Psychological Research

, Volume 81, Issue 1, pp 143–156 | Cite as

Sensorimotor synchronization: neurophysiological markers of the asynchrony in a finger-tapping task

  • Luz BavassiEmail author
  • Juan E. Kamienkowski
  • Mariano Sigman
  • Rodrigo Laje
Original Article


Sensorimotor synchronization (SMS) is a form of referential behavior in which an action is coordinated with a predictable external stimulus. The neural bases of the synchronization ability remain unknown, even in the simpler, paradigmatic task of finger tapping to a metronome. In this task the subject is instructed to tap in synchrony with a periodic sequence of brief tones, and the time difference between each response and the corresponding stimulus tone (asynchrony) is recorded. We make a step towards the identification of the neurophysiological markers of SMS by recording high-density EEG event-related potentials and the concurrent behavioral response-stimulus asynchronies during an isochronous paced finger-tapping task. Using principal component analysis, we found an asymmetry between the traces for advanced and delayed responses to the stimulus, in accordance with previous behavioral observations from perturbation studies. We also found that the amplitude of the second component encodes the higher-level percept of asynchrony 100 ms after the current stimulus. Furthermore, its amplitude predicts the asynchrony of the next step, past 300 ms from the previous stimulus, independently of the period length. Moreover, the neurophysiological processing of synchronization errors is performed within a fixed-duration interval after the stimulus. Our results suggest that the correction of a large asynchrony in a periodic task and the recovery of synchrony after a perturbation could be driven by similar neural processes.


Synchronization Error Error Correction Mechanism Sensorimotor Synchronization Phase Correction Response Positive Perturbation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Manuel Eguía for technical support in the building of the Arduino shield, Laura Kaczer, Veronica Perez Schuster, Pablo Bartfeld and Martín Graziano for useful discussions. This work was funded by grant PICT 881/07 (Agencia Nacional de Promoción Científica y Tecnológica, Argentina), grant UNQ 53/3004 (Universidad Nacional de Quilmes, Argentina) and grant Milstein/Raíces (Ministerio de Ciencia y Tecnología, Argentina). M.S. is sponsored by CONICET and the James McDonnell Foundation 21st Century ScienceInitiative in Understanding Human Cognition— Scholar Award.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Departamento de FísicaFCEyN, UBA and IFIBA-CONICETBuenos AiresArgentina
  2. 2.Laboratorio de Neurobiología de la Memoria, Departamento de Fisiología, Biología Molecular y Celular FCEyN, UBA and IFIBYNE-CONICETBuenos AiresArgentina
  3. 3.Laboratorio de Inteligencia Artificial Aplicada, Departamento de ComputaciónFCEyN, UBABuenos AiresArgentina
  4. 4.Universidad Torcuato Di TellaBuenos AiresArgentina
  5. 5.Departamento de Ciencia y TecnologíaUniversidad Nacional de Quilmes, Argentina, and CONICET ArgentinaBuenos AiresArgentina

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