Journal of Computational Neuroscience

, Volume 37, Issue 1, pp 65–80 | Cite as

Inhibitory synapses between striatal projection neurons support efficient enhancement of cortical signals: A computational model

  • Andrea Stocco
  • Christian Lebiere


The function of lateral inhibitory synapses between striatal projection neurons is currently poorly understood. This paper puts forward a model suggesting that inhibitory collaterals can be used to enhance the incoming cortical signals. In particular, we propose that lateral inhibition between projection neurons performs a signal-enhancing process that resembles the image processing technique of “unsharp masking”, where a blurred copy is used to enhance and sharpen an input image. The paper also presents the results of computer simulations deomsntrating that the proposed mechanisms is compatible with known properties of striatal projection neurons, and outperforms alternative models of lateral inhibition. Finally, this paper illustrates the advantages of the proposed model and discusses the relevance of these conclusions for existing computational models of the basal ganglia and their role in cognition.


Striatum Lateral inhibition Unsharp masking Medium spiny neurons Projection neurons 



  1. Albin, R.L., Young, A.B., Penney, J.B. (1989). The functional anatomy of basal ganglia disorders. Trends in Neurosciences, 12, 366–375.PubMedCrossRefGoogle Scholar
  2. Alexander, G.E., DeLong, M.R., Strick, P.L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9, 357–381.PubMedCrossRefGoogle Scholar
  3. Bar-Gad, I., Havazelet-Heimer, G., Goldberg, J.A., Ruppin, E., Bergman, H. (2000). Reinforcement-driven dimensionality reduction–a model for information processing in the basal ganglia. Journal of Basic and Clinical Physiology and Pharmacology, 11, 305–320.PubMedCrossRefGoogle Scholar
  4. Bogacz, R., & Gurney, K. (2007). The basal ganglia and cortex implement optimal decision making between alternative actions. Neural computation, 19(2), 442–477.PubMedCrossRefGoogle Scholar
  5. Fox, M.D., Snyder, A., Vincent, J., Corbetta, M., Essen, D.V., Raichle, M. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, 102, 9673–9678.CrossRefGoogle Scholar
  6. Frank, M.J., & Claus, E.D. (2006). Anatomy of a decision: striatoorbitofrontal interactions in reinforcement learning, decision making, and reversal. Psychological Review, 113(2), 300.PubMedCrossRefGoogle Scholar
  7. Frank, M.J., Loughry, B., O’Reilly, R.C. (2001). Interactions between frontal cortex and basal ganglia in working memory: a computational model. Cognitive, Affective & Behavioral Neuroscience, 1, 137–160.CrossRefGoogle Scholar
  8. Frank, M.J., Seeberger, L.C., O’Reilly, R.C. (2004). By carrot or by stick: cognitive reinforcement learning in parkinsonism. Science, 306(5703), 1940–1943.PubMedCrossRefGoogle Scholar
  9. Gurney, K., Prescott, T.J., Redgrave, P. (2001a). A computational model of action selection in the basal ganglia. i. a new functional anatomy. Biological Cybernetics, 84, 401–410.PubMedCrossRefGoogle Scholar
  10. Gurney, K., Prescott, T.J., Redgrave, P. (2001b). A computational model of action selection in the basal ganglia. ii. analysis and simulation of behaviour. Biological Cybernetics, 84, 411–423.PubMedCrossRefGoogle Scholar
  11. Haber, S.N. (2003). The primate basal ganglia: parallel and integrative networks. Journal of Chemical Neuroanatomy, 26(4), 317–330.PubMedCrossRefGoogle Scholar
  12. Humphries, M.D., Wood, R., Gurney, K. (2009). Dopamine-modulated dynamic cell assemblies generated by the gabaergic striatal micro-circuit. Neural Networks, 22(8), 1174–1188.PubMedCrossRefGoogle Scholar
  13. Humphries, M.D., Wood, R., Gurney, K. (2010). Reconstructing the three-dimensional gabaergic microcircuit of the striatum. PLoS Computational Biology, 6(11), e1001,011.CrossRefGoogle Scholar
  14. Izhikevich, E.M., & Edelman, G. (2008). Large-scale model of mammalian thalamocortical systems. Proceedings of the National Academy of Sciences, 105, 3593–3598.CrossRefGoogle Scholar
  15. Jaeger, D., Kita, H., Wilson, C.J. (1994). Surround inhibition among projection neurons is weak or nonexistent in the rat neostriatum. Journal of Neurophysiology, 72, 2555–2558.PubMedGoogle Scholar
  16. Kemp, J.M., & Powell, T.P. (1970). The corticostriate projection in the monkey. Brain, 93, 525–546.PubMedCrossRefGoogle Scholar
  17. Levi, L. (1974). Unsharp masking and related image enhancement techniques. Computer Graphics and Image Processing, 3, 163–177.CrossRefGoogle Scholar
  18. Lippman, R.P. (1987). An introduction to computing with neural nets. IEEE Transaction on Acoustics, Speech, and Signal Processing, 35, 2–44.CrossRefGoogle Scholar
  19. McNab, F., & Klingberg, T. (2008). Prefrontal cortex and basal ganglia control access to working memory. Nature Neuroscience, 11, 103–107.PubMedCrossRefGoogle Scholar
  20. Moyer, J.T., Wolf, J.A., Finkel, L.H. (2007). Effects of dopaminergic modulation on the integrative properties of the ventral striatal medium spiny neuron. Journal of Neurophysiology, 98(6), 3731–3748.PubMedCrossRefGoogle Scholar
  21. Nisenbaum, E., & Berger, T. (1992). Functionally distinct subpopulations of striatal neurons are differentially regulated by gabaergic and dopaminergic inputs—I. In vivo analysis. Neuroscience, 48(3), 561–578.PubMedCrossRefGoogle Scholar
  22. O’Reilly, R.C., & Frank, M.J. (2006). Making working memory work: A computational model of learning in the prefrontal cortex and basal ganglia. Neural Computation, 18, 283–328.PubMedCrossRefGoogle Scholar
  23. O’Reilly, R.C., & Munakata, Y. (2000). Computational explorations in cognitive neuroscience. Cambridge: MIT Press.Google Scholar
  24. Packard, M.G., & Knowlton, B.J. (2002). Learning and memory functions of the basal ganglia. Annual Review of Neuroscience, 25(1), 563–593.PubMedCrossRefGoogle Scholar
  25. Parent, A., & Hazrati, L.N. (1995a). Functional anatomy of the basal ganglia. i. the cortico-basal ganglia-thalamo-cortical loop. Brain Research Reviews, 20(1), 91–127.PubMedCrossRefGoogle Scholar
  26. Parent, A., & Hazrati, L.N. (1995b). Functional anatomy of the basal ganglia. ii. the place of subthalamic nucleus and external pallidium in basal ganglia circuitry. Brain Research Reviews, 20(1), 128–154.PubMedCrossRefGoogle Scholar
  27. Plenz, D. (2003). When inhibition goes incognito: feedback interaction between spiny projection neurons in striatal function. Trends in Neurosciences, 26(8), 436–443.PubMedCrossRefGoogle Scholar
  28. Pouget, A., Dayan, P., Zemel, R. (2000). Information processing with population codes. Nature Reviews Neuroscience, 1, 125–132.PubMedCrossRefGoogle Scholar
  29. Redgrave, P., Prescott, T.J., Gurney, K. (1999). The basal ganglia: A vertebrate solution to the selection problem. Neuroscience, 89, 1009–1023.PubMedCrossRefGoogle Scholar
  30. Schultz, W., Dayan, P., Montague, P.R. (1997). A neural substrate of prediction and reward. Science, 275(5306), 1593–1599PubMedCrossRefGoogle Scholar
  31. Stern, E.A., Jaeger, D., Wilson, C.J. (1998). Membrane potential synchrony of simultaneously recorded striatal spiny neurons in vivo. Nature, 394(6692), 475–478.PubMedCrossRefGoogle Scholar
  32. Stocco, A. (2012). Acetylcholine-based entropy in response selection: a model of how striatal interneurons modulate exploration, exploitation, and response variability in decision-making. Frontiers in Neuroscience, 6.Google Scholar
  33. Stocco, A., & Anderson, J.R. (2008). Endogenous control and task representation: an fmri study in algebraic problem-solving. Journal of Cognitive Neuroscience, 20(7), 1300–1314.PubMedCrossRefGoogle Scholar
  34. Stocco, A., Lebiere, C., Anderson, J.R. (2010). Conditional routing of information to the cortex: A model of the basal ganglia’s role in cognitive coordination. Psychological Review, 117, 541–574.PubMedCentralPubMedCrossRefGoogle Scholar
  35. Stocco, A., Lebiere, C., O’Reilly, R.C., Anderson, J.R. (2012). Distinct contributions of the caudate nucleus, rostral prefrontal cortex, and parietal cortex to the execution of instructed tasks. Cognitive, Affective, & Behavioral Neuroscience, 12(4), 611–628.CrossRefGoogle Scholar
  36. Tecuapetla, F., Carrillo-Reid, L., Guzmán, J.N., Galarraga, E., Bargas, J. (2005). Different inhibitory inputs onto neostriatal projection neurons as revealed by field stimulation. Journal of Neurophysiology, 93(2), 1119–1126.PubMedCrossRefGoogle Scholar
  37. Tepper, J.M., Koós, T., Wilson, C.J. (2004). Gabaergic microcircuits in the neostriatum. Trends in Neurosciences, 27(11), 662–669.PubMedCrossRefGoogle Scholar
  38. Tepper, J.M.,Wilson, C.J., Koós, T. (2008). Feedforward and feedback inhibition in neostriatal gabaergic spiny neurons. Brain Research Reviews, 58(2), 272–281.PubMedCentralPubMedCrossRefGoogle Scholar
  39. Tunstall, M.J., Oorschot, D.E., Kean, A., Wickens, J.R. (2002). Inhibitory interactions between spiny projection neurons in the rat striatum. Journal of Neurophysiology, 88, 1263–1269.PubMedGoogle Scholar
  40. Wickens, J., Kotter, R., Alexander, M. (1995). Effects of local connectivity on striatal function: Simulation and analysis of a model. Synapse, 20(4), 281–298.PubMedCrossRefGoogle Scholar
  41. Wilson, C.J. (2007). Gabaergic inhibition in the neostriatum. Progress in Brain Research, 160, 91–110.PubMedCrossRefGoogle Scholar
  42. Yelnik, J., Francois, C., Percheron, G., Tande, D. (1991). Morphological taxonomy of the neurons of the primate striatum. Journal of Comparative Neurology, 313, 273–294.PubMedCrossRefGoogle Scholar
  43. Yin, H.H., & Knowlton, B.J. (2006). The role of the basal ganglia in habit formation. Nature Reviews Neuroscience, 7(6), 464–476.PubMedCrossRefGoogle Scholar
  44. Zheng, T., & Wilson, C.J. (2002). Corticostriatal combinatorics: The implications of corticostriatal axonal arborizations. Journal of Neurophysiology, 87(2), 1007–1017.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Psychology and Institute for Learning and Brain SciencesUniversity of WashingtonSeattleUSA
  2. 2.Department of PsychologyCarnegie Mellon UniversityPittsburghUSA

Personalised recommendations