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Cortico–basal ganglia circuit mechanism for a decision threshold in reaction time tasks

Abstract

Growing evidence from primate neurophysiology and modeling indicates that in reaction time tasks, a perceptual choice is made when the firing rate of a selective cortical neural population reaches a threshold. This raises two questions: what is the neural substrate of the threshold and how can it be adaptively tuned according to behavioral demands? Using a biophysically based network model of spiking neurons, we show that local dynamics in the superior colliculus gives rise to an all-or-none burst response that signals threshold crossing in upstream cortical neurons. Furthermore, the threshold level depends only weakly on the efficacy of the cortico-collicular pathway. In contrast, the threshold and the rate of reward harvest are sensitive to, and hence can be optimally tuned by, the strength of cortico-striatal synapses, which are known to be modifiable by dopamine-dependent plasticity. Our model provides a framework to describe the main computational steps in a reaction time task and suggests that separate brain pathways are critical to the detection and adjustment of a decision threshold.

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Figure 1: A large-scale brain network model for the reaction time version of a random-dot task.
Figure 2: Threshold detection by burst discharge in the superior colliculus network.
Figure 3: Reaction time simulation by the full network model, in a single trial with motion coherence of 12.8%.
Figure 4: Invariance of the threshold across trials, regardless of decision times and coherence levels.
Figure 5: Roles of cortico-collicular (Cx-SC) and cortico-striatal (Cx-CD) pathways in the determination of the decision threshold.
Figure 6: Dependence of psychometric and chronometric functions on the Cx-CD efficacy.
Figure 7: Optimization of decision-making process.

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References

  1. Luce, R.D. Response Times (Oxford University Press, New York, 1986).

    Google Scholar 

  2. Usher, M. & McClelland, J.L. The time course of perceptual choice: the leaky, competing accumulator model. Psychol. Rev. 108, 550–592 (2001).

    Article  CAS  PubMed  Google Scholar 

  3. Reddi, B.A.J., Asrress, K.N. & Carpenter, R.H.S. Accuracy, information, and response time in a saccadic decision task. J. Neurophysiol. 90, 3538–3546 (2003).

    Article  CAS  PubMed  Google Scholar 

  4. Ratcliff, R. & Smith, P.L. A comparison of sequential sampling models for two-choice reaction time. Psychol. Rev. 111, 333–367 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Newsome, W.T., Britten, K.H. & Movshon, J.A. Neuronal correlates of a perceptual decision. Nature 341, 52–54 (1989).

    Article  CAS  PubMed  Google Scholar 

  6. Roitman, J.D. & Shadlen, M.N. Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. J. Neurosci. 22, 9475–9489 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Kim, J.N. & Shadlen, M.N. Neural correlates of a decision in the dorsolateral prefrontal cortex of the macaque. Nat. Neurosci. 2, 176–185 (1999).

    Article  PubMed  Google Scholar 

  8. Hanes, D.P. & Schall, J.D. Neural control of voluntary movement initiation. Science 274, 427–430 (1996).

    Article  CAS  PubMed  Google Scholar 

  9. Schall, J.D. & Thompson, K.G. Neural selection and control of visually guided eye movements. Annu. Rev. Neurosci. 22, 241–259 (1999).

    Article  CAS  PubMed  Google Scholar 

  10. Gold, J.I. & Shadlen, M.N. Neural computations that underlie decisions about sensory stimuli. Trends Cogn. Sci. 5, 10–16 (2001).

    Article  PubMed  Google Scholar 

  11. Gold, J.I. & Shadlen, M.N. Banburismus and the brain: decoding the relationship between sensory stimuli, decisions, and reward. Neuron 36, 299–308 (2002).

    Article  CAS  PubMed  Google Scholar 

  12. Smith, P.L. & Ratcliff, R. Psychology and neurobiology of simple decisions. Trends Neurosci. 27, 161–168 (2004).

    Article  CAS  PubMed  Google Scholar 

  13. Wang, X.-J. Probabilistic decision making by slow reverberation in cortical circuits. Neuron 36, 955–968 (2002).

    Article  CAS  PubMed  Google Scholar 

  14. Wong, K.-F. & Wang, X.-J. A recurrent network mechanism of time integration in perceptual decisions. J. Neurosci. 26, 1314–1328 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Brown, E. et al. Simple neural networks that optimize decisions. Int. J. Bifurc. Chaos 15, 803–826 (2005).

    Article  Google Scholar 

  16. Palmer, J., Huk, A.C. & Shadlen, M.H. The effect of stimulus strength on the speed and accuracy of a perceptual decision. J. Vis. 5, 376–404 (2005).

    Article  PubMed  Google Scholar 

  17. Hall, W.C., Moschovakis, A. (eds.). The Superior Colliculus: New Approaches for Studying Sensorimotor Integration (CRC Press, New York, 2003).

    Book  Google Scholar 

  18. Munoz, D.P. & Wurtz, R.H. Saccade-related activity in monkey superior colliculus. I. Characteristics of burst and buildup cells. J. Neurophysiol. 73, 2313–2333 (1995).

    Article  CAS  PubMed  Google Scholar 

  19. Sparks, D.L. The brainstem control of saccadic eye movements. Nat. Rev. Neurosci. 3, 952–964 (2002).

    Article  CAS  PubMed  Google Scholar 

  20. Scudder, C.A., Kaneko, C.R.S. & Fuchs, A.F. The brainstem burst generator for saccadic eye movements: a modern synthesis. Exp. Brain Res. 142, 439–462 (2002).

    Article  PubMed  Google Scholar 

  21. Pettit, D.L., Helms, M.C., Lee, P.L., Augustine, G.J. & Hall, W.C. Local excitatory circuits in the intermediate gray layer of the superior colliculus. J. Neurophysiol. 81, 1424–1427 (1999).

    Article  CAS  PubMed  Google Scholar 

  22. Saito, Y. & Isa, T. Electrophysiological and morphological properties of neurons in the rat superior colliculus. I. Neurons in the intermediate layer. J. Neurophysiol. 82, 754–767 (1999).

    Article  CAS  PubMed  Google Scholar 

  23. Saito, Y. & Isa, T. Local excitatory network and NMDA receptor activation generate a synchronous and bursting command from the superior colliculus. J. Neurosci. 23, 5854–5864 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Saito, Y. & Isa, T. Laminar specific distribution of lateral excitatory connections in the rat superior colliculus. J. Neurophysiol. 92, 3500–3510 (2004).

    Article  PubMed  Google Scholar 

  25. Hikosaka, O., Takikawa, Y. & Kawagoe, R. Role of the basal ganglia in the control of purposive saccadic eye movements. Physiol. Rev. 80, 953–978 (2000).

    Article  CAS  PubMed  Google Scholar 

  26. Houk, J.C., Davis, J.L. & Beiser, D.G. (eds.). Model of Information Processing in the Basal Ganglia 2nd edn. (MIT Press, Cambridge, Massachusetts, 1998).

    Google Scholar 

  27. Graybiel, A.M. Building action repertoires: memory and learning functions of the basal ganglia. Curr. Opin. Neurobiol. 5, 733–741 (1995).

    Article  CAS  PubMed  Google Scholar 

  28. Wickens, J. Basal ganglia: structure and computations. Network: Comput. Neural Syst. 8, 77–109 (1997).

    Article  Google Scholar 

  29. Hikosaka, O., Nakamura, K. & Nakahara, H. Basal ganglia orient eyes to reward. J. Neurophysiol. 95, 567–584 (2006).

    Article  PubMed  Google Scholar 

  30. Nicola, S.M., Surmeier, D.T. & Malenka, R.C. Dopaminergic modulation of neuronal excitability in the striatum and nucleus accumbens. Annu. Rev. Neurosci. 23, 185–215 (2000).

    Article  CAS  PubMed  Google Scholar 

  31. Reynolds, J.N.J., Hyland, B.I. & Wickens, J.R. A cellular mechanism of reward-related learning. Nature 413, 67–70 (2001).

    Article  CAS  PubMed  Google Scholar 

  32. Schultz, W. Getting formal with dopamine and reward. Neuron 36, 241–263 (2002).

    Article  CAS  PubMed  Google Scholar 

  33. Kawagoe, R., Takikawa, Y. & Hikosaka, O. Reward-predicting activity of dopamine and caudate neurons—a possible mechanism of motivational control of saccadic eye movement. J. Neurophysiol. 91, 1013–1024 (2004).

    Article  CAS  PubMed  Google Scholar 

  34. Hikosaka, O. & Wurtz, R.H. Visual and oculomotor functions of monkey substantia nigra pars reticulata. I. Relation of visual and auditory responses to saccades. J. Neurophysiol. 49, 1230–1253 (1983).

    Article  CAS  PubMed  Google Scholar 

  35. Sato, M. & Hikosaka, O. Role of primate substantia nigra pars reticulata in reward-oriented saccadic eye movement. J. Neurosci. 22, 2363–2373 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Munoz, D.P., Dorris, M.C., Pare, M. & Everling, S. On your mark, get set: brainstem circuitry underlying saccadic initiation. Can. J. Physiol. Pharmacol. 78, 934–944 (2000).

    Article  CAS  PubMed  Google Scholar 

  37. Ali, A.B. & Thomson, A.M. Facilitating pyramid to horizontal oriens-alveus interneurone inputs: dual intracellular recordings in slices of rat hippocampus. J. Physiol. (Lond.) 507, 185–199 (1998).

    Article  CAS  Google Scholar 

  38. Markram, H., Wang, Y . & Tsodyks, Y. Differential signaling via the same axon of neocortical pyramidal neurons. Proc. Natl. Acad. Sci. USA. 95, 5323–5328 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Munoz, D.P. & Istvan, P.J. Lateral inhibitory interactions in the intermediate layers of the monkey superior colliculus. J. Neurophysiol. 79, 1193–1209 (1998).

    Article  CAS  PubMed  Google Scholar 

  40. Horwitz, G.D. & Newsome, W.T. Target selection for saccadic eye movements: prelude activity in the superior colliculus during a direction-discrimination task. J. Neurophysiol. 86, 2543–2558 (2001).

    Article  CAS  PubMed  Google Scholar 

  41. Wilson, C.J. & Kawaguchi, Y. The origins of two-state spontaneous membrane potential fluctuations of neostriatal spiny neurons. J. Neurosci. 16, 2397–2410 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Gruber, A.J., Solla, S.A., Surmeier, D.J. & Houk, J.C. Modulation of striatal single units by expected reward: a spiny neuron model displaying dopamine-induced bistability. J. Neurophysiol. 90, 1095–1114 (2003).

    Article  PubMed  Google Scholar 

  43. Jiang, H., Stein, B.E. & McHaffie, J.G. Opposing basal ganglia processes shape midbrain visuomotor activity bilaterally. Nature 423, 982–986 (2003).

    Article  CAS  PubMed  Google Scholar 

  44. Frank, M.J., Seeberger, L.C. & O'Reilly, R.C. By carrot or by stick: cognitive reinforcement learning in parkinsonism. Science 306, 1940–1943 (2004).

    Article  CAS  PubMed  Google Scholar 

  45. Soltani, A. & Wang, X.-J.A. Biophysically based neural model of matching law behavior: melioration by stochastic synapses. J. Neurosci. 26, 3731–3744 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Lauwereyns, J., Watanabe, K., Coe, B. & Hikosaka, O. A neural correlate of response bias in monkey caudate nucleus. Nature 418, 413–417 (2002).

    Article  CAS  PubMed  Google Scholar 

  47. Britten, K.H., Shadlen, M.N., Newsome, W.T. & Movshon, J.A. Responses of neurons in macaque MT to stochastic motion signals. Vis. Neurosci. 10, 1157–1169 (1993).

    Article  CAS  PubMed  Google Scholar 

  48. Behan, M., Steinhacker, K., Jeffrey-Borger, S. & Meredith, M.A. Chemoarchitecture of GABAergic neurons in the ferret superior colliculus. J. Comp. Neurol. 452, 334–359 (2002).

    Article  CAS  PubMed  Google Scholar 

  49. Sommer, M.A. & Wurtz, R.H. What the brain stem tells the frontal cortex. II. Role of the SC-MD-FEF pathway in corollary discharge. J. Neurophysiol. 91, 1403–1423 (2004).

    Article  PubMed  Google Scholar 

  50. Hikosaka, O., Sakamoto, M. & Usui, S. Functional properties of monkey caudate neurons. I. Activities related to saccadic eye movements. J. Neurophysiol. 61, 780–798 (1989).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank S. Fusi for early work on the computer program used in this study, and D. Lee and P. Miller for helpful comments on the manuscript. This work was supported by the Swartz Foundation and the US National Institutes of Health (MH 062349).

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Correspondence to Xiao-Jing Wang.

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Supplementary information

Supplementary Fig. 1

The sensitivity of the decision threshold to the cortico-collicular (Cx-SC) efficacy in the absence of the basal ganglia. (PDF 12 kb)

Supplementary Fig. 2

Full network simulations in which single CD neurons are endowed with additional intrinsic ion channel mechanisms and exhibit Up and Down membrane states. (PDF 1078 kb)

Supplementary Fig. 3

Relationship between the bound height in the diffusion model and parameters of our model. (PDF 1065 kb)

Supplementary Methods (PDF 45 kb)

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Lo, CC., Wang, XJ. Cortico–basal ganglia circuit mechanism for a decision threshold in reaction time tasks. Nat Neurosci 9, 956–963 (2006). https://doi.org/10.1038/nn1722

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