Isoflurane Impairs Low-Frequency Feedback but Leaves High-Frequency Feedforward Connectivity Intact in the Fly Brain

Cohen, Dror; Swinderen, Bruno van; Tsuchiya, Naotsugu

doi:10.1523/eneuro.0329-17.2018

Cited by 27 publications

(49 citation statements)

References 81 publications

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“…To conclude, the spectral decomposition of integrated information we derived provides a new tool for investigating frequency-specific causal influences. This will be particularly useful for systems for which frequency-specific causal influences are masked in the time-domain, as increasingly reported in neural systems [13,14,18,41,42]. In particular, the spectral decomposition of integrated information we presented offers a new angle for empirically investigating the integrated information theory of consciousness [43][44][45][46][47][48][49].…”

Section: Discussionmentioning

confidence: 91%

“…For example, a number of studies have shown that transfer entropy from frontal to parietal brain areas is disconnected during unconsciousness as induced by various general anesthetics [15][16][17]. Recently, we have reported that general anesthesia reduces low-frequency feedback from the center to the periphery of the fly brain, while high-frequency feedforward in the opposite direction remained intact [18].…”

Section: Introductionmentioning

confidence: 99%

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A general spectral decomposition of causal influences applied to integrated information

Cohen

Sasai

Tsuchiya

et al. 2019

Preprint

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Quantifying causal influences between elements of a system remains a central topic in many fields of research. In neuroscience, causal influences among neurons, quantified as integrated information, have been suggested to play a critical role in supporting subjective conscious experience. Recent empirical work has shown that the spectral decomposition of causal influences can reveal frequency-specific influences that are not observed in the time-domain. To date however, a spectral decomposition of integrated information has not been put forward. In this paper, we propose a spectral decomposition of integrated information in linear autoregressive processes. Our proposal is based on a general and flexible framework for deriving the spectral decompositions of causal influences in autoregressive processes. We show that the framework can retrieve the spectral decompositions of other well-known measures such as Granger causality. In simulation, we demonstrate a complex interplay between the spectral decomposition of integrated information and other measures that is not observed in the time-domain. We propose that the spectral decomposition of integrated information will be particularly useful when the underlying frequency-specific causal influences are masked in the time-domain. The proposed method opens the door for empirically investigating the relevance of integrated information to subjective conscious experience in a frequency-specific manner. Author summaryUnderstanding how different parts of the brain influence each other is fundamental to neuroscience. Integrated information measures overall causal influences in the brain and has been theorized to directly relate to subjective consciousness experience. For example, integrated information is predicted to be high during wakefulness and low during sleep or general anesthesia. At the same time, neural activity is characterized by well-known spectral signatures. For example, there is a prominent increase in low frequency power of neural activity during sleep and general anesthesia. Taking account of the spectral characteristics of neural activity, it is important to separately quantify integrated information at each frequency. In this paper, we propose a method for decomposing integrated information in the frequency domain. The proposed framework is general and can be used to derive the spectral decomposition of other well-known measures such as Granger causality. The spectral decomposition of integrated information we

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Section: Discussionmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

A general spectral decomposition of causal influences applied to integrated information

Cohen

Sasai

Tsuchiya

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Drosophila exposed to isoflurane demonstrate an uncoupling of neural activity patterns from movement at lower doses and cessation of movement at higher doses that correlate with local field potential characteristics [155]. More recent work in Drosophila has focused on hierarchical brain organization, assessing the effects of isoflurane anesthesia on higher-order central structures and lower-order peripheral structures [156]. As in mammalian brain systems, there were faster frequencies associated with feedforward directed connectivity (from lower-order to higher-order) and slower frequencies associated with feedback directed connectivity (from higher-order to lower-order).…”

Section: Network Effects Of General Anesthetics Across Speciesmentioning

confidence: 99%

The Biology of General Anesthesia from Paramecium to Primate

Kelz

Mashour

2019

Current Biology

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General anesthesia serves a critically important function in the clinical care of human patients. However, the anesthetized state has foundational implications for biology because anesthetic drugs are effective in organisms ranging from paramecia, to plants, to primates. Although unconsciousness is typically considered the cardinal feature of general anesthesia, this endpoint is only strictly applicable to a select subset of organisms that are susceptible to being anesthetized. We review the behavioral endpoints of general anesthetics across species and propose the isolation of an organism from its environment-both in terms of the afferent arm of sensation and the efferent arm of action-as a generalizable definition. We also consider the various targets and putative mechanisms of general anesthetics across biology and identify key substrates that are conserved, including cytoskeletal elements, ion channels, mitochondria, and functionally coupled electrical or neural activity. We conclude with a unifying framework related to network function and suggest that general anesthetics-from single cells to complex brains-create inefficiency and enhance modularity, leading to the dissociation of functions both within an organism and between the organism and its surroundings. Collectively, we demonstrate that general anesthesia is not restricted to the domain of modern medicine but has broad biological relevance with wide-ranging implications for a diverse array of species.

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“…To construct the IIS, we used local field potentials (LFPs; hereafter referred to as "channels") recorded from the fruit fly brain ( Fig 1A; see Methods; [11]). LFPs were recorded using a linear multi-electrode array, such that the 15 channels covered both peripheral and central regions of the brain.…”

Section: Constructing Integrated Information Structures From Fly Locamentioning

confidence: 99%

“…And third, can estimating the informational structures give us any biological hints as to the "interesting" regions of the brain that correlate with the level of consciousness? We address these questions by analyzing neural recordings from a simple biological system (fruit flies), collected during wakefulness and isoflurane anesthesia [11,21].…”

Section: Introductionmentioning

confidence: 99%

Integrated information structure collapses with anesthetic loss of conscious arousal inDrosophila melanogaster

Leung

Cohen

Swinderen

et al. 2020

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The physical basis of consciousness remains one of the most elusive concepts in current science. One influential conjecture is that consciousness is to do with some form of causality, measurable through information. The integrated information theory of consciousness (IIT) proposes that conscious experience, filled with rich and specific content, corresponds directly to a hierarchically organised, irreducible pattern of causal interactions; i.e. an integrated informational structure among elements of a system. Here, we tested this conjecture in a simple biological system (fruit flies), estimating the information structure of the system during wakefulness and general anesthesia. We found that causal interactions among populations of neurons during wakefulness collapsed to isolated clusters of interactions during anesthesia. We used classification analysis to quantify the accuracy of discrimination between wakeful and anesthetised states, and found that informational structures inferred conscious states with greater accuracy than a scalar summary of the structure, a measure which is generally championed as the main measure of IIT. Spatially, we found that the information structures collapsed rather uniformly across the fly brain. Our results speak to the potential utility of the novel concept of an "informational structure" as a measure for level of consciousness, above and beyond simple scalar values. Author summaryThe physical basis of consciousness remains elusive. Efforts to measure consciousness have generally been restricted to simple, scalar quantities which summarise the complexity of a system, inspired by integrated information theory, which links a multi-dimensional, informational structure to the contents of experience in a system. Due to the complexity of the definition of the structure, assessment of its utility as a measure of conscious arousal in a system has largely been ignored. In this manuscript we evaluate the utility of such an information structure in measuring the level of consciousness in the fruit fly. Our results indicate that this structure can be more informative about the level of consciousness in a system than even the scalar summary proposed by the theory itself. These results may push consciousness research towards the notion of multi-dimensional informational structures, instead of traditional summaries.

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Isoflurane Impairs Low-Frequency Feedback but Leaves High-Frequency Feedforward Connectivity Intact in the Fly Brain

Cited by 27 publications

References 81 publications

A general spectral decomposition of causal influences applied to integrated information

A general spectral decomposition of causal influences applied to integrated information

The Biology of General Anesthesia from Paramecium to Primate

Integrated information structure collapses with anesthetic loss of conscious arousal inDrosophila melanogaster

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