Mazurek, M. E., Kiani, R., Hopp, E., & Shadlen, M. N.
- Affiliations
- Howard Hughes Medical Institute (US)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2011-04-27
- Volume
- 31
- Issue
- 17
- Pages
- 6339-6352
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC3356114
- OpenAlex
- W1987728722
- Cited by
- 378
- References
- 65
- Citations by year
- 2026: 22 · 2025: 27 · 2024: 27 · 2023: 49 · 2022: 26 · 2021: 20 · 2020: 25 · 2019: 27 · 2018: 26 · 2017: 17 · 2016: 25 · 2015: 22 · 2014: 25 · 2013: 15 · 2012: 21
- FWCI
- 10.55
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of Neuroscience (publishedVersion, cc-by-nc-sa)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (RR001 66, 5t32gm007108-40, GM07108)
- National Eye Institute (EY11378, R01EY011378)
- National Institute of General Medical Sciences (T32GM-007108, GM-07108)
- National Center for Research Resources (RR00166, P51RR000166)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- perceptual decision making, prior probability, reliability of evidence, Bayesian decision theory, motion direction discrimination, reaction time, speed-accuracy trade-off, lateral intraparietal area, rhesus monkeys, neuronal firing rate
- MeSH terms
- Action Potentials, Animals, Decision Making, Discrimination, Psychological, Female, Humans, Macaca mulatta, Male, Models, Psychological, Motion Perception, Neurons, Parietal Lobe, Photic Stimulation, Probability, Psychophysics, Reaction Time, Regression Analysis, Time Perception, Bias
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