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Choice-specific sequences in parietal cortex during a virtual-navigation decision task

Nature volume 484, pages 62–68 (2012)Cite this article

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Abstract

The posterior parietal cortex (PPC) has an important role in many cognitive behaviours; however, the neural circuit dynamics underlying PPC function are not well understood. Here we optically imaged the spatial and temporal activity patterns of neuronal populations in mice performing a PPC-dependent task that combined a perceptual decision and memory-guided navigation in a virtual environment. Individual neurons had transient activation staggered relative to one another in time, forming a sequence of neuronal activation spanning the entire length of a task trial. Distinct sequences of neurons were triggered on trials with opposite behavioural choices and defined divergent, choice-specific trajectories through a state space of neuronal population activity. Cells participating in the different sequences and at distinct time points in the task were anatomically intermixed over microcircuit length scales (<100 micrometres). During working memory decision tasks, the PPC may therefore perform computations through sequence-based circuit dynamics, rather than long-lived stable states, implemented using anatomically intermingled microcircuits.

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Figure 1: A PPC-dependent decision task in virtual reality.
Figure 2: Imaging PPC neuronal activity during the T-maze task.
Figure 3: Neuronal activity in individual behavioural periods.
Figure 4: Neuronal circuit trajectories on correct and error trials.
Figure 5: Anatomical micro-organization in the PPC

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References

  1. Shadlen, M. N. & Newsome, W. T. Neural basis of a perceptual decision in the parietal cortex (area LIP) of the rhesus monkey. J. Neurophysiol. 86, 1916–1936 (2001)

    Article  CAS  Google Scholar 

  2. Gold, J. I. & Shadlen, M. N. The neural basis of decision making. Annu. Rev. Neurosci. 30, 535–574 (2007)

    Article  CAS  Google Scholar 

  3. Freedman, D. J. & Assad, J. A. A proposed common neural mechanism for categorization and perceptual decisions. Nature Neurosci. 14, 143–146 (2011)

    Article  CAS  Google Scholar 

  4. Andersen, R. A. & Cui, H. Intention, action planning, and decision making in parietal-frontal circuits. Neuron 63, 568–583 (2009)

    Article  CAS  Google Scholar 

  5. Bisley, J. W. & Goldberg, M. E. Attention, intention, and priority in the parietal lobe. Annu. Rev. Neurosci. 33, 1–21 (2010)

    Article  CAS  Google Scholar 

  6. McNaughton, B. L. et al. Cortical representation of motion during unrestrained spatial navigation in the rat. Cereb. Cortex 4, 27–39 (1994)

    Article  CAS  Google Scholar 

  7. Nitz, D. A. Tracking route progression in the posterior parietal cortex. Neuron 49, 747–756 (2006)

    Article  CAS  Google Scholar 

  8. Whitlock, J. R., Sutherland, R. J., Witter, M. P., Moser, M. B. & Moser, E. I. Navigating from hippocampus to parietal cortex. Proc. Natl Acad. Sci. USA 105, 14755–14762 (2008)

    Article  ADS  CAS  Google Scholar 

  9. Calton, J. L. & Taube, J. S. Where am I and how will I get there from here? A role for posterior parietal cortex in the integration of spatial information and route planning. Neurobiol. Learn. Mem. 91, 186–196 (2009)

    Article  Google Scholar 

  10. Harvey, C. D., Collman, F., Dombeck, D. A. & Tank, D. W. Intracellular dynamics of hippocampal place cells during virtual navigation. Nature 461, 941–946 (2009)

    Article  ADS  CAS  Google Scholar 

  11. Dombeck, D. A., Khabbaz, A. N., Collman, F., Adelman, T. L. & Tank, D. W. Imaging large-scale neural activity with cellular resolution in awake, mobile mice. Neuron 56, 43–57 (2007)

    Article  CAS  Google Scholar 

  12. Dombeck, D. A., Harvey, C. D., Tian, L., Looger, L. L. & Tank, D. W. Functional imaging of hippocampal place cells at cellular resolution during virtual navigation. Nature Neurosci. 13, 1433–1440 (2010)

    Article  CAS  Google Scholar 

  13. Curtis, C. E. & Lee, D. Beyond working memory: the role of persistent activity in decision making. Trends Cogn. Sci. 14, 216–222 (2010)

    Article  Google Scholar 

  14. Barash, S., Bracewell, R. M., Fogassi, L., Gnadt, J. W. & Andersen, R. A. Saccade-related activity in the lateral intraparietal area. I. Temporal properties; comparison with area 7a. J. Neurophysiol. 66, 1095–1108 (1991)

    Article  CAS  Google Scholar 

  15. Chafee, M. V. & Goldman-Rakic, P. S. Matching patterns of activity in primate prefrontal area 8a and parietal area 7ip neurons during a spatial working memory task. J. Neurophysiol. 79, 2919–2940 (1998)

    Article  CAS  Google Scholar 

  16. Wang, X. J. Decision making in recurrent neuronal circuits. Neuron 60, 215–234 (2008)

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  18. Mazurek, M. E., Roitman, J. D., Ditterich, J. & Shadlen, M. N. A role for neural integrators in perceptual decision making. Cereb. Cortex 13, 1257–1269 (2003)

    Article  Google Scholar 

  19. Ganguli, S. et al. One-dimensional dynamics of attention and decision making in LIP. Neuron 58, 15–25 (2008)

    Article  CAS  Google Scholar 

  20. Miller, P., Brody, C. D., Romo, R. & Wang, X. J. A recurrent network model of somatosensory parametric working memory in the prefrontal cortex. Cereb. Cortex 13, 1208–1218 (2003)

    Article  Google Scholar 

  21. Machens, C. K., Romo, R. & Brody, C. D. Flexible control of mutual inhibition: a neural model of two-interval discrimination. Science 307, 1121–1124 (2005)

    Article  ADS  CAS  Google Scholar 

  22. Machens, C. K., Romo, R. & Brody, C. D. Functional, but not anatomical, separation of “what” and “when” in prefrontal cortex. J. Neurosci. 30, 350–360 (2010)

    Article  CAS  Google Scholar 

  23. Jun, J. K. et al. Heterogenous population coding of a short-term memory and decision task. J. Neurosci. 30, 916–929 (2010)

    Article  CAS  Google Scholar 

  24. Singh, R. & Eliasmith, C. Higher-dimensional neurons explain the tuning and dynamics of working memory cells. J. Neurosci. 26, 3667–3678 (2006)

    Article  CAS  Google Scholar 

  25. Batuev, A. S. Two neuronal systems involved in short-term spatial memory in monkeys. Acta Neurobiol. Exp. (Warsz.) 54, 335–344 (1994)

    CAS  Google Scholar 

  26. Seidemann, E., Meilijson, I., Abeles, M., Bergman, H. & Vaadia, E. Simultaneously recorded single units in the frontal cortex go through sequences of discrete and stable states in monkeys performing a delayed localization task. J. Neurosci. 16, 752–768 (1996)

    Article  CAS  Google Scholar 

  27. Baeg, E. H. et al. Dynamics of population code for working memory in the prefrontal cortex. Neuron 40, 177–188 (2003)

    Article  CAS  Google Scholar 

  28. Fujisawa, S., Amarasingham, A., Harrison, M. T. & Buzsaki, G. Behavior-dependent short-term assembly dynamics in the medial prefrontal cortex. Nature Neurosci. 11, 823–833 (2008)

    Article  CAS  Google Scholar 

  29. Pastalkova, E., Itskov, V., Amarasingham, A. & Buzsaki, G. Internally generated cell assembly sequences in the rat hippocampus. Science 321, 1322–1327 (2008)

    Article  ADS  CAS  Google Scholar 

  30. Crowe, D. A., Averbeck, B. B. & Chafee, M. V. Rapid sequences of population activity patterns dynamically encode task-critical spatial information in parietal cortex. J. Neurosci. 30, 11640–11653 (2010)

    Article  CAS  Google Scholar 

  31. Ohki, K., Chung, S., Ch'ng, Y. H., Kara, P. & Reid, R. C. Functional imaging with cellular resolution reveals precise micro-architecture in visual cortex. Nature 433, 597–603 (2005)

    Article  ADS  CAS  Google Scholar 

  32. Komiyama, T. et al. Learning-related fine-scale specificity imaged in motor cortex circuits of behaving mice. Nature 464, 1182–1186 (2010)

    Article  ADS  CAS  Google Scholar 

  33. Erlich, J. C., Bialek, M. & Brody, C. D. A cortical substrate for memory-guided orienting in the rat. Neuron 72, 330–343 (2011)

    Article  CAS  Google Scholar 

  34. Corwin, J. V. & Reep, R. L. Rodent posterior parietal cortex as a component of a cortical network mediating directed spatial attention. Psychobiology 26, 87–102 (1998)

    Google Scholar 

  35. Tian, L. et al. Imaging neural activity in worms, flies and mice with improved GCaMP calcium indicators. Nature Methods 6, 875–881 (2009)

    Article  CAS  Google Scholar 

  36. Mazor, O. & Laurent, G. Transient dynamics versus fixed points in odor representations by locust antennal lobe projection neurons. Neuron 48, 661–673 (2005)

    Article  CAS  Google Scholar 

  37. Briggman, K. L., Abarbanel, H. D. & Kristan, W. B., Jr Optical imaging of neuronal populations during decision-making. Science 307, 896–901 (2005)

    Article  ADS  CAS  Google Scholar 

  38. Churchland, M. M., Yu, B. M., Sahani, M. & Shenoy, K. V. Techniques for extracting single-trial activity patterns from large-scale neural recordings. Curr. Opin. Neurobiol. 17, 609–618 (2007)

    Article  CAS  Google Scholar 

  39. Goldman, M. S. Memory without feedback in a neural network. Neuron 61, 621–634 (2009)

    Article  CAS  Google Scholar 

  40. Ganguli, S., Huh, D. & Sompolinsky, H. Memory traces in dynamical systems. Proc. Natl Acad. Sci. USA 105, 18970–18975 (2008)

    Article  ADS  CAS  Google Scholar 

  41. Maass, W., Joshi, P. & Sontag, E. D. Computational aspects of feedback in neural circuits. PLOS Comput. Biol. 3, e165 (2007)

    Article  ADS  MathSciNet  Google Scholar 

  42. Sussillo, D. & Abbott, L. F. Generating coherent patterns of activity from chaotic neural networks. Neuron 63, 544–557 (2009)

    Article  CAS  Google Scholar 

  43. Leon, M. I. & Shadlen, M. N. Representation of time by neurons in the posterior parietal cortex of the macaque. Neuron 38, 317–327 (2003)

    Article  CAS  Google Scholar 

  44. Wood, E. R., Dudchenko, P. A., Robitsek, R. J. & Eichenbaum, H. Hippocampal neurons encode information about different types of memory episodes occurring in the same location. Neuron 27, 623–633 (2000)

    Article  CAS  Google Scholar 

  45. Burke, S. N. et al. Differential encoding of behavior and spatial context in deep and superficial layers of the neocortex. Neuron 45, 667–674 (2005)

    Article  CAS  Google Scholar 

  46. Braitenberg, V. B. & Schuz, A. Anatomy of the Cortex: Statistics and Geometry (Springer, 1991)

    Book  Google Scholar 

  47. Binzegger, T., Douglas, R. J. & Martin, K. A. A quantitative map of the circuit of cat primary visual cortex. J. Neurosci. 24, 8441–8453 (2004)

    Article  CAS  Google Scholar 

  48. Yoshimura, Y., Dantzker, J. L. & Callaway, E. M. Excitatory cortical neurons form fine-scale functional networks. Nature 433, 868–873 (2005)

    Article  ADS  CAS  Google Scholar 

  49. Song, S., Sjostrom, P. J., Reigl, M., Nelson, S. & Chklovskii, D. B. Highly nonrandom features of synaptic connectivity in local cortical circuits. PLoS Biol. 3, e68 (2005)

    Article  Google Scholar 

  50. Ko, H. et al. Functional specificity of local synaptic connections in neocortical networks. Nature 473, 87–91 (2011)

    Article  ADS  CAS  Google Scholar 

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Acknowledgements

We thank D. Dombeck for assistance with imaging methods and analysis; C. Domnisoru, M. de Bettencourt, C. Brody and A. Miri for discussions; and M. Goldman, J. Hopfield, D. Aronov, B. Scott and T. Hanks for comments on the manuscript. This work was supported by the NIH (R01-MH083686; RC1-NS068148), a fellowship from the Helen Hay Whitney Foundation (C.D.H.), and a Burroughs Wellcome Fund Career Award at the Scientific Interface (C.D.H.)

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Author notes

  1. Christopher D. Harvey

    Present address: Present address: Department of Neurobiology, Harvard Medical School, Boston, Massachusetts 02115, USA.,

Authors and Affiliations

  1. Princeton Neuroscience Institute, Princeton University, Princeton, 08544, New Jersey, USA

    Christopher D. Harvey, Philip Coen & David W. Tank

  2. Bezos Center for Neural Circuit Dynamics, Princeton University, Princeton, 08544, New Jersey, USA

    David W. Tank

  3. Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, 08544, New Jersey, USA

    Christopher D. Harvey & David W. Tank

  4. Department of Molecular Biology, Princeton University, Princeton, 08544, New Jersey, USA

    Christopher D. Harvey, Philip Coen & David W. Tank

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Contributions

C.D.H. performed experiments with assistance from P.C. on the retrograde tracing experiments; D.W.T. implemented the imaging instrumentation; C.D.H. analysed the data with strategy and methods contributions from D.W.T.; C.D.H. and D.W.T. wrote the paper.

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Correspondence to Christopher D. Harvey or David W. Tank.

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Harvey, C., Coen, P. & Tank, D. Choice-specific sequences in parietal cortex during a virtual-navigation decision task. Nature 484, 62–68 (2012). https://doi.org/10.1038/nature10918

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