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

Communications Biology
  • 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. communications biology
  3. articles
  4. article
A division of labor in perception-action integration via hierarchical alpha-beta to beta-gamma coupling and local catecholaminergic control
Download PDF
Download PDF
  • Article
  • Open access
  • Published: 21 January 2026

A division of labor in perception-action integration via hierarchical alpha-beta to beta-gamma coupling and local catecholaminergic control

  • Marida Zhupa1 &
  • Christian Beste  ORCID: orcid.org/0000-0002-2989-95611,2 

Communications Biology , Article number:  (2026) Cite this article

  • 845 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

  • Cognitive control
  • Human behaviour

Abstract

The flexible handling of perception-action representations is crucial for cognitive control such as response inhibition, which depends on the catecholaminergic system. However, how cross-frequency interactions support perception-action integration during response inhibition, and how they are modulated by catecholamines, remains unknown. In this placebo-controlled study employing methylphenidate, using electroencephalography (EEG) and a modified Go/Nogo task, we investigate phase-amplitude coupling (PAC) between theta (θ), alpha (α), beta (β), and gamma (γ) oscillations. We demonstrate that these interactions are hierarchically organized, with early α-β PAC supporting perceptual-motor representation, and subsequent β-γ coupling refining downstream processing. Transfer entropy analyses indicate a feed-forward α-β to β-γ influence, suggesting that slower oscillations gate updates in faster bands. Crucially, methylphenidate selectively enhances late β-γ coupling, supporting a functional specialization where α-β rhythms enable access and reconfiguration, while β-γ rhythms mediate local control. These findings suggest a temporally structured mechanism where the catecholaminergic system modulates flexible perception-action integration during response inhibition.

Similar content being viewed by others

Enhancing memory capacity by experimentally slowing theta frequency oscillations using combined EEG-tACS

Article Open access 20 August 2022

Differential GABA dynamics across brain functional networks in autism

Article Open access 24 January 2026

Theta oscillations shift towards optimal frequency for cognitive control

Article 21 April 2022

Data availability

Supplementary Data 1 and the additional datasets analyzed in this study are available in the OSF repository76, https://doi.org/10.17605/OSF.IO/5UENV.

Code availability

Further custom code used to process the data can be found here76: https://doi.org/10.17605/OSF.IO/5UENV.

References

  1. Engel, A. K. & Singer, W. Temporal binding and the neural correlates of sensory awareness. Trends Cogn. Sci. 5, 16–25 (2001).

    Google Scholar 

  2. Fries, P. Rhythms for cognition: communication through coherence. Neuron 88, 220–235 (2015).

    Google Scholar 

  3. Varela, F., Lachaux, J.-P., Rodriguez, E. & Martinerie, J. The brainweb: phase synchronization and large-scale integration. Nat. Rev. Neurosci. 2, 229–239 (2001).

    Google Scholar 

  4. Beste, C., Münchau, A. & Frings, C. Towards a systematization of brain oscillatory activity in actions. Commun. Biol. 6, 137 (2023).

    Google Scholar 

  5. Frings, C. et al. Consensus definitions of perception-action-integration in action control. Commun. Psychol. 2, 7 (2024).

    Google Scholar 

  6. Frings, C. et al. Binding and retrieval in action control (BRAC). Trends Cogn. Sci. 24, 375–387 (2020).

    Google Scholar 

  7. Hommel, B. Event files: feature binding in and across perception and action. Trends Cogn. Sci. 8, 494–500 (2004).

    Google Scholar 

  8. Hommel, B., Müsseler, J., Aschersleben, G. & Prinz, W. The Theory of Event Coding (TEC): a framework for perception and action planning. Behav. Brain Sci. 24, 849–878 (2001).

    Google Scholar 

  9. Prochnow, A., Eggert, E., Münchau, A., Mückschel, M. & Beste, C. Alpha and theta bands dynamics serve distinct functions during perception–action integration in response inhibition. J. Cogn. Neurosci. 34, 1053–1069 (2022).

    Google Scholar 

  10. Prochnow, A., Wendiggensen, P., Eggert, E., Münchau, A. & Beste, C. Pre-trial fronto-occipital electrophysiological connectivity affects perception–action integration in response inhibition. Cortex 152, 122–135 (2022).

    Google Scholar 

  11. Wendiggensen, P. et al. Interplay between alpha and theta band activity enables management of perception-action representations for goal-directed behavior. Commun. Biol. 6, 494 (2023).

    Google Scholar 

  12. Canolty, R. T. & Knight, R. T. The functional role of cross-frequency coupling. Trends Cogn. Sci. 14, 506–515 (2010).

    Google Scholar 

  13. Gholamipourbarogh, N. et al. Perception-action integration during inhibitory control is reflected in a concomitant multi-region processing of specific codes in the neurophysiological signal. Psychophysiology https://doi.org/10.1111/psyp.14178 (2022).

  14. Gholamipourbarogh, N. et al. Evidence for independent representational contents in inhibitory control subprocesses associated with frontoparietal cortices. Hum. Brain Mapp. https://doi.org/10.1002/hbm.26135 (2022).

  15. Veltz, R. & Sejnowski, T. J. Periodic forcing of inhibition-stabilized networks: nonlinear resonances and phase-amplitude coupling. Neural Comput. 27, 2477–2509 (2015).

    Google Scholar 

  16. Galindo-Leon, E. E., Nolte, G., Pieper, F., Engler, G. & Engel, A. K. Causal interactions between amplitude correlation and phase coupling in cortical networks. Sci. Rep. 15, 11975 (2025).

    Google Scholar 

  17. Martínez-Cancino, R. et al. What can local transfer entropy tell us about phase-amplitude coupling in electrophysiological signals? Entropy 22, 1262 (2020).

    Google Scholar 

  18. Shi, W., Yeh, C.-H. & Hong, Y. Cross-frequency transfer entropy characterize coupling of interacting nonlinear oscillators in complex systems. IEEE Trans. Biomed. Eng. 66, 521–529 (2019).

    Google Scholar 

  19. Eggert, E. et al. Cognitive science theory-driven pharmacology elucidates the neurobiological basis of perception-motor integration. Commun. Biol. 5, 919 (2022).

    Google Scholar 

  20. Eggert, E. et al. Perception-action integration is modulated by the catecholaminergic system depending on learning experience. Int. J. Neuropsychopharmacol. 24, 592–600 (2021).

    Google Scholar 

  21. Mayer, J. et al. Pharmacological modulation of directed network communication and neural hubs in action–effect integration. Int. J. Neuropsychopharmacol. 28, pyaf031 (2025).

    Google Scholar 

  22. Prochnow, A. et al. The ability to voluntarily regulate theta band activity affects how pharmacological manipulation of the catecholaminergic system impacts cognitive control. Int. J. Neuropsychopharmacol. 27, pyae003 (2024).

    Google Scholar 

  23. Andino-Pavlovsky, V. et al. Dopamine modulates delta-gamma phase-amplitude coupling in the prefrontal cortex of behaving rats. Front. Neural Circuits 11, 29 (2017).

    Google Scholar 

  24. Devergnas, A., Caiola, M., Pittard, D. & Wichmann, T. Cortical phase-amplitude coupling in a progressive model of parkinsonism in nonhuman primates. Cereb. Cortex 29, 167–177 (2019).

    Google Scholar 

  25. Wang, Z., Cao, Q., Bai, W., Zheng, X. & Liu, T. Decreased phase–amplitude coupling between the mPFC and BLA during exploratory behaviour in chronic unpredictable mild stress-induced depression model of rats. Front. Behav. Neurosci. 15, 799556 (2021).

    Google Scholar 

  26. Chmielewski, W. X. & Beste, C. Stimulus-response recoding during inhibitory control is associated with superior frontal and parahippocampal processes. NeuroImage 196, 227–236 (2019).

    Google Scholar 

  27. Prochnow, A. et al. Neural dynamics of stimulus-response representations during inhibitory control. J. Neurophysiol. 126, 680–692 (2021).

    Google Scholar 

  28. Wolman, A., Lechner, S., Angeletti, L. L., Goheen, J. & Northoff, G. From the brain’s encoding of input dynamics to its behavior: neural dynamics shape bias in decision making. Commun. Biol. 7, 1538 (2024).

    Google Scholar 

  29. Tort, A. B. L., Komorowski, R., Eichenbaum, H. & Kopell, N. Measuring phase-amplitude coupling between neuronal oscillations of different frequencies. J. Neurophysiol. 104, 1195–1210 (2010).

    Google Scholar 

  30. Maris, E. & Oostenveld, R. Nonparametric statistical testing of EEG- and MEG-data. J. Neurosci. Methods 164, 177–190 (2007).

    Google Scholar 

  31. Hämäläinen, M. S. & Ilmoniemi, R. J. Interpreting magnetic fields of the brain: minimum norm estimates. Med. Biol. Eng. Comput. 32, 35–42 (1994).

    Google Scholar 

  32. Tzourio-Mazoyer, N. et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage 15, 273–289 (2002).

    Google Scholar 

  33. Schreiber, T. Measuring information transfer. Phys. Rev. Lett. 85, 461–464 (2000).

    Google Scholar 

  34. Vicente, R., Wibral, M., Lindner, M. & Pipa, G. Transfer entropy—a model-free measure of effective connectivity for the neurosciences. J. Comput. Neurosci. 30, 45–67 (2011).

    Google Scholar 

  35. Wibral, M., Vicente, R. & Lizier, J.T. Directed Information Measures in Neuroscience (Springer, 2014).

  36. Talebi, N. et al. Neural mechanisms of adaptive behavior: dissociating local cortical modulations and interregional communication patterns. iScience 27, 110995 (2024).

    Google Scholar 

  37. Engel, A. K. & Fries, P. Beta-band oscillations–signalling the status quo? Curr. Opin. Neurobiol. 20, 156–165 (2010).

    Google Scholar 

  38. Spitzer, B. & Haegens, S. Beyond the status quo: a role for beta oscillations in endogenous content (re)activation. eneuro 4, ENEURO.0170–17.2017 (2017).

    Google Scholar 

  39. Seghier, M. L. The angular gyrus: multiple functions and multiple subdivisions. Neuroscientist 19, 43–61 (2013).

    Google Scholar 

  40. Leech, R. & Sharp, D. J. The role of the posterior cingulate cortex in cognition and disease. Brain 137, 12–32 (2014).

    Google Scholar 

  41. Northoff, G. & Buccellato, A. From slow spontaneous oscillations to consciousness—dynamic layer model of brain (DLB). Comment on “Dark brain energy: toward an integrative model of spontaneous slow oscillations” by Zhu-Qing Gong and Xi-Nian Zuo. Phys. Life Rev. 54, 169–172 (2025).

    Google Scholar 

  42. Northoff, G., Buccellato, A. & Zilio, F. Connecting brain and mind through temporo-spatial dynamics: towards a theory of common currency. Phys. Life Rev. 52, 29–43 (2025).

    Google Scholar 

  43. Pastötter, B., Moeller, B. & Frings, C. Watching the brain as it (un)binds: beta synchronization relates to distractor–response binding. J. Cogn. Neurosci. 33, 1581–1594 (2021).

    Google Scholar 

  44. Pastötter, B. et al. Increased beta synchronization underlies perception-action hyperbinding in functional movement disorders. Brain Commun. 6, fcae301 (2024).

    Google Scholar 

  45. Faraone, S. V. The pharmacology of amphetamine and methylphenidate: relevance to the neurobiology of attention-deficit/hyperactivity disorder and other psychiatric comorbidities. Neurosci. Biobehav. Rev. 87, 255–270 (2018).

    Google Scholar 

  46. Aston-Jones, G. & Cohen, J. D. An integrative theory of locus coeruleus-norepinephrine function: adaptive gain and optimal performance. Annu. Rev. Neurosci. 28, 403–450 (2005).

    Google Scholar 

  47. Hauser, T. U., Fiore, V. G., Moutoussis, M. & Dolan, R. J. Computational psychiatry of ADHD: neural gain impairments across marrian levels of analysis. Trends Neurosci. 39, 63–73 (2016).

    Google Scholar 

  48. Barone, J. & Rossiter, H. E. Understanding the role of sensorimotor beta oscillations. Front. Syst. Neurosci. 15, 655886 (2021).

    Google Scholar 

  49. Orekhova, E. V. et al. Neural gain control measured through cortical gamma oscillations is associated with sensory sensitivity. Hum. Brain Mapp. 40, 1583–1593 (2019).

    Google Scholar 

  50. Weiss, E., Kann, M. & Wang, Q. Neuromodulation of neural oscillations in health and disease. Biology 12, 371 (2023).

    Google Scholar 

  51. Iskhakova, L. et al. Modulation of dopamine tone induces frequency shifts in cortico-basal ganglia beta oscillations. Nat. Commun. 12, 7026 (2021).

    Google Scholar 

  52. Mather, M., Clewett, D., Sakaki, M. & Harley, C. W. Norepinephrine ignites local hotspots of neuronal excitation: how arousal amplifies selectivity in perception and memory. Behav. Brain Sci. 39, e200 (2016).

    Google Scholar 

  53. Seamans, J. K. & Yang, C. R. The principal features and mechanisms of dopamine modulation in the prefrontal cortex. Prog. Neurobiol. 74, 1–58 (2004).

    Google Scholar 

  54. Groom, M. J. et al. Effects of motivation and medication on electrophysiological markers of response inhibition in children with attention-deficit/hyperactivity disorder. Biol. Psychiatry 67, 624–631 (2010).

    Google Scholar 

  55. Groom, M. J. et al. Event-related potentials in adolescents with schizophrenia and their siblings: a comparison with attention-deficit/hyperactivity disorder. Biol. Psychiatry 63, 784–792 (2008).

    Google Scholar 

  56. Mückschel, M., Eggert, E., Prochnow, A. & Beste, C. Learning experience reverses catecholaminergic effects on adaptive behavior. Int. J. Neuropsychopharmacol. 23, 12–19 (2020).

    Google Scholar 

  57. Achenbach, T. M. Achenbach system of empirically based assessment (ASEBA). in The Encyclopedia of Clinical Psychology (eds Cautin, R. L. & Lilienfeld, S. O) 1–8 (Wiley, 2015).

  58. Lehrl, S. Manual zum MWT-B: Mehrfachwahl-Wortschatz-Intelligenztest (Spitta GmbH, 2018).

  59. Senn, S. Cross-over Trials in Clinical Research (Wiley, 2002).

  60. Bensmann, W., Zink, N., Roessner, V., Stock, A.-K. & Beste, C. Catecholaminergic effects on inhibitory control depend on the interplay of prior task experience and working memory demands. J. Psychopharmacol. 33, 678–687 (2019).

    Google Scholar 

  61. Kimko, H. C., Cross, J. T. & Abernethy, D. R. Pharmacokinetics and clinical effectiveness of methylphenidate. Clin. Pharmacokinet. 37, 457–470 (1999).

    Google Scholar 

  62. Challman, T. D. & Lipsky, J. J. Methylphenidate: its pharmacology and uses. Mayo Clin. Proc. 75, 711–721 (2000).

    Google Scholar 

  63. On Behalf of the Study Group et al. A randomised, placebo-controlled, 24-week, study of low-dose extended-release methylphenidate in adults with attention-deficit/hyperactivity disorder. Eur. Arch. Psychiatry Clin. Neurosci. 259, 120–129 (2009).

    Google Scholar 

  64. Delorme, A. & Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–21 (2004).

    Google Scholar 

  65. Mullen, T. et al. Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2184–2187 (IEEE, 2013).

  66. Pion-Tonachini, L., Kreutz-Delgado, K. & Makeig, S. The ICLabel dataset of electroencephalographic (EEG) independent component (IC) features. Data Brief. 25, 104101 (2019).

    Google Scholar 

  67. Gramfort, A. et al. MNE software for processing MEG and EEG data. NeuroImage 86, 446–460 (2014).

    Google Scholar 

  68. Samiee, S. & Baillet, S. Time-resolved phase-amplitude coupling in neural oscillations. NeuroImage 159, 270–279 (2017).

    Google Scholar 

  69. Oran, S. & Yıldırım, E. Effects of sampling length and overlap ratio on EEG mental arithmetic task performance: a comparative study. Gazi Univ. J. Sci. 37, 1718–1733 (2024).

    Google Scholar 

  70. Wilson, L. E., Da Silva Castanheira, J. & Baillet, S. Time-resolved parameterization of aperiodic and periodic brain activity. eLife 11, e77348 (2022).

    Google Scholar 

  71. Munia, T. T. K. & Aviyente, S. Time-frequency based phase-amplitude coupling measure for neuronal oscillations. Sci. Rep. 9, 12441 (2019).

    Google Scholar 

  72. Fischl, B. FreeSurfer. NeuroImage 62, 774–781 (2012).

    Google Scholar 

  73. Kerby, D. S. The simple difference formula: an approach to teaching nonparametric correlation. Compr. Psychol. 3, 11.IT.3.1 (2014).

    Google Scholar 

  74. Phipson, B. & Smyth, G. K. Permutation P-values should never be zero: calculating exact p-values when permutations are randomly drawn. Stat. Appl. Genet. Mol. Biol. 9, Article39 (2010).

  75. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Methodol. 57, 289–300 (1995).

    Google Scholar 

  76. Zhupa, M. & Beste, C. A division of labor in perception-action integration via hierarchical alpha-beta to beta-gamma coupling and local catecholaminergic control. OSF https://doi.org/10.17605/OSF.IO/5UENV (2026).

Download references

Acknowledgements

This work was supported by the Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF) as part of the German Center for Child and Adolescent Health (DZKJ) under the funding code 01GL2405B and by the Deutsche Forschungsgemeinschaft (DFG) FOR 2698 and 2790.

Funding

Open Access funding enabled and organized by Projekt DEAL.

Author information

Authors and Affiliations

  1. Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany

    Marida Zhupa & Christian Beste

  2. German Center for Child and Adolescent Health (DZKJ), Partner Site Leipzig/Dresden, Dresden, Germany

    Christian Beste

Authors
  1. Marida Zhupa
    View author publications

    Search author on:PubMed Google Scholar

  2. Christian Beste
    View author publications

    Search author on:PubMed Google Scholar

Contributions

M.Z. and C.B. conceptualized the study. M.Z. performed the data analysis. M.Z. and C.B. contributed to writing the first draft of the manuscript. All authors revised it critically. All authors contributed to and have approved the final manuscript.

Corresponding author

Correspondence to Christian Beste.

Ethics declarations

Competing interests

C.B. is an Editorial Board Member for Communications Biology, but was not involved in the editorial review of, nor the decision to publish this article. All other authors declare no competing interests.

Peer review

Peer review information

Communications Biology thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Jasmine Pan.

Additional information

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

Supplementary information

Supplemental Information

Description of Additional Supplementary File

Supplementary Data 1

reporting summary

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, 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 changes were made. 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/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhupa, M., Beste, C. A division of labor in perception-action integration via hierarchical alpha-beta to beta-gamma coupling and local catecholaminergic control. Commun Biol (2026). https://doi.org/10.1038/s42003-026-09564-4

Download citation

  • Received: 20 September 2025

  • Accepted: 09 January 2026

  • Published: 21 January 2026

  • DOI: https://doi.org/10.1038/s42003-026-09564-4

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

Download PDF

Advertisement

Explore content

  • Research articles
  • Reviews & Analysis
  • News & Comment
  • Collections
  • Follow us on Twitter
  • Sign up for alerts
  • RSS feed

About the journal

  • Journal Information
  • Open Access Fees and Funding
  • Journal Metrics
  • Editors
  • Editorial Board
  • Calls for Papers
  • Referees
  • Contact
  • Editorial policies
  • Aims & Scope

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

Communications Biology (Commun Biol)

ISSN 2399-3642 (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