Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Scientific Reports
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • RSS feed
  1. nature
  2. scientific reports
  3. articles
  4. article
Single-pulse TMS functional mapping of sensorimotor cortex during decision-making task
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 07 February 2026

Single-pulse TMS functional mapping of sensorimotor cortex during decision-making task

  • Anna Udoratina1,2 na1,
  • Nikita Grigorev1 na1,
  • Andrey Savosenkov2,
  • Denis Ermolaev3,
  • Usama Muhammad5,
  • Anton Kiselev4,
  • Vladimir Maksimenko1,2,5 &
  • …
  • Susanna Gordleeva1,2,3 

Scientific Reports , Article number:  (2026) Cite this article

  • 580 Accesses

  • Metrics details

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Biological techniques
  • Neuroscience

Abstract

Perceptual decision-making involves distinct sub-processes, including sensory encoding, decision formation, and motor execution. Studying the specific contributions of cortical areas to these components could deepen our understanding of decision-making mechanisms and inform therapeutic approaches for cognitive impairment. Single-pulse transcranial magnetic stimulation (spTMS) enables the functional investigation of cortical involvement during task performance, revealing the participation of specific regions in cognitive processes. When combined with the drift diffusion model (DDM), spTMS can precisely characterize effects on different decision sub-processes. In this study, 30 healthy participants performed a perceptual decision-making task requiring right-hand finger responses to complex visual stimuli. We delivered spTMS to sensorimotor cortex regions at two time points during task performance (200 ms and 800 ms post-stimulus onset). Results demonstrated region-specific modulation patterns: stimulation of the premotor dorsal caudal cortex (PMdc) selectively reduced reaction time (RT) by decreasing non-decision time (NDT), indicating its role in motor preparation. In contrast, primary motor cortex (M1) and primary somatosensory cortex (S1) stimulation produced opposing effects - decreased NDT coupled with increased evidence accumulation time (EAT) - resulting in no net RT change. These findings highlight how spTMS combined with DDM can dissect distinct cortical contributions to decision-making sub-processes.

Similar content being viewed by others

Sensorimotor performance after high-definition transcranial direct current stimulation over the primary somatosensory or motor cortices in men versus women

Article Open access 01 July 2022

Concurrent tDCS-fMRI after stroke reveals link between attention network organization and motor improvement

Article Open access 20 August 2024

Neural mechanisms of emotional health in traumatic brain injury patients undergoing rTMS treatment

Article Open access 06 July 2023

Data availability

The datasets used and analysed during the current study available from the corresponding author on reasonable request.

References

  1. Heekeren, H. R., Marrett, S. & Ungerleider, L. G. The neural systems that mediate human perceptual decision making. Nat. Rev. Neurosci.9, 467–479 (2008).

    Google Scholar 

  2. Kelly, S. P. & O’Connell, R. G. The neural processes underlying perceptual decision making in humans: recent progress and future directions. J. Physiol.109, 27–37 (2015).

    Google Scholar 

  3. Edwards, L. L., King, E. M., Buetefisch, C. M. & Borich, M. R. Putting the sensory into sensorimotor control: the role of sensorimotor integration in goal-directed hand movements after stroke. Front. Integr. Neurosci.13, 16 (2019).

    Google Scholar 

  4. Wasaka, T. & Kakigi, R. Sensorimotor integration: The somatosensory system and voluntary movement. In Supek, S. & Aine, C. J. (eds.) Magnetoencephalography, 957–975, https://doi.org/10.1007/978-3-030-00087-5_34 (Springer International Publishing, 2019).

  5. Gallivan, J. P., Chapman, C. S., Wolpert, D. M. & Flanagan, J. R. Decision-making in sensorimotor control. Nat. Rev. Neurosci.19, 519–534 (2018).

    Google Scholar 

  6. Balsdon, T., Verdonck, S., Loossens, T. & Philiastides, M. G. Secondary motor integration as a final arbiter in sensorimotor decision-making. PLoS Biol.21, e3002200 (2023).

    Google Scholar 

  7. Sandhaeger, F., Omejc, N., Pape, A.-A. & Siegel, M. Abstract perceptual choice signals during action-linked decisions in the human brain. PLoS Biol.21, e3002324. https://doi.org/10.1371/journal.pbio.3002324 (2023).

    Google Scholar 

  8. Peixoto, D. et al. Decoding and perturbing decision states in real time. Nature591, 604–609. https://doi.org/10.1038/s41586-020-03181-9 (2021).

    Google Scholar 

  9. Donner, T. H., Siegel, M., Fries, P. & Engel, A. K. Buildup of choice-predictive activity in human motor cortex during perceptual decision making. Curr. Biol.19, 1581–1585 (2009).

    Google Scholar 

  10. Brunoni, A. R. & Vanderhasselt, M.-A. Working memory improvement with non-invasive brain stimulation of the dorsolateral prefrontal cortex: a systematic review and meta-analysis. Brain Cogn.86, 1–9 (2014).

    Google Scholar 

  11. Ellison, A., Lane, A. R. & Schenk, T. The interaction of brain regions during visual search processing as revealed by transcranial magnetic stimulation. Cereb. Cortex17, 2579–2584 (2007).

    Google Scholar 

  12. Ruzzoli, M., Marzi, C. A. & Miniussi, C. The neural mechanisms of the effects of transcranial magnetic stimulation on perception. J. Neurophysiol.103, 2982–2989. https://doi.org/10.1152/jn.01096.2009 (2010).

    Google Scholar 

  13. Thut, G. et al. Effects of single-pulse transcranial magnetic stimulation (TMS) on functional brain activity: a combined event-related TMS and evoked potential study. Clin. Neurophysiol.114, 2071–2080. https://doi.org/10.1016/S1388-2457(03)00205-0 (2003).

    Google Scholar 

  14. Rushworth, M. & Taylor, P. TMS in the parietal cortex: Updating representations for attention and action. Neuropsychologia44, 2700–2716. https://doi.org/10.1016/j.neuropsychologia.2005.12.007 (2006).

    Google Scholar 

  15. Berkay, D., Eser, H. Y., Sack, A. T., Çakmak, Y. î & Balci, F. The modulatory role of pre-SMA in speed-accuracy tradeoff: a bi-directional TMS study. Neuropsychologia109, 255–261 (2018).

  16. Willacker, L., Roccato, M., Can, B. N., Dieterich, M. & Taylor, P. C. J. Reducing variability of perceptual decision making with offline theta-burst TMS of dorsal medial frontal cortex. Brain Stimul.13, 1689–1696. https://doi.org/10.1016/j.brs.2020.09.011 (2020).

    Google Scholar 

  17. Pleger, B. et al. Repetitive transcranial magnetic stimulation-induced changes in sensorimotor coupling parallel improvements of somatosensation in humans. J. Neurosci.26, 1945–1952. https://doi.org/10.1523/JNEUROSCI.4097-05.2006 (2006).

    Google Scholar 

  18. Turton, A. J., McCabe, C. S., Harris, N. & Filipovic, S. R. Sensorimotor integration in complex regional pain syndrome: A transcranial magnetic stimulation study. Pain127, 270–275. https://doi.org/10.1016/j.pain.2006.08.021 (2007).

    Google Scholar 

  19. Fischer, M. & Orth, M. Short-latency sensory afferent inhibition: conditioning stimulus intensity, recording site, and effects of 1 hz repetitive TMS. Brain Stimul.4, 202–209 (2011).

    Google Scholar 

  20. Ferreri, F. et al. Human brain connectivity during single and paired pulse transcranial magnetic stimulation. Neuroimage54, 90–102 (2011).

    Google Scholar 

  21. Luber, B. et al. Effects of online single pulse transcranial magnetic stimulation on prefrontal and parietal cortices in deceptive processing: a preliminary study. Front. Hum. Neurosci.16, 883337 (2022).

    Google Scholar 

  22. Uithol, S. et al. Single-pulse transcranial magnetic stimulation reveals contribution of premotor cortex to object shape recognition. Brain Stimul.8, 953–956. https://doi.org/10.1016/j.brs.2015.04.012 (2015).

    Google Scholar 

  23. Bashir, S. et al. Role of single low pulse intensity of transcranial magnetic stimulation over the frontal cortex for cognitive function. Front. Hum. Neurosci.14, 205 (2020).

    Google Scholar 

  24. Ku, Y. et al. Sequential roles of primary somatosensory cortex and posterior parietal cortex in tactile-visual cross-modal working memory: a single-pulse transcranial magnetic stimulation (spTMS) study. Brain Stimul.8, 88–91 (2015).

    Google Scholar 

  25. Thickbroom, G. W., Byrnes, M. L., Archer, S. A., Kermode, A. G. & Mastaglia, F. L. Corticomotor organisation and motor function in multiple sclerosis. J. Neurol.252, 765–771. https://doi.org/10.1007/s00415-005-0728-9 (2005).

    Google Scholar 

  26. Franza, M. et al. Hand perceptions induced by single pulse transcranial magnetic stimulation over the primary motor cortex. Brain Stimul.12, 693–701 (2019).

    Google Scholar 

  27. Siebner, H. R., Hartwigsen, G., Kassuba, T. & Rothwell, J. C. How does transcranial magnetic stimulation modify neuronal activity in the brain? implications for studies of cognition. Cortex45, 1035–1042. https://doi.org/10.1016/j.cortex.2009.02.007 (2009).

    Google Scholar 

  28. Miraglia, F. et al. The effects of directional and non-directional stimuli during a visuomotor task and their correlation with reaction time: An ERP study. Sensors23, 3143 (2023).

    Google Scholar 

  29. Jain, A., Bansal, R., Kumar, A. & Singh, K. D. A comparative study of visual and auditory reaction times on the basis of gender and physical activity levels of medical first year students. Int. J. Appl. Basic Med. Res.5, 124–127 (2015).

  30. Noorani, I. & Carpenter, R. H. The LATER model of reaction time and decision. Neurosci. Biobehav. Rev.64, 229–251 (2016).

    Google Scholar 

  31. Farrell, P. et al. Drift-diffusion models. In Handbook of optoelectronic device modeling and simulation, 733–772 (CRC Press, 2017).

  32. Ratcliff, R., Smith, P. L., Brown, S. D. & McKoon, G. Diffusion decision model: Current issues and history. Trends Cogn. Sci.20, 260–281. https://doi.org/10.1016/j.tics.2016.01.007 (2016).

    Google Scholar 

  33. McGovern, D. P., Hayes, A., Kelly, S. P. & O’Connell, R. G. Reconciling age-related changes in behavioural and neural indices of human perceptual decision-making. Nat. Hum. Behav.2, 955–966 (2018).

    Google Scholar 

  34. Scaramozzino, F., McKay, R. & Furl, N. Posterior parietal cortex modulates perceptual decisions depending on psychotic phenotype https://doi.org/10.1101/2024.11.08.24316920 (2024).

    Google Scholar 

  35. Rolle, C. E. et al. The role of the dorsal–lateral prefrontal cortex in reward sensitivity during approach–avoidance conflict. Cereb. Cortex32, 1269–1285. https://doi.org/10.1093/cercor/bhab292 (2022).

    Google Scholar 

  36. Farzan, F. Single-Pulse Transcranial Magnetic Stimulation (TMS) Protocols and Outcome Measures. In Rotenberg, A., Horvath, J. C. & Pascual-Leone, A. (eds.) Transcranial Magnetic Stimulation, vol. 89, 69–115, https://doi.org/10.1007/978-1-4939-0879-0_5 (Springer New York, New York, NY, 2014). Series Title: Neuromethods.

  37. Mochizuki, H., Ugawa, Y., Terao, Y. & Sakai, K. L. Cortical hemoglobin-concentration changes under the coil induced by single-pulse TMS in humans: a simultaneous recording with near-infrared spectroscopy. Exp. Brain Res.169, 302–310. https://doi.org/10.1007/s00221-005-0149-0 (2006).

    Google Scholar 

  38. Carlton, L. G. Visual processing time and the control of movement. In Advances in psychology, vol. 85, 3–31 (Elsevier, 1992).

  39. Duecker, F. & Sack, A. T. Rethinking the role of sham TMS. Front. Psychol.6, 210 (2015).

    Google Scholar 

  40. Ratcliff, R. & McKoon, G. The diffusion decision model: theory and data for two-choice decision tasks. Neural Comput.20, 873–922 (2008).

    Google Scholar 

  41. Myers, C. E., Interian, A. & Moustafa, A. A. A practical introduction to using the drift diffusion model of decision-making in cognitive psychology, neuroscience, and health sciences. Front. Psychol.13, 1039172 (2022).

    Google Scholar 

  42. JASP Team. JASP (Version 0.19.1)[Computer software] (2024).

  43. Mathis, M. W. & Schneider, S. Motor control: Neural correlates of optimal feedback control theory. Curr. Biol.31, R356–R358 (2021).

    Google Scholar 

  44. Omrani, M., Murnaghan, C. D., Pruszynski, J. A. & Scott, S. H. Distributed task-specific processing of somatosensory feedback for voluntary motor control. Elife5, e13141 (2016).

    Google Scholar 

  45. Arbuckle, S. A., Pruszynski, J. A. & Diedrichsen, J. Mapping the integration of sensory information across fingers in human sensorimotor cortex. J. Neurosci.42, 5173–5185 (2022).

    Google Scholar 

  46. Ariani, G., Pruszynski, J. A. & Diedrichsen, J. Motor planning brings human primary somatosensory cortex into action-specific preparatory states. elife11, e69517 (2022).

  47. Nakayama, Y. et al. The dorsal premotor cortex encodes the step-by-step planning processes for goal-directed motor behavior in humans. NeuroImage256, 119221 (2022).

  48. Buccino, G. et al. Action observation activates premotor and parietal areas in a somatotopic manner: an fMRI study. Eur. J. Neurosci.13, 400–404. https://doi.org/10.1111/j.1460-9568.2001.01385.x (2001).

    Google Scholar 

  49. Pascual-Leone, A. Transcranial magnetic stimulation: studying the brain-behaviour relationship by induction of ‘virtual lesions’. Phil. Trans. R. Soc. Lond. B354, 1229–1238. https://doi.org/10.1098/rstb.1999.0476 (1999).

    Google Scholar 

  50. Walsh, V. & Rushworth, M. A primer of magnetic stimulation as a tool for neuropsychology. Neuropsychologia37, 125–135 (1999).

    Google Scholar 

  51. Bolognini, N. & Ro, T. Transcranial magnetic stimulation: disrupting neural activity to alter and assess brain function. J. Neurosci.30, 9647–9650 (2010).

  52. Vural, G., Katruss, N. & Soutschek, A. Pre-supplementary motor area strengthens reward sensitivity in intertemporal choice. Neuroimage299, 120838. https://doi.org/10.1016/j.neuroimage.2024.120838 (2024).

    Google Scholar 

  53. Wittkuhn, L. et al. Repetitive transcranial magnetic stimulation over dorsolateral prefrontal cortex modulates value-based learning during sequential decision-making. Neuroimage167, 384–395. https://doi.org/10.1016/j.neuroimage.2017.11.057 (2018).

    Google Scholar 

  54. Abe, M. & Hanakawa, T. Functional coupling underlying motor and cognitive functions of the dorsal premotor cortex. Behav. Brain Res.198, 13–23 (2009).

    Google Scholar 

  55. Passingham, R. E. Premotor cortex and preparation for movement. Exp. Brain Res.70, 590–596 (1988).

  56. Sugawara, K. et al. Activation of the human premotor cortex during motor preparation in visuomotor tasks. Brain Topogr.26, 581–590. https://doi.org/10.1007/s10548-013-0299-5 (2013).

    Google Scholar 

  57. Chandrasekaran, C., Peixoto, D., Newsome, W. T. & Shenoy, K. V. Laminar differences in decision-related neural activity in dorsal premotor cortex. Nat. Commun.8, 614 (2017).

    Google Scholar 

  58. Silvanto, J., Cattaneo, Z., Battelli, L. & Pascual-Leone, A. Baseline cortical excitability determines whether TMS disrupts or facilitates behavior. J. Neurophysiol.99, 2725–2730. https://doi.org/10.1152/jn.01392.2007 (2008).

    Google Scholar 

  59. Thura, D. & Cisek, P. Deliberation and commitment in the premotor and primary motor cortex during dynamic decision making. Neuron81, 1401–1416. https://doi.org/10.1016/j.neuron.2014.01.031 (2014).

    Google Scholar 

  60. Silvanto, J. & Pascual-Leone, A. State-dependency of transcranial magnetic stimulation. Brain Topogr.21, 1–10. https://doi.org/10.1007/s10548-008-0067-0 (2008).

    Google Scholar 

  61. Schwarzkopf, D. S., Silvanto, J. & Rees, G. Stochastic resonance effects reveal the neural mechanisms of transcranial magnetic stimulation. J. Neurosci.31, 3143–3147. https://doi.org/10.1523/JNEUROSCI.4863-10.2011 (2011).

    Google Scholar 

  62. Tomasevic, L. et al. Relationship between high-frequency activity in the cortical sensory and the motor hand areas, and their myelin content. Brain Stimul.15, 717–726 (2022).

  63. Dubbioso, R., Madsen, K. H., Thielscher, A. & Siebner, H. R. The myelin content of the human precentral hand knob reflects interindividual differences in manual motor control at the physiological and behavioral level. J. Neurosci.41, 3163–3179 (2021).

  64. Borich, M. R., Brodie, S. M., Gray, W. A., Ionta, S. & Boyd, L. A. Understanding the role of the primary somatosensory cortex: Opportunities for rehabilitation. Neuropsychologia79, 246–255 (2015).

  65. Perruchoud, D., Murray, M. M., Lefebvre, J. & Ionta, S. Focal dystonia and the sensory-motor integrative loop for enacting (SMILE). Front. Hum. Neurosci.8, https://doi.org/10.3389/fnhum.2014.00458 (2014).

Download references

Funding

The authors acknowledge the financial support from the following sources: Nikita Grigorev, Vladimir Maksimenko and Susanna Gordleeva from the Basic Research Program of the National Research University Higher School of Economics (HSE University); Andrey Savosenkov, Denis Ermolaev from the Ministry of Science and Higher Education of the Russian Federation (Grant No. FSWR-2025-0009). This work was supported in part by the Russian Science Foundation under Project No. 25-69-00047, covering the development and execution of the experimental design.

Author information

Author notes
  1. These authors contributed equally: Anna Udoratina and Nikita Grigorev.

Authors and Affiliations

  1. Center for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, 101000, Russian Federation

    Anna Udoratina, Nikita Grigorev, Vladimir Maksimenko & Susanna Gordleeva

  2. Neuromorphic computing center, Neimark University, Nizhny Novgorod, 603081, Russian Federation

    Anna Udoratina, Andrey Savosenkov, Vladimir Maksimenko & Susanna Gordleeva

  3. Neurodynamics and Cognitive Technology Laboratory, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, 603022, Russian Federation

    Denis Ermolaev & Susanna Gordleeva

  4. Coordinating Center for Fundamental Research, National Medical Research Center for Therapy and Preventive Medicine, Moscow, 101990, Russian Federation

    Anton Kiselev

  5. Faculty of Computer science and Engineering, Innopolis University, Innopolis, 420500, Russian Federation

    Usama Muhammad & Vladimir Maksimenko

Authors
  1. Anna Udoratina
    View author publications

    Search author on:PubMed Google Scholar

  2. Nikita Grigorev
    View author publications

    Search author on:PubMed Google Scholar

  3. Andrey Savosenkov
    View author publications

    Search author on:PubMed Google Scholar

  4. Denis Ermolaev
    View author publications

    Search author on:PubMed Google Scholar

  5. Usama Muhammad
    View author publications

    Search author on:PubMed Google Scholar

  6. Anton Kiselev
    View author publications

    Search author on:PubMed Google Scholar

  7. Vladimir Maksimenko
    View author publications

    Search author on:PubMed Google Scholar

  8. Susanna Gordleeva
    View author publications

    Search author on:PubMed Google Scholar

Contributions

S.G. and V.M. conceived the experiment, N.G. and A.S. prepared experimental protocol, A.U., N.G., A.S. and D.E. conducted the experiment, A.U. analyzed behavioral data, U.M. fitted drift-diffusion model, A.U., N.G. and V.M analyzed model parameters. A.U. and N.G. wrote the main manuscript text, N.G., A.K. and S.G. prepared discussion. All authors reviewed the manuscript.

Corresponding author

Correspondence to Susanna Gordleeva.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary Information.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Udoratina, A., Grigorev, N., Savosenkov, A. et al. Single-pulse TMS functional mapping of sensorimotor cortex during decision-making task. Sci Rep (2026). https://doi.org/10.1038/s41598-026-35439-z

Download citation

  • Received: 04 July 2025

  • Accepted: 06 January 2026

  • Published: 07 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-35439-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Perceptual decision-making
  • transcranial magnetic stimulation
  • functional mapping
  • drift diffusion model
  • sensorimotor cortex
  • reaction time
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Collections
  • Subjects
  • Follow us on Facebook
  • Follow us on X
  • Sign up for alerts
  • RSS feed

About the journal

  • About Scientific Reports
  • Contact
  • Journal policies
  • Guide to referees
  • Calls for Papers
  • Editor's Choice
  • Journal highlights
  • Open Access Fees and Funding

Publish with us

  • For authors
  • Language editing services
  • Open access funding
  • Submit manuscript

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Scientific Reports (Sci Rep)

ISSN 2045-2322 (online)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2026 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing