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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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“Neural activity associated with motor planning and preparation has been observed in motor and premotor cortices for a variety of different motor tasks in rodents and primates (Chen et al., 2017; Churchland et al., 2010a; Churchland et al., 2006a; Churchland et al., 2006b; Economo et al., 2018; Inagaki et al., 2019; Ka…”
BackgroundGe, M.-J., Chen, G., Zhang, Z., Yu, Z.-H., Shen, J., Pan, C., Han, F., Xu, H., Zhu, X.-L., & Lu, Y.-P. (2024) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2024.110981 · Cited by 25
“…(Spellman et al., 2015, Liu and Carter, 2018, S ´ anchez-Bellot, 2019), and claustrum (Anastasiades and Carter, 2021), as well as the contralateral PFC (cPFC) (Little and Carter, 2012, Little and Carter, 2013, Lee et al., 2014, Dembrow et al., 2015, Li et al., 2016, Anasta-siades et al., 2018).”
Striatal bilateral control of skilled forelimb movement
López-Huerta, V. G., Denton, J. A., Nakano, Y., Jáidar, O., Garcia-Munoz, M., & Arbuthnott, G. W. (2021) · Cell Reports · doi:10.1016/j.celrep.2020.108651 · Cited by 32
Two-photon Imaging with Silicon Photomultipliers
Modi, M. N., Daie, K., Turner, G. C., & Podgorski, K. (2019) · bioRxiv · doi:10.1101/717850 · Cited by 26
Self-citationTractography of supplementary motor area projections in progressive speech apraxia and aphasia
Carbó, A. V., Reid, R. I., Tosakulwong, N., Weigand, S. D., Duffy, J. R., Clark, H. M., Utianski, R. L., Botha, H., Machulda, M. M., Strand, E. A., et al. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.102999 · Cited by 32
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Sensory expectations shape neural population dynamics in motor circuits
Michaels, J. A., Kashefi, M., Zheng, J., Codol, O., Weiler, J., Kersten, R., Lau, J. C., Gribble, P. L., Diedrichsen, J., & Pruszynski, J. A. (2025) · Nature · doi:10.1038/s41586-025-09690-9 · Cited by 29
“…but motor cortical activity represents parameters of the future movement 4–11 , predicts movement variability 12 and reaction time 13–16 , and is causally linked to motor execution 17,18 , presumably by setting the initial state of the dynamical system that ultimately produces movement 19–21 .”
Conti, E., Scaglione, A., de Vito, G., Calugi, F., Pasquini, M., Pizzorusso, T., Micera, S., Mascaro, A. L. A., & Pavone, F. S. (2021) · Neurorehabilitation and neural repair · doi:10.1177/15459683211056656 · Cited by 27
Three-dimensional multi-site random access photostimulation (3D-MAP)
Xue, Y., Waller, L., Adesnik, H., & Pégard, N. C. (2022) · eLife · doi:10.7554/elife.73266 · Cited by 26
“Multisite photostimulation is crucial for perturbing or mapping brain circuits because only the activation of neural populations in parallel can drive the sophisticated activity patterns needed to understand network dynamics or behavior (Li et al., 2016).”
BackgroundRubin, J. E., Vich, C., Clapp, M., Noneman, K. K., & Verstynen, T. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.14745 · Cited by 24
Distinct contributions of mouse cortical areas to visual discriminationPreprint
Zatka-Haas, P., Steinmetz, N. A., Carandini, M., & Harris, K. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/501627 · Cited by 21
Trajkovic, J., Romei, V., Rushworth, M. F. S., & Sel, A. (2023) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2023.102487 · Cited by 24
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Cognition and the single neuron: How cell types construct the dynamic computations of frontal cortex
Christensen, A. J., Ott, T., & Kepecs, Á. (2022) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2022.102630 · Cited by 24
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“This approach has been used to identify neural activity trajectories that are informative about stimuli and behaviour and yield insights into neural computations [7, 8, 9, 10, 11, 12, 13].”
MethodSynaptic-resolution connectomics: towards large brains and connectomic screening
Helmstaedter, M. N. (2025) · Nature reviews. Neuroscience · doi:10.1038/s41583-025-00998-z · Cited by 25
Ipsilateral-Dominant Control of Limb Movements in Rodent Posterior Parietal Cortex
Soma, S., Yoshida, J., Kato, S., Takahashi, Y., Nonomura, S., Sugimura, Y. K., Ríos, A., Kawabata, M., Kobayashi, K., Kato, F., et al. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1584-18.2018 · Cited by 36
“…whereas M2 neurons seem to be associated with motor planning and preparation rather than the motor execution (Narayanan and Laubach, 2009; Li et al., 2016); this is similar to M1 and PM/SMA neurons in primates (Weinrich and Wise, 1982; Mushiake et al., 1991; Hoshi and Tanji, 2000;…”
BackgroundInfluentialBerlot, E., Popp, N. J., & Diedrichsen, J. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.11.003 · Cited by 18
Conserved brain-wide emergence of emotional response from sensory experience in humans and mice
Kauvar, I., Richman, E. B., Liu, T. X., Li, C., Vesuna, S. S., Chibukhchyan, A., Yamada, L., Fogarty, A. S., Solomon, E. A., Choi, E. Y., et al. (2025) · Science · doi:10.1126/science.adt3971 · Cited by 28
“…shown to underlie behaviorally relevant persistent activity, such as recurrent activity between anterior lateral motor cortex (ALM) hemi-spheres ( 47 ), or between the ALM and thalamus in the context of a delayed-response whisker-detection task in mice ( 48 ), or between the PFC and MD thalamus…”
Superior colliculus bidirectionally modulates choice activity in frontal cortex
Thomas, A. M., Yang, W., Wang, C., Tipparaju, S. L., Chen, G., Sullivan, B. J., Swiekatowski, K. R., Tatam, M., Gerfen, C. R., & Li, N. (2023) · Nature Communications · doi:10.1038/s41467-023-43252-9 · Cited by 24
“…if multiple network nodes independently mediate choice competition and maintain choice activity, dynamics will quickly recover after a transient perturbation to single network nodes because other redundant nodes recover the state of choice activity based on their own activity states 55,61 .”
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Wang, Z., Chen, S.-S., Liu, Y., Liu, D., Svoboda, K., Li, N., & Druckmann, S. (2023) · bioRxiv · doi:10.1101/2023.06.08.544257 · Cited by 20
Self-citationApproaches to inferring multi-regional interactions from simultaneous population recordings
Kang, B., & Druckmann, S. (2020) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2020.10.004 · Cited by 27
“Such decoders have been shown to capture aspects of the state of behavior-related computations [100,125] and therefore between brain area influence that affects them may be more directly interpretable.”
BackgroundMethodResultInfluentialSelf-citationAramburu, Ó., Ceballos, F. C., Casanova, A., Moan, A. L., Hemmer‐Hansen, J., Bekkevold, D., Bouza, C., & Martı́nez, P. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00296 · Cited by 27
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Lateralization of short-term memory in the frontal cortex
Yin, X., Wang, Y., Li, J., & Guo, Z. V. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111190 · Cited by 19
Attention Decorrelates Sensory and Motor Signals in the Mouse Visual Cortex
Abdolrahmani, M., Lyamzin, D. R., Aoki, R., & Benucci, A. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109377 · Cited by 30
Wong, C., Pearson, K. G., & Lomber, S. G. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx186 · Cited by 23
“The involvement of other brain regions in working memoryrelated processes would establish functional redundancies that provide safeguarding mechanisms preventing data loss (Li et al. 2016; Yu 2016).”
BackgroundFrontiers and Progress of Current Soft Matter Research
Hu, W., Komura, S., & Liu, X.-Y. (2021) · doi:10.1007/978-981-15-9297-3 · Cited by 19
Functional alterations of the prefrontal circuit underlying cognitive aging in mice
Chong, H. R., Ranjbar-Slamloo, Y., Ho, M. Z. H., Ouyang, X., & Kamigaki, T. (2023) · Nature Communications · doi:10.1038/s41467-023-43142-0 · Cited by 19
“Bilateral inactivation caused more severe impairment than unilateral inactivation, which is consistent with a previous study 18 .”
InfluentialChaotic recurrent neural networks for brain modelling: A review
Mattera, A., Alfieri, V., Granato, G., & Baldassarre, G. (2024) · Neural Networks · doi:10.1016/j.neunet.2024.107079 · Cited by 19
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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