The Cortical Topography of Local Sleep

Michael      Murphy; Reto      Huber; Steve      Esser; Brady      A. Riedner; Marcello      Massimini; Fabio      Ferrarelli; M.      Felice Ghilardi; Giulio      Tononi

doi:10.2174/156802611797470303

Abstract

In a recent series of experiments, we demonstrated that a visuomotor adaptation task, 12 hours of left arm immobilization, and rapid transcranial magnetic stimulation (rTMS) during waking can each induce local changes in the topography of electroencephalographic (EEG) slow wave activity (SWA) during subsequent non-rapid eye movement (NREM) sleep. However, the poor spatial resolution of EEG and the difficulty of relating scalp potentials to the activity of the underlying cortex limited the interpretation of these results. In order to better understand local cortical regulation of sleep, we used source modeling to show that plastic changes in specific cortical areas during waking produce correlated changes in SWA during sleep in those same areas. We found that implicit learning of a visuomotor adaptation task induced an increase in SWA in right premotor and sensorimotor cortices when compared to a motor control. These same areas have previously been shown to be selectively involved in the performance of this task. We also found that arm immobilization resulted in a decrease in SWA in sensorimotor cortex. Inducing cortical potentiation with repetitive transcranial magnetic stimulation (rTMS) caused an increase in SWA in the targeted area and a decrease in SWA in the contralateral cortex. Finally, we report the first evidence that these modulations in SWA may be related to the dynamics of individual slow waves. We conclude that there is a local, plasticity dependent component to sleep regulation and confirm previous inferences made from the scalp data.

Keywords: Local sleep, slow waves, EEG, source modeling, SWA, plastic changes, rapid transcranial magnetic stimulation (rTMS), electroencephalographic (EEG), visuomotor adaptation, sensorimotor cortex, cortical potentiation, scalp data, mechanisms responsible, hypothesis