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A motor cortex circuit for motor planning and movement

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Abstract

Activity in motor cortex predicts specific movements seconds before they occur, but how this preparatory activity relates to upcoming movements is obscure. We dissected the conversion of preparatory activity to movement within a structured motor cortex circuit. An anterior lateral region of the mouse cortex (a possible homologue of premotor cortex in primates) contains equal proportions of intermingled neurons predicting ipsi- or contralateral movements, yet unilateral inactivation of this cortical region during movement planning disrupts contralateral movements. Using cell-type-specific electrophysiology, cellular imaging and optogenetic perturbation, we show that layer 5 neurons projecting within the cortex have unbiased laterality. Activity with a contralateral population bias arises specifically in layer 5 neurons projecting to the brainstem, and only late during movement planning. These results reveal the transformation of distributed preparatory activity into movement commands within hierarchically organized cortical circuits.

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Figure 1: ALM is required for movement planning.
Figure 2: ALM contains neurons with bilateral movement selectivity.
Figure 3: Cell-type-specific electrophysiology.
Figure 4: Cell-type-specific imaging.
Figure 5: Preparatory activity in pyramidal tract neurons drives upcoming movements.

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References

  1. Shenoy, K. V., Sahani, M. & Churchland, M. M. Cortical control of arm movements: a dynamical systems perspective. Annu. Rev. Neurosci. 36, 337–359 (2013)

    Article  CAS  PubMed  Google Scholar 

  2. Kerkhoff, G. Spatial hemineglect in humans. Prog. Neurobiol. 63, 1–27 (2001)

    Article  CAS  PubMed  Google Scholar 

  3. Rizzolatti, G., Matelli, M. & Pavesi, G. Deficits in attention and movement following the removal of postarcuate (area 6) and prearcuate (area 8) cortex in macaque monkeys. Brain 106, 655–673 (1983)

    Article  PubMed  Google Scholar 

  4. 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  PubMed  PubMed Central  Google Scholar 

  5. 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)

    Article  CAS  PubMed  Google Scholar 

  6. Turner, R. S. & DeLong, M. R. Corticostriatal activity in primary motor cortex of the macaque. J. Neurosci. 20, 7096–7108 (2000)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Crutcher, M. D. & Alexander, G. E. Movement-related neuronal activity selectively coding either direction or muscle pattern in three motor areas of the monkey. J. Neurophysiol. 64, 151–163 (1990)

    Article  CAS  PubMed  Google Scholar 

  8. Riehle, A. & Requin, J. Monkey primary motor and premotor cortex: single-cell activity related to prior information about direction and extent of an intended movement. J. Neurophysiol. 61, 534–549 (1989)

    Article  CAS  PubMed  Google Scholar 

  9. Scott, S. H. Inconvenient truths about neural processing in primary motor cortex. J. Physiol. (Lond.) 586, 1217–1224 (2008)

    Article  CAS  Google Scholar 

  10. Huber, D. et al. Multiple dynamic representations in the motor cortex during sensorimotor learning. Nature 484, 473–478 (2012)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  11. Rizzolatti, G. et al. Functional organization of inferior area 6 in the macaque monkey. II. Area F5 and the control of distal movements. Exp. Brain Res. 71, 491–507 (1988)

    Article  CAS  PubMed  Google Scholar 

  12. Arce, F. I., Lee, J. C., Ross, C. F., Sessle, B. J. & Hatsopoulos, N. G. Directional information from neuronal ensembles in the primate orofacial sensorimotor cortex. J. Neurophysiol. 110, 1357–1369 (2013)

    Article  CAS  PubMed  Google Scholar 

  13. Guo, Z. V. et al. Flow of cortical activity underlying a tactile decision in mice. Neuron 81, 179–194 (2014)

    Article  CAS  PubMed  Google Scholar 

  14. Bruce, C. J. & Goldberg, M. E. Primate frontal eye fields. I. Single neurons discharging before saccades. J. Neurophysiol. 53, 603–635 (1985)

    Article  CAS  PubMed  Google Scholar 

  15. 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  PubMed  Google Scholar 

  16. Shepherd, G. M. Corticostriatal connectivity and its role in disease. Nature Rev. Neurosci. 14, 278–291 (2013)

    Article  CAS  Google Scholar 

  17. Kiritani, T., Wickersham, I. R., Seung, H. S. & Shepherd, G. M. Hierarchical connectivity and connection-specific dynamics in the corticospinal-corticostriatal microcircuit in mouse motor cortex. J. Neurosci. 32, 4992–5001 (2012)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Brown, S. P. & Hestrin, S. Intracortical circuits of pyramidal neurons reflect their long-range axonal targets. Nature 457, 1133–1136 (2009)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  19. Morishima, M. & Kawaguchi, Y. Recurrent connection patterns of corticostriatal pyramidal cells in frontal cortex. J. Neurosci. 26, 4394–4405 (2006)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. O'Connor, D. H. et al. Vibrissa-based object localization in head-fixed mice. J. Neurosci. 30, 1947–1967 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Guo, Z. V. et al. Procedures for behavioral experiments in head-fixed mice. PLoS ONE 9, e88678 (2014)

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  22. Travers, J. B., Dinardo, L. A. & Karimnamazi, H. Motor and premotor mechanisms of licking. Neurosci. Biobehav. Rev. 21, 631–647 (1997)

    Article  CAS  PubMed  Google Scholar 

  23. Stanek, E., t, Cheng, S., Takatoh, J., Han, B. X. & Wang, F. Monosynaptic premotor circuit tracing reveals neural substrates for oro-motor coordination. eLife 3, e02511 (2014)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Li, C. X. & Waters, R. S. Organization of the mouse motor cortex studied by retrograde tracing and intracortical microstimulation (ICMS) mapping. Can. J. Neurol. Sci. 18, 28–38 (1991)

    Article  CAS  PubMed  Google Scholar 

  25. Hall, R. D. & Lindholm, E. P. Organization of motor and somatosensory neocortex in the albino rat. Brain Res. 66, 23–38 (1974)

    Article  Google Scholar 

  26. Neafsey, E. J. et al. The organization of the rat motor cortex: a microstimulation mapping study. Brain Res. 396, 77–96 (1986)

    Article  CAS  PubMed  Google Scholar 

  27. Bennett, G. A. & Ramsay, A. J. Experimental studies on the movements of the mammalian tongue. I. Movements of the split tongue (dog). Anat. Rec. 79, 39–51 (1941)

    Article  Google Scholar 

  28. Petreanu, L., Huber, D., Sobczyk, A. & Svoboda, K. Channelrhodopsin-2-assisted circuit mapping of long-range callosal projections. Nature Neurosci. 10, 663–668 (2007)

    Article  CAS  PubMed  Google Scholar 

  29. Beloozerova, I. N., Sirota, M. G. & Swadlow, H. A. Activity of different classes of neurons of the motor cortex during locomotion. J. Neurosci. 23, 1087–1097 (2003)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Swadlow, H. A. Efferent neurons and suspected interneurons in motor cortex of the awake rabbit: axonal properties, sensory receptive fields, and subthreshold synaptic inputs. J. Neurophysiol. 71, 437–453 (1994)

    Article  CAS  PubMed  Google Scholar 

  31. Bauswein, E., Fromm, C. & Preuss, A. Corticostriatal cells in comparison with pyramidal tract neurons: contrasting properties in the behaving monkey. Brain Res. 493, 198–203 (1989)

    Article  CAS  PubMed  Google Scholar 

  32. Chen, T. W. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Sato, T. R. & Svoboda, K. The functional properties of barrel cortex neurons projecting to the primary motor cortex. J. Neurosci. 30, 4256–4260 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Yamashita, T. et al. Membrane potential dynamics of neocortical projection neurons driving target-specific signals. Neuron 80, 1477–1490 (2013)

    Article  CAS  PubMed  Google Scholar 

  35. Reep, R. L., Corwin, J. V., Hashimoto, A. & Watson, R. T. Efferent connections of the rostral portion of medial agranular cortex in rats. Brain Res. Bull. 19, 203–221 (1987)

    Article  CAS  PubMed  Google Scholar 

  36. Rouiller, E. M., Moret, V. & Liang, F. Comparison of the connectional properties of the two forelimb areas of the rat sensorimotor cortex: support for the presence of a premotor or supplementary motor cortical area. Somatosens. Mot. Res. 10, 269–289 (1993)

    Article  CAS  PubMed  Google Scholar 

  37. 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)

    Article  CAS  PubMed  Google Scholar 

  38. Sul, J. H., Jo, S., Lee, D. & Jung, M. W. Role of rodent secondary motor cortex in value-based action selection. Nature Neurosci. 14, 1202–1208 (2011)

    Article  CAS  PubMed  Google Scholar 

  39. 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)

    Article  CAS  PubMed  Google Scholar 

  40. Hikosaka, O. & Wurtz, R. H. Modification of saccadic eye movements by GABA-related substances. II. Effects of muscimol in monkey substantia nigra pars reticulata. J. Neurophysiol. 53, 292–308 (1985)

    Article  CAS  PubMed  Google Scholar 

  41. Pan, W. X., Brown, J. & Dudman, J. T. Neural signals of extinction in the inhibitory microcircuit of the ventral midbrain. Nature Neurosci. 16, 71–78 (2013)

    Article  CAS  PubMed  Google Scholar 

  42. Shibasaki, H. & Hallett, M. What is the Bereitschaftspotential? Clin. Neurophysiol. 117, 2341–2356 (2006)

    Article  PubMed  Google Scholar 

  43. Murray, G. M. & Sessle, B. J. Functional properties of single neurons in the face primary motor cortex of the primate. III. Relations with different directions of trained tongue protrusion. J. Neurophysiol. 67, 775–785 (1992)

    Article  CAS  PubMed  Google Scholar 

  44. Zhao, S. et al. Cell type-specific channelrhodopsin-2 transgenic mice for optogenetic dissection of neural circuitry function. Nature Methods 8, 745–752 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Hippenmeyer, S. et al. A developmental switch in the response of DRG neurons to ETS transcription factor signaling. PLoS Biol. 3, e159 (2005)

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Lin, J. Y., Knutsen, P. M., Muller, A., Kleinfeld, D. & Tsien, R. Y. ReaChR: a red-shifted variant of channelrhodopsin enables deep transcranial optogenetic excitation. Nature Neurosci. 16, 1499–1508 (2013)

    Article  CAS  PubMed  Google Scholar 

  47. 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)

    Article  CAS  PubMed  Google Scholar 

  48. Madisen, L. et al. A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing. Nature Neurosci. 15 793–802 10.1038/nn.3078 (2012)

    Article  CAS  PubMed  Google Scholar 

  49. O'Connor, D. H. et al. Neural coding during active somatosensation revealed using illusory touch. Nature Neurosci. 16, 958–965 (2013)

    Article  CAS  PubMed  Google Scholar 

  50. Simmons, P. A. & Pearlman, A. L. Receptive-field properties of transcallosal visual cortical neurons in the normal and reeler mouse. J. Neurophysiol. 50, 838–848 (1983)

    Article  CAS  PubMed  Google Scholar 

  51. Alstermark, B. & Ogawa, J. In vivo recordings of bulbospinal excitation in adult mouse forelimb motoneurons. J. Neurophysiol. 92, 1958–1962 (2004)

    Article  PubMed  Google Scholar 

  52. Swadlow, H. A., Waxman, S. G. & Rosene, D. L. Latency variability and the identification of antidromically activated neurons in mammalian brain. Exp. Brain Res. 32, 439–443 (1978)

    Article  CAS  PubMed  Google Scholar 

  53. Chen, T.-W. A Systems Level Analysis of Neuronal Network Function in the Olfactory Bulb: Coding, Connectivity, and Modular organization PhD Thesis. University of Göttingen, Göttingen, Germany (2008)

    Google Scholar 

  54. Kerlin, A. M., Andermann, M. L., Berezovskii, V. K. & Reid, R. C. Broadly tuned response properties of diverse inhibitory neuron subtypes in mouse visual cortex. Neuron 67, 858–871 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank B. Dickson, S. Druckmann, J. Dudman, D. Gutnisky, H. Inagaki, V. Jayaraman, D. O’Connor, S. Peron, T. Sato and G. Shepherd for comments on the manuscript and discussion, L. Walendy and E. Ophir for animal training, S. Michael and A. Hu for histology, T. Harris and B. Barbarits for the silicon probe recording system. This work was funded by the Howard Hughes Medical Institute. N.L. is a Helen Hay Whitney Foundation postdoctoral fellow.

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Authors and Affiliations

Authors

Contributions

N.L., Z.G. and K.S. initiated this study. N.L. performed electrophysiology and optogenetic experiments. T.W.C. performed imaging. T.W.C., N.L., and C.G. performed anatomical experiments. N.L., T.W.C., K.S. analysed data. N.L. and K.S. wrote the paper, with input from all authors.

Corresponding author

Correspondence to Karel Svoboda.

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The authors declare no competing financial interests.

Additional information

Data have been deposited at https://crcns.org/ and can be accessed at http://dx.doi.org/10.6080/K0RF5RZT.

Extended data figures and tables

Extended Data Figure 1 Neural selectivity in ALM.

a, Single-unit classification. Left, overlaid mean spike waveforms for putative fast-spiking (FS) interneurons (grey, n = 124) and putative pyramidal neurons (black, n = 1245). A small subset of single units with intermediate spike durations were not classified (brown, n = 39). Right, histogram of spike durations (Methods). b, Fast-spiking neurons population response (mean ± s.e.m.) during the lick right trials (contralateral, blue) and lick left trials (ipsilateral, red). Neurons are sorted by their preferred trial type using spike counts from 10 trials and the remaining data was used to compute the selectivity. Left, contra-preferring neurons. Right, ipsi-preferring neurons. c, Left, proportion of neurons in b with preparatory and peri-movement activity. Right, contra-preferring versus ipsi-preferring selectivity. Error bars, s.e.m. across animals, bootstrap. d, e, Same as (b) and (c) but for putative pyramidal neurons. f, Number of significantly selective putative pyramidal neurons as a function of time. Significant selectivity was based on spike counts in 200-ms time windows, P < 0.05, two-tailed t-test. Dashed lines, behavioural epochs.

Extended Data Figure 2 ALM neurons exhibit temporally complex responses and choice-specific selectivity.

a, Twenty example ALM neurons responding during different epochs of the object location discrimination. Correct lick right (blue) and lick left (red) trials only. Dashed lines, behavioural epochs. Averaging window, 200 ms. b, Six example ALM neurons during object location discrimination. Top, peri-stimulus time histogram for correct lick right and lick left trials. Bottom, peri-stimulus time histogram for error trials (transparent colour). c, ALM neurons show choice-specific preparatory activity. Selectivity is the firing rate difference between lick right and lick left trials during sample, delay or response epochs ((firing rate lick right)–(firing rate lick left)). Circles, individual neurons (n = 912). Filled circles, neurons with significant selectivity (P < 0.05, two-tailed t-test). On error trials, when mice licked in the opposite direction to the instruction provided by object location (Fig. 1a), a majority of ALM neurons switched their trial type preference to predict the licking direction, as indicated by the negative correlations (r, Pearson’s correlation).

Extended Data Figure 3 ALM pyramidal tract neurons control contralateral licking.

a, Axonal projections of intratelencephalic neurons (top, Tlx_PL56 mice) and pyramidal tract neurons (bottom, Sim1_KJ18 mice). b, Top, retrogradely labelled pyramidal tract neurons in contralateral ALM. Bottom, intermediate nucleus of the reticular formation (IRt) axonal projections in the hypoglossal nucleus, 12N. c, Top, retrogradely labelled IRt neurons. Bottom, hypoglossal nerves. d, Retrograde labelling of pyramidal tract neurons (green) and intratelencephalic neurons (magenta). The ALM coronal slice shows intermingled labelling of pyramidal tract neurons and intratelencephalic neurons without overlap. e, Unilateral stimulation of ALM pyramidal tract or intratelencephalic neurons triggered contralateral licking during behaviour (blue, contralateral licking; red, ipsilateral licking). Top, average lick rate during ALM (left) and left vibrissal motor cortex (vM1) (right) photostimulation, n = 8 mice. Dashed lines, behavioural epochs. Cyan region, photostimulation. Bottom, fraction of trials in which photostimulation caused ‘early lick’ as a function of laser power. Sample and delay epoch photostimulation data were combined. IT, intratelencephalic; PT, pyramidal tract. f, Unilateral stimulation of ALM pyramidal tract or intratelencephalic neurons triggered contralateral licking in untrained mice (n = 6 mice). Fraction of trials in which photostimulation caused licking as a function of laser power. g, Unilateral stimulation of left vM1 pyramidal tract or intratelencephalic neurons triggered whisker movements in untrained mice. Left, whisker azimuthal angle traces, individual trials. Right, average whisker angle 500 ms before photostimulation (baseline) and during vM1 photostimulation (n = 6 mice).

Extended Data Figure 4 Transgenic ChR2 expression in intratelencephalic and pyramidal tract neurons.

a, ChR2 expression in layer 5 intratelencephalic neurons. Tlx_PL56-Cre mouse crossed to a Rosa-ChR2-eYFP reporter mouse (Ai32). Top, ChR2 expression in ALM. Bottom, ChR2 expression in three coronal sections from anterior to posterior. b, Same as a for ChR2 expression in pyramidal tract neurons. Sim1_KJ18-Cre mouse crossed to Ai32.

Extended Data Figure 5 Cell-type-specific recording with ChR2 tagging.

a, Pyramidal tract neuron recordings. Top, left ALM neurons were infected with AAV2/5-FLEX-ChR2-tdTomato (Sim1_KJ18-Cre mice). An optical fibre was implanted into the left (ipsilateral) reticular formation to antidromically stimulate the pyramidal tract neuron axons. Pyramidal tract neurons were identified based on back-propagating antidromic spikes (tagging). Bottom, expression of ChR2-tdTomato in left ALM; injection site (left), axon terminals in the reticular formation (right). b, Recording traces for four example neurons activated by antidromic stimulation of pyramidal tract neurons (blue). Red ticks, individual spikes. Red traces, collision tests. Left, two pyramidal tract neurons that passed the collision test; antidromic spikes were absent when preceded by spontaneous spikes. These neurons were classified as pyramidal tract neurons. Right, two neurons that failed the collision test. The top neuron could not be tested for collision due to an absence of baseline firing. The bottom neuron failed the collision test because light-evoked spikes occurred even when preceded by spontaneous spikes. This neuron was classified as a pyramidal-tract-activated neuron. Scale bars, 200 µV, 5 ms. c, d, Same as a and b but for intratelencephalic neuron recordings. e, Antidromic spike latency versus jitter (SD) for pyramidal tract neurons, intratelencephalic neurons, pyramidal-tract-activated neurons, and intratelencephalic-activated neurons. f, Recording yield. ‘Activated’, neurons activated by antidromic stimulation; ‘Passed’, subsets of activated neurons that passed the collision test. These neurons were classified as pyramidal tract neurons or intratelencephalic neurons. ‘Failed’, subsets of activated neurons in which spontaneous spikes failed to block light-evoked spikes. ‘Could not test’, the subset of activated neurons without spontaneous activity. These neurons were excluded from analyses. ‘Suppressed’, neurons suppressed by antidromic stimulation. g, Top, light-evoked responses across all pyramidal tract neurons and intratelencephalic neurons. Middle, pyramidal-tract-activated neurons and intratelencephalic-activated neurons. Bottom, pyramidal-tract-suppressed neurons and intratelencephalic-suppressed neurons.

Extended Data Figure 6 Photostimulation of intratelencephalic and pyramidal tract neurons biases upcoming licking direction.

a, Performance change, pyramidal tract neurons activation. Re-plot of the data in Fig. 5b. Grey areas represent 95% confidence interval of expected behavioural variability. We estimated the behavioural variability by computing performance changes on re-sampled data sets in which we sampled with replacement from only the control trials (Methods, repeated 104 times). The number of trials in the re-sampled data sets was matched to the actual experiments. b, Dose response for individual mouse in a. Delay epoch photostimulation data only. c, d, Same as a and b but for intratelencephalic neurons activation.

Extended Data Figure 7 Photostimulation of pyramidal tract neurons during the sample epoch causes persistent changes in ALM activity and a directional bias.

a, Simultaneous recordings and photostimulation of left ALM pyramidal tract neurons during behaviour. Two mice, eight sessions, 91 neurons. b, Stimulation of left ALM pyramidal tract neurons during the sample epoch biased the upcoming licking to the contralateral direction. Top, sample epoch photostimulation. Bottom, performance change relative to the control trials. Thick lines, mean; thin lines, individual mice. c, Spike raster plots and peri-stimulus time histograms of six example neurons. Correct lick right (blue) and lick left (red) trials only. Dashed lines, behavioural epochs. For each neuron: top, control trials; bottom, photostimulation trials (solid colour). Control trials are overlaid in transparent colour. Averaging window, 200 ms. d, Average population selectivity (black line, ±s.e.m. across neurons). Left, control trials. Right, photostimulation trials. Neurons are sorted by their preferred trial type (top, contra-preferring neurons; bottom, ipsi-preferring neurons). Selectivity is the difference in spike rate between the preferred and non-preferred trial type.

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Li, N., Chen, TW., Guo, Z. et al. A motor cortex circuit for motor planning and movement. Nature 519, 51–56 (2015). https://doi.org/10.1038/nature14178

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