{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T09:58:34Z","timestamp":1780048714498,"version":"3.53.1"},"reference-count":74,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2024,7,28]],"date-time":"2024-07-28T00:00:00Z","timestamp":1722124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"UK-ESRC","award":["ES\/T002409\/1"],"award-info":[{"award-number":["ES\/T002409\/1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The drift-diffusion model (DDM) is a common approach to understanding human decision making. It considers decision making as accumulation of evidence about visual stimuli until sufficient evidence is reached to make a decision (decision boundary). Recently, Smith and colleagues proposed an extension of DDM, the time-varying DDM (TV-DDM). Here, the standard simplification that evidence accumulation operates on a fully formed representation of perceptual information is replaced with a perceptual integration stage modulating evidence accumulation. They suggested that this model particularly captures decision making regarding stimuli with dynamic noise. We tested this new model in two studies by using Bayesian parameter estimation and model comparison with marginal likelihoods. The first study replicated Smith and colleagues\u2019 findings by utilizing the classical random-dot kinomatogram (RDK) task, which requires judging the motion direction of randomly moving dots (motion discrimination task). In the second study, we used a novel type of stimulus designed to be like RDKs but with randomized hue of stationary dots (color discrimination task). This study also found TV-DDM to be superior, suggesting that perceptual integration is also relevant for static noise possibly where integration over space is required. We also found support for within-trial changes in decision boundaries (\u201ccollapsing boundaries\u201d). Interestingly, and in contrast to most studies, the boundaries increased with increasing task difficulty (amount of noise). Future studies will need to test this finding in a formal model.<\/jats:p>","DOI":"10.3390\/e26080642","type":"journal-article","created":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T12:27:43Z","timestamp":1722256063000},"page":"642","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Support for the Time-Varying Drift Rate Model of Perceptual Discrimination in Dynamic and Static Noise Using Bayesian Model-Fitting Methodology"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2796-5622","authenticated-orcid":false,"given":"Jordan","family":"Deakin","sequence":"first","affiliation":[{"name":"School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK"},{"name":"Faculty of Psychology and Human Movement Science, General Psychology, Universit\u00e4t Hamburg, Von-Melle-Park 11, 20146 Hamburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Schofield","sequence":"additional","affiliation":[{"name":"School of Psychology, Aston University, Birmingham B4 7ET, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3632-7569","authenticated-orcid":false,"given":"Dietmar","family":"Heinke","sequence":"additional","affiliation":[{"name":"School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1325","DOI":"10.1016\/j.neunet.2003.06.005","article-title":"Learning and Inference in the Brain","volume":"16","author":"Friston","year":"2003","journal-title":"Neural Netw."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1038\/nrn2787","article-title":"The Free-Energy Principle: A Unified Brain Theory?","volume":"11","author":"Friston","year":"2010","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Friston, K. (2008). Hierarchical Models in the Brain. PLoS Comput. Biol., 4.","DOI":"10.1371\/journal.pcbi.1000211"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1098\/rstb.2005.1622","article-title":"A Theory of Cortical Responses","volume":"360","author":"Friston","year":"2005","journal-title":"Philos. Trans. R. Soc. B Biol. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"20180344","DOI":"10.1098\/rsif.2018.0344","article-title":"Excitatory versus Inhibitory Feedback in Bayesian Formulations of Scene Construction","volume":"16","author":"Abadi","year":"2019","journal-title":"J. R. Soc. Interface"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"985","DOI":"10.3758\/s13414-014-0825-x","article-title":"Modeling Visual Search Using Three-Parameter Probability Functions in a Hierarchical Bayesian Framework","volume":"77","author":"Lin","year":"2015","journal-title":"Atten. Percept. Psychophys."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1037\/0033-295X.111.1.159","article-title":"A Diffusion Model Account of the Lexical Decision Task","volume":"111","author":"Ratcliff","year":"2004","journal-title":"Psychol. Rev."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.neuroimage.2014.03.063","article-title":"Trial-by-Trial Fluctuations in CNV Amplitude Reflect Anticipatory Adjustment of Response Caution","volume":"96","author":"Boehm","year":"2014","journal-title":"NeuroImage"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1146\/annurev.neuro.29.051605.113038","article-title":"The Neural Basis of Decision Making","volume":"30","author":"Gold","year":"2007","journal-title":"Annu. Rev. Neurosci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"19434","DOI":"10.1523\/JNEUROSCI.3355-13.2013","article-title":"Internal and External Influences on the Rate of Sensory Evidence Accumulation in the Human Brain","volume":"33","author":"Kelly","year":"2013","journal-title":"J. Neurosci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2335","DOI":"10.1523\/JNEUROSCI.4156-11.2012","article-title":"Bias in the Brain: A Diffusion Model Analysis of Prior Probability and Potential Payoff","volume":"32","author":"Mulder","year":"2012","journal-title":"J. Neurosci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1167\/5.5.1","article-title":"The Effect of Stimulus Strength on the Speed and Accuracy of a Perceptual Decision","volume":"5","author":"Palmer","year":"2005","journal-title":"J. Vis."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"873","DOI":"10.1162\/neco.2008.12-06-420","article-title":"The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks","volume":"20","author":"Ratcliff","year":"2008","journal-title":"Neural Comput."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.tics.2016.01.007","article-title":"Diffusion Decision Model: Current Issues and History","volume":"20","author":"Ratcliff","year":"2016","journal-title":"Trends Cogn. Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.neuron.2016.12.003","article-title":"Perceptual Decision Making in Rodents, Monkeys, and Humans","volume":"93","author":"Hanks","year":"2017","journal-title":"Neuron"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"10420","DOI":"10.1523\/JNEUROSCI.4684-04.2005","article-title":"Neural Activity in Macaque Parietal Cortex Reflects Temporal Integration of Visual Motion Signals during Perceptual Decision Making","volume":"25","author":"Huk","year":"2005","journal-title":"J. Neurosci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1113\/jphysiol.1958.sp005978","article-title":"Temporal and Spatial Summation in Human Vision at Different Background Intensities","volume":"141","author":"Barlow","year":"1958","journal-title":"J. Physiol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2341","DOI":"10.1016\/0042-6989(92)90097-3","article-title":"Temporal and Spatial Integration in Dynamic Random-Dot Stimuli","volume":"32","author":"Watamaniuk","year":"1992","journal-title":"Vision Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"882","DOI":"10.3758\/s13423-020-01742-7","article-title":"Vision for the Blind: Visual Psychophysics and Blinded Inference for Decision Models","volume":"27","author":"Smith","year":"2020","journal-title":"Psychon. Bull. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1037\/a0015156","article-title":"An Integrated Theory of Attention and Decision Making in Visual Signal Detection","volume":"116","author":"Smith","year":"2009","journal-title":"Psychol. Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.jmp.2013.05.007","article-title":"Modeling Perceptual Discrimination in Dynamic Noise: Time-Changed Diffusion and Release from Inhibition","volume":"59","author":"Smith","year":"2014","journal-title":"J. Math. Psychol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.neunet.2015.10.005","article-title":"Choice Reaching with a LEGO Arm Robot (CoRLEGO): The Motor System Guides Visual Attention to Movement-Relevant Information","volume":"72","author":"Strauss","year":"2015","journal-title":"Neural Netw."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Makwana, M., Zhang, F., Heinke, D., and Song, J.-H. (2023). Continuous Action with a Neurobiologically Inspired Computational Approach Reveals the Dynamics of Selection History. PLoS Comput. Biol., 19.","DOI":"10.1371\/journal.pcbi.1011283"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.3758\/s13423-017-1417-2","article-title":"The Quality of Response Time Data Inference: A Blinded, Collaborative Assessment of the Validity of Cognitive Models","volume":"26","author":"Dutilh","year":"2019","journal-title":"Psychon. Bull. Rev."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/0001-6918(69)90055-9","article-title":"The Discovery of Processing Stages: Extensions of Donders\u2019 Method","volume":"30","author":"Sternberg","year":"1969","journal-title":"Acta Psychol. (Amst.)"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Deakin, J., Porat, L., van Zoest, W., and Heinke, D. (2021). Behavioral Research, Overt Performance. Encyclopedia of Behavioral Neuroscience, Elsevier.","DOI":"10.1016\/B978-0-12-819641-0.00162-6"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/BF02296650","article-title":"Selective Influence through Conditional Independence","volume":"68","author":"Dzhafarov","year":"2003","journal-title":"Psychometrika"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1037\/a0034190","article-title":"Unfalsifiability and Mutual Translatability of Major Modeling Schemes for Choice Reaction Time","volume":"121","author":"Jones","year":"2014","journal-title":"Psychol. Rev."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"108058","DOI":"10.1016\/j.visres.2022.108058","article-title":"Deep Neural Networks and Image Classification in Biological Vision","volume":"197","author":"Leek","year":"2022","journal-title":"Vision Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"61","DOI":"10.3758\/s13423-010-0022-4","article-title":"Diffusion versus Linear Ballistic Accumulation: Different Models but the Same Conclusions about Psychological Processes?","volume":"18","author":"Donkin","year":"2011","journal-title":"Psychon. Bull. Rev."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Heathcote, A., and Love, J. (2012). Linear Deterministic Accumulator Models of Simple Choice. Front. Psychol., 3.","DOI":"10.3389\/fpsyg.2012.00292"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1037\/a0036801","article-title":"The Hare and the Tortoise: Emphasizing Speed Can Change the Evidence Used to Make Decisions","volume":"40","author":"Rae","year":"2014","journal-title":"J. Exp. Psychol. Learn. Mem. Cogn."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1007\/s00426-014-0608-y","article-title":"Empirical Validation of the Diffusion Model for Recognition Memory and a Comparison of Parameter-Estimation Methods","volume":"79","author":"Arnold","year":"2015","journal-title":"Psychol. Res."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1283","DOI":"10.1162\/jocn_a_00967","article-title":"Transcranial Direct Current Stimulation Does Not Influence the Speed\u2013Accuracy Tradeoff in Perceptual Decision-Making: Evidence from Three Independent Studies","volume":"28","author":"Labruna","year":"2016","journal-title":"J. Cogn. Neurosci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.neuropsychologia.2015.07.012","article-title":"Different Effects of Dopaminergic Medication on Perceptual Decision-Making in Parkinson\u2019s Disease as a Function of Task Difficulty and Speed\u2013Accuracy Instructions","volume":"75","author":"Huang","year":"2015","journal-title":"Neuropsychologia"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Mulder, M.J., and van Maanen, L. (2013). Are Accuracy and Reaction Time Affected via Different Processes?. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0080222"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.3758\/BF03196893","article-title":"Interpreting the Parameters of the Diffusion Model: An Empirical Validation","volume":"32","author":"Voss","year":"2004","journal-title":"Mem. Cognit."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1037\/a0028151","article-title":"Diffusion Model Drift Rates Can Be Influenced by Decision Processes: An Analysis of the Strength-Based Mirror Effect","volume":"38","author":"Starns","year":"2012","journal-title":"J. Exp. Psychol. Learn. Mem. Cogn."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1732","DOI":"10.1037\/xlm0001285","article-title":"Reexamining the Effects of Speed-Accuracy Instructions with a Diffusion-Model-Based Analysis","volume":"49","author":"Ratcliff","year":"2023","journal-title":"J. Exp. Psychol. Learn. Mem. Cogn."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s00426-014-0542-z","article-title":"Time Pressure Affects the Efficiency of Perceptual Processing in Decisions under Conflict","volume":"79","author":"Dambacher","year":"2015","journal-title":"Psychol. Res."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1037\/xlm0000725","article-title":"The Role of Passing Time in Decision-Making","volume":"46","author":"Evans","year":"2020","journal-title":"J. Exp. Psychol. Learn. Mem. Cogn."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1037\/0033-295X.113.4.700","article-title":"The Physics of Optimal Decision Making: A Formal Analysis of Models of Performance in Two-Alternative Forced-Choice Tasks","volume":"113","author":"Bogacz","year":"2006","journal-title":"Psychol. Rev."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1146\/annurev-psych-122414-033645","article-title":"Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions","volume":"67","author":"Forstmann","year":"2016","journal-title":"Annu. Rev. Psychol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"971","DOI":"10.3758\/s13423-017-1340-6","article-title":"Time-Varying Decision Boundaries: Insights from Optimality Analysis","volume":"25","author":"Malhotra","year":"2018","journal-title":"Psychon. Bull. Rev."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1016\/j.neuron.2013.10.047","article-title":"Decision Making as a Window on Cognition","volume":"80","author":"Shadlen","year":"2013","journal-title":"Neuron"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.3758\/s13423-018-1479-9","article-title":"Some Task Demands Induce Collapsing Bounds: Evidence from a Behavioral Analysis","volume":"25","author":"Palestro","year":"2018","journal-title":"Psychon. Bull. Rev."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1520","DOI":"10.3758\/s13414-019-01806-4","article-title":"A Theoretical Analysis of the Reward Rate Optimality of Collapsing Decision Criteria","volume":"82","author":"Boehm","year":"2020","journal-title":"Atten. Percept. Psychophys."},{"key":"ref_48","unstructured":"Laming, D.R.J. (1968). Information Theory of Choice-Reaction Times, Academic Press."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"438","DOI":"10.3758\/BF03196302","article-title":"Estimating Parameters of the Diffusion Model: Approaches to Dealing with Contaminant Reaction Times and Parameter Variability","volume":"9","author":"Ratcliff","year":"2002","journal-title":"Psychon. Bull. Rev."},{"key":"ref_50","unstructured":"The MathWorks Inc. (2021). MATLAB Version: 9.11.0 (R2021b), The MathWorks Inc.. Available online: https:\/\/www.mathworks.com."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Chakraborty, U.K. (2008). Differential Evolution Research\u2014Trends and Open Questions. Advances in Differential Evolution, Springer.","DOI":"10.1007\/978-3-540-68830-3"},{"key":"ref_52","unstructured":"Qiang, J. (2024, June 10). A Unified Differential Evolution Algorithm for Global Optimization. Available online: https:\/\/escholarship.org\/uc\/item\/41b84414."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.jmp.2012.06.004","article-title":"Approximate Bayesian Computation with Differential Evolution","volume":"56","author":"Turner","year":"2012","journal-title":"J. Math. Psychol."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"227","DOI":"10.3758\/s13423-013-0530-0","article-title":"A Generalized, Likelihood-Free Method for Posterior Estimation","volume":"21","author":"Turner","year":"2014","journal-title":"Psychon. Bull. Rev."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1080\/13506285.2017.1352055","article-title":"Serial versus Parallel Search: A Model Comparison Approach Based on Reaction Time Distributions","volume":"25","author":"Narbutas","year":"2017","journal-title":"Vis. Cogn."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2630","DOI":"10.1016\/j.patcog.2011.03.019","article-title":"Multivariate Online Kernel Density Estimation with Gaussian Kernels","volume":"44","author":"Kristan","year":"2011","journal-title":"Pattern Recognit."},{"key":"ref_57","unstructured":"Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis, Chapman and Hall."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.jmp.2015.08.006","article-title":"A Practical Guide to the Probability Density Approximation (PDA) with Improved Implementation and Error Characterization","volume":"68\u201369","author":"Holmes","year":"2015","journal-title":"J. Math. Psychol."},{"key":"ref_59","unstructured":"Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A., and Rubin, D.B. (2015). Bayesian Data Analysis, Chapman and Hall\/CRC. [3rd ed.]."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1080\/01621459.1995.10476572","article-title":"Bayes Factors","volume":"90","author":"Kass","year":"1995","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"930","DOI":"10.3758\/s13428-018-1172-y","article-title":"Thermodynamic Integration via Differential Evolution: A Method for Estimating Marginal Likelihoods","volume":"51","author":"Evans","year":"2019","journal-title":"Behav. Res. Methods"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Jeffreys, H. (1998). Theory of Probability, Clarendon Press.","DOI":"10.1093\/oso\/9780198503682.001.0001"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"388","DOI":"10.3758\/s13428-019-01237-x","article-title":"Gorilla in Our Midst: An Online Behavioral Experiment Builder","volume":"52","author":"Flitton","year":"2020","journal-title":"Behav. Res. Methods"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3758\/s13428-014-0458-y","article-title":"jsPsych: A JavaScript Library for Creating Behavioral Experiments in a Web Browser","volume":"47","year":"2015","journal-title":"Behav. Res. Methods"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"904","DOI":"10.1038\/s41598-019-57204-1","article-title":"Controlling for Participants\u2019 Viewing Distance in Large-Scale, Psychophysical Online Experiments Using a Virtual Chinrest","volume":"10","author":"Li","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Rajananda, S., Lau, H., and Odegaard, B. (2018). A Random-Dot Kinematogram for Web-Based Vision Research. J. Open Res. Softw., 6.","DOI":"10.5334\/jors.194"},{"key":"ref_67","unstructured":"Gonzalez, R.C., and Woods, R.E. (2008). Digital Image Processing, Prentice Hall. [3rd ed.]."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1037\/0033-295X.85.2.59","article-title":"A Theory of Memory Retrieval","volume":"85","author":"Ratcliff","year":"1978","journal-title":"Psychol. Rev."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1111\/1467-9280.00067","article-title":"Modeling Response Times for Two-Choice Decisions","volume":"9","author":"Ratcliff","year":"1998","journal-title":"Psychol. Sci."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1037\/a0018128","article-title":"Perceptual Discrimination in Static and Dynamic Noise: The Temporal Relation between Perceptual Encoding and Decision Making","volume":"139","author":"Ratcliff","year":"2010","journal-title":"J. Exp. Psychol. Gen."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1167\/jov.23.1.6","article-title":"Revisiting the Color-Motion Asynchrony","volume":"23","author":"Huang","year":"2023","journal-title":"J. Vis."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Standage, D., You, H., Wang, D., and Dorris, M.C. (2011). Gain Modulation by an Urgency Signal Controls the Speed\u2013Accuracy Trade-Off in a Network Model of a Cortical Decision Circuit. Front. Comput. Neurosci., 5.","DOI":"10.3389\/fncom.2011.00007"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1830","DOI":"10.3758\/s13423-015-0851-2","article-title":"The Urgency-Gating Model Can Explain the Effects of Early Evidence","volume":"22","author":"Carland","year":"2015","journal-title":"Psychon. Bull. Rev."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1016\/j.neunet.2006.05.042","article-title":"Stochastic Models of Decisions about Motion Direction: Behavior and Physiology","volume":"19","author":"Ditterich","year":"2006","journal-title":"Neural Netw."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/26\/8\/642\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:25:25Z","timestamp":1760109925000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/26\/8\/642"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,28]]},"references-count":74,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["e26080642"],"URL":"https:\/\/doi.org\/10.3390\/e26080642","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,28]]}}}