PMID: 3751302May 1, 1986Paper

Spectral-correlation characteristics of the electrical activity of the brain of the rabbit in a state of calm wakefulness

Zhurnal vyssheĭ nervnoĭ deiatelnosti imeni I P Pavlova
E V Rusinova, G Ia Drozdovska

Abstract

Inter- and intrahemispheric relations of electrical activity of the pre-motor, sensorimotor (representation of forelimb and blinking) and visual zones of rabbit's cerebral cortex in calm alertness was studied by method of spectral-correlative analysis. Mean coherence levels of the EEG of tested hemispheric symmetric points and symmetric pairs of leads in the left and right hemispheres were characterized by a high temporal stability in the state of calm alertness and during sensory stimulation. A comparison of mean coherence values of EEG in symmetric leads, revealed a tendency to left-side dominance of statistical bonds of electrical processes. A tendency was shown towards interhemispheric asymmetry by mean parameters of EEG power spectra: the left hemisphere of the rabbit is characterized by a lower mean frequency of electrical activity and a more narrow effective frequency of the spectrum.

Related Concepts

Related Feeds

Barrel cortex

Here is the latest research on barrel cortex, a region of somatosensory and motor corticies in the brain, which are used by animals that rely on whiskers for world exploration.

Auditory Perception

Auditory perception is the ability to receive and interpret information attained by the ears. Here is the latest research on factors and underlying mechanisms that influence auditory perception.

Related Papers

Zhurnal vyssheĭ nervnoĭ deiatelnosti imeni I P Pavlova
E V Rusinova
Zhurnal vyssheĭ nervnoĭ deiatelnosti imeni I P Pavlova
G N Boldyreva, L A Zhavoronkova
Zhurnal vyssheĭ nervnoĭ deiatelnosti imeni I P Pavlova
E V Rusinova, G Ia Roshchina
Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology
M P DaveyN D Schiff
Zhurnal vyssheĭ nervnoĭ deiatelnosti imeni I P Pavlova
EfremovaTMI R Rezvova
© 2021 Meta ULC. All rights reserved