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      Sleep Neuroimaging and Models of Consciousness

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          Abstract

          Human deep sleep is characterized by reduced sensory activity, responsiveness to stimuli, and conscious awareness. Given its ubiquity and reversible nature, it represents an attractive paradigm to study the neural changes which accompany the loss of consciousness in humans. In particular, the deepest stages of sleep can serve as an empirical test for the predictions of theoretical models relating the phenomenology of consciousness with underlying neural activity. A relatively recent shift of attention from the analysis of evoked responses toward spontaneous (or “resting state”) activity has taken place in the neuroimaging community, together with the development of tools suitable to study distributed functional interactions. In this review we focus on recent functional Magnetic Resonance Imaging (fMRI) studies of spontaneous activity during sleep and their relationship with theoretical models for human consciousness generation, considering the global workspace theory, the information integration theory, and the dynamical core hypothesis. We discuss the venues of research opened by these results, emphasizing the need to extend the analytic methodology in order to obtain a dynamical picture of how functional interactions change over time and how their evolution is modulated during different conscious states. Finally, we discuss the need to experimentally establish absent or reduced conscious content, even when studying the deepest sleep stages.

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          Breakdown of cortical effective connectivity during sleep.

          When we fall asleep, consciousness fades yet the brain remains active. Why is this so? To investigate whether changes in cortical information transmission play a role, we used transcranial magnetic stimulation together with high-density electroencephalography and asked how the activation of one cortical area (the premotor area) is transmitted to the rest of the brain. During quiet wakefulness, an initial response (approximately 15 milliseconds) at the stimulation site was followed by a sequence of waves that moved to connected cortical areas several centimeters away. During non-rapid eye movement sleep, the initial response was stronger but was rapidly extinguished and did not propagate beyond the stimulation site. Thus, the fading of consciousness during certain stages of sleep may be related to a breakdown in cortical effective connectivity.
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            BOLD correlates of EEG topography reveal rapid resting-state network dynamics.

            Resting-state functional connectivity studies with fMRI showed that the brain is intrinsically organized into large-scale functional networks for which the hemodynamic signature is stable for about 10s. Spatial analyses of the topography of the spontaneous EEG also show discrete epochs of stable global brain states (so-called microstates), but they remain quasi-stationary for only about 100 ms. In order to test the relationship between the rapidly fluctuating EEG-defined microstates and the slowly oscillating fMRI-defined resting states, we recorded 64-channel EEG in the scanner while subjects were at rest with their eyes closed. Conventional EEG-microstate analysis determined the typical four EEG topographies that dominated across all subjects. The convolution of the time course of these maps with the hemodynamic response function allowed to fit a linear model to the fMRI BOLD responses and revealed four distinct distributed networks. These networks were spatially correlated with four of the resting-state networks (RSNs) that were found by the conventional fMRI group-level independent component analysis (ICA). These RSNs have previously been attributed to phonological processing, visual imagery, attention reorientation, and subjective interoceptive-autonomic processing. We found no EEG-correlate of the default mode network. Thus, the four typical microstates of the spontaneous EEG seem to represent the neurophysiological correlate of four of the RSNs and show that they are fluctuating much more rapidly than fMRI alone suggests. Copyright 2010 Elsevier Inc. All rights reserved.
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              An information integration theory of consciousness

              Background Consciousness poses two main problems. The first is understanding the conditions that determine to what extent a system has conscious experience. For instance, why is our consciousness generated by certain parts of our brain, such as the thalamocortical system, and not by other parts, such as the cerebellum? And why are we conscious during wakefulness and much less so during dreamless sleep? The second problem is understanding the conditions that determine what kind of consciousness a system has. For example, why do specific parts of the brain contribute specific qualities to our conscious experience, such as vision and audition? Presentation of the hypothesis This paper presents a theory about what consciousness is and how it can be measured. According to the theory, consciousness corresponds to the capacity of a system to integrate information. This claim is motivated by two key phenomenological properties of consciousness: differentiation – the availability of a very large number of conscious experiences; and integration – the unity of each such experience. The theory states that the quantity of consciousness available to a system can be measured as the Φ value of a complex of elements. Φ is the amount of causally effective information that can be integrated across the informational weakest link of a subset of elements. A complex is a subset of elements with Φ>0 that is not part of a subset of higher Φ. The theory also claims that the quality of consciousness is determined by the informational relationships among the elements of a complex, which are specified by the values of effective information among them. Finally, each particular conscious experience is specified by the value, at any given time, of the variables mediating informational interactions among the elements of a complex. Testing the hypothesis The information integration theory accounts, in a principled manner, for several neurobiological observations concerning consciousness. As shown here, these include the association of consciousness with certain neural systems rather than with others; the fact that neural processes underlying consciousness can influence or be influenced by neural processes that remain unconscious; the reduction of consciousness during dreamless sleep and generalized seizures; and the time requirements on neural interactions that support consciousness. Implications of the hypothesis The theory entails that consciousness is a fundamental quantity, that it is graded, that it is present in infants and animals, and that it should be possible to build conscious artifacts.
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                Author and article information

                Journal
                Front Psychol
                Front Psychol
                Front. Psychol.
                Frontiers in Psychology
                Frontiers Media S.A.
                1664-1078
                13 May 2013
                2013
                : 4
                : 256
                Affiliations
                [1] 1Neurology Department and Brain Imaging Center, Goethe University Frankfurt Frankfurt am Main, Germany
                [2] 2Department of Neurology, Schleswig Holstein University Hospital Kiel, Germany
                Author notes

                Edited by: Ursula Voss, Rheinische Friedrich-Wilhelms University Bonn, Germany

                Reviewed by: Daniel Collerton, Northumberland, Tyne and Wear NHS Foundation Trust, UK; Ursula Voss, Rheinische Friedrich-Wilhelms University Bonn, Germany

                *Correspondence: Enzo Tagliazucchi, Neurology Department and Brain Imaging Center, Goethe University Frankfurt, Schleusenweg 2 – 16, Haus 95 H, D – 60528 Frankfurt am Main, Germany. e-mail: nztglzcch@ 123456gmail.com

                This article was submitted to Frontiers in Consciousness Research, a specialty of Frontiers in Psychology.

                Article
                10.3389/fpsyg.2013.00256
                3651967
                23717291
                f08f5f34-c882-4241-ba4e-76bf90045ec3
                Copyright © 2013 Tagliazucchi, Behrens and Laufs.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 31 March 2013
                : 17 April 2013
                Page count
                Figures: 4, Tables: 0, Equations: 0, References: 75, Pages: 9, Words: 7526
                Categories
                Psychology
                Review Article

                Clinical Psychology & Psychiatry
                consciousness,sleep,fmri,eeg,resting state
                Clinical Psychology & Psychiatry
                consciousness, sleep, fmri, eeg, resting state

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