Peters, A. J., Chen, S. X. & Komiyama, T. Emergence of reproducible spatiotemporal activity during motor learning. Nature 510, 263–267 (2014).
Peters, A. J., Liu, H. & Komiyama, T. Learning in the rodent motor cortex. Annu. Rev. Neurosci. 40, 77–97 (2017).
Guo, L. et al. Dynamic rewiring of neural circuits in the motor cortex in mouse models of Parkinson’s disease. Nat. Neurosci. 18, 1299–1309 (2015).
Hedrick, N. G. et al. Learning binds new inputs into functional synaptic clusters via spinogenesis. Nat. Neurosci. 25, 726–737 (2022).
Hedrick, N. G., Wright, W. J. & Komiyama, T. Local and global predictors of synapse elimination during motor learning. Sci. Adv. 10, eadk0540 (2024).
Chen, S. X., Kim, A. N., Peters, A. J. & Komiyama, T. Subtype-specific plasticity of inhibitory circuits in motor cortex during motor learning. Nat. Neurosci. 18, 1109–1115 (2015).
Makino, H., Hwang, E. J., Hedrick, N. G. & Komiyama, T. Circuit mechanisms of sensorimotor learning. Neuron 92, 705–721 (2016).
Sanes, J. N. & Donoghue, J. P. Plasticity and primary motor cortex. Annu. Rev. Neurosci. 23, 393–415 (2000).
Kawai, R. et al. Motor cortex is required for learning but not for executing a motor skill. Neuron 86, 800–812 (2015).
Hwang, E. J. et al. Disengagement of motor cortex from movement control during long-term learning. Sci. Adv. 5, eaay0001 (2019).
Hwang, E. J., Dahlen, J. E., Mukundan, M. & Komiyama, T. Disengagement of motor cortex during long-term learning tracks the performance level of learned movements. J. Neurosci. 41, 7029–7047 (2021).
Weiler, N., Wood, L., Yu, J., Solla, S. A. & Shepherd, G. M. G. Top-down laminar organization of the excitatory network in motor cortex. Nat. Neurosci. 11, 360–366 (2008).
Itokazu, T. et al. Streamlined sensory motor communication through cortical reciprocal connectivity in a visually guided eye movement task. Nat. Commun. 9, 338 (2018).
Hooks, B. M. et al. Organization of cortical and thalamic input to pyramidal neurons in mouse motor cortex. J. Neurosci. 33, 748–760 (2013).
Mao, T. et al. Long-range neuronal circuits underlying the interaction between sensory and motor cortex. Neuron 72, 111–123 (2011).
Muñoz-Castañeda, R. et al. Cellular anatomy of the mouse primary motor cortex. Nature 598, 159–166 (2021).
Broussard, G. J. et al. In vivo measurement of afferent activity with axon-specific calcium imaging. Nat. Neurosci. 21, 1272–1280 (2018).
Klapoetke, N. C. et al. Independent optical excitation of distinct neural populations. Nat. Methods 11, 338–346 (2014).
Chen, T.-W. et al. Ultra-sensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).
Vong, L. et al. Leptin action on GABAergic neurons prevents obesity and reduces inhibitory tone to POMC neurons. Neuron 71, 142–154 (2011).
Meamardoost, S. et al. FARCI: fast and robust connectome inference. Brain Sci. 11, 1556 (2021).
Krashes, M. J. et al. Rapid, reversible activation of AgRP neurons drives feeding behavior in mice. J. Clin. Invest. 121, 1424–1428 (2011).
Sauerbrei, B. A. et al. Cortical pattern generation during dexterous movement is input-driven. Nature 577, 386–391 (2020).
Tanaka, Y. H. et al. Thalamocortical axonal activity in motor cortex exhibits layer-specific dynamics during motor learning. Neuron 100, 244–258 (2018).
Dacre, J. et al. A cerebellar–thalamocortical pathway drives behavioral context-dependent movement initiation. Neuron 109, 2326–2338 (2021).
Inagaki, H. K. et al. A midbrain–thalamus–cortex circuit reorganizes cortical dynamics to initiate movement. Cell 185, 1065–1081 (2022).
Yang, W., Tipparaju, S. L., Chen, G. & Li, N. Thalamus-driven functional populations in frontal cortex support decision-making. Nat. Neurosci. 25, 1339–1352 (2022).
Russo, A. A. et al. Motor cortex embeds muscle-like commands in an untangled population response. Neuron 97, 953–966 (2018).
Churchland, M. et al. Neural population dynamics during reaching. Nature 487, 51–56 (2012).
Schimel, M., Kao, T.-C. & Hennequin, G. When and why does motor preparation arise in recurrent neural network models of motor control? eLife 12, RP89131 (2023).
Kalidindi, H. T. et al. Rotational dynamics in motor cortex are consistent with a feedback controller. eLife 10, e67256 (2021).
Sohn, J. et al. Presynaptic supervision of cortical spine dynamics in motor learning. Sci. Adv. 8, eabm0531 (2022).
Takahashi, N. et al. Thalamic input to motor cortex facilitates goal-directed action initiation. Curr. Biol. 31, 4148–4155 (2021).
Guo, K., Yamawaki, N., Svoboda, K. & Shepherd, G. M. G. Anterolateral motor cortex connects with a medial subdivision of ventromedial thalamus through cell type-specific circuits, forming an excitatory thalamo-cortico-thalamic loop via layer 1 apical tuft dendrites of layer 5B pyramidal tract type neurons. J. Neurosci. 38, 8787–8797 (2018).
Moll, F. W. et al. Thalamus drives vocal onsets in the zebra finch courtship song. Nature 616, 132–136 (2023).
Mooney, R. The neurobiology of innate and learned vocalizations in rodents and songbirds. Curr. Opin. Neurobiol. 64, 24–31 (2020).
Biane, J. S., Takashima, Y., Scanziani, M., Conner, J. M. & Tuszynski, M. H. Thalamocortical projections exhibit plasticity onto behaviorally-relevant neurons during adult motor learning. Neuron 89, 1173–1179 (2016).
Hasegawa, R., Ebina, T., Tanaka, Y. R., Kobayashi, K. & Matsuzaki, M. Structural dynamics and stability of corticocortical and thalamocortical axon terminals during motor learning. PLoS One 15, e0234930 (2020).
Dunton, K. L. et al. Divergent learning-related transcriptional states of cortical glutamatergic neurons. J. Neurosci. 44, e0302232023 (2024).
Alejandre-García, T., Kim, S., Pérez-Ortega, J. & Yuste, R. Intrinsic excitability mechanisms of neuronal ensemble formation. eLife 11, e77470 (2022).
Hotelling, H. in Breakthroughs in Statistics: Methodology and Distribution (eds Kotz, S. & Johnson, N. L.) 162–190 (Springer, 1992).
Perkins, S. M., Cunningham, J. P., Wang, Q. & Churchland, M. M. Simple decoding of behavior from a complicated neural manifold. eLife 12, RP89421 (2023).
Sani, O. G., Abbaspourazad, H., Wong, Y. T., Pesaran, B. & Shanechi, M. M. Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification. Nat. Neurosci. 24, 140–149 (2021).
Safaie, M. et al. Preserved neural dynamics across animals performing similar behaviour. Nature 623, 765–771 (2023).
Peters, A. J., Lee, J., Hedrick, N. G., O’Neil, K. & Komiyama, T. Reorganization of corticospinal output during motor learning. Nat. Neurosci. 20, 1133 (2017).
Pachitariu, M. et al. Suite2p: beyond 10,000 neurons with standard two-photon microscopy. Preprint at bioRxiv https://doi.org/10.1101/061507 (2017).
Pachitariu, M., Stringer, C. & Harris, K. D. Robustness of spike deconvolution for neuronal calcium imaging. J. Neurosci. 38, 7976–7985 (2018).
Pedregosa, F. et al. Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
Boyle, L. M., Posani, L., Irfan, S., Siegelbaum, S. A. & Fusi, S. Tuned geometries of hippocampal representations meet the computational demands of social memory. Neuron 112, 1358–1371 (2024).
Bernardi, S. et al. The geometry of abstraction in the hippocampus and prefrontal cortex. Cell 183, 954–967 (2020).
