Search bioRxivSearch

Biology subjects

Achermann, P.

Publications and source records attributed to Achermann, P..

2 recordsLinked to original sources

From thoughtless awareness to effortful cognition: alpha - theta cross-frequency dynamics in experienced meditators during meditation, rest and arithmetic

Neural activity is known to oscillate within discrete frequency bands and the synchronization between these rhythms is hypothesized to underlie information integration in the brain. Since strict synchronization is only possible for harmonic frequencies, a recent theory proposes that the interaction between different brain rhythms is facilitated by transient harmonic frequency arrangements. In this line, it has been recently shown that the transient occurrence of 2:1 harmonic cross-frequency relationships between alpha and theta rhythms (i.e. falpha{approx}12 Hz; ftheta{approx}6 Hz) is enhanced during effortful cognition. In this study, we tested whether achieving a state of mental emptiness during meditation is accompanied by a relative decrease in the occurrence of 2:1 harmonic cross-frequency relationships between alpha and theta rhythms. Continuous EEG recordings (19 electrodes) were obtained from 43 highly experienced meditators during meditation practice, rest and an arithmetic task. We show that the occurrence of transient alpha:theta 2:1 harmonic relationships increased linearly from a meditative to an active cognitive processing state (i.e. meditation< rest< arithmetic task). It is argued that transient EEG cross-frequency arrangements that prevent alpha:theta cross-frequency coupling could facilitate the experience of mental emptiness by avoiding the interaction between the memory and executive components of cognition.

neuroscience

Cortical neuronal activity determines the dynamics of local sleep homeostasis

The homeostatic regulation of sleep manifests as a relative constancy of its daily amount and intensity. Theoretical descriptions of this phenomenon define "Process S", a variable with dynamics dependent only on sleep-wake history, whose levels are reflected in electroencephalogram (EEG) slow wave activity (0.5 - 4 Hz) during sleep. Here we developed novel mathematical models of Process S in mice, assuming that its dynamics are a function of the deviation of cortical neuronal firing rates from a locally defined set-point, crucially without explicit knowledge of sleep-wake state. Our results suggest that Process S tracks global sleep-wake history through an integration of local cortical neuronal activity levels over time. We posit that, instead of reflecting sleep-wake-dependent changes in specific variables and serving their homeostatic regulation, Process S may be a time-keeping mechanism which enables individuals to obtain a species-specific and ecologically-relevant quantity of sleep, even in the absence of external temporal information.

neuroscience