Elsevier

Neuroscience Letters

Volume 387, Issue 3, 28 October 2005, Pages 145-150
Neuroscience Letters

Volatile anesthetics disrupt frontal-posterior recurrent information transfer at gamma frequencies in rat

https://doi.org/10.1016/j.neulet.2005.06.018Get rights and content

Abstract

We seek to understand neural correlates of anesthetic-induced unconsciousness. We hypothesize that cortical integration of sensory information may underlie conscious perception and may be disrupted by anesthetics. A critical role in frontal-posterior interactions has been proposed, and gamma (20–60 Hz) oscillations have also been assigned an essential role in consciousness. Here we investigated whether general anesthetics may interfere with the exchange of information encoded in gamma oscillations between frontal and posterior cortices. Bipolar electrodes for recording of event-related potentials (ERP) were chronically implanted in the primary visual cortex, parietal association and frontal association cortices of six rats. Sixty light flashes were presented every 5 s, and ERPs were recorded at increasing concentrations of halothane or isoflurane (0–2%). Information exchange was estimated by transfer entropy, a novel measure of directional information transfer. Transfer entropy was calculated from 1-s wavelet-transformed ERPs. We found that (1) feedforward transfer entropy (FF-TE) and feedback transfer entropy (FB-TE) were balanced in conscious-sedated state; (2) anesthetics at concentrations producing unconsciousness augmented both FF-TE and FB-TE at 30 Hz but reduced them at 50 Hz; (3) reduction at 50 Hz was more pronounced for FB-TE, especially between frontal and posterior regions; (4) at high concentrations, both FF-TE and FB-TE at all frequencies were at or below conscious-sedated baseline. Our findings suggest that inhalational anesthetics preferentially impair frontal-posterior FB information transfer at high gamma frequencies consistent with the postulated role of frontal-posterior interactions in consciousness.

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Acknowledgements

This publication is based on work supported by grants from the NIH (GM-56398), and from the NSF (BES-0002945), and by predoctoral GAANN fellowship from the Department of Education. We thank Richard Rys (Senior Research Engineer) for the design and construction of electronic equipment, and Samhita S. Rhodes, Ph.D. for the implementation of the peak-detection algorithm.

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