Sensory expectations shape neural population dynamics in motor circuits
Churchland, M. M. & Shenoy, K. V. Preparatory activity and the expansive null-space. Nat. Rev. Neurosci. 25, 213–236 (2024).
Google Scholar
Shenoy, K. V., Sahani, M. & Churchland, M. M. Cortical control of arm movements: a dynamical systems perspective. Annu. Rev. Neurosci. 36, 337–359 (2013).
Google Scholar
Codol, O., Michaels, J. A., Kashefi, M., Pruszynski, J. A. & Gribble, P. L. MotorNet, a Python toolbox for controlling differentiable biomechanical effectors with artificial neural networks. eLife 12, RP88591 (2024).
Google Scholar
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).
Google Scholar
Churchland, M. M., Santhanam, G. & Shenoy, K. V. Preparatory activity in premotor and motor cortex reflects the speed of the upcoming reach. J. Neurophysiol. 96, 3130–3146 (2006).
Google Scholar
Messier, J. & Kalaska, J. F. Covariation of primate dorsal premotor cell activity with direction and amplitude during a memorized-delay reaching task. J. Neurophysiol. 84, 152–165 (2000).
Google Scholar
Weinrich, M., Wise, S. P. & Mauritz, K. H. A neurophysiological study of the premotor cortex in the rhesus monkey. Brain 107, 385–414 (1984).
Google Scholar
Kaufman, M. T., Churchland, M. M., Ryu, S. I. & Shenoy, K. V. Cortical activity in the null space: permitting preparation without movement. Nat. Neurosci. 17, 440–448 (2014).
Google Scholar
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).
Google Scholar
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).
Google Scholar
Cisek, P. & Kalaska, J. F. Neural correlates of reaching decisions in dorsal premotor cortex: specification of multiple direction choices and final selection of action. Neuron 45, 801–814 (2005).
Google Scholar
Churchland, M. M., Afshar, A. & Shenoy, K. V. A central source of movement variability. Neuron 52, 1085–1096 (2006).
Google Scholar
Riehle, A. & Requin, J. The predictive value for performance speed of preparatory changes in neuronal activity of the monkey motor and premotor cortex. Behav. Brain Res. 53, 35–49 (1993).
Google Scholar
Churchland, M. M., Yu, B. M., Ryu, S. I., Santhanam, G. & Shenoy, K. V. Neural variability in premotor cortex provides a signature of motor preparation. J. Neurosci. 26, 3697–3712 (2006).
Google Scholar
Afshar, A. et al. Single-trial neural correlates of arm movement preparation. Neuron 71, 555–564 (2011).
Google Scholar
Michaels, J. A., Dann, B., Intveld, R. W. & Scherberger, H. Predicting reaction time from the neural state space of the premotor and parietal grasping network. J. Neurosci. 35, 11415–11432 (2015).
Google Scholar
Churchland, M. M. & Shenoy, K. V. Delay of movement caused by disruption of cortical preparatory activity. J. Neurophysiol. 97, 348–359 (2007).
Google Scholar
Li, N., Daie, K., Svoboda, K. & Druckmann, S. Robust neuronal dynamics in premotor cortex during motor planning. Nature 532, 459–464 (2016).
Google Scholar
Churchland, M. M. et al. Neural population dynamics during reaching. Nature 487, 51–56 (2012).
Google Scholar
Logiaco, L., Abbott, L. F. & Escola, S. Thalamic control of cortical dynamics in a model of flexible motor sequencing. Cell Rep. 35, 109090 (2021).
Google Scholar
Michaels, J. A., Schaffelhofer, S., Agudelo-Toro, A. & Scherberger, H. A goal-driven modular neural network predicts parietofrontal neural dynamics during grasping. Proc. Natl Acad. Sci. USA 117, 32124–32135 (2020).
Google Scholar
Todorov, E. & Jordan, M. I. Optimal feedback control as a theory of motor coordination. Nat. Neurosci. 5, 1226–1235 (2002).
Google Scholar
Crevecoeur, F. & Scott, S. H. Priors engaged in long-latency responses to mechanical perturbations suggest a rapid update in state estimation. PLoS Comput. Biol. 9, e1003177 (2013).
Google Scholar
Pruszynski, J. A. & Scott, S. H. Optimal feedback control and the long-latency stretch response. Exp. Brain Res. 218, 341–359 (2012).
Google Scholar
Hatsopoulos, N. G. & Suminski, A. J. Sensing with the motor cortex. Neuron 72, 477–487 (2011).
Google Scholar
Pruszynski, J. A. et al. Primary motor cortex underlies multi-joint integration for fast feedback control. Nature 478, 387–390 (2011).
Google Scholar
Evarts, E. V. & Tanji, J. Gating of motor cortex reflexes by prior instruction. Brain Res. 71, 479–494 (1974).
Google Scholar
Pruszynski, J. A., Omrani, M. & Scott, S. H. Goal-dependent modulation of fast feedback responses in primary motor cortex. J. Neurosci. 34, 4608–4617 (2014).
Google Scholar
Omrani, M., Murnaghan, C. D., Pruszynski, J. A. & Scott, S. H. Distributed task-specific processing of somatosensory feedback for voluntary motor control. eLife 5, e13141 (2016).
Google Scholar
Picard, N. & Smith, A. M. Primary motor cortical responses to perturbations of prehension in the monkey. J. Neurophysiol. 68, 1882–1894 (1992).
Google Scholar
Evarts, E. V. & Fromm, C. Sensory responses in motor cortex neurons during precise motor control. Neurosci. Lett. 5, 267–272 (1977).
Google Scholar
Wolpaw, J. R. Amplitude of responses to perturbation in primate sensorimotor cortex as a function of task. J. Neurophysiol. 44, 1139–1147 (1980).
Google Scholar
Reschechtko, S. & Pruszynski, J. A. Stretch reflexes. Curr. Biol. 30, R1025–R1030 (2020).
Google Scholar
Cheney, P. D. & Fetz, E. E. Corticomotoneuronal cells contribute to long-latency stretch reflexes in the rhesus monkey. J. Physiol. 349, 249–272 (1984).
Google Scholar
Pruszynski, J. A., Kurtzer, I., Lillicrap, T. P. & Scott, S. H. Temporal evolution of automatic gain-scaling. J. Neurophysiol. 102, 992–1003 (2009).
Google Scholar
Lara, A. H., Elsayed, G. F., Zimnik, A. J., Cunningham, J. P. & Churchland, M. M. Conservation of preparatory neural events in monkey motor cortex regardless of how movement is initiated. eLife 7, e31826 (2018).
Google Scholar
Kaufman, M. T. et al. The largest response component in the motor cortex reflects movement timing but not movement type. eNeuro 3, ENEURO.0085-16.2016 (2016).
Google Scholar
Trautmann, E. M. et al. Large-scale high-density brain-wide neural recording in nonhuman primates. Nat. Neurosci. 28, 1562–1575 (2025).
Google Scholar
Darian-Smith, C., Tan, A. & Edwards, S. Comparing thalamocortical and corticothalamic microstructure and spatial reciprocity in the macaque ventral posterolateral nucleus (VPLc) and medial pulvinar. J. Comp. Neurol. 410, 211–234 (1999).
Google Scholar
Horne, M. K. & Tracey, D. J. The afferents and projections of the ventroposterolateral thalamus in the monkey. Exp. Brain Res. 36, 129–141 (1979).
Google Scholar
Morel, A., Liu, J., Wannier, T., Jeanmonod, D. & Rouiller, E. M. Divergence and convergence of thalamocortical projections to premotor and supplementary motor cortex: a multiple tracing study in the macaque monkey: Thalamocortical connections of premotor cortex. Eur. J. Neurosci. 21, 1007–1029 (2005).
Google Scholar
Rouiller, E. M., Liang, F., Babalian, A., Moret, V. & Wiesendanger, M. Cerebellothalamocortical and pallidothalamocortical projections to the primary and supplementary motor cortical areas: a multiple tracing study in macaque monkeys. J. Comp. Neurol. 345, 185–213 (1994).
Google Scholar
Vyas, S., Golub, M. D., Sussillo, D. & Shenoy, K. V. Computation through neural population dynamics. Annu. Rev. Neurosci. 43, 249–275 (2020).
Google Scholar
Mauritz, K. H. & Wise, S. P. Premotor cortex of the rhesus monkey: neuronal activity in anticipation of predictable environmental events. Exp. Brain Res. 61, 229–244 (1986).
Google Scholar
Glaser, J. I., Perich, M. G., Ramkumar, P., Miller, L. E. & Kording, K. P. Population coding of conditional probability distributions in dorsal premotor cortex. Nat. Commun. 9, 1788 (2018).
Google Scholar
Rickert, J., Riehle, A., Aertsen, A., Rotter, S. & Nawrot, M. P. Dynamic encoding of movement direction in motor cortical neurons. J. Neurosci. 29, 13870–13882 (2009).
Google Scholar
Bastian, A., Schöner, G. & Riehle, A. Preshaping and continuous evolution of motor cortical representations during movement preparation. Eur. J. Neurosci. 18, 2047–2058 (2003).
Google Scholar
Smoulder, A. L. et al. A neural basis of choking under pressure. Neuron 112, 3424–3433.e8 (2024).
Google Scholar
Selen, L. P. J., Shadlen, M. N. & Wolpert, D. M. Deliberation in the motor system: reflex gains track evolving evidence leading to a decision. J. Neurosci. 32, 2276–2286 (2012).
Google Scholar
Johansson, R. S. & Flanagan, J. R. Coding and use of tactile signals from the fingertips in object manipulation tasks. Nat. Rev. Neurosci. 10, 345–359 (2009).
Google Scholar
Turecek, J. & Ginty, D. D. Coding of self and environment by Pacinian neurons in freely moving animals. Neuron 112, 3267–3277.e6 (2024).
Google Scholar
Dimitriou, M. & Edin, B. B. Human muscle spindles act as forward sensory models. Curr. Biol. 20, 1763–1767 (2010).
Google Scholar
Jiang, L. P. & Rao, R. P. N. Predictive coding theories of cortical function. in Oxford Research Encyclopedia of Neuroscience https://doi.org/10.1093/acrefore/9780190264086.013.328 (2022).
Richter, D., Kietzmann, T. C. & de Lange, F. P. High-level visual prediction errors in early visual cortex. PLoS Biol. 22, e3002829 (2024).
Google Scholar
Rouhani, N. & Niv, Y. Signed and unsigned reward prediction errors dynamically enhance learning and memory. eLife 10, e61077 (2021).
Google Scholar
Li, J. S., Sarma, A. A., Sejnowski, T. J. & Doyle, J. C. Internal feedback in the cortical perception-action loop enables fast and accurate behavior. Proc. Natl Acad. Sci. USA 120, e2300445120 (2023).
Google Scholar
Wolpert, D. M., Miall, R. C. & Kawato, M. Internal models in the cerebellum. Trends Cogn. Sci. 2, 338–347 (1998).
Google Scholar
Miall, R. C., Christensen, L. O. D., Cain, O. & Stanley, J. Disruption of state estimation in the human lateral cerebellum. PLoS Biol. 5, e316 (2007).
Google Scholar
Diedrichsen, J., Criscimagna-Hemminger, S. E. & Shadmehr, R. Dissociating timing and coordination as functions of the cerebellum. J. Neurosci. 27, 6291–6301 (2007).
Google Scholar
Hore, J. & Vilis, T. Loss of set in muscle responses to limb perturbations during cerebellar dysfunction. J. Neurophysiol. 51, 1137–1148 (1984).
Google Scholar
Scott, S. H. Apparatus for measuring and perturbing shoulder and elbow joint positions and torques during reaching. J. Neurosci. Methods 89, 119–127 (1999).
Google Scholar
Matthews, P. B. Observations on the automatic compensation of reflex gain on varying the pre-existing level of motor discharge in man. J. Physiol. 374, 73–90 (1986).
Google Scholar
Pruszynski, J. A., Kurtzer, I. & Scott, S. H. Rapid motor responses are appropriately tuned to the metrics of a visuospatial task. J. Neurophysiol. 100, 224–238 (2008).
Google Scholar
Jung, B. et al. A comprehensive macaque fMRI pipeline and hierarchical atlas. Neuroimage 235, 117997 (2021).
Google Scholar
Seidlitz, J. et al. A population MRI brain template and analysis tools for the macaque. Neuroimage 170, 121–131 (2018).
Google Scholar
Reveley, C. et al. Three-dimensional digital template atlas of the macaque brain. Cereb. Cortex 27, 4463–4477 (2017).
Google Scholar
Hartig, R. et al. The Subcortical Atlas of the Rhesus Macaque (SARM) for neuroimaging. Neuroimage 235, 117996 (2021).
Google Scholar
Hirai, T. & Jones, E. G. A new parcellation of the human thalamus on the basis of histochemical staining. Brain Res. Rev. 14, 1–34 (1989).
Google Scholar
Boussard, J., Varol, E., Lee, H. D., Dethe, N. & Paninski, L. Three-dimensional spike localization and improved motion correction for Neuropixels recordings. Preprint at bioRxiv https://doi.org/10.1101/2021.11.05.467503 (2021).
Varol, E. et al. in ICASSP 2021–2021 IEEE International Conference on Acoustics, Speech and Signal Processing 1085–1089 (IEEE, 2021).
Buccino, A. P. et al. SpikeInterface, a unified framework for spike sorting. eLife 9, e61834 (2020).
Google Scholar
Pachitariu, M., Sridhar, S., Pennington, J. & Stringer, C. Spike sorting with Kilosort4. Nat. Methods 21, 914–921 (2024).
Google Scholar
Trautmann, E. M. et al. Accurate estimation of neural population dynamics without spike sorting. Neuron 103, 292–308.e4 (2019).
Google Scholar
Mussa-Ivaldi, F. A., Hogan, N. & Bizzi, E. Neural, mechanical, and geometric factors subserving arm posture in humans. J. Neurosci. 5, 2732–2743 (1985).
Google Scholar
Thelen, D. G. Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults. J. Biomech. Eng. 125, 70–77 (2003).
Google Scholar
Kistemaker, D. A., Wong, J. D. & Gribble, P. L. The central nervous system does not minimize energy cost in arm movements. J. Neurophysiol. 104, 2985–2994 (2010).
Google Scholar
Glorot, X. & Bengio, Y. Understanding the difficulty of training deep feedforward neural networks. In Proc. 13th International Conference on Artificial Intelligence and Statistics 249–256 (JMLR, 2010).
Hu, W., Xiao, L. & Pennington, J. Provable benefit of orthogonal initialization in optimizing deep linear networks. Preprint at https://doi.org/10.48550/arXiv.2001.05992 (2020).
Kingma, D. P. & Ba, J. Adam: A method for stochastic optimization. Preprint at https://doi.org/10.48550/arXiv.1412.6980 (2014).
Scott, M. & Su-In, L. A unified approach to interpreting model predictions. Adv. Neural Inf. Process. Syst. 30, 4765–4774 (2017).
Shapley, L. S. in Contribution to the Theory of Games (eds Kuhn, H. & Tucker, A.) 307–317 (Princeton Univ. Press, 1953).
Diedrichsen, J. & Kriegeskorte, N. Representational models: a common framework for understanding encoding, pattern-component, and representational-similarity analysis. PLoS Comput. Biol. 13, e1005508 (2017).
Google Scholar
Michaels, J. A. & Pruszynski, J. A. Data from: Sensory expectations shape neural population dynamics in motor circuits (Dataset). Dryad https://doi.org/10.5061/dryad.0vt4b8hbr (2025).
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