Robust neuronal dynamics in premotor cortex during motor planning

Nature

Volumn 532, Issue 7600, 2016, Pages 459-464

  Li, Nuo ^a   Daie, Kayvon ^a   Svoboda, Karel ^a   Druckmann, Shaul ^a  

^a HOWARD HUGHES MEDICAL INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; DATA SET; INFORMATION; NERVOUS SYSTEM; NEUROLOGY; RODENT;

ANIMAL CELL; ANIMAL EXPERIMENT; ANIMAL TISSUE; ANTERIOR LATERAL MOTOR CORTEX; ARTICLE; AXON; BRAIN ELECTROPHYSIOLOGY; CELL POPULATION; CONTROLLED STUDY; CORPUS CALLOSUM; FEMALE; FRONTAL CORTEX; MALE; MOTOR ACTIVITY; MOUSE; NERVE POTENTIAL; NONHUMAN; OPTOGENETICS; PHOTOINHIBITION; PHOTOSTIMULATION; PREMOTOR CORTEX; PRIORITY JOURNAL; PYRAMIDAL NERVE CELL; ANIMAL; BIOLOGICAL MODEL; BRAIN MAPPING; CYTOLOGY; EXECUTIVE FUNCTION; LIGHT; MOTOR CORTEX; MOVEMENT (PHYSIOLOGY); NERVE CELL; PHYSIOLOGY; RADIATION RESPONSE; SHORT TERM MEMORY;

ANIMALS; BRAIN MAPPING; CORPUS CALLOSUM; EXECUTIVE FUNCTION; FEMALE; LIGHT; MALE; MEMORY, SHORT-TERM; MICE; MODELS, NEUROLOGICAL; MOTOR CORTEX; MOVEMENT; NEURONS; OPTOGENETICS;

EID: 84964896806     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/nature17643     Document Type: Article

References (50)

1. Tanji, J. & Evarts, E. V. Anticipatory activity of motor cortex neurons in relation to direction of an intended movement. J. Neurophysiol. 39, 1062-1068 (1976).
2. Churchland, M. M., Cunningham, J. P., Kaufman, M. T., Ryu, S. I. & Shenoy, K. V. Cortical preparatory activity: representation of movement or frst cog in a dynamical machine? Neuron 68, 387-400 (2010).
3. Guo, Z. V. et al. Flow of cortical activity underlying a tactile decision in mice. Neuron 81, 179-194 (2014).
4. Erlich, J. C., Bialek, M. & Brody, C. D. A cortical substrate for memory-guided orienting in the rat. Neuron 72, 330-343 (2011).
5. Murakami, M., Vicente, M. I., Costa, G. M. & Mainen, Z. F. Neural antecedents of self-initiated actions in secondary motor cortex. Nature Neurosci. 17, 1574-1582 (2014).
6. Maimon, G. & Assad, J. A. A cognitive signal for the proactive timing of action in macaque LIP. Nature Neurosci. 9, 948-955 (2006).
7. Fuster, J. M. & Alexander, G. E. Neuron activity related to short-term memory. Science 173, 652-654 (1971).
8. Funahashi, S., Bruce, C. J. & Goldman-Rakic, P. S. Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex. J. Neurophysiol. 61, 331-349 (1989).
9. Romo, R., Brody, C. D., Hernandez, A. & Lemus, L. Neuronal correlates of parametric working memory in the prefrontal cortex. Nature 399, 470-473 (1999).
10. Liu, D. et al. Medial prefrontal activity during delay period contributes to learning of a working memory task. Science 346, 458-463 (2014).
11. Wang, X. J. Decision making in recurrent neuronal circuits. Neuron 60, 215-234 (2008).
12. Gold, J. I. & Shadlen, M. N. The neural basis of decision making. Annu. Rev. Neurosci. 30, 535-574 (2007).
13. Hanks, T. D. et al. Distinct relationships of parietal and prefrontal cortices to evidence accumulation. Nature 520, 220-223 (2015).
14. Mainen, Z. F. & Sejnowski, T. J. Reliability of spike timing in neocortical neurons. Science 268, 1503-1506 (1995).
15. Cannon, S. C., Robinson, D. A. & Shamma, S. A proposed neural network for the integrator of the oculomotor system. Biol. Cybern. 49, 127-136 (1983).
16. Shefeld, M. E., Best, T. K., Mensh, B. D., Kath, W. L. & Spruston, N. Slow integration leads to persistent action potential fring in distal axons of coupled interneurons. Nature Neurosci. 14, 200-207 (2011).
17. Yoshida, M. & Hasselmo, M. E. Persistent fring supported by an intrinsic cellular mechanism in a component of the head direction system. J. Neurosci. 29, 4945-4952 (2009).
18. Barak, O., Sussillo, D., Romo, R., Tsodyks, M. & Abbott, L. F. From fxed points to chaos: three models of delayed discrimination. Prog. Neurobiol. 103, 214-222 (2013).
19. Murakami, M. & Mainen, Z. F. Preparing and selecting actions with neural populations: toward cortical circuit mechanisms. Curr. Opin. Neurobiol. 33, 40-46 (2015).
20. Fisher, D., Olasagasti, I., Tank, D. W., Aksay, E. R. & Goldman, M. S. A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit. Neuron 79, 987-1000 (2013).
21. Wang, X. J. Synaptic reverberation underlying mnemonic persistent activity. Trends Neurosci. 24, 455-463 (2001).
22. Sussillo, D. & Abbott, L. F. Generating coherent patterns of activity from chaotic neural networks. Neuron 63, 544-557 (2009).
23. Laje, R. & Buonomano, D. V. Robust timing and motor patterns by taming chaos in recurrent neural networks. Nature Neurosci. 16, 925-933 (2013).
24. Mante, V., Sussillo, D., Shenoy, K. V. & Newsome, W. T. Context-dependent computation by recurrent dynamics in prefrontal cortex. Nature 503, 78-84 (2013).
25. London, M., Roth, A., Beeren, L., Hausser, M. & Latham, P. E. Sensitivity to perturbations in vivo implies high noise and suggests rate coding in cortex. Nature 466, 123-127 (2010).
26. Kitano, H. Biological robustness. Nature Rev. Genet. 5, 826-837 (2004).
27. Csete, M. E. & Doyle, J. C. Reverse engineering of biological complexity. Science 295, 1664-1669 (2002).
28. Aksay, E. et al. Functional dissection of circuitry in a neural integrator. Nature Neurosci. 10, 494-504 (2007).
29. Kopec, C. D., Erlich, J. C., Brunton, B. W., Deisseroth, K. & Brody, C. D. Cortical and subcortical contributions to short-term memory for orienting movements. Neuron 88, 367-377 (2015).
30. Li, N., Chen, T. W., Guo, Z. V., Gerfen, C. R. & Svoboda, K. A motor cortex circuit for motor planning and movement. Nature 519, 51-56 (2015).
31. Komiyama, T. et al. Learning-related fne-scale specifcity imaged in motor cortex circuits of behaving mice. Nature 464, 1182-1186 (2010).
32. Shenoy, K. V., Sahani, M. & Churchland, M. M. Cortical control of arm movements: a dynamical systems perspective. Annu. Rev. Neurosci. 36, 337-359 (2013).
33. Kaufman, M. T., Churchland, M. M., Ryu, S. I. & Shenoy, K. V. Cortical activity in the null space: permitting preparation without movement. Nature Neurosci. 17, 440-448 (2014).
34. Tanaka, M. Cognitive signals in the primate motor thalamus predict saccade timing. J. Neurosci. 27, 12109-12118 (2007).
35. Seung, H. S. How the brain keeps the eyes still. Proc. Natl Acad. Sci. USA 93, 13339-13344 (1996).
36. Amit, D. J. & Brunel, N. Model of global spontaneous activity and local structured activity during delay periods in the cerebral cortex. Cereb. Cortex 7, 237-252 (1997).
37. Lim, S. & Goldman, M. S. Balanced cortical microcircuitry for maintaining information in working memory. Nature Neurosci. 16, 1306-1314 (2013).
38. Stopfer, M., Jayaraman, V. & Laurent, G. Intensity versus identity coding in an olfactory system. Neuron 39, 991-1004 (2003).
39. Cisek, P., Puskas, G. A. & El-Murr, S. Decisions in changing conditions: the urgency-gating model. J. Neurosci. 29, 11560-11571 (2009).
40. Druckmann, S. & Chklovskii, D.B. Neuronal circuits underlying persistent representations despite time varying activity. Curr. Biol 22, 2095-2103 (2012).
41. Goldman, M. S. Memory without feedback in a neural network. Neuron 61, 621-634 (2009).
42. Diester, I. et al. An optogenetic toolbox designed for primates. Nature Neurosci. 14, 387-397 (2011).
43. Sadtler, P. T. et al. Neural constraints on learning. Nature 512, 423-426 (2014).
44. Hippenmeyer, S. et al. A developmental switch in the response of DRG neurons to ETS transcription factor signaling. PLoS Biol. 3, e159 (2005).
45. Hooks, B. M., Lin, J. Y., Guo, C. & Svoboda, K. Dual-channel circuit mapping reveals sensorimotor convergence in the primary motor cortex. J. Neurosci. 35, 4418-4426 (2015).
46. Gerfen, C. R., Paletzki, R. & Heintz, N. GENSAT BAC cre-recombinase driver lines to study the functional organization of cerebral cortical and basal ganglia circuits. Neuron 80, 1368-1383 (2013).
47. Madisen, L. et al. A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing. Nature Neurosci. 15, 793-802 (2012).
48. Guo, Z. V. et al. Procedures for behavioral experiments in head-fxed mice. PLoS ONE 9, e88678 (2014).
49. Sompolinsky, H., Crisanti, A. & Sommers, H. J. Chaos in random neural networks. Phys. Rev. Lett. 61, 259-262 (1988).
50. Haykin, S. Adaptive Filter Theory 4th edn (Prentice Hall, 2002).