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.
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Data availability
The datasets used and analysed during the current study available from the corresponding author on reasonable request.
References
Heekeren, H. R., Marrett, S. & Ungerleider, L. G. The neural systems that mediate human perceptual decision making. Nat. Rev. Neurosci.9, 467–479 (2008).
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).
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).
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).
Gallivan, J. P., Chapman, C. S., Wolpert, D. M. & Flanagan, J. R. Decision-making in sensorimotor control. Nat. Rev. Neurosci.19, 519–534 (2018).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Ferreri, F. et al. Human brain connectivity during single and paired pulse transcranial magnetic stimulation. Neuroimage54, 90–102 (2011).
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).
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).
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).
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).
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).
Franza, M. et al. Hand perceptions induced by single pulse transcranial magnetic stimulation over the primary motor cortex. Brain Stimul.12, 693–701 (2019).
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).
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).
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).
Noorani, I. & Carpenter, R. H. The LATER model of reaction time and decision. Neurosci. Biobehav. Rev.64, 229–251 (2016).
Farrell, P. et al. Drift-diffusion models. In Handbook of optoelectronic device modeling and simulation, 733–772 (CRC Press, 2017).
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).
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).
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).
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).
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.
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).
Carlton, L. G. Visual processing time and the control of movement. In Advances in psychology, vol. 85, 3–31 (Elsevier, 1992).
Duecker, F. & Sack, A. T. Rethinking the role of sham TMS. Front. Psychol.6, 210 (2015).
Ratcliff, R. & McKoon, G. The diffusion decision model: theory and data for two-choice decision tasks. Neural Comput.20, 873–922 (2008).
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).
JASP Team. JASP (Version 0.19.1)[Computer software] (2024).
Mathis, M. W. & Schneider, S. Motor control: Neural correlates of optimal feedback control theory. Curr. Biol.31, R356–R358 (2021).
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).
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).
Ariani, G., Pruszynski, J. A. & Diedrichsen, J. Motor planning brings human primary somatosensory cortex into action-specific preparatory states. elife11, e69517 (2022).
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).
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).
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).
Walsh, V. & Rushworth, M. A primer of magnetic stimulation as a tool for neuropsychology. Neuropsychologia37, 125–135 (1999).
Bolognini, N. & Ro, T. Transcranial magnetic stimulation: disrupting neural activity to alter and assess brain function. J. Neurosci.30, 9647–9650 (2010).
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).
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).
Abe, M. & Hanakawa, T. Functional coupling underlying motor and cognitive functions of the dorsal premotor cortex. Behav. Brain Res.198, 13–23 (2009).
Passingham, R. E. Premotor cortex and preparation for movement. Exp. Brain Res.70, 590–596 (1988).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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.
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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.
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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
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DOI: https://doi.org/10.1038/s41598-026-35439-z


