Start/stop signals emerge in nigrostriatal circuits during sequence learning

Journal name:
Nature
Volume:
466,
Pages:
457–462
Date published:
DOI:
doi:10.1038/nature09263
Received
Accepted

Abstract

Learning new action sequences subserves a plethora of different abilities such as escaping a predator, playing the piano, or producing fluent speech. Proper initiation and termination of each action sequence is critical for the organization of behaviour, and is compromised in nigrostriatal disorders like Parkinson’s and Huntington’s diseases. Using a self-paced operant task in which mice learn to perform a particular sequence of actions to obtain an outcome, we found neural activity in nigrostriatal circuits specifically signalling the initiation or the termination of each action sequence. This start/stop activity emerged during sequence learning, was specific for particular actions, and did not reflect interval timing, movement speed or action value. Furthermore, genetically altering the function of striatal circuits disrupted the development of start/stop activity and selectively impaired sequence learning. These results have important implications for understanding the functional organization of actions and the sequence initiation and termination impairments observed in basal ganglia disorders.

At a glance

Figures

  1. Mice learn to perform a specific sequence of actions.
    Figure 1: Mice learn to perform a specific sequence of actions.

    a, b, Example of the microstructure of the behaviour of a mouse during a session on the first day of FR8 training (a) and the last day of FR8 training (b). Each dot indicates a lever press, with red and black indicating the first and final press of each individual sequence. The black and red solid lines on the x axis represent magazine entries and licks, respectively. The black dashed lines indicated the time of reward delivery and the corresponding lever press. cf, Average number of lever presses per sequence (c), sequence duration (d), ISI (e) and within-sequence press rate (f), during the first, sixth and twelfth day of FR8 training. gj, Variability, measured as coefficient of variance (CV), of sequence length (g), sequence duration (h), ISI (i) and within-sequence press rate (j) during the first, sixth and twelfth day of FR8 training. Error bars denote s.e.m.

  2. Lever-press-related activity in nigrostriatal circuits.
    Figure 2: Lever-press-related activity in nigrostriatal circuits.

    a, b, Examples of MSNs showing positive (a) and negative (b) modulation of firing rate in relation to lever pressing. c, d, Examples of negative (c) and positive (d) modulation of firing rate of SN GABA neurons relative to lever pressing. e, Example of positive modulation of firing rate in an SN DA neuron before lever pressing. Top, raster plot where each dot indicates a spike; bottom, perievent time histogram (PETH) of spiking activity for the same neuron; time zero is the time of lever pressing (ae). f, Percentage of MSNs (left), SN GABA (middle) and SN DA (right) neurons displaying press-related activity throughout learning. Error bars denote s.e.m.

  3. Neural activity signalling the initiation and termination of action sequences emerges in nigrostriatal circuits during learning.
    Figure 3: Neural activity signalling the initiation and termination of action sequences emerges in nigrostriatal circuits during learning.

    ac, Example of a striatal MSN (a), an SN GABA neuron (b) and an SN DA neuron (c) showing significantly higher phasic firing selectively before the first press of a sequence. d, Example of a striatal MSN showing a phasic increase in activity preferentially before the last press of a sequence. e, Example of an SN GABA neuron showing both sequence initiation and termination related activity. Top, raster plot where each black dot indicates a spike and each orange triangle represents a lever press; bottom, PETH for the same neuron (ae). From left to right, each column shows the PETH of the same neuron related to the first, second, third, third to final, second to final and final press of each sequence (ae). fh, Proportion of striatal MSNs (f), SN GABA neurons (g) and SN DA neurons (h) showing sequence start/stop-related activity (including only initiation, only termination or both) throughout training. ik, Proportion of striatal MSNs (i), SN GABA neurons (j) and SN DA neurons (k) showing activity signalling sequence initiation, termination, or both initiation and termination (day12). Error bars denote s.e.m.

  4. Sequence start/stop-related activity does not reflect differences in expected value and can be action specific.
    Figure 4: Sequence start/stop-related activity does not reflect differences in expected value and can be action specific.

    a, Total number of licks for left and right single-lever FR8 forced-choice sessions, where the left lever sequences led to a small reward and the right lever to a larger reward; after six days the lever–reward-magnitude contingency was switched. b, Mice prefer the lever leading to a larger reward during two-lever choice extinction tests on day 7 and day 13. c, Percentage of striatal MSNs, SN GABA and SN DA neurons showing action-specific start/stop-related activity. d, g, j, Firing rate modulation of striatal MSNs (d), SN GABA neurons (g) and SN DA neurons (j) in relation to lever pressing during small and large reward sessions. e, h, k, The corresponding population average. f, i, l, The rate modulation for each press within the action sequence for striatal MSNs (f), SN GABA (i) and SN DA (l) neurons. Error bars denote s.e.m.

  5. Striatal-specific deletion of NMDA receptors disrupts the development of start/stop activity and impairs sequence learning.
    Figure 5: Striatal-specific deletion of NMDA receptors disrupts the development of start/stop activity and impairs sequence learning.

    a, Average lever pressing rate per session during three days of CRF followed by six days of FR8 training for striatal NR1-knockout (KO) mutants and their littermate controls (CT). b, Proportion of MSNs in striatal NR1-knockout mutants and littermate controls showing lever-press-related activity during early and late stages of training. c, Proportion of MSNs in striatal NR1-knockout mutants and littermate controls showing sequence start/stop-related activity during the early and late stages of training. d, e, Example of the behaviour microstructure of the same striatal NR1-knockout mouse during the first day of FR8 training (d) and the sixth day of FR8 training (e). All markers and insets are the same as those used in Fig. 1a, b. fi, Average sequence length (f), duration (g), ISI (h) and within-sequence press rate (i) for mutants and littermate controls. jm, CV of sequence length (j), duration (k), ISI (l) and within-sequence press rate (m) during the first and sixth day of FR8 training for striatal NR1-knockout mice and littermate controls. Error bars denote s.e.m.

References

  1. Lashley, K. S. in Cerebral Mechanisms in Behavior (ed. Jeffress, L. A.) (John Wiley, 1951)
  2. Gallistel, C. R. The Organization of Action: A New Synthesis (Lawrence Erlbaum Associates, 1980)
  3. Grillner, S. & Wallén, P. Central pattern generators for locomotion, with special reference to vertebrates. Annu. Rev. Neurosci. 8, 233261 (1985)
  4. Marder, E. & Bucher, D. Central pattern generators and the control of rhythmic movements. Curr. Biol. 11, R986R996 (2001)
  5. Hikosaka, O. et al. Parallel neural networks for learning sequential procedures. Trends Neurosci. 22, 464471 (1999)
  6. Yin, H. H. et al. Dynamic reorganization of striatal circuits during the acquisition and consolidation of a skill. Nature Neurosci. 12, 333341 (2009)
  7. Graybiel, A. M. The basal ganglia and chunking of action repertoires. Neurobiol. Learn. Mem. 70, 119136 (1998)
  8. Hikosaka, O., Miyashita, K., Miyachi, S., Sakai, K. & Lu, X. Differential roles of the frontal cortex, basal ganglia, and cerebellum in visuomotor sequence learning. Neurobiol. Learn. Mem. 70, 137149 (1998)
  9. Bailey, K. R. & Mair, R. G. The role of striatum in initiation and execution of learned action sequences in rats. J. Neurosci. 26, 10161025 (2006)
  10. Benecke, R., Rothwell, J. C., Dick, J. P., Day, B. L. & Marsden, C. D. Disturbance of sequential movements in patients with Parkinson’s disease. Brain 110, 361379 (1987)
  11. Agostino, R., Berardelli, A., Formica, A., Accornero, N. & Manfredi, M. Sequential arm movements in patients with Parkinson’s disease, Huntington’s disease and dystonia. Brain 115, 14811495 (1992)
  12. Castiello, U., Stelmach, G. E. & Lieberman, A. N. Temporal dissociation of the prehension pattern in Parkinson’s disease. Neuropsychologia 31, 395402 (1993)
  13. Phillips, J. G., Chiu, E., Bradshaw, J. L. & Iansek, R. Impaired movement sequencing in patients with Huntington’s disease: a kinematic analysis. Neuropsychologia 33, 365369 (1995)
  14. Willingham, D. B. & Koroshetz, W. J. Evidence for dissociable motor skills in Huntington’s disease patients. Psychobiology 21, 173182 (1993)
  15. Stefanova, E. D., Kostic, V. S., Ziropadja, L., Markovic, M. & Ocic, G. G. Visuomotor skill learning on serial reaction time task in patients with early Parkinson’s disease. Mov. Disord. 15, 10951103 (2000)
  16. Boyd, L. A. et al. Motor sequence chunking is impaired by basal ganglia stroke. Neurobiol. Learn. Mem. 92, 3544 (2009)
  17. Fujii, N. & Graybiel, A. M. Representation of action sequence boundaries by macaque prefrontal cortical neurons. Science 301, 12461249 (2003)
  18. Aldridge, J. W. & Berridge, K. C. Coding of serial order by neostriatal neurons: a “natural action” approach to movement sequence. J. Neurosci. 18, 27772787 (1998)
  19. Meyer-Luehmann, M., Thompson, J. F., Berridge, K. C. & Aldridge, J. W. Substantia nigra pars reticulata neurons code initiation of a serial pattern: implications for natural action sequences and sequential disorders. Eur. J. Neurosci. 16, 15991608 (2002)
  20. Dang, M. T. et al. Disrupted motor learning and long-term synaptic plasticity in mice lacking NMDAR1 in the striatum. Proc. Natl Acad. Sci. USA 103, 1525415259 (2006)
  21. Gong, S. et al. Targeting Cre recombinase to specific neuron populations with bacterial artificial chromosome constructs. J. Neurosci. 27, 98179823 (2007)
  22. Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G. & Deisseroth, K. Millisecond-timescale, genetically targeted optical control of neural activity. Nature Neurosci. 8, 12631268 (2005)
  23. Lima, S. Q., Hromadka, T., Znamenskiy, P. & Zador, A. M. PINP: a new method of tagging neuronal populations for identification during in vivo electrophysiological recording. PLoS ONE 4 e6099 doi:10.1371/journal.pone.0006099 (2009)
  24. Meck, W. H., Penney, T. B. & Pouthas, V. Cortico-striatal representation of time in animals and humans. Curr. Opin. Neurobiol. 18, 145152 (2008)
  25. Samejima, K., Ueda, Y., Doya, K. & Kimura, M. Representation of action-specific reward values in the striatum. Science 310, 13371340 (2005)
  26. Lau, B. & Glimcher, P. W. Value representations in the primate striatum during matching behavior. Neuron 58, 451463 (2008)
  27. Morris, G., Nevet, A., Arkadir, D., Vaadia, E. & Bergman, H. Midbrain dopamine neurons encode decisions for future action. Nature Neurosci. 9, 10571063 (2006)
  28. Roesch, M. R., Calu, D. J. & Schoenbaum, G. Dopamine neurons encode the better option in rats deciding between differently delayed or sized rewards. Nature Neurosci. 10, 16151624 (2007)
  29. Calabresi, P., Pisani, A., Mercuri, N. B. & Bernardi, G. Long-term potentiation in the striatum is unmasked by removing the voltage-dependent magnesium block of NMDA receptor channels. Eur. J. Neurosci. 4, 929935 (1992)
  30. Shen, W., Flajolet, M., Greengard, P. & Surmeier, D. J. Dichotomous dopaminergic control of striatal synaptic plasticity. Science 321, 848851 (2008)
  31. Pomata, P. E., Belluscio, M. A., Riquelme, L. A. & Murer, M. G. NMDA receptor gating of information flow through the striatum in vivo . J. Neurosci. 28, 1338413389 (2008)
  32. Brainard, M. S. & Doupe, A. J. What songbirds teach us about learning. Nature 417, 351358 (2002)
  33. Kimura, M. Behaviorally contingent property of movement-related activity of the primate putamen. J. Neurophysiol. 63, 12771296 (1990)
  34. Kermadi, I. & Joseph, J. P. Activity in the caudate nucleus of monkey during spatial sequencing. J. Neurophysiol. 74, 911933 (1995)
  35. Jog, M. S., Kubota, Y., Connolly, C. I., Hillegaart, V. & Graybiel, A. M. Building neural representations of habits. Science 286, 17451749 (1999)
  36. Miyachi, S., Hikosaka, O. & Lu, X. Differential activation of monkey striatal neurons in the early and late stages of procedural learning. Exp. Brain Res. 146, 122126 (2002)
  37. Schultz, W., Dayan, P. & Montague, P. R. A neural substrate of prediction and reward. Science 275, 15931599 (1997)
  38. Schultz, W. Multiple dopamine functions at different time courses. Annu. Rev. Neurosci. 30, 259288 (2007)
  39. Redgrave, P. & Gurney, K. The short-latency dopamine signal: a role in discovering novel actions? Nature Rev. Neurosci. 7, 967975 (2006)
  40. Hilário, M. R. F., Clouse, E., Yin, H. H. & Costa, R. M. Endocannabinoid signaling is critical for habit formation. Front. Integr. Neurosci. 1, 6 (2007)

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Author information

Affiliations

  1. Laboratory for Integrative Neuroscience, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 5625 Fishers Lane, Bethesda, Maryland 20892-9412, USA

    • Xin Jin &
    • Rui M. Costa
  2. Champalimaud Neuroscience Programme at Instituto Gulbenkian de Ciência, Rua da Quinta Grande, Oeiras 2780-156, Portugal

    • Rui M. Costa

Contributions

X.J. performed the experiments and analysed the data. R.M.C. conducted the optogenetics experiment. X.J. and R.M.C. designed the experiments and wrote the paper.

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The authors declare no competing financial interests.

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  1. Supplementary Information (1.3M)

    This file contains Supplementary Methods, References, Supplementary Statistics for Figures 1-5 in the main paper, Supplementary Figures 1-18 with legends and Supplementary Tables 1-2.

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