Breakdown of local information processing may underlie isoflurane anesthesia effects

Abstract

The disruption of coupling between brain areas has been suggested as the mechanism underlying loss of consciousness in anesthesia. This hypothesis has been tested previously by measuring the information transfer between brain areas, and by taking reduced information transfer as a proxy for decoupling. Yet, information transfer is a function of the amount of information available in the information source-such that transfer decreases even for unchanged coupling when less source information is available. Therefore, we asked whether impaired local information processing leads to a loss of information transfer. An important prediction of this alternative hypothesis is that changes in locally available information (signal entropy) should be at least as pronounced as changes in information transfer. We tested this prediction by recording local field potentials in two ferrets after administration of isoflurane in concentrations of 0.0 %, 0.5 %, and 1.0 %. We found strong decreases in the source entropy under isoflurane in area V1 and the prefrontal cortex (PFC)-as predicted by our alternative hypothesis. The decrease in source entropy was stronger in PFC. Information transfer between V1 and PFC was reduced bidirectionally, but with a stronger decrease from PFC to V1. This links the stronger decrease in information transfer to the stronger decrease in source entropy, suggesting reduced source entropy reduces information transfer. This conclusion fits the observation that the synaptic targets of isoflurane are located in local cortical circuits rather than on the synapses formed by interareal axonal projections. Thus, changes in information transfer under isoflurane seem to be a consequence of changes in local processing more than of decoupling between brain areas. We suggest that source entropy changes must be considered whenever interpreting changes in information transfer as decoupling.

48 pages, 11 Figures

References in corpus (10)

• Measuring Information Transfer
• Estimating Mutual Information
• JIDT: An information-theoretic toolkit for studying the dynamics of complex systems
• Entropy and information in neural spike trains: Progress on the sampling problem
• Differentiating information transfer and causal effect
• Efficient transfer entropy analysis of non-stationary neural time series
• Bits from Biology for Computational Intelligence
• Transfer entropy in continuous time, with applications to jump and neural spiking processes
• Generalized Measures of Information Transfer
• Szemerédi's regularity lemma revisited

Cited by in corpus (4)

• Multiscale Information Decomposition: Exact Computation for Multivariate Gaussian Processes
• Information estimation using nonparametric copulas
• Quantifying the predictability of visual scanpaths using active information storage
• Consciousness as a physical process caused by the organization of energy in the brain