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Neuronal network analysis based on arrival times of active-sleep specific inhibitory postsynaptic potentials in spinal cord motoneurons of the cat.

作者信息

Engelhardt J K, Chase M H

机构信息

Department of Physiology and the Brain Research Institute, UCLA School of Medicine, 90095, Los Angeles, CA, USA.

出版信息

Brain Res. 2001 Jul 20;908(1):75-85. doi: 10.1016/s0006-8993(01)02609-9.

DOI:10.1016/s0006-8993(01)02609-9
PMID:11457433
Abstract

The neuronal network responsible for motoneuron inhibition and loss of muscle tone during active (REM) sleep can be activated by the injection of the cholinergic agonist carbachol into a circumscribed region of the brainstem reticular formation. In the present report, we studied the arrival times of inhibitory postsynaptic potentials (IPSPs) observed in intracellular recordings from cat spinal cord motoneurons. These recordings were obtained during episodes of motor inhibition induced by carbachol or during motor inhibition associated with naturally occurring active sleep. When the observed IPSP arrival times were analyzed as a superposition of renewal processes occurring in a pool of pre-motor inhibitory interneurons, it was possible to estimate the following parameters: (1) the number of independent sources of the IPSPs; (2) the rate at which each source was bombarded with excitatory postsynaptic potentials (EPSPs); and (3) the number of EPSPs required to bring each source to threshold. From the data based upon the preceding parameters and the unusually large amplitudes of the active sleep-specific IPSPs, we suggest that each source is a cluster of synchronously discharging pre-motor inhibitory interneurons. The analysis of IPSP arrival times as a superposition of renewal processes, therefore, provides quantitative information regarding neuronal activity that is as far as two synapses upstream from the site of the recording electrode. Consequently, we suggest that a study of the temporal evolution of these parameters could provide a basis for dynamic analyses of this neuronal network and, in the future, for other neuronal networks as well.

摘要

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