Stochastic models of decisions about motion direction: Behavior and physiology

Neural Networks

Volumn 19, Issue 8, 2006, Pages 981-1012

  Ditterich, Jochen ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Diffusion process; LIP; Monkey; MT; Probability summation; Temporal integration; Threshold; Time variant

Indexed keywords

PARIETAL CORTEX; PROBABILITY SUMMATION; TEMPORAL INTEGRATION; TIME CONSTANT;

CONSTRAINT THEORY; DECISION MAKING; DIFFUSION; MATHEMATICAL MODELS; NEUROPHYSIOLOGY; THRESHOLD LOGIC; TIME VARYING CONTROL SYSTEMS;

STOCHASTIC CONTROL SYSTEMS;

ARTICLE; BEHAVIOR; DECISION MAKING; MATHEMATICAL COMPUTING; MOTION; MOVEMENT (PHYSIOLOGY); NERVE CELL; NEUROBIOLOGY; NEUROPHYSIOLOGY; NONHUMAN; PARIETAL LOBE; PRIORITY JOURNAL; PROBABILITY; QUANTITATIVE ANALYSIS; STATISTICAL ANALYSIS; STOCHASTIC MODEL; VISUAL CORTEX;

ACTION POTENTIALS; ANIMALS; BEHAVIOR; BEHAVIOR, ANIMAL; DECISION MAKING; DISCRIMINATION (PSYCHOLOGY); HUMANS; MODELS, BIOLOGICAL; MODELS, NEUROLOGICAL; MOTION; MOTION PERCEPTION; NEURONS; REACTION TIME; STOCHASTIC PROCESSES; TIME FACTORS; VISUAL CORTEX;

EID: 33749078502     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2006.05.042     Document Type: Article

References (45)

1. Aminoff M.J., and Goodin D.S. The decision to make a movement: Neurophysiological insights. Canadian Journal of Neurological Sciences 24 (1997) 181-190
2. Ashby F.G. A stochastic version of general recognition theory. Journal of Mathematical Psychology 44 (2000) 310-329
3. Barlow H., and Tripathy S.P. Correspondence noise and signal pooling in the detection of coherent visual motion. Journal of Neuroscience 17 (1997) 7954-7966
4. Britten K.H., Newsome W.T., Shadlen M.N., Celebrini S., and Movshon J.A. A relationship between behavioral choice and the visual responses of neurons in macaque MT. Visual Neuroscience 13 (1996) 87-100
5. Britten K.H., Shadlen M.N., Newsome W.T., and Movshon J.A. Responses of neurons in macaque MT to stochastic motion signals. Visual Neuroscience 10 (1993) 1157-1169
6. Busemeyer J.R., and Townsend J.T. Fundamental derivations from decision field theory. Mathematical Social Sciences 23 (1992) 255-282
7. Busemeyer J.R., and Townsend J.T. Decision field theory: A dynamic-cognitive approach to decision making in an uncertain environment. Psychological Review 100 (1993) 432-459
8. Carpenter R.H.S. Sensorimotor processing: charting the frontier. Current Biology 7 (1997) R348-R351
9. Diederich A. Dynamic stochastic models for decision making under time constraints. Journal of Mathematical Psychology 41 (1997) 260-274
10. Diederich A., and Busemeyer J.R. Simple matrix methods for analyzing diffusion models of choice probability, choice response time, and simple response time. Journal of Mathematical Psychology 47 (2003) 304-322
11. Ditterich J. Computational approaches to visual decision making. In: Chadwick D.J., Diamond M., and Goode J. (Eds). Percept, decision, action: Bridging the gaps. No. 270. Novartis foundation symposium (2006), John Wiley & Sons, Chichester 114-126
12. Ditterich J., Mazurek M.E., and Shadlen M.N. Microstimulation of visual cortex affects the speed of perceptual decisions. Nature Neuroscience 6 (2003) 891-898
13. Erlhagen W., and Schöner G. Dynamic field theory of movement preparation. Psychological Review 109 (2002) 545-572
14. Glimcher P.W. Making choices: the neurophysiology of visual-saccadic decision making. Trends in Neurosciences 24 (2001) 654-659
15. Gold J.I., and Shadlen M.N. Neural computations that underlie decisions about sensory stimuli. Trends in Cognitive Sciences 5 (2001) 10-16
16. Gronlund S.D., and Ratcliff R. Analysis of the Hockley and Murdock decision model. Journal of Mathematical Psychology 35 (1991) 319-344
17. Hockley W.E., and Murdock B.B. A decision model for accuracy and response latency in recognition memory. Psychological Review 94 (1987) 341-358
18. Link S.W. The Wave theory of difference and similarity (1992), Erlbaum, Hillsdale
19. Luce R.D. Response times (1986), Oxford University Press, New York
20. Mazurek M.E., Roitman J.D., Ditterich J., and Shadlen M.N. A role for neural integrators in perceptual decision making. Cerebral Cortex 13 (2003) 1257-1269
21. Nosofsky R.M., and Palmeri T.J. An exemplar-based random walk model of speeded classification. Psychological Review 104 (1997) 266-300
22. Palmer J., Huk A.C., and Shadlen M.N. The effect of stimulus strength on the speed and accuracy of a perceptual decision. Journal of Vision 5 (2005) 376-404
23. Paré M., and Munoz D.P. Saccadic reaction time in the monkey: Advanced preparation of oculomotor programs is primarily responsible for express saccade occurrence. Journal of Neurophysiology 76 (1996) 3666-3681
24. Platt M.L. Neural correlates of decisions. Current Opinion in Neurobiology 12 (2002) 141-148
25. Ratcliff R., Cherian A., and Segraves M. A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of two-choice decisions. Journal of Neurophysiology 90 (2003) 1392-1407
26. Ratcliff R., and Rouder J.N. Modeling response times for two-choice decisions. Psychological Science 9 (1998) 347-356
27. Ratcliff R., and Smith P.L. A comparison of sequential sampling models for two-choice reaction time. Psychological Review 111 (2004) 333-367
28. Reddi B.A. Decision making: the two stages of neural judgement. Current Biology 11 (2001) R603-R606
29. Reddi B.A., and Carpenter R.H. The influence of urgency on decision time. Nature Neuroscience 3 (2000) 827-830
30. Reynolds J.H., and Chelazzi L. Attentional modulation of visual processing. Annual Review of Neuroscience 27 (2004) 611-647
31. Roitman J.D., and Shadlen M.N. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. Journal of Neuroscience 22 (2002) 9475-9489
32. Romo R., and Salinas E. Touch and go: decision-making mechanisms in somatosensation. Annual Review of Neuroscience 24 (2001) 107-137
33. Salzman C.D., Murasugi C.M., Britten K.H., and Newsome W.T. Microstimulation in visual area MT: Effects on direction discrimination performance. Journal of Neuroscience 12 (1992) 2331-2355
34. Schall J.D., and Bichot N.P. Neural correlates of visual and motor decision processes. Current Opinion in Neurobiology 8 (1998) 211-217
35. Shadlen M.N., and Newsome W.T. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. Journal of Neurophysiology 86 (2001) 1916-1936
36. Skellam J.G. The frequency distribution of the difference between two Poisson variates belonging to different populations. Journal of the Royal Statistical Society: Series A 109 (1946) 296
37. Smith P.L. A note on the distribution of response times for a random walk with gaussian increments. Journal of Mathematical Psychology 34 (1990) 445-459
38. Smith P.L. Stochastic dynamic models of response time and accuracy: A foundational primer. Journal of Mathematical Psychology 44 (2000) 408-463
39. Sompolinsky H., Yoon H., Kang K., and Shamir M. Population coding in neuronal systems with correlated noise. Physical Reviews E 64 (2001) 051904
40. Svahn, E. (2001). Parallel matlab toolbox. user documentation. Chalmers University of Technology, Sweden, Dept. of Computer Science & Ecole Polytechnique de Montreal, Canada, Dept. of Biomedical Engineering
41. Usher M., and McClelland J.L. The time course of perceptual choice: The leaky, competing accumulator model. Psychological Review 108 (2001) 550-592
42. Vickers D. Evidence for an accumulator model of psychophysical discrimination. Ergonomics 13 (1970) 37-58
43. Wang X.-J. Probabilistic decision making by slow reverberation in cortical circuits. Neuron 36 (2002) 955-968
44. Wong K.-F., and Wang X.-J. A recurrent network mechanism of time integration in perceptual decisions. Journal of Neuroscience 26 (2006) 1314-1328
45. Zohary E., Shadlen M.N., and Newsome W.T. Correlated neuronal discharge rate and its implications for psychophysical performance. Nature 370 (1994) 140-143