Abstract
In this chapter, we provide a tutorial review of the class of sequential sampling models of two-choice decision-making. These models, which have been developed in cognitive and mathematical psychology over the last 50 years, provide a detailed quantitative account of performance in simple, speeded choice tasks. The models explain the major findings from a wide variety of behavioral decision tasks, including the relationship between choice probabilities and response time (RT), the speed-accuracy tradeoff, the shapes of RT distributions, and the relative speed of correct and error responses. More recently, electrophysiological recordings from decision-related brain areas in awake behaving monkeys have revealed a correspondence between patterns of neural firing and the statistical processes of evidence accumulation assumed in the psychological models. We discuss the theoretical relationship between the cognitive process of evidence accumulation and neural firing rates and show how neural data can constrain behavioral models. Importantly, constraints from neurophysiological data can be used to test between models that are otherwise difficult to distinguish. The convergence of psychological theory and neurophysiological data suggests that a common theoretical and mathematical framework is sufficient to account for simple decision-making data at neural and behavioral levels of analysis.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Audley RJ, Pike AR (1965) Some alternative stochastic models of choice. Br J Math Stat Psychol 18:207–225
Bennur S, Gold JI (2011) Distinct representations of a perceptual decision and the associated oculomotor plan in the monkey lateral intraparietal area. J Neurosci 31:913–921
Bode S, Sewell DK, Lilburn SD, Forte JD, Smith PL, Stahl J (2012) Predicting perceptual decision biases from early brain activity. J Neurosci 32:12488–12498
Bogacz R (2007) Optimal decision-making theories: linking neurobiology with behaviour. Trends Cogn Sci 11:118–125
Bogacz R, Brown E, Moehlis J, Holmes P, Cohen JD (2006) The physics of optimal decision making: a formal analysis of models of performance in two-alternative forced-choice tasks. Psychol Rev 113:700–765
Britten KH, Shadlen MN, Newsome WT, Movshon JA (1993) Responses of neurons in macaque MT to stochastic motion signals. Vis Neurosci 10:1157–1169
Britten KH, Newsome WT, Shadlen MN, Celebrini S, Movshon JA (1996) A relationship between behavioral choice and the visual response of neurons in macaque MT. Vis Neurosci 13:87–100
Brown SD, Heathcote A (2008) The simplest complete model of choice response time: Linear ballistic accumulation. Cogn Psychol 57:153–178
Busemeyer JR, Townsend JT (1993) Decision field theory: a dynamic-cognitive approach to decision making in an uncertain environment. Psychol Rev 100:432–459
Churchland AK, Kiani R, Shadlen MN (2008) Decision-making with multiple alternatives. Nat Neurosci 11:693–702
Ditterich J (2006) Evidence for time-variant decision making. Eur J Neurosci 24:3628–3641
Ditterich J, Mazurek ME, Shadlen MN (2003) Microstimulation of visual cortex affects the speed of perceptual decisions. Nat Neurosci 6:891–898
Edwards W (1965) Optimal strategies for seeking information: models for statistics, choice reaction times, and human information processing. J Math Psychol 2:312–329
Forstmann BU, Brown S, Dutilh G, Neumann J, Wagenmakers EJ (2010) The neural substrate of prior information in perceptual decision making: a model-based analysis. Frontiers in Human Neuroscience 4:1–12
Gnadt JW, Andersen RA (1988) Memory related motor planning activity in posterior parietal cortex of macaque. Exp Brain Res 70:216–220
Gold JI, Shadlen MN (2000) Representation of a perceptual decision in developing oculomotor commands. Nature 404:390–394
Gold JI, Shadlen MN (2001) Neural computations that underlie decisions about sensory stimuli. Trends in Cognitive Sciences 5:10–16
Gold JI, Shadlen MN (2002) Banburismus and the brain: decoding the relationship between sensory stimuli, decisions, and reward. Neuron 36:299–308
Gold JI, Shadlen MN (2003) The influence of behavioral context on the representation of a perceptual decision in developing oculomotor commands. J Neurosci 23:632–651
Gold JI, Shadlen MN (2007) The neural basis of decision making. Annu Rev Neurosci 30:535–574
Green DM, Swets JA (1966) Signal detection theory and psychophysics. Wiley, New York
Green DM, Smith AF, von Gierke SM (1983) Choice reaction time with a random foreperiod. Percept Psychophys 34:195–208
Hanes DP, Schall JD (1996) Neural control of voluntary movement initiation. Science 274:427–430
Hanks TD, Ditterich J, Shadlen MN (2006) Microstimulation of macaque area LIP affects decision-making in a motion discrimination task. Nat Neurosci 9:682–689
Huk AC, Meister MLR (2012) Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making. Front Integr Neurosci 6:1–13
Huk AC, Shadlen MN (2005) Neural activity in macaque parietal cortex reflects temporal integration of visual motion signals during perceptual decision making. J Neurosci 25:10420–10436
Kiani R, Hanks TD, Shadlen MN (2008) Bounded integration in parietal cortex underlies decisions even when viewing duration is dictated by the environment. J Neurosci 28:3017–3029
LaBerge D (1962) A recruitment theory of simple behavior. Psychometrika 27:375–396
LaBerge D (1994) Quantitative models of attention and response processing in shape identification tasks. J Math Psychol 38:198–243
Laming DRJ (1968) Information theory of choice reaction time. Wiley, New York
Link SW, Heath RA (1975) A sequential theory of psychological discrimination. Psychometrika 40:77–105
Lo C-C, Wang X-J (2006) Cortico-basal ganglia circuit mechanism for a decision threshold in reaction time tasks. Nat Neurosci 9:956–963
Luce RD (1986) Response times: Their role in inferring elementary mental organization. Oxford University Press, Oxford
Mazurek ME, Roitman JD, Ditterich J, Shadlen MN (2003) A role for neural integrators in perceptual decision making. Cereb Cortex 13:1257–1269
Mulder MJ, Wagenmakers EJ, Ratcliff R, Boekel W, Forstmann BU (2012) Bias in the brain: a diffusion model analysis of prior probability and potential payoff. J Neurosci 32:2335–2343
Palmer J, Huk AC, Shadlen MN (2005) The effect of stimulus strength on the speed and accuracy of a perceptual decision. Journal of Vision 5:376–404
Pike AR (1966) Stochastic models of choice behaviour: response probabilities and latencies of finite Markov chain systems. Br J Math Stat Psychol 21:161–182
Pike AR (1973) Response latency models for signal detection. Psychol Rev 80:53–68
Purcell BA, Heitz RP, Cohen JY, Schall JD, Logan GD, Palmeri TJ (2010) Neurally constrained modeling of perceptual decision making. Psychol Rev 117:1113–1143
Purcell BA, Schall JD, Logan GD, Palmeri TJ (2012) From salience to saccades: multiple-alternative gated stochastic accumulator model of visual search. J Neurosci 32:3433–3446
Rao V, DeAngelis GC, Snyder LH (2012) Neural correlates of prior expectations of motion in the lateral intraparietal and middle temporal areas. J Neurosci 32:10063–10074
Ratcliff R (1978) A theory of memory retrieval. Psychol Rev 85:59–108
Ratcliff R (1988) Continuous versus discrete information processing: modeling accumulation of partial information. Psychol Rev 95:238–255
Ratcliff R (2002) A diffusion model account of response time and accuracy in a brightness discrimination task: fitting real data and failing to fit fake but plausible data. Psychon Bull Rev 9:278–291
Ratcliff R (2006) Modeling response signal and response time data. Cogn Psychol 53:195–237
Ratcliff R, McKoon G (2008) The diffusion decision model: theory and data for two-choice decision tasks. Neural Comput 20:873–922
Ratcliff R, Rouder JN (1998) Modeling response times for two-choice decisions. Psychol Sci 9:347–356
Ratcliff R, Rouder JN (2000) A diffusion model account of masking in two-choice letter identification. J Exp Psychol Hum Percept Perform 26:127–140
Ratcliff R, Smith PL (2004) A comparison of sequential sampling models for two-choice reaction time. Psychol Rev 111:333–367
Ratcliff R, Smith PL (2010) Perceptual discrimination in static and dynamic noise: the temporal relation between perceptual encoding and decision making. J Exp Psychol Gen 139:70–94
Ratcliff R, Van Zandt T, McKoon G (1999) Connectionist and diffusion models of reaction time. Psychol Rev 106:261–300
Ratcliff R, Cherian A, Segraves MA (2003) A comparison of macaque behavior and superior colliculus neuronal activity to predictions from models of two-choice decisions. J Neurophysiol 90:1392–1407
Ratcliff R, Gomez P, McKoon G (2004) A diffusion model account of the lexical decision task. Psychol Rev 111:159–182
Ratcliff R, Hasegawa YT, Hasegawa RP, Smith PL, Segraves MA (2007) Dual diffusion model for single-cell recording data from the superior colliculus in a brightness-discrimination task. J Neurophysiol 97:1756–1774
Ratcliff R, Hasegawa YT, Hasegawa RP, Childers R, Smith PL, Segraves MA (2011) Inhibition in superior colliculus neurons in a brightness discrimination task? Neural Comput 23:1790–1820
Roe RM, Busemeyer JR, Townsend JT (2001) Multialternative decision field theory: a dynamic connectionist model of decision making. Psychol Rev 108:370–392
Roitman JD, Shadlen MN (2002) Response of neurons in the later intraparietal area during a combined visual discrimination reaction time task. J Neurosci 22:9475–9489
Rorie AE, Gao J, McClelland JL, Newsome WT (2010) Integration of sensory and reward information during perceptual decision-making in lateral intraparietal cortex (LIP) of the macaque monkey. PLoS ONE 5:1–21
Schall JD (2004) On building a bridge between brain and behavior. Annu Rev Psychol 55:23–50
Seidemann E, Zohary E, Newsome WT (1998) Temporal gating of neural signals during performance of a visual discrimination task. Nature 394:72–75
Sewell DK, Smith PL (2012) Attentional control in visual signal detection: effects of abrupt-onset and no-onset stimuli. J Exp Psychol Hum Percept Perform 38:1043–1068
Shadlen MN, Newsome WT (1996) Motion perception: seeing and deciding. Proc Nat Acad Sci 93:628–633
Shadlen MN, Newsome WT (2001) Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J Neurophysiol 86:1916–1936
Smith PL (1995) Psychophysically principled models of visual simple reaction time. Psychol Rev 102:567–593
Smith PL (2000) Stochastic dynamic models of response time and accuracy: a foundational primer. J Math Psychol 44:408–463
Smith PL (2010) From poisson shot noise to the integrated Ornstein-Uhlenbeck process: neurally principled models of information accumulation in decision-making and response time. J Math Psychol 54:266–283
Smith PL, McKenzie CRL (2011) Diffusive information accumulation by minimal recurrent neural models of decision-making. Neural Comput 23:2000–2031
Smith PL, Ratcliff R (2004) Psychology and neurobiology of simple decisions. Trends Neurosci 27:161–168
Smith PL, Ratcliff R (2009) An integrated theory of attention and decision making in visual signal detection. Psychol Rev 116:283–317
Smith PL, Van Zandt T (2000) Time-dependent poisson counter models of response latency in simple judgment. Br J Math Stat Psychol 53:293–315
Smith PL, Vickers D (1988) The accumulator model of two-choice discrimination. J Math Psychol 32:135–168
Smith PL, Ratcliff R, Wolfgang BJ (2004) Attention orienting and the timecourse of perceptual decisions: response time distributions with masked and unmasked displays. Vision Res 44:1297–1320
Smith PL, Ellis R, Sewell DK, Wolfgang BJ (2010) Cued detection with compound integration-interruption masks reveals multiple attentional mechanisms. J Vis 10:1–28
Stone M (1960) Models for choice-reaction time. Psychometrika 25:251–260
Teller DY (1984) Linking propositions. Vision Res 10:1233–1246
Thompson KG, Hanes DP, Bichot NP, Schall JD (1996) Perceptual and motor processing stages identified in the activity of macaque frontal eye field neurons during visual search. J Neurophysiol 76:4040–4055
Thompson KG, Bichot NP, Schall JD (1997) Dissociation of visual discrimination from saccade programming in macaque frontal eye field. J Neurophysiol 77:1046–1050
Thornton TL, Gilden DL (2007) Parallel and serial processes in visual search. Psychol Rev 114:71–103
Townsend JT, Ashby FG (1983) Stochastic modeling of elementary psychological processes. Cambridge University Press, Cambridge
Usher M, McClelland JL (2001) The time course of perceptual choice: the leaky, competing accumulator model. Psychol Rev 108:550–592
Van Zandt T, Colonius H, Proctor RW (2000) A comparison of two response time models applied to perceptual matching. Psychon Bull Rev 7:208–256
Vickers D (1970) Evidence for an accumulator model of psychophysical discrimination. Ergonomics 13:37–58
Vickers D (1979) Decision processes in visual perception. Academic Press, New York
Wagenmakers EJ, Brown S (2007) On the linear relation between the mean and the standard deviation of a response time distribution. Psychol Rev 114:830–841
Wald A (1947) Sequential analysis. Wiley, New York
Wang X-J (2001) Synaptic reverberation underlying mnemonic persistent activity. Trends Neurosci 24:455–463
Wang X-J (2002) Probabilistic decision making by slow reverberation in cortical circuits. Neuron 36:955–968
Wickelgren WA (1977) Speed-accuracy tradeoff and information processing dynamics. Acta Psychol 41:67–85
Wong K-F, Wang X-J (2006) A recurrent network mechanism of time integration in perceptual decisions. J Neurosci 26:1314–1328
Acknowledgments
This work was supported by ARC Discovery Grant DP110103406 awarded to P.L. Smith and R. Ratcliff. We thank Simon Lilburn for helpful comments on a previous version of the manuscript. David Sewell is now at the University of Queensland.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Sewell, D.K., Smith, P.L. (2016). The Psychology and Psychobiology of Simple Decisions: Speeded Choice and Its Neural Correlates. In: Reuter, M., Montag, C. (eds) Neuroeconomics. Studies in Neuroscience, Psychology and Behavioral Economics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35923-1_14
Download citation
DOI: https://doi.org/10.1007/978-3-642-35923-1_14
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35922-4
Online ISBN: 978-3-642-35923-1
eBook Packages: Behavioral Science and PsychologyBehavioral Science and Psychology (R0)