Stochastic models of decisions about motion direction: Behavior and physiology

The time course of perceptual choice: The leaky, competing accumulator model.

Usher, M., & McClelland, J. L. (2001) · Psychological Review · doi:10.1037/0033-295x.108.3.550 · Cited by 2,152

Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment.

Busemeyer, J. R., & Townsend, J. T. (1993) · Psychological Review · doi:10.1037/0033-295x.100.3.432 · Cited by 1,925

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

Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task

Roitman, J. D., & Shadlen, M. N. (2002) · The Journal of Neuroscience · doi:10.1523/jneurosci.22-21-09475.2002 · Cited by 1,589

Modeling Response Times for Two-Choice Decisions

Ratcliff, R., & Rouder, J. N. (1998) · Psychological Science · doi:10.1111/1467-9280.00067 · Cited by 1,478

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 1,288

Probabilistic decision making by slow reverberation in cortical circuits

Wang, X.-J. (2002) · Neuron · doi:10.1016/s0896-6273(02)01092-9 · Cited by 1,242

Correlated neuronal discharge rate and its implications for psychophysical performance

Zohary, E., Shadlen, M. N., & Newsome, W. T. (1994) · Nature · doi:10.1038/370140a0 · Cited by 1,237

Attentional modulation of visual processing

Reynolds, J. H., & Chelazzi, L. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.26.041002.131039 · Cited by 1,158

A relationship between behavioral choice and the visual responses of neurons in macaque MT

Britten, K. H., Newsome, W. T., Shadlen, M. N., Celebrini, S., & Movshon, J. A. (1996) · Visual Neuroscience · doi:10.1017/s095252380000715x · Cited by 1,049

Stochastic Choice and Optimal Sequential SamplingPreprint

Fudenberg, D., Strack, P., & Strzalecki, T. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2602927 · Cited by 34

The Effects of Evidence Bounds on Decision-Making: Theoretical and Empirical Developments

Zhang, J. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00263 · Cited by 33

Temporal integration is a robust feature of perceptual decisions

Hyafil, A., de la Rocha, J., Pericas, C., Katz, L. N., Huk, A. C., & Pillow, J. W. (2023) · eLife · doi:10.7554/elife.84045 · Cited by 33

Prediction of Decisions from Noise in the Brain before the Evidence is Provided

Rolls, E. T., & Deco, G. (2011) · Frontiers in Neuroscience · doi:10.3389/fnins.2011.00033 · Cited by 30

A rational model of people's inferences about others' preferences based on response times

Gates, V., Callaway, F., Ho, M. K., & Griffiths, T. L. (2021) · Cognition · doi:10.1016/j.cognition.2021.104885 · Cited by 28

A General Integrative Neurocognitive Modeling Framework to Jointly Describe EEG and Decision-making on Single Trials

Ghaderi-Kangavari, A., Rad, J. A., & Nunez, M. D. (2023) · Computational Brain & Behavior · doi:10.1007/s42113-023-00167-4 · Cited by 39

Testing Optimal Timing in Value-Linked Decision Making

Bhui, R. (2019) · Computational Brain & Behavior · doi:10.1007/s42113-019-0025-9 · Cited by 28

Food decision-making under time pressure

Huseynov, S., & Palma, M. A. (2020) · Food Quality and Preference · doi:10.1016/j.foodqual.2020.104072 · Cited by 27

Dynamics of individual perceptual decisions

Merfeld, D. M., Clark, T. K., Lu, Y. M., & Karmali, F. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00225.2015 · Cited by 27

Explicit melioration by a neural diffusion model

Simen, P., & Cohen, J. D. (2009) · Brain Research · doi:10.1016/j.brainres.2009.07.017 · Cited by 27

The gated cascade diffusion model: An integrated theory of decision making, motor preparation, and motor execution.

Dendauw, E., Evans, N. J., Logan, G. D., Haffen, É., Bennabi, D., Gajdos, T., & Servant, M. (2024) · Psychological Review · doi:10.1037/rev0000464 · Cited by 31

How Prior Probability Influences Decision Making: A Unifying Probabilistic Model

Huang, Y., Hanks, T. D., Shadlen, M. N., Friesen, A. L., & Rao, R. P. N. (2012) · Cited by 25

Categorical evidence, confidence, and urgency during probabilistic categorization

Braunlich, K., & Seger, C. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.11.011 · Cited by 24

Reaction time impairments in decision-making networks as a diagnostic marker for traumatic brain injuries and neurological diseases

Maia, P. D., & Kutz, J. N. (2017) · Journal of Computational Neuroscience · doi:10.1007/s10827-017-0643-y · Cited by 24

Dynamic combination of sensory and reward information under time pressure

Farashahi, S. G., Ting, C.-C., Kao, C.-H., Wu, S., & Soltani, A. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006070 · Cited by 22

Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model

Standage, D., You, H., Wang, D., & Dorris, M. C. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003021 · Cited by 21

Time-Varying Perturbations Can Distinguish Among Integrate-to-Threshold Models for Perceptual Decision Making in Reaction Time Tasks

Zhou, X., Wong‐Lin, K., & Holmes, P. J. (2009) · Neural Computation · doi:10.1162/neco.2009.07-08-817 · Cited by 23

Temporal integration of sensory evidence for saccade target selection

Ludwig, C. J. H. (2009) · Vision Research · doi:10.1016/j.visres.2009.08.012 · Cited by 23

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation

Colas, J. T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0186822 · Cited by 21

Inhibition in Superior Colliculus Neurons in a Brightness Discrimination Task?

Ratcliff, R., Hasegawa, Y. T., Hasegawa, R. P., Childers, R., Smith, P. L., & Segraves, M. A. (2011) · Neural Computation · doi:10.1162/neco_a_00135 · Cited by 21

Diffusion models with time-dependent parameters: An analysis of computational effort and accuracy of different numerical methods

Richter, T., Ulrich, R., & Janczyk, M. (2023) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2023.102756 · Cited by 21

Optimal decision-making theories

Bogacz, R. (2009) · Elsevier eBooks · doi:10.1016/b978-0-12-374620-7.00018-2 · Cited by 21

Decision prioritization and causal reasoning in decision hierarchies

Zylberberg, A. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009688 · Cited by 20

Neural population dynamics underlying evidence accumulation in multiple rat brain regions

DePasquale, B., Brody, C. D., & Pillow, J. W. (2024) · eLife · doi:10.7554/elife.84955 · Cited by 22

Confluence of Timing and Reward Biases in Perceptual Decision-Making Dynamics

Shinn, M., Ehrlich, D. B., Lee, D., Murray, J. D., & Seo, H. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.0544-20.2020 · Cited by 19

Fast solutions for the first-passage distribution of diffusion models with space-time-dependent drift functions and time-dependent boundaries

Boehm, U., Cox, S., Gantner, G., & Stevenson, R. P. (2021) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2021.102613 · Cited by 19

Correlates of Perceptual Learning in an Oculomotor Decision Variable

Connolly, P. M., Bennur, S., & Gold, J. I. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.3962-08.2009 · Cited by 19

On mimicry among sequential sampling models

Khodadadi, A., & Townsend, J. T. (2015) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2015.08.007 · Cited by 22

Is saccade averaging determined by visual processing or movement planning?

Bhutani, N., Ray, S., & Murthy, A. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00344.2012 · Cited by 17

“Reliable organisms from unreliable components” revisited: the linear drift, linear infinitesimal variance model of decision making

Smith, P. L. (2023) · Psychonomic Bulletin & Review · doi:10.3758/s13423-022-02237-3 · Cited by 19

Neurocognitive Modeling of Perceptual Decision Making

Palmeri, T. J., Schall, J. D., & Logan, G. D. (2015) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199957996.013.15 · Cited by 17

A probabilistic, distributed, recursive mechanism for decision-making in the brain

Caballero, J. A., Humphries, M. D., & GURNEY, K. N. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006033 · Cited by 16

Systematic and random sources of variability in perceptual decision-making: Comment on Ratcliff, Voskuilen, and McKoon (2018).

Evans, N. J., Tillman, G., & Wagenmakers, E. (2020) · Psychological Review · doi:10.1037/rev0000192 · Cited by 20

Linear Integration of Sensory Evidence over Space and Time Underlies Face Categorization

Okazawa, G., Sha, L., & Kiani, R. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.3055-20.2021 · Cited by 16

Motion discrimination under uncertainty and ambiguity

Kalisvaart, J. P., Klaver, I., & Goossens, J. (2011) · Journal of Vision · doi:10.1167/11.1.20 · Cited by 17

Learning to allocate limited time to decisions with different expected outcomes

Khodadadi, A., Fakhari, P., & Busemeyer, J. R. (2017) · Cognitive Psychology · doi:10.1016/j.cogpsych.2017.03.002 · Cited by 18

Closed-Form Approximations of First-Passage Distributions for a Stochastic Decision-Making Model

Broderick, T., Wong‐Lin, K., & Holmes, P. J. (2010) · Applied Mathematics Research eXpress · doi:10.1093/amrx/abp008 · Cited by 16

Discrimination of Regular and Irregular Rhythms Explained by a Time Difference Accumulation Model

Espinoza-Monroy, M., & de Lafuente, V. (2021) · Neuroscience · doi:10.1016/j.neuroscience.2021.01.035 · Cited by 12

An Optimizing Neuroeconomic Model of Discrete Choice

Woodford, M. (2014) · National Bureau of Economic Research · doi:10.3386/w19897 · Cited by 16

Computational analysis of speed-accuracy tradeoff

Penconek, M. (2022) · Scientific Reports · doi:10.1038/s41598-022-26120-2 · Cited by 14

Optimal metacognitive control of memory recall.

Callaway, F., Griffiths, T. L., Norman, K. A., & Zhang, Q. (2023) · Psychological Review · doi:10.1037/rev0000441 · Cited by 23

Estimating the growth of internal evidence guiding perceptual decisions

Ludwig, C. J. H., & Davies, J. R. (2011) · Cognitive Psychology · doi:10.1016/j.cogpsych.2011.05.002 · Cited by 14

Reach target selection in humans using ambiguous decision cues containing variable amounts of conflicting sensory evidence supporting each target choice

Coallier, É., & Kalaska, J. F. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00145.2014 · Cited by 15

Response time modelling reveals evidence for multiple, distinct sources of moral decision caution

Andrejević, M., White, J. P., Feuerriegel, D., Laham, S. M., & Bode, S. (2022) · Cognition · doi:10.1016/j.cognition.2022.105026 · Cited by 16

Reaction time in ankle movements: a diffusion model analysis

Michmizos, K. P., & Krebs, H. I. (2014) · Experimental Brain Research · doi:10.1007/s00221-014-4032-8 · Cited by 15

The Influence of Spatiotemporal Structure of Noisy Stimuli in Decision Making

Insabato, A., Dempere‐Marco, L., Pannunzi, M., Deco, G., & Romo, R. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003492 · Cited by 15

Environmental uncertainty and the advantage of impulsive choice strategies

Burk, D. C., & Averbeck, B. B. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010873 · Cited by 16

Temporal Integration of Auditory Information Is Invariant to Temporal Grouping Cues

Liu, A., Tsunada, J., Gold, J. I., & Cohen, Y. E. (2015) · eNeuro · doi:10.1523/eneuro.0077-14.2015 · Cited by 13

ChaRTr: An R toolbox for modeling choices and response times in decision-making tasks

Chandrasekaran, C., & Hawkins, G. E. (2019) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2019.108432 · Cited by 15

7T functional MRI finds no evidence for distinct functional subregions in the subthalamic nucleus during a speeded decision-making task

Miletić, S., Keuken, M. C., Mulder, M., Trampel, R., de Hollander, G., & Forstmann, B. U. (2022) · Cortex · doi:10.1016/j.cortex.2022.06.014 · Cited by 13

Robust parallel decision-making in neural circuits with nonlinear inhibition

Kriener, B., Chaudhuri, R., & Fiete, I. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1917551117 · Cited by 13

Diffusion theory of the antipodal “shadow” mode in continuous-outcome, coherent-motion decisions.

Smith, P. L., Corbett, E. A., & Lilburn, S. D. (2022) · Psychological Review · doi:10.1037/rev0000377 · Cited by 13

Different Forms of Variability Could Explain a Difference Between Human and Rat Decision Making

Nguyen, Q. N., & Reinagel, P. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.794681 · Cited by 16

Information Search Within a Web Page: Modeling the Full Sequence of Eye Movement Decisions, Subjective Value Updating, and First Clicks

Lu, J., & Hutchinson, J. W. (2024) · Management Science · doi:10.1287/mnsc.2022.02983 · Cited by 10

Consistent Implementation of Decisions in the Brain

Marshall, J. A. R., Bogacz, R., & Gilchrist, I. D. (2012) · PLoS ONE · doi:10.1371/journal.pone.0043443 · Cited by 11

Perceptual Decision-Making

Summerfield, C., & Blangero, A. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-805308-9.00012-9 · Cited by 17

Numerical approximation of the first-passage time distribution of time-varying diffusion decision models: A mesh-free approach

Rasanan, A. H. H., Evans, N. J., Rieskamp, J., & Rad, J. A. (2023) · Engineering Analysis with Boundary Elements · doi:10.1016/j.enganabound.2023.03.005 · Cited by 12

Eye dominance alternations in binocular rivalry do not require visual awareness

Platonov, A., & Goossens, J. (2014) · Journal of Vision · doi:10.1167/14.11.2 · Cited by 9

Deep Brain Stimulation of the Subthalamic Nucleus Does Not Affect the Decrease of Decision Threshold during the Choice Process When There Is No Conflict, Time Pressure, or Reward

Leimbach, F., Georgiev, D., Vladimir Litvak, A., Antoniades, C. A., Limousin, P. D., Jahanshahi, M., & Bogacz, R. (2018) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01252 · Cited by 8

A theoretical analysis of the reward rate optimality of collapsing decision criteria

Boehm, U., van Maanen, L., Evans, N. J., Brown, S. D., & Wagenmakers, E. (2019) · Attention Perception & Psychophysics · doi:10.3758/s13414-019-01806-4 · Cited by 10

Further perceptions of probability: In defence of associative models.

Forsgren, M., Juslin, P., & van den Berg, R. (2023) · Psychological Review · doi:10.1037/rev0000410 · Cited by 8

Response Time Distributions and the Accumulation of Visual Evidence in Freely Moving Mice

Treviño, M., y León, R. M., & Lezama, E. (2022) · Neuroscience · doi:10.1016/j.neuroscience.2022.08.015 · Cited by 7

Optimal policy for uncertainty estimation concurrent with decision making

Li, X., Su, R., Chen, Y., & Yang, T. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112232 · Cited by 6

Support for the Time-Varying Drift Rate Model of Perceptual Discrimination in Dynamic and Static Noise Using Bayesian Model-Fitting Methodology

Deakin, J., Schofield, A. J., & Heinke, D. G. (2024) · Entropy · doi:10.3390/e26080642 · Cited by 6

Clarifying the nature of stochastic fluctuations and accumulation processes in spontaneous movements

Bogler, C., Grujičić, B., & Haynes, J. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1271180 · Cited by 8

A parameter recovery assessment of a wide class of evidence accumulation models of decision-makingPreprint

Murrow, M., & Holmes, W. R. (2024) · Research Square · doi:10.21203/rs.3.rs-4722049/v1 · Cited by 8

Grounding computational cognitive models.

Ludwig, C. J. H., Stuchlý, E., & Malhotra, G. (2025) · Psychological Review · doi:10.1037/rev0000533 · Cited by 5

Neural dynamics encoding risky choices during deliberation reveal separate choice subspaces

Peters, L. M., Roadarmel, A., Overton, J. A., Stickle, M. P., Lin, J. J., Kong, Z., Sáez, I., & Moxon, K. A. (2025) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2025.102776 · Cited by 5

Mental kinematics: dynamics and mechanics of neurocognitive systems

Barack, D. L. (2020) · Synthese · doi:10.1007/s11229-020-02766-1 · Cited by 5

A note on decomposition of sources of variability in perceptual decision-making

Kang, I., Ratcliff, R., & Voskuilen, C. (2020) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2020.102431 · Cited by 5

No cause for pause: new analyses of ramping and stepping dynamics in LIP (Rebuttal to Response to Reply to Comment on Latimer et al 2015)Preprint

Latimer, K. W., Huk, A. C., & Pillow, J. W. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/160994 · Cited by 7

Overcoming indecision by changing the decision boundaryPreprint

Malhotra, G., Leslie, D., Ludwig, C. J. H., & Bogacz, R. (2017) · doi:10.31219/osf.io/2rdrw · Cited by 5

A cross-species framework for investigating perceptual evidence accumulationPreprint

Chakravarty, S., Delgado-Sallent, C., Kane, G. A., Xia, H., Do, Q. H., Senne, R. A., & Scott, B. B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.17.589945 · Cited by 5

Of Rodents and Primates: Time-Variant Gain in Drift–Diffusion Decision Models

Asadpour, A., Tan, H. R., Lenfesty, B., & Wong‐Lin, K. (2024) · Computational Brain & Behavior · doi:10.1007/s42113-023-00194-1 · Cited by 8

Rule-based and stimulus-based cues bias auditory decisions via different computational and physiological mechanisms

Tardiff, N., Suriya-Arunroj, L., Cohen, Y. E., & Gold, J. I. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010601 · Cited by 7

The Influence of Past Decision Information on Decision Making in the Present

Olianezhad, F., Zabbah, S., & Ebrahimpour, R. (2016) · The Neuroscience Journal of Shefaye Khatam · doi:10.18869/acadpub.shefa.4.3.1 · Cited by 4

Sequential Sampling Models Without Random Between-Trial Variability: The Racing Diffusion Model of Speeded DecisionPreprint

Tillman, G. (2017) · doi:10.31234/osf.io/xuwbk · Cited by 4

Control Limited Perceptual Decision MakingPreprint

de Saa, J. R. C., & Renart, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.24.497481 · Cited by 5

A general integrative neurocognitive modeling framework to jointly describe EEG and decision-making on single trialsPreprint

Ghaderi-Kangavari, A., Rad, J. A., & Nunez, M. D. (2022) · doi:10.31234/osf.io/pqv2c · Cited by 4

A cross-species framework for investigating perceptual evidence accumulationPreprint

Chakravarty, S., Delgado-Sallent, C., Kane, G. A., Xia, H., Do, Q. H., Senne, R. A., & Scott, B. B. (2025) · eLife · doi:10.7554/elife.105116 · Cited by 4

Conflict in moral and nonmoral decision making: an empirical study coupled with a computational model

Gautheron, F., Quinton, J., & Smeding, A. (2024) · Cognitive Processing · doi:10.1007/s10339-024-01178-0 · Cited by 7

Second Guessing in Perceptual Decision-Making

McLean, C. S., Ouyang, B., & Ditterich, J. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.2787-19.2020 · Cited by 3

Micropools of reliable area MT neurons explain rapid motion detection

Krause, B. M., & Ghose, G. M. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00845.2017 · Cited by 3

Estimating systematic and random sources of variability in perceptual decision-making: A reply to Evans, Tillman, & Wagenmakers (2020).

Ratcliff, R., & Smith, P. L. (2021) · Psychological Review · doi:10.1037/rev0000212 · Cited by 3

Accumulation of Evidence in Decision Making

Huk, A. C., Katz, L. N., & Yates, J. L. (2014) · Encyclopedia of Computational Neuroscience · doi:10.1007/978-1-4614-7320-6_309-2 · Cited by 3

Reaction time impairments in decision-making networks as a diagnostic marker for traumatic brain injuries and neurodegenerative diseasesPreprint

Maia, P. D., & Kutz, J. N. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1608.05778 · Cited by 3

A neural substrate for Bayesian integration in human parietal cortexPreprint

Singletary, N. M., Gottlieb, J. P., & Horga, G. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.30.466508 · Cited by 3

To integrate or not to integrate: Testing degenerate strategies for solving an accumulation of perceptual evidence decision-making taskPreprint

Kopec, C. D., Luo, T. Z., Bondy, A., Gupta, D., Elliott, V. A., Charlton, J. A., Breda, J. R., Stagnaro, W. M., Reyes, E. J., Sirko, A. I., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.21.609064 · Cited by 2

A cross-species framework for investigating perceptual evidence accumulationPreprint

Chakravarty, S., Delgado-Sallent, C., Kane, G. A., Xia, H., Do, Q. H., Senne, R. A., & Scott, B. B. (2025) · eLife · doi:10.7554/elife.105116.1 · Cited by 4

Bayesian inference for latent stepping and ramping models of spike train data

Latimer, K. W., Huk, A., & Pillow, J. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781139941433.008 · Cited by 2

Perceptual Decisions in the Presence of Relevant and Irrelevant Sensory Evidence

Anders, U., McLean, C. S., Ouyang, B., & Ditterich, J. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00618 · Cited by 2

Can the wrong horse win: The ability of race models to predict fast or slow errors

Townsend, J. T., & Liu, Y. (2020) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2020.102360 · Cited by 4

Distinguishing Between Models of Perceptual Decision Making

Ditterich, J. (2015) · Springer eBooks · doi:10.1007/978-1-4939-2236-9_13 · Cited by 2

Unifying and generalizing models of neural dynamics during decision-makingPreprint

Zoltowski, D. M., Pillow, J. W., & Linderman, S. W. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2001.04571 · Cited by 6

Further Perceptions of Probability: In Defence of Associative Models – A Commentary on Gallistel et al. 2014Preprint

Forsgren, M., Juslin, P., & van den Berg, R. (2019) · bioRxiv · doi:10.1101/2020.01.30.927558 · Cited by 2

Trial-history biases in evidence accumulation can give rise to apparent lapsesPreprint

Gupta, D., DePasquale, B., Kopec, C. D., & Brody, C. D. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.18.524599 · Cited by 2

An Introduction and Tutorial to Fitting (Time-Dependent) Diffusion Models with the R-Package dRiftDMPreprint

Koob, V., Richter, T., Ulrich, R., & Janczyk, M. (2024) · doi:10.31219/osf.io/3t2vf · Cited by 3

Asynchronous decision making in a memorized paddle pressing task

Dankert, J. R., Olson, B., & Si, J. (2008) · Journal of Neural Engineering · doi:10.1088/1741-2560/5/4/001 · Cited by 1

Dynamics of a Recurrent Spiking Neural Network in the Two-Alternative Choice Task

Pugavko, M. M., Maslennikov, O. V., & Nekorkin, V. I. (2022) · Radiophysics and Quantum Electronics · doi:10.1007/s11141-022-10175-2 · Cited by 1

Speeded response tasks with unpredictable deadlines

Blurton, S. P., Feifel, J., & Gondan, M. (2023) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2023.102776 · Cited by 3

doi:10.1111/j.1460-9568.2006.05221.x Evidence for time-variant decision making

Ditterich, J. (2014)

Evidence for time‐variant decision making

Ditterich, J. (2006) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2006.05221.x · Cited by 240

Direct observation of the neural computations underlying a single decision

Steinemann, N. A., Stine, G. M., Trautmann, E. M., Zylberberg, A., Wolpert, D. M., & Shadlen, M. N. (2023) · eLife · doi:10.7554/elife.90859.3 · Cited by 87

A 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

Temporal dynamics underlying perceptual decision making: Insights from the interplay between an attractor model and parietal neurophysiology

Wong‐Lin, K. (2008) · Frontiers in Neuroscience · doi:10.3389/neuro.01.028.2008 · Cited by 22