Paired Associative Stimulation Rewired: A Novel Paradigm to Modulate Resting-State Intracortical Connectivity

in Journal of Motor Learning and Development
Restricted access

Purchase article

USD  $24.95

Student 1 year subscription

USD  $41.00

1 year subscription

USD  $55.00

Student 2 year subscription

USD  $79.00

2 year subscription

USD  $103.00

Recent neuroimaging research has demonstrated that resting-state intracortical connectivity (i.e., the shared communication between two brain regions) can serve as a robust predictor of motor performance and learning. Theoretically, direct modulation of resting-state intracortical connectivity within the motor system could then improve motor performance and learning. However, previous neuromodulation techniques such as repetitive Transcranial Magnetic Stimulation may be limited in the capacity to modulate targeted intracortical connectivity. Paired Associative Stimulation (PAS) has shown efficacy in facilitating connectivity primarily between the central and peripheral nervous system based on the neuroplasticity mechanism of Spike Timing Dependent Plasticity. It may therefore be plausible for a reconfigured corticocortical PAS paradigm to modulate resting-state intracortical connectivity using a dual stimulator methodology over specific cortical nodes. However, potential theoretical and technological considerations of such a paradigm first need to be addressed prior to application for the purposes of manipulating motor behavior. We posit a corticocortical PAS paradigm used in conjunction with resting-state electroencephalography to demonstrate efficacy of potentiating motor learning associated resting-state intracortical connectivity within the human brain. Here we provide a precise PAS/EEG experimental design, details on data analysis, recommendations for maintaining scientific rigor, and preliminary proof of principle within a single-subject.

The authors are with the Department of Biokinesiology, University of Southern California, Los Angeles, CA.

Hooyman (hooyman@usc.edu) is corresponding author.
  • Anwar, A.R., Muthalib, M., Perrey, S., Galka, A., Granert, O., Wolff, S., . . . Methuraman, M. (2016). Effective connectivity of cortical sensorimotor networks during finger movement tasks: A simultaneous fNIRS, fMRI, EEG study. Brain Topography, 29, 645–660. PubMed ID: 27438589 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bi, G.Q., & Poo, M.M. (1998). Synaptic modifications in cultured hippocampal neurons: Dependence on spike timing, synaptic strength, and postsynaptic cell type. The Journal of Neuroscience, 18(24), 10464–10472. PubMed ID: 31243093 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carter, A.R., Shulman, G.L., & Corbetta, M. (2012). Why use a connectivity-based approach to study stroke and recovery of function? NeuroImage, 62(4), 2271–2280. PubMed ID: 22414990 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Casula, E.P., Pellicciari, M.C., Picazio, S., Caltagirone, C., & Koch, G. (2016). Spike-timing-dependent plasticity in the human dorso-lateral prefrontal cortex. NeuroImage, 143, 204–213. PubMed ID: 27591116 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Civardi, C., Cantello, R., Asselman, P., & Rothwell, J.C. (2001). Transcranial magnetic stimulation can be used to test connections to primary motor areas from frontal and medial cortex in humans. NeuroImage, 14(6), 1444–1453. PubMed ID: 11707100 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delorme, A., & Makeig, S. (2004). EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9–21. PubMed ID: 15102499 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delorme, A., Sejnowski, T., & Makeig, S. (2007). Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. NeuroImage, 34(4), 1443–1449. PubMed ID: 17188898 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Weerth, C., Zijl, R.H., & Buitelaar, J.K. (2003). Development of cortisol circadian rhythm in infancy. Early Human Development, 73(1–2), 39–52. PubMed ID: 12932894 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Farzan, F., Vernet, M., Shafi, M.M.D., Rotenberg, A., Daskalakis, Z.J., & Pascual-Leone, A. (2016). Characterizing and modulating brain circuitry through transcranial magnetic stimulation combined with electroencephalography. Frontiers in Neural Circuits, 10, 73. PubMed ID: 27713691 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gustafsson, F. (1996). Determining the initial states in forward-backward filtering. IEEE Transactions on Signal Processing, 44(4), 988–992. doi:

  • Hallett, M. (2007). Transcranial magnetic stimulation: A primer. Neuron, 55(2), 187–199. PubMed ID: 17640522 doi:

  • Hamada, M., Galea, J.M., Di Lazzaro, V., Mazzone, P., Ziemann, U., & Rothwell, J.C. (2014). Two distinct interneuron circuits in human motor cortex are linked to different subsets of physiological and behavioral plasticity. The Journal of Neuroscience, 34(38), 12837–12849. PubMed ID: 31243093 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hamada, M., Murase, N., Hasan, A., Balaratnam, M., & Rothwell, J.C. (2013). The role of interneuron networks in driving human motor cortical plasticity. Cerebral Cortex, 23(7), 1593–1605. PubMed ID: 22661405 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hardwick, R.M., Lesage, E., Eickhoff, C.R., Clos, M., Fox, P., & Eickhoff, S.B. (2015). Multimodal connectivity of motor learning-related dorsal premotor cortex. NeuroImage, 123, 114–128. PubMed ID: 26282855 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hooyman, A., Babikian, S., Kutch, J., & Winstein, C. (2017, November). Is learning encoded in the resting brain? Poster Presented at American Society of Neurorehabilitation. Baltimore, MD.

    • Search Google Scholar
    • Export Citation
  • Hordacre, B., Rogasch, N.C., & Goldsworthy, M.R. (2016). Commentary: Utility of EEG measures of brain function in patients with acute stroke. Frontiers in Human Neuroscience, 10, 621. PubMed ID: 27994547 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, Y.-Y., Pittenger, C., & Kandel, E.R. (2004). A form of long-lasting, learning-related synaptic plasticity in the hippocampus induced by heterosynaptic low-frequency pairing. Proceedings of the National Academy of Sciences of the United States of America, 101(3), 859–864. PubMed ID: 14711997 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Johnson, J.S., Hamidi, M., & Postle, B.R. (2010). Using EEG to explore how rTMS produces its effects on behavior. Brain Topography, 22(4), 281–293. PubMed ID: 19915972 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klomjai, W., Katz, R., & Lackmy-Vallee, A. (2015). Basic principles of transcranial magnetic stimulation (TMS) and repetitive TMS (rTMS). Annals of Physical and Rehabilitation Medicine, 58(4), 208–213. PubMed ID: 26319963 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lewis, C.M., Baldassarre, A., Committeri, G., Romani, G.L., & Corbetta, M. (2009). Learning sculpts the spontaneous activity of the resting human brain. Proceedings of the National Academy of Sciences, 106(41), 17558–17563. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • López-Alonso, V., Cheeran, B., & Fernández-del-Olmo, M. (2015).Relationship between non-invasive brain stimulation-induced plasticity and capacity for motor learning. Brain Stimulation, 8(6), 1209–1219. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mary, A., Wens, V., Op de Beeck, M., Leproult, R., De Tiège, X., & Peigneux, P. (2017). Age-related differences in practice-dependent resting-state functional connectivity related to motor sequence learning. Human Brain Mapping, 38(2), 923–937. PubMed ID: 27726263 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Muraskin, J., Dodhia, S., Lieberman, G., Garcia, J.O., Verstynen, T., Vettel, J.M., . . . Sajda, P. (2016). Brain dynamics of post-task resting state are influenced by expertise: Insights from baseball players. Human Brain Mapping, 37(12), 4454–4471. PubMed ID: 27448098 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rajji, T.K., Liu, S.-K., Frantseva, M.V., Mulsant, B.H., Thoma, J., Chen, R., . . . Daskalakis, Z.J. (2011). Exploring the effect of inducing long-term potentiation in the human motor cortex on motor learning. Brain Stimulation, 4(3), 137–144. PubMed ID: 21777873 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rajji, T.K., Sun, Y., Zomorrodi-Moghaddam, R., Farzan, F., Blumberger, D.M., Mulsant, B.H., . . . Daskalakis, Z.J. (2013). PAS-induced potentiation of cortical-evoked activity in the dorsolateral prefrontal cortex. Neuropsychopharmacology, 38(12), 2545–2552. PubMed ID: 31247301 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ros, T., & Gruzelier, J.H. (2011). Neurofeedback and neuromodulation techniques and applications. London: Elsevier. doi:

  • Rossi, S., Hallett, M., Rossini, P.M., & Pascual-Leone, A. (2009). Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clinical Neurophysiology, 120(12), 2008–2039. PubMed ID: 19833552 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rossini, P.M., Burke, D., Chen, R., Cohen, L.G., Daskalakis, Z., Di Iorio, R., . . . Ziemann, U. (2015). Non-invasive electrical and magnetic stimulation of the brain, spinal cord, roots and peripheral nerves: Basic principles and procedures for routine clinical and research application: An updated report from an I.F.C.N. Committee. Clinical Neurophysiology, 126(6), 1071–1107. PubMed ID: 25797650 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rothwell, J.C. (2012). Clinical applications of noninvasive electrical stimulation: Problems and potential. Clinical EEG and Neuroscience, 43(3), 209–214. PubMed ID: 22715492 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Srinivasan, R., Winter, W.R., Ding, J., & Nunez, P.L. (2007). EEG and MEG coherence: Measures of functional connectivity at distinct spatial scales of neocortical dynamics. Journal of Neuroscience Methods, 166(1), 41–52. PubMed ID: 17698205 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stefan, K., Kunesch, E., Cohen, L., Benecke, R., & Classen, J. (2000). Induction of plasticity in the human motor cortex by paired associative stimulation. Brain, 123(3), 572–584. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Veniero, D., Ponzo, V., & Koch, G. (2013). Paired associative stimulation enforces the communication between interconnected areas. Journal of Neuroscience, 33(34), 13773–13783. PubMed ID: 23966698 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wiethoff, S., Hamada, M., & Rothwell, J.C. (2014). Variability in response to transcranial direct current stimulation of the motor cortex. Brain Stimulation, 7(3), 468–475. PubMed ID: 24630848 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woźniak-Kwaśniewska, A., Szekely, D., Aussedat, P., Bougerol, T., & David, O. (2014). Changes of oscillatory brain activity induced by repetitive transcranial magnetic stimulation of the left dorsolateral prefrontal cortex in healthy subjects. NeuroImage, 88, 91–99. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, J., Knapp, F., Cramer, S.C., & Srinivasan, R. (2018). Electroencephalographic connectivity measures predict learning of a motor sequencing task. Journal of Neurophysiology, 119(2), 490–498. PubMed ID: 29093171 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, J., Quinlan, E.B., Dodakian, L., McKenzie, A., Kathuria, N., Zhou, R.J., . . . Cramer, S.C. (2015). Connectivity measures are robust biomarkers of cortical function and plasticity after stroke. Brain, 138(8), 2359–2369. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, J., Srinivasan, R., Burke Quinlan, E., Solodkin, A., Small, S.L., & Cramer, S.C. (2016). Utility of EEG measures of brain function in patients with acute stroke. Journal of Neurophysiology, 115(5), 2399–2405. PubMed ID: 26936984 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, J., Srinivasan, R., Kaur, A., & Cramer, S.C. (2014). Resting-state cortical connectivity predicts motor skill acquisition. NeuroImage, 91, 84–90. PubMed ID: 24473097 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 56 56 15
Full Text Views 2 2 0
PDF Downloads 0 0 0