Stimulus-induced change in long-range temporal correlations and scaling behaviour of sensorimotor oscillations

Klaus Linkenkaer-Hansen*, Vadim V. Nikulin, J. Matias Palva, Kai Kaila, Risto J. Ilmoniemi

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

100 Citations (Scopus)


The human brain spontaneously generates large-scale network oscillations at around 10 and 20 Hz. The amplitude envelope of these oscillations fluctuates intermittently and was recently reported to exhibit power-law decay of the autocorrelation for hundreds of seconds. This indicates that the underlying networks are in a dynamic state resembling the self-organized critical state known to exist in many complex systems. Based on the mechanism of how correlations emerge in these systems, we hypothesized that the physiological basis of long-range power-law correlations is the buildup of a memory of past activity by a continuous modification of the network's functional connectivity by the ongoing oscillations. In this framework, exogenous perturbations of ongoing oscillations would degrade or abolish this dynamic network memory. We investigated the sensitivity of the temporal correlations in sensorimotor 10- and 20-Hz oscillations to median nerve stimulation that is known to have immediate effects on ongoing oscillations. Our results show that the amplitude fluctuations of these oscillations were effectively modulated by the somatosensory stimuli but still exhibited long-range temporal correlations and power-law scaling behaviour. The magnitude of the temporal correlations was, however, attenuated and the power-law exponents were decreased. This implies that the stimuli indeed degraded the network's memory of its past.

Original languageEnglish
Pages (from-to)203-218
Number of pages16
JournalEuropean Journal of Neuroscience
Issue number1
Publication statusPublished - 1 Jan 2004
MoE publication typeA1 Journal article-refereed


  • Electroencephalography
  • Human
  • Magnetoencephalography
  • Memory
  • Neuronal dynamics
  • Scaling behaviour


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