Behavioral and cortical arousal from sleep, muscimol-induced coma, and anesthesia by direct optogenetic stimulation of cortical neurons.

The cerebral cortex is widely considered part of the neural substrate of consciousness, but direct causal evidence is missing. Here, we tested in mice whether optogenetic activation of cortical neurons in posterior parietal cortex (PtA) or medial prefrontal cortex (mPFC) is sufficient for arousal from three behavioral states characterized by progressively deeper unresponsiveness: sleep, a coma-like state induced by muscimol injection in the midbrain, and deep sevoflurane-dexmedetomidine anesthesia. We find that cortical stimulation always awakens the mice from both NREM sleep and REM sleep, with PtA requiring weaker/shorter light pulses than mPFC. Moreover, in most cases light pulses produce both cortical activation (decrease in low frequencies) and behavioral arousal (recovery of the righting reflex) from brainstem coma, as well as cortical activation from anesthesia. These findings provide evidence that direct activation of cortical neurons is sufficient for behavioral and/or cortical arousal from sleep, brainstem coma, and anesthesia.

Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms.

This paper presents Integrated Information Theory (IIT) 4.0. IIT aims to account for the properties of experience in physical (operational) terms. It identifies the essential properties of experience (axioms), infers the necessary and sufficient properties that its substrate must satisfy (postulates), and expresses them in mathematical terms. In principle, the postulates can be applied to any system of units in a state to determine whether it is conscious, to what degree, and in what way. IIT offers a parsimonious explanation of empirical evidence, makes testable predictions concerning both the presence and the quality of experience, and permits inferences and extrapolations. IIT 4.0 incorporates several developments of the past ten years, including a more accurate formulation of the axioms as postulates and mathematical expressions, the introduction of a unique measure of intrinsic information that is consistent with the postulates, and an explicit assessment of causal relations. By fully unfolding a system's irreducible cause-effect power, the distinctions and relations specified by a substrate can account for the quality of experience.

Sleep/wake changes in perturbational complexity in rats and mice.

In humans, the level of consciousness is assessed by quantifying the spatiotemporal complexity of cortical responses using Perturbational Complexity Index (PCI) and related PCIst (st, state transitions). Here we validate PCIst in freely moving rats and mice by showing that it is lower in NREM sleep and slow wave anesthesia than in wake or REM sleep, as in humans. We then show that (1) low PCIst is associated with the occurrence of an OFF period of neuronal silence; (2) stimulation of deep, but not superficial, cortical layers leads to reliable PCIst changes across sleep/wake and anesthesia; (3) consistent PCIst changes are independent of which single area is being stimulated or recorded, except for recordings in mouse prefrontal cortex. These experiments show that PCIst can reliably measure vigilance states in unresponsive animals and support the hypothesis that it is low when an OFF period disrupts causal interactions in cortical networks.

System Integrated Information.

Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of consciousness (called a complex), which are then used to formulate a mathematical framework for assessing both the quality and quantity of experience. The explanatory identity proposed by IIT is that an experience is identical to the cause-effect structure unfolded from a maximally irreducible substrate (a Φ-structure). In this work we introduce a definition for the integrated information of a system (φs) that is based on the existence, intrinsicality, information, and integration postulates of IIT. We explore how notions of determinism, degeneracy, and fault lines in the connectivity impact system-integrated information. We then demonstrate how the proposed measure identifies complexes as systems, the φs of which is greater than the φs of any overlapping candidate systems.

Local Sleep Slow-Wave Activity Colocalizes With the Ictal Symptomatogenic Zone in a Patient With Reflex Epilepsy: A High-Density EEG Study.

Background: Slow-wave activity (SWA) during non-rapid eye movement (NREM) sleep reflects synaptic potentiation during preceding wakefulness. Epileptic activity may induce increases in state-dependent SWA in human brains, therefore, localization of SWA may prove useful in the presurgical workup of epileptic patients. We analyzed high-density electroencephalography (HDEEG) data across vigilance states from a reflex epilepsy patient with a clearly localizable ictal symptomatogenic zone to provide a proof-of-concept for the testability of this hypothesis. Methods: Overnight HDEEG recordings were obtained in the patient during REM sleep, NREM sleep, wakefulness, and during a right facial motor seizure then compared to 10 controls. After preprocessing, SWA (i.e., delta power; 1-4 Hz) was calculated at each channel. Scalp level and source reconstruction analyses were computed. We assessed for statistical differences in maximum SWA between the patient and controls within REM sleep, NREM sleep, wakefulness, and seizure. Then, we completed an identical statistical comparison after first subtracting intrasubject REM sleep SWA from that of NREM sleep, wakefulness, and seizure SWA. Results: The topographical analysis revealed greater left hemispheric SWA in the patient vs. controls in all vigilance states except REM sleep (which showed a right hemispheric maximum). Source space analysis revealed increased SWA in the left inferior frontal cortex during NREM sleep and wakefulness. Ictal data displayed poor source-space localization. Comparing each state to REM sleep enhanced localization accuracy; the most clearly localizing results were observed when subtracting REM sleep from wakefulness. Conclusion: State-dependent SWA during NREM sleep and wakefulness may help to identify aspects of the potential epileptogenic zone. Future work in larger cohorts may assess the clinical value of sleep SWA to help presurgical planning.

Quantitative spatio-temporal characterization of epileptic spikes using high density EEG: Differences between NREM sleep and REM sleep.

In this study, we applied high-density EEG recordings (HD-EEG) to quantitatively characterize the fine-grained spatiotemporal distribution of inter-ictal epileptiform discharges (IEDs) across different sleep stages. We quantified differences in spatial extent and duration of IEDs at the scalp and cortical levels using HD-EEG source-localization, during non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep, in six medication-refractory focal epilepsy patients during epilepsy monitoring unit admission. Statistical analyses were performed at single subject level and group level across different sleep stages for duration and distribution of IEDs. Tests were corrected for multiple comparisons across all channels and time points. Compared to NREM sleep, IEDs during REM sleep were of significantly shorter duration and spatially more restricted. Compared to NREM sleep, IEDs location in REM sleep also showed a higher concordance with electrographic ictal onset zone from scalp EEG recording. This study supports the localizing value of REM IEDs over NREM IEDs and suggests that HD-EEG may be of clinical utility in epilepsy surgery work-up.

The evolving view of replay and its functions in wake and sleep.

The term hippocampal replay originally referred to the temporally compressed reinstantiation, during rest, of sequential neural activity observed during prior active wake. Since its description in the 1990s, hippocampal replay has often been viewed as the key mechanism by which a memory trace is repeatedly rehearsed at high speeds during sleep and gradually transferred to neocortical circuits. However, the methods used to measure the occurrence of replay remain debated, and it is now clear that the underlying neural events are considerably more complicated than the traditional narratives had suggested. "Replay-like" activity happens during wake, can play out in reverse order, may represent trajectories never taken by the animal, and may have additional functions beyond memory consolidation, from learning values and solving the problem of credit assignment to decision-making and planning. Still, we know little about the role of replay in cognition, and to what extent it differs between wake and sleep. This may soon change, however, because decades-long efforts to explain replay in terms of reinforcement learning (RL) have started to yield testable predictions and possible explanations for a diverse set of observations. Here, we (1) survey the diverse features of replay, focusing especially on the latest findings; (2) discuss recent attempts at unifying disparate experimental results and putatively different cognitive functions under the banner of RL; (3) discuss methodological issues and theoretical biases that impede progress or may warrant a partial revaluation of the current literature, and finally; (4) highlight areas of considerable uncertainty and promising avenues of inquiry.

PyPhi: A toolbox for integrated information theory.

Integrated information theory provides a mathematical framework to fully characterize the cause-effect structure of a physical system. Here, we introduce PyPhi, a Python software package that implements this framework for causal analysis and unfolds the full cause-effect structure of discrete dynamical systems of binary elements. The software allows users to easily study these structures, serves as an up-to-date reference implementation of the formalisms of integrated information theory, and has been applied in research on complexity, emergence, and certain biological questions. We first provide an overview of the main algorithm and demonstrate PyPhi's functionality in the course of analyzing an example system, and then describe details of the algorithm's design and implementation. PyPhi can be installed with Python's package manager via the command 'pip install pyphi' on Linux and macOS systems equipped with Python 3.4 or higher. PyPhi is open-source and licensed under the GPLv3; the source code is hosted on GitHub at https://github.com/wmayner/pyphi. Comprehensive and continually-updated documentation is available at https://pyphi.readthedocs.io. The pyphi-users mailing list can be joined at https://groups.google.com/forum/#!forum/pyphi-users. A web-based graphical interface to the software is available at http://integratedinformationtheory.org/calculate.html.

Altered sleep homeostasis correlates with cognitive impairment in patients with focal epilepsy.

In animal studies, both seizures and interictal spikes induce synaptic potentiation. Recent evidence suggests that electroencephalogram slow wave activity during sleep reflects synaptic potentiation during wake, and that its homeostatic decrease during the night is associated with synaptic renormalization and its beneficial effects. Here we asked whether epileptic activity induces plastic changes that can be revealed by high-density electroencephalography recordings during sleep in 15 patients with focal epilepsy and 15 control subjects. Compared to controls, patients with epilepsy displayed increased slow wave activity power during non-rapid eye movement sleep over widespread, bilateral scalp regions. This global increase in slow wave activity power was positively correlated with the frequency of secondarily generalized seizures in the 3-5 days preceding the recordings. Individual patients also showed local increases in sleep slow wave activity power at scalp locations matching their seizure focus. This local increase in slow wave activity power was positively correlated with the frequency of interictal spikes during the last hour of wakefulness preceding sleep. By contrast, frequent interictal spikes during non-rapid eye movement sleep predicted a reduced homeostatic decrease in the slope of sleep slow waves during the night, which in turn predicted reduced daytime learning. Patients also showed an increase in sleep spindle power, which was negatively correlated with intelligence quotient. Altogether, these findings suggest that both seizures and interictal spikes may induce long-lasting changes in the human brain that can be sensitively detected by electroencephalographic markers of sleep homeostasis. Furthermore, abnormalities in sleep markers are correlated with cognitive impairment, suggesting that not only seizures, but also interictal spikes can have negative consequences.