From the accumulated results, we hypothesize that neurons in the central processor systems of the brain generally exhibit a common state-dependency in slow dynamics of their spontaneous activities during sleep. In this paper, activities of relay cells in the cat's lateral geniculate nucleus (LGN) were studied to see if our hypothesis can be applied in this thalamic region. Data segments in polygraphically steady states were strictly extracted in order to sample the activities whose stationarity was guaranteed in a statistical sense. During slow wave sleep (SWS), the discharge pattern was characterized by short bursts. In contrast, the rather tonic discharge pattern was observed to prevail during rapid eye movement (REM) sleep. Spectral analyses showed white noise-like spectra in the low frequency range of 0.04-1.0 Hz during SWS, and 1/f noise-like spectra in the same frequency range during REM sleep. This state-dependency of the slow dynamics was consistently characterized by the other statistical parameters concerning the second-order moment as well. In contrast, the fast dynamics over 1.0 Hz tended to exhibit neuron-specific changes associated with the sleep state in terms of the Markovian dependency analysis. Consequently, our working hypothesis was not rejected for the LGN relay cells. The result here extends the possibility that the state-dependency of the slow dynamics we found is a general rule concerning single neuronal dynamics in widespread areas of the brain during sleep. The state-dependency of the slow dynamics of the LGN relay cells could be understood according to the proposed mechanism that a state-associated alteration in the global biasing input to a neural network during sleep induces the phenomenon with which we are concerned. The slow dynamics of neuronal activities might provide a novel framework defining SWS and REM sleep states instead of the polygraphic characteristics.
|Number of pages||8|
|Journal||Sleep Research Online|
|Publication status||Published - 2000 Dec 1|
ASJC Scopus subject areas
- Neuropsychology and Physiological Psychology