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Stochastic models of decisions about motion direction: Behavior and physiology
Abstract
Roitman and Shadlen [Roitman J. D., & Shadlen M. N. (2002). Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. Journal of Neuroscience, 22, 9475-9489] have published a non-human primate study on visual decision making. They collected both behavioral and neurophysiological data and provided evidence that the data are qualitatively consistent with a mechanism based on accumulating sensory evidence up to a decision threshold. I have previously demonstrated that a time-variant diffusion model can account quite well quantitatively for both the behavioral and the neural data. In this manuscript I discuss how well the data constrains different components and parameters of the computational process. I also discuss the biological plausibility of the model parameters. I will demonstrate that a relatively large class of models, both with and without temporal integration and both stationary and time-variant could account for the behavioral data. Both the single cell recordings from the parietal cortex and previously published data from the extrastriate visual cortex provide additional constraints. Overall, the data favor a diffusion model with time-variant gain and leaky integrators. The integration time constant, however, turns out not to be well-constrained by the data.
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“The model with urgency explains the longer RTs on error trials 36 (Supplementary Fig. 7).”
From Decision-making with multiple alternatives (2008) · cites this paper as [36]
In the citing paper
“Because chance represents 50% correct, there is less impetus to complete the trial at weak motion strengths, which probably explains the weaker urgency signal, u(t), seen previously in 2-choice experiments2,36.”
From Decision-making with multiple alternatives (2008) · cites this paper as [36]
In the citing paper
“According to the model, the longer RT on errors arises as a consequence of the urgency signal, u(t), which effectively imposes a more lax criterion for terminating the decision (as if the bound were dropping as a function of time), thereby rendering errors more frequent36.”
From Decision-making with multiple alternatives (2008) · cites this paper as [36]
Citations
Cites
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
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
A Recurrent Network Mechanism of Time Integration in Perceptual Decisions
Wong, K.-F., & Wang, X.-J. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.3733-05.2006 · Cited by 1,029
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
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
Microstimulation in visual area MT: effects on direction discrimination performance
Salzman, C., Murasugi, C., Britten, K., & Newsome, W. (1992) · The Journal of Neuroscience · doi:10.1523/jneurosci.12-06-02331.1992 · Cited by 657
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
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
Dynamic field theory of movement preparation.
Erlhagen, W., & Schöner, G. (2002) · Psychological Review · doi:10.1037/0033-295x.109.3.545 · Cited by 546
The influence of urgency on decision time
Reddi, B. A. J., & Carpenter, R. H. S. (2000) · Nature Neuroscience · doi:10.1038/77739 · Cited by 411
Ratcliff, R., Cherian, A., & Segraves, M. A. (2003) · Journal of Neurophysiology · doi:10.1152/jn.01049.2002 · Cited by 380
Skellam, J. G. (1946) · Journal Of The Royal Statistical Society · doi:10.2307/2981372 · Cited by 380
Evidence for an Accumulator Model of Psychophysical Discrimination
VICKERS, D. (1970) · Ergonomics · doi:10.1080/00140137008931117 · Cited by 369
The Wave Theory of Difference and Similarity
Link, S. W. (2020) · Routledge eBooks · doi:10.1201/9780429054709 · Cited by 351
Population coding in neuronal systems with correlated noise
Sompolinsky, H., Yoon, H., Kang, K., & Shamir, M. (2001) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.64.051904 · Cited by 325
Stochastic Dynamic Models of Response Time and Accuracy: A Foundational Primer
Smith, P. L. (2000) · Journal of Mathematical Psychology · doi:10.1006/jmps.1999.1260 · Cited by 271
An Exemplar-Based Random Walk Model of Speeded Classification
Nosofsky, R., & Palmeri, T. (1997) · Psychological Review · doi:10.1037/0033-295x.104.2.266 · Cited by 271
Touch and Go: Decision-Making Mechanisms in Somatosensation
Romo, R., & Salinas, E. (2001) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.24.1.107 · Cited by 262
Dynamic Stochastic Models for Decision Making under Time Constraints
Diederich, A. (1997) · Journal of Mathematical Psychology · doi:10.1006/jmps.1997.1167 · Cited by 244
Microstimulation of visual cortex affects the speed of perceptual decisions
Ditterich, J., Mazurek, M. E., & Shadlen, M. N. (2003) · Nature Neuroscience · doi:10.1038/nn1094 · Cited by 234
Self-citationParé, M., & Munoz, D. P. (1996) · Journal of Neurophysiology · doi:10.1152/jn.1996.76.6.3666 · Cited by 230
Fundamental derivations from decision field theory
Busemeyer, J. R., & Townsend, J. T. (1992) · Mathematical Social Sciences · doi:10.1016/0165-4896(92)90043-5 · Cited by 161
Neural correlates of decisions
Platt, M. L. (2002) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(02)00302-1 · Cited by 153
Diederich, A., & Busemeyer, J. R. (2003) · Journal of Mathematical Psychology · doi:10.1016/s0022-2496(03)00003-8 · Cited by 142
A Stochastic Version of General Recognition Theory
Ashby, F. G. (2000) · Journal of Mathematical Psychology · doi:10.1006/jmps.1998.1249 · Cited by 130
Correspondence Noise and Signal Pooling in the Detection of Coherent Visual Motion
Barlow, H. B., & Tripathy, S. P. (1997) · Journal of Neuroscience · doi:10.1523/jneurosci.17-20-07954.1997 · Cited by 126
Making choices: the neurophysiology of visual-saccadic decision making
Glimcher, P. W. (2001) · Trends in Neurosciences · doi:10.1016/s0166-2236(00)01932-9 · Cited by 101
Neural correlates of visual and motor decision processes
Schall, J. D., & Bichot, N. P. (1998) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(98)80142-6 · Cited by 99
A decision model for accuracy and response latency in recognition memory.
Hockley, W. E., & Murdock, B. B. (1987) · Psychological Review · doi:10.1037/0033-295x.94.3.341 · Cited by 95
A note on the distribution of response times for a random walk with Gaussian increments
Smith, P. L. (1990) · Journal of Mathematical Psychology · doi:10.1016/0022-2496(90)90023-3 · Cited by 51
Decision making: The two stages of neuronal judgement
Reddi, B. A. J. (2001) · Current Biology · doi:10.1016/s0960-9822(01)00363-3 · Cited by 32
Computational approaches to visual decision making.
Ditterich, J. (2006) · Novartis Foundation symposium · doi:10.1002/9780470034989.ch10 · Cited by 20
Self-citationAnalysis of the Hockley and Murdock decision model
Gronlund, S. D., & Ratcliff, R. (1991) · Journal of Mathematical Psychology · doi:10.1016/0022-2496(91)90051-t · Cited by 17
Percept, Decision, Action: Bridging the Gaps
(2006) · Novartis Foundation symposium · doi:10.1002/9780470034989 · Cited by 15
The Decision to Make a Movement: Neurophysiological Insights
Aminoff, M. J., & Goodin, D. S. (1997) · Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · doi:10.1017/s0317167100021788 · Cited by 9
Sensorimotor processing: Charting the frontier
Carpenter, R. H. S. (1997) · Current Biology · doi:10.1016/s0960-9822(06)00171-0 · Cited by 8
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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
Visual fixations and the computation and comparison of value in simple choice
Krajbich, I., Armel, C., & Rangel, A. (2010) · Nature Neuroscience · doi:10.1038/nn.2635 · Cited by 1,408
The speed-accuracy tradeoff: history, physiology, methodology, and behavior
Heitz, R. P. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00150 · Cited by 1,054
Decision-making with multiple alternatives
Churchland, A. K., Kiani, R., & Shadlen, M. N. (2008) · Nature Neuroscience · doi:10.1038/nn.2123 · Cited by 671
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
Metadata
- Authors
- Ditterich, J.
- Affiliations
- University of California, Davis (US)
- Corresponding author
- Ditterich, Jochen
- ORCID
- Ditterich, Jochen
- Venue
- Neural Networks
- Publisher
- Elsevier BV
- Published
- 2006-10
- Volume
- 19
- Issue
- 8
- Pages
- 981-1012
- ISSN
- 0893-6080 (ISSN-L)
- OpenAlex
- W2002824768
- Cited by
- 233
- References
- 44
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 13 · 2023: 16 · 2022: 13 · 2021: 11 · 2020: 16 · 2019: 9 · 2018: 18 · 2017: 15 · 2016: 13 · 2015: 15 · 2014: 15 · 2013: 11 · 2012: 12
- FWCI
- 3.22
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neural Networks (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- motion direction discrimination, visual decision making, diffusion models, decision threshold, sensory evidence accumulation, lateral intraparietal area, parietal cortex, extrastriate cortex, leaky integrator, computational neuroscience, single-unit recording
- MeSH terms
- Action Potentials, Animals, Behavior, Behavior, Animal, Decision Making, Discrimination, Psychological, Humans, Models, Biological, Models, Neurological, Motion, Motion Perception, Neurons, Reaction Time, Stochastic Processes, Time Factors, Visual Cortex
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