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Robust neuronal dynamics in premotor cortex during motor planning
Open accessAbstract
Neural activity maintains representations that bridge past and future events, often over many seconds. Network models can produce persistent and ramping activity, but the positive feedback that is critical for these slow dynamics can cause sensitivity to perturbations. Here we use electrophysiology and optogenetic perturbations in the mouse premotor cortex to probe the robustness of persistent neural representations during motor planning. We show that preparatory activity is remarkably robust to large-scale unilateral silencing: detailed neural dynamics that drive specific future movements were quickly and selectively restored by the network. Selectivity did not recover after bilateral silencing of the premotor cortex. Perturbations to one hemisphere are thus corrected by information from the other hemisphere. Corpus callosum bisections demonstrated that premotor cortex hemispheres can maintain preparatory activity independently. Redundancy across selectively coupled modules, as we observed in the premotor cortex, is a hallmark of robust control systems. Network models incorporating these principles show robustness that is consistent with data.
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“Serial transformation of sensory inputs along bottom–up hierarchical pathways has been observed in rodents engaged in whisker-discrimination tasks (8, 9) with an increasingly stronger association with perceptual choice in S2 (10, 11) and premotor areas (12–14) rather than whisker-related wS1 (9).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [13]
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“Therefore, this global regulation is unlikely to originate directly from frontal cortical premotor areas (12–14) since frontal cortices have a high degree of symmetry for both ipsilateral and contralateral projections (59).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [13]
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“Hence, peak 4 is likely to reflect participation of the primary somatosensory cortex in motor preparatory activity, often observed in higher motor cortices (12–14).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [13]
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“Indeed, across other domains of neuroscience, premotor populations are known to be active during planning of an upcoming action (Nakayama et al., 2008; Pearce and Moran, 2012; Li et al., 2016; Xu et al., 2022).”
BackgroundOptimal anticipatory control as a theory of motor preparation: a thalamo-cortical circuit modelPreprint
Kao, T.-C., Sadabadi, M. S., & Hennequin, G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.02.931246 · Cited by 5
“In recent years, neu404 rophysiologists have begun to dissect the causal circuit 405 mechanisms responsible for movement planning, by sys406 tematically perturbing activity in various brain struc407 tures (Li et al., 2016; Guo et al., 2017; Gao et al., 2018; 408 Sauerbrei et al., 2019), and analyzing population record…”
BackgroundLow-dimensional and monotonic preparatory activity in mouse anterior lateral motor cortex
Inagaki, H. K., Inagaki, M., Romani, S., & Svoboda, K. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.3152-17.2018 · Cited by 111
Self-citationStavisky, S. D., Kao, J. C., Ryu, S. I., & Shenoy, K. V. (2017) · Neuron · doi:10.1016/j.neuron.2017.05.023 · Cited by 113
“More recent studies have suggested that reliable motor planning (Li et al., 2016) and motor control (Flint et al., 2016) is achieved by motor cortical circuits tolerating output-null firing rate changes while selectively maintaining the stability of different, ‘‘output-potent’’ patterns that do…”
Hippocampal astrocytes encode reward location
Doron, A., Rubin, A., Benmelech-Chovav, A., Benaim, N., Carmi, T., Refaeli, R., Novick, N., Kreisel, T., Ziv, Y., & Goshen, I. (2022) · Nature · doi:10.1038/s41586-022-05146-6 · Cited by 125
Optogenetic rewiring of thalamocortical circuits to restore function in the stroke injured brain
Tennant, K. A., Taylor, S. L., White, E. R., & Brown, C. E. (2017) · Nature Communications · doi:10.1038/ncomms15879 · Cited by 106
Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models
Williamson, R. C., Cowley, B. R., Litwin-Kumar, A., Doiron, B., Kohn, A., Smith, M. A., & Yu, B. M. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005141 · Cited by 102
Multiple Maps of the Same Spatial Context Can Stably Coexist in the Mouse Hippocampus
Sheintuch, L., Geva, N., Baumer, H., Rechavi, Y., Rubin, A., & Ziv, Y. (2020) · Current Biology · doi:10.1016/j.cub.2020.02.018 · Cited by 88
Anastasiades, P. G., Boada, C. M., & Carter, A. G. (2018) · bioRxiv · doi:10.1101/370536 · Cited by 100
“By increasing the firing of L5 D1+ IT cells projecting across the corpus callosum, D1-R activation may increase communication between hemispheres, which plays an important role in delay period activity (Li et al. 2016).”
BackgroundHerz, D. M., Little, S. J., Pedrosa, D. J., Tinkhauser, G., Cheeran, B., Foltynie, T., Bogacz, R., & Brown, P. (2018) · Current Biology · doi:10.1016/j.cub.2018.02.057 · Cited by 96
Sensory coding and the causal impact of mouse cortex in a visual decision
Zatka-Haas, P., Steinmetz, N. A., Carandini, M., & Harris, K. D. (2021) · eLife · doi:10.7554/elife.63163 · Cited by 122
Targeted photostimulation uncovers circuit motifs supporting short-term memory
Daie, K., Svoboda, K., & Druckmann, S. (2021) · Nature Neuroscience · doi:10.1038/s41593-020-00776-3 · Cited by 103
Self-citationGenetic Dissection of Neural Circuits: A Decade of Progress
Luo, L., Callaway, E. M., & Svoboda, K. (2018) · Neuron · doi:10.1016/j.neuron.2018.05.004 · Cited by 90
“…A uthor M anuscript biological insight from optogenetic experiments requires careful characterization of the dynamics of the stimulated neurons and downstream neurons and brain areas using neurophysiology and benefit from models of neural circuits (Li et al., 2016; Phillips and Hasenstaub, 2016).”
Self-citationInferring brain-wide interactions using data-constrained recurrent neural network models
Perich, M. G., Arlt, C., Soares, S., Zhou, S., Beirán, M., Andalman, A. S., Benster, T., Young, M. E., Mosher, C. P., Minxha, J., et al. (2026) · Neuron · doi:10.1016/j.neuron.2026.07.016 · Cited by 71
The promise and perils of causal circuit manipulations
Wolff, S. B. E., & Ölveczky, B. P. (2018) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.01.004 · Cited by 121
Rethinking brain-wide interactions through multi-region “network of networks” modelsPreprint
Perich, M. G., & Rajan, K. (2020) · Current Opinion in Neurobiology · doi:10.31219/osf.io/58qwj · Cited by 2
“…applied to show the necessity of different cortical regions to generate perceptual decisions [25,26], select motor plans [27,28] or actions [29] in response to visual cues, generate robust dynamics for motor output [30], and to study interactions between cortical and subcortical regions [31,32].”
BackgroundAnastasiades, P. G., Marlin, J. J., & Carter, A. G. (2018) · Cell Reports · doi:10.1016/j.celrep.2017.12.073 · Cited by 90
“However, because CC neurons are more excitable, they are also recruited by callosal input, enabling communication between hemispheres (Li et al., 2016).”
BackgroundRotational dynamics in motor cortex are consistent with a feedback controller
Kalidindi, H. T., Cross, K. P., Lillicrap, T. P., Omrani, M., Falotico, E., Sabes, P. N., & Scott, S. H. (2021) · eLife · doi:10.7554/elife.67256 · Cited by 83
Kauvar, I., Machado, T. A., Yuen, E., Kochalka, J., Choi, M., Allen, W. E., Wetzstein, G., & Deisseroth, K. A. (2020) · Neuron · doi:10.1016/j.neuron.2020.04.023 · Cited by 92
“In the motor system, persistent activity may be mediated by interhemispheric feedback in mouse motor cortex (Li et al., 2016) in addition to other long-range loops between the motor cortex and the thalamus (Guo et al.”
Metastable attractors explain the variable timing of stable behavioral action sequencesPreprint
Recanatesi, S., Pereira, U., Murakami, M., Mainen, Z., & Mazzucato, L. (2020) · bioRxiv · doi:10.1101/2020.01.24.919217 · Cited by 82
“Previous studies in rodents have identified the secondary motor cortex (M2) as part of a distributed network involved in motor planning, working memory [8] and self-initiated tasks [6, 7].”
BackgroundBrainstem Circuits Controlling Action Diversification
Ruder, L., & Arber, S. (2019) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070918-050201 · Cited by 69
A genetically defined insula-brainstem circuit selectively controls motivational vigor
Deng, H., Xiao, X., Yang, T., Ritola, K., Hantman, A., Li, Y., Huang, Z. J., & Li, B. (2021) · Cell · doi:10.1016/j.cell.2021.11.019 · Cited by 75
Cerebellar granule cell axons support high-dimensional representations
Lanore, F., Cayco-Gajic, N. A., Gurnani, H., Coyle, D., & Silver, R. A. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00873-x · Cited by 80
The role of forelimb motor cortex areas in goal directed action in mice
Morandell, K., & Huber, D. (2017) · Scientific Reports · doi:10.1038/s41598-017-15835-2 · Cited by 90
Guo, K., Yamawaki, N., Svoboda, K., & Shepherd, G. M. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1333-18.2018 · Cited by 133
“This recurrent circuit architecture may relate to the physiological functions of the ALM 7 VM circuit, by supporting persistent activity associated with motor preparation (Li et al., 2016), representing a form of short-term memory.”
BackgroundSelf-citationPyramidal Cell Subtypes and Their Synaptic Connections in Layer 5 of Rat Frontal Cortex
Kawaguchi, Y. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx252 · Cited by 85
“The reverberating circuits composed of mutual monosynaptic or closed multisynaptic connections can induce persistent activity, used for the short-term memory buffer (Wang 2008; Sussillo 2014; Li et al. 2016; Rajan et al. 2016).”
Mayrhofer, J. M., El‐Boustani, S., Foustoukos, G., Auffret, M., Tamura, K., & Petersen, C. C. H. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.008 · Cited by 106
“The direction-specific preparatory activity in tjM1 might be related to anticipatory neuronal activity (or working memory) in delay tasks (Chen et al., 2017; Guo et al., 2014; Li et al., 2016).”
Neural Correlates of Optimal Multisensory Decision MakingPreprint
Hou, H., Zheng, Q., Zhao, Y., Pouget, A., & Gu, Y. (2018) · bioRxiv · doi:10.1101/480178 · Cited by 76
“, 2019), and interactions among different brain regions (Li et al., 2016).”
Background50 years of mnemonic persistent activity: quo vadis?
Wang, X. (2021) · Trends in Neurosciences · doi:10.1016/j.tins.2021.09.001 · Cited by 106
“fixed endpoints in the state space of recorded neural population activity, in support of discrete attractor models (Figure 1B) [63].”
BackgroundMethodRotational dynamics in motor cortex are consistent with a feedback controllerPreprint
Kalidindi, H., Cross, K., Lillicrap, T., Omrani, M., Falotico, E., Sabes, P. N., & Scott, S. (2020) · bioRxiv · doi:10.1101/2020.11.17.387043 · Cited by 75
“…that perturb neural circuits through stimulation, cooling probes or optogenetics will also provide valuable insight into how inputs are transformed by MC (Guo et al., 2020; Hore et al., 1977; Li et al., 2016; Nashef et al., 2018, 2019; Perich et al., 2020; Svoboda and Li, 2018; Takei et al., 2020).”
BackgroundModularity and robustness of frontal cortical networks
Chen, G., Kang, B., Lindsey, J. W., Druckmann, S., & Li, N. (2021) · Cell · doi:10.1016/j.cell.2021.05.026 · Cited by 70
Self-citationEncoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks
Goudar, V., & Buonomano, D. (2017) · bioRxiv · doi:10.1101/176198 · Cited by 74
“…on the sub-second scale, and represent time-varying patterns, relies on the inherent continuous dynamics, and computational potential, of recurrent neural networks (Rabinovich et al., 2008; Buonomano and Maass, 2009; Mante et al., 2013; Crowe et al., 2014; Carnevale et al., 2015; Li et al., 2016).”
BackgroundPreBötzinger complex neurons drive respiratory modulation of blood pressure and heart rate
Menuet, C., Connelly, A., Bassi, J., Melo, M., Le, S., Kamar, J., Kumar, N. N., McDougall, S., McMullan, S., & Allen, A. M. (2020) · eLife · doi:10.7554/elife.57288 · Cited by 73
“Redundancy is usually a characteristic feature of neuronal networks, as it provides robustness to perturbations (Li et al., 2016).”
Independent representations of ipsilateral and contralateral limbs in primary motor cortex
Heming, E. A., Cross, K. P., Takei, T., Cook, D. J., & Scott, S. H. (2019) · eLife · doi:10.7554/elife.48190 · Cited by 83
“Li et al. (2016) highlights how activity in ipsilateral motor cortex improves the robustness of activity in the contralateral motor cortex.”
BackgroundWilliamson, R. C., Doiron, B., Smith, M. A., & Yu, B. M. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2018.12.009 · Cited by 66
“106 This concept of functionally-defined neuronal subspaces has also been used in other studies of 107 motor control [47,48], decision making [21,49], short-term memory [21,50], learning [15], and 108 stimulus encoding [51].”
BackgroundMethodOutput Planning at the Input Stage: Action Imprinting for Future Memory-Guided Behaviour
Boettcher, S., Gresch, D., Nobre, A. C., & van Ede, F. (2020) · Science Advances · doi:10.1126/sciadv.abe8212 · Cited by 90
Genetic Dissection of Neural Circuits: A Decade of Progress
Luo, L., Callaway, E. M., & Svoboda, K. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.040 · Cited by 454
Self-citation
Metadata
- Authors
- Li, N., Daie, K., Svoboda, K., & Druckmann, S.
- Affiliations
- Howard Hughes Medical Institute (US)
- Corresponding author
- Svoboda, Karel
- Druckmann, Shaul
- Venue
- Nature
- Published
- 2016-04-13
- Volume
- 532
- Issue
- 7600
- Pages
- 459-464
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5081260
- OpenAlex
- W2336155947
- Cited by
- 492
- References
- 53
- Citations by year
- 2026: 39 · 2025: 52 · 2024: 55 · 2023: 56 · 2022: 51 · 2021: 59 · 2020: 50 · 2019: 41 · 2018: 39 · 2017: 37 · 2016: 13
- FWCI
- 27.58
- Type
- journal article
- Language
- en
- Update notices
- erratum (2016-06-29)
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- premotor cortex, motor planning, preparatory activity, network robustness, interhemispheric connectivity, network redundancy, working memory, optogenetic perturbation, mouse cortex, network models
- MeSH terms
- Animals, Brain Mapping, Corpus Callosum, Female, Light, Male, Memory, Short-Term, Models, Neurological, Motor Cortex, Movement, Neurons, Mice, Executive Function, Optogenetics
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