Upper bounds for integrated information.

Originally developed as a theory of consciousness, integrated information theory provides a mathematical framework to quantify the causal irreducibility of systems and subsets of units in the system. Specifically, mechanism integrated information quantifies how much of the causal powers of a subset of units in a state, also referred to as a mechanism, cannot be accounted for by its parts. If the causal powers of the mechanism can be fully explained by its parts, it is reducible and its integrated information is zero. Here, we study the upper bound of this measure and how it is achieved. We study mechanisms in isolation, groups of mechanisms, and groups of causal relations among mechanisms. We put forward new theoretical results that show mechanisms that share parts with each other cannot all achieve their maximum. We also introduce techniques to design systems that can maximize the integrated information of a subset of their mechanisms or relations. Our results can potentially be used to exploit the symmetries and constraints to reduce the computations significantly and to compare different connectivity profiles in terms of their maximal achievable integrated information.

Effects of non-rapid eye movement sleep on the cortical synaptic expression of GluA1-containing AMPA receptors.

Converging electrophysiological, molecular and ultrastructural evidence supports the hypothesis that sleep promotes a net decrease in excitatory synaptic strength, counteracting the net synaptic potentiation caused by ongoing learning during waking. However, several outstanding questions about sleep-dependent synaptic weakening remain. Here, we address some of these questions by using two established molecular markers of synaptic strength, the levels of the AMPA (alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptors containing the GluA1 subunit and the phosphorylation of GluA1 at serine 845 (p-GluA1(845)). We previously found that, in the rat cortex and hippocampus, these markers are lower after 6-8 h of sleep than after the same time spent awake. Here, we measure GluA1 and p-GluA1(845) levels in synaptosomes of mouse cortex after 5 h of either sleep, sleep deprivation, recovery sleep after sleep deprivation or selective REM sleep deprivation (32 C57BL/B6 adult mice, 16 females). We find that relative to after sleep deprivation, these synaptic markers are lower after sleep independent of whether the mice were allowed to enter REM sleep. Moreover, 5 h of recovery sleep following acute sleep deprivation is enough to renormalize their expression. Thus, the renormalization of GluA1 and p-GluA1(845) expression crucially relies on NREM sleep and can occur in a few hours of sleep after acute sleep deprivation.

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.

Consciousness and sleep.

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

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.

TMS-EEG and resting-state EEG applied to altered states of consciousness: oscillations, complexity, and phenomenology.

Exploring the neurobiology of the profound changes in consciousness induced by classical psychedelic drugs may require novel neuroimaging methods. Serotonergic psychedelic drugs such as psilocybin produce states of increased sensory-emotional awareness and arousal, accompanied by increased spontaneous electroencephalographic (EEG) signal diversity. By directly stimulating cortical tissue, the altered dynamics and propagation of the evoked EEG activity can reveal drug-induced changes in the overall brain state. We combine Transcranial Magnetic Stimulation (TMS) and EEG to reveal that psilocybin produces a state of increased chaotic brain activity which is not a result of altered complexity in the underlying causal interactions between brain regions. We also map the regional effects of psilocybin on TMS-evoked activity and identify changes in frontal brain structures that may be associated with the phenomenology of psychedelic experiences.

Origin, synchronization, and propagation of sleep slow waves in children.

STUDY OBJECTIVES: Sleep slow wave activity, as measured using EEG delta power (<4 Hz), undergoes significant changes throughout development, mirroring changes in brain function and anatomy. Yet, age-dependent variations in the characteristics of individual slow waves have not been thoroughly investigated. Here we aimed at characterizing individual slow wave properties such as origin, synchronization, and cortical propagation at the transition between childhood and adulthood. METHODS: We analyzed overnight high-density (256 electrodes) EEG recordings of healthy typically developing children (N = 21, 10.3 ± 1.5 years old) and young healthy adults (N = 18, 31.1 ± 4.4 years old). All recordings were preprocessed to reduce artifacts, and NREM slow waves were detected and characterized using validated algorithms. The threshold for statistical significance was set at p = 0.05. RESULTS: The slow waves of children were larger and steeper, but less widespread than those of adults. Moreover, they tended to mainly originate from and spread over more posterior brain areas. Relative to those of adults, the slow waves of children also displayed a tendency to more strongly involve and originate from the right than the left hemisphere. The separate analysis of slow waves characterized by high and low synchronization efficiency showed that these waves undergo partially distinct maturation patterns, consistent with their possible dependence on different generation and synchronization mechanisms. CONCLUSIONS: Changes in slow wave origin, synchronization, and propagation at the transition between childhood and adulthood are consistent with known modifications in cortico-cortical and subcortico-cortical brain connectivity. In this light, changes in slow-wave properties may provide a valuable yardstick to assess, track, and interpret physiological and pathological development.

Measuring Consciousness in the Intensive Care Unit.

Early reemergence of consciousness predicts long-term functional recovery for patients with severe brain injury. However, tools to reliably detect consciousness in the intensive care unit are lacking. Transcranial magnetic stimulation electroencephalography has the potential to detect consciousness in the intensive care unit, predict recovery, and prevent premature withdrawal of life-sustaining therapy.

A survey of neurophysiological differentiation across mouse visual brain areas and timescales.

Neurophysiological differentiation (ND), a measure of the number of distinct activity states that a neural population visits over a time interval, has been used as a correlate of meaningfulness or subjective perception of visual stimuli. ND has largely been studied in non-invasive human whole-brain recordings where spatial resolution is limited. However, it is likely that perception is supported by discrete neuronal populations rather than the whole brain. Therefore, here we use Neuropixels recordings from the mouse brain to characterize the ND metric across a wide range of temporal scales, within neural populations recorded at single-cell resolution in localized regions. Using the spiking activity of thousands of simultaneously recorded neurons spanning 6 visual cortical areas and the visual thalamus, we show that the ND of stimulus-evoked activity of the entire visual cortex is higher for naturalistic stimuli relative to artificial ones. This finding holds in most individual areas throughout the visual hierarchy. Moreover, for animals performing an image change detection task, ND of the entire visual cortex (though not individual areas) is higher for successful detection compared to failed trials, consistent with the assumed perception of the stimulus. Together, these results suggest that ND computed on cellular-level neural recordings is a useful tool highlighting cell populations that may be involved in subjective perception.

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.

An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory.

The relationship between conscious experience and brain activity has intrigued scientists and philosophers for centuries. In the last decades, several theories have suggested different accounts for these relationships. These theories have developed in parallel, with little to no cross-talk among them. To advance research on consciousness, we established an adversarial collaboration between proponents of two of the major theories in the field, Global Neuronal Workspace and Integrated Information Theory. Together, we devised and preregistered two experiments that test contrasting predictions of these theories concerning the location and timing of correlates of visual consciousness, which have been endorsed by the theories' proponents. Predicted outcomes should either support, refute, or challenge these theories. Six theory-impartial laboratories will follow the study protocol specified here, using three complementary methods: Functional Magnetic Resonance Imaging (fMRI), Magneto-Electroencephalography (M-EEG), and intracranial electroencephalography (iEEG). The study protocol will include built-in replications, both between labs and within datasets. Through this ambitious undertaking, we hope to provide decisive evidence in favor or against the two theories and clarify the footprints of conscious visual perception in the human brain, while also providing an innovative model of large-scale, collaborative, and open science practice.

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.

Distinct signatures of loss of consciousness in focal impaired awareness versus tonic-clonic seizures.

Loss of consciousness is a hallmark of many epileptic seizures and carries risks of serious injury and sudden death. While cortical sleep-like activities accompany loss of consciousness during focal impaired awareness seizures, the mechanisms of loss of consciousness during focal to bilateral tonic-clonic seizures remain unclear. Quantifying differences in markers of cortical activation and ictal recruitment between focal impaired awareness and focal to bilateral tonic-clonic seizures may also help us to understand their different consequences for clinical outcomes and to optimize neuromodulation therapies. We quantified clinical signs of loss of consciousness and intracranial EEG activity during 129 focal impaired awareness and 50 focal to bilateral tonic-clonic from 41 patients. We characterized intracranial EEG changes both in the seizure onset zone and in areas remote from the seizure onset zone with a total of 3386 electrodes distributed across brain areas. First, we compared the dynamics of intracranial EEG sleep-like activities: slow-wave activity (1-4 Hz) and beta/delta ratio (a validated marker of cortical activation) during focal impaired awareness versus focal to bilateral tonic-clonic. Second, we quantified differences between focal to bilateral tonic-clonic and focal impaired awareness for a marker validated to detect ictal cross-frequency coupling: phase-locked high gamma (high-gamma phased-locked to low frequencies) and a marker of ictal recruitment: the epileptogenicity index. Third, we assessed changes in intracranial EEG activity preceding and accompanying behavioural generalization onset and their correlation with electromyogram channels. In addition, we analysed human cortical multi-unit activity recorded with Utah arrays during three focal to bilateral tonic-clonic seizures. Compared to focal impaired awareness, focal to bilateral tonic-clonic seizures were characterized by deeper loss of consciousness, even before generalization occurred. Unlike during focal impaired awareness, early loss of consciousness before generalization was accompanied by paradoxical decreases in slow-wave activity and by increases in high-gamma activity in parieto-occipital and temporal cortex. After generalization, when all patients displayed loss of consciousness, stronger increases in slow-wave activity were observed in parieto-occipital cortex, while more widespread increases in cortical activation (beta/delta ratio), ictal cross-frequency coupling (phase-locked high gamma) and ictal recruitment (epileptogenicity index). Behavioural generalization coincided with a whole-brain increase in high-gamma activity, which was especially synchronous in deep sources and could not be explained by EMG. Similarly, multi-unit activity analysis of focal to bilateral tonic-clonic revealed sustained increases in cortical firing rates during and after generalization onset in areas remote from the seizure onset zone. Overall, these results indicate that unlike during focal impaired awareness, the neural signatures of loss of consciousness during focal to bilateral tonic-clonic consist of paradoxical increases in cortical activation and neuronal firing found most consistently in posterior brain regions. These findings suggest differences in the mechanisms of ictal loss of consciousness between focal impaired awareness and focal to bilateral tonic-clonic and may account for the more negative prognostic consequences of focal to bilateral tonic-clonic.

Ultrastructural effects of sleep and wake on the parallel fiber synapses of the cerebellum.

Multiple evidence in rodents shows that the strength of excitatory synapses in the cerebral cortex and hippocampus is greater after wake than after sleep. The widespread synaptic weakening afforded by sleep is believed to keep the cost of synaptic activity under control, promote memory consolidation, and prevent synaptic saturation, thus preserving the brain's ability to learn day after day. The cerebellum is highly plastic and the Purkinje cells, the sole output neurons of the cerebellar cortex, are endowed with a staggering number of excitatory parallel fiber synapses. However, whether these synapses are affected by sleep and wake is unknown. Here, we used serial block face scanning electron microscopy to obtain the full 3D reconstruction of more than 7000 spines and their parallel fiber synapses in the mouse posterior vermis. This analysis was done in mice whose cortical and hippocampal synapses were previously measured, revealing that average synaptic size was lower after sleep compared to wake with no major changes in synapse number. Here, instead, we find that while the average size of parallel fiber synapses does not change, the number of branched synapses is reduced in half after sleep compared to after wake, corresponding to ~16% of all spines after wake and ~8% after sleep. Branched synapses are harbored by two or more spines sharing the same neck and, as also shown here, are almost always contacted by different parallel fibers. These findings suggest that during wake, coincidences of firing over parallel fibers may translate into the formation of synapses converging on the same branched spine, which may be especially effective in driving Purkinje cells to fire. By contrast, sleep may promote the off-line pruning of branched synapses that were formed due to spurious coincidences.

Sleep and wake in a model of the thalamocortical system with Martinotti cells.

The mechanisms leading to the alternation between active (UP) and silent (DOWN) states during sleep slow waves (SWs) remain poorly understood. Previous models have explained the transition to the DOWN state by a progressive failure of excitation because of the build-up of adaptation currents or synaptic depression. However, these models are at odds with recent studies suggesting a role for presynaptic inhibition by Martinotti cells (MaCs) in generating SWs. Here, we update a classical large-scale model of sleep SWs to include MaCs and propose a different mechanism for the generation of SWs. In the wake mode, the network exhibits irregular and selective activity with low firing rates (FRs). Following an increase in the strength of background inputs and a modulation of synaptic strength and potassium leak potential mimicking the reduced effect of acetylcholine during sleep, the network enters a sleep-like regime in which local increases of network activity trigger bursts of MaC activity, resulting in strong disfacilitation of the local network via presynaptic GABAB1a -type inhibition. This model replicates findings on slow wave activity (SWA) during sleep that challenge previous models, including low and skewed FRs that are comparable between the wake and sleep modes, higher synchrony of transitions to DOWN states than to UP states, the possibility of triggering SWs by optogenetic stimulation of MaCs, and the local dependence of SWA on synaptic strength. Overall, this work points to a role for presynaptic inhibition by MaCs in the generation of DOWN states during sleep.

Increase in NREM sleep slow waves following injections of sodium oxybate in the mouse cerebral cortex and the role of somatostatin-positive interneurons.

The systemic administration of sodium oxybate (SXB), the sodium salt of gamma-hydroxybutyric acid, promotes slow wave activity (SWA, 0.5-4 Hz EEG power) and increases non-rapid eye movement (NREM) sleep. These effects are mediated by the widely expressed GABAb receptors, and thus, the brain areas targeted by SXB remain unclear. Because slow waves are mainly a cortical phenomenon, we tested here whether systemic SXB promotes SWA by acting directly on the cortex. Moreover, because somatostatin (SOM) + cortical interneurons play a key role in SWA generation, we also assessed their contribution to the effects of SXB. In adult SOM-Cre mice, the injection of SXB in left secondary motor cortex increased SWA during NREM sleep in the first 30 min post-injection (11 mice: either sex). SWA, the amplitude and frequency of the slow waves, and the frequency of the OFF periods increased ipsilaterally and contralaterally to the SXB injection in frontal and parietal cortex. All these changes disappeared when the intracortical injection of SXB was preceded by the chemogenetic inhibition of the SOM+ cells. Thus, SXB may promote the slow waves of NREM sleep, at least in part, by acting directly on the cortex, and this effect involves GABAergic SOM+ interneurons. Our working hypothesis is that SXB potentiates the ability of these cells to inhibit all other cortical cell types via a GABAb mechanism, thus promoting the transition from ON to OFF periods during NREM sleep.

Multiple traces and altered signal-to-noise in systems consolidation: Evidence from the 7T fMRI Natural Scenes Dataset.

The brain mechanisms of memory consolidation remain elusive. Here, we examine blood-oxygen-level-dependent (BOLD) correlates of image recognition through the scope of multiple influential systems consolidation theories. We utilize the longitudinal Natural Scenes Dataset, a 7-Tesla functional magnetic resonance imaging human study in which ∼135,000 trials of image recognition were conducted over the span of a year among eight subjects. We find that early- and late-stage image recognition associates with both medial temporal lobe (MTL) and visual cortex when evaluating regional activations and a multivariate classifier. Supporting multiple-trace theory (MTT), parts of the MTL activation time course show remarkable fit to a 20-y-old MTT time-dynamical model predicting early trace intensity increases and slight subsequent interference (R2 > 0.90). These findings contrast a simplistic, yet common, view that memory traces are transferred from MTL to cortex. Next, we test the hypothesis that the MTL trace signature of memory consolidation should also reflect synaptic "desaturation," as evidenced by an increased signal-to-noise ratio. We find that the magnitude of relative BOLD enhancement among surviving memories is positively linked to the rate of removal (i.e., forgetting) of competing traces. Moreover, an image-feature and time interaction of MTL and visual cortex functional connectivity suggests that consolidation mechanisms improve the specificity of a distributed trace. These neurobiological effects do not replicate on a shorter timescale (within a session), implicating a prolonged, offline process. While recognition can potentially involve cognitive processes outside of memory retrieval (e.g., re-encoding), our work largely favors MTT and desaturation as perhaps complementary consolidative memory mechanisms.

fMRI spectral signatures of sleep.

Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of nonrapid-eye-movement (NREM) sleep is the shift from high-frequency, low-amplitude wake EEG to low-frequency, high-amplitude sleep EEG dominated by spindles and slow waves. Here we identified signatures of sleep in brain hemodynamic activity, using simultaneous functional MRI (fMRI) and EEG. We found that, at the transition from wake to sleep, fMRI blood oxygen level-dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (<0.1 Hz) oscillation prominent in light sleep and correlated with the occurrence of spindles, and a high-frequency oscillation (>0.1 Hz) prominent in deep sleep and correlated with the occurrence of slow waves. The two oscillations were both detectable across the brain but exhibited distinct spatiotemporal patterns. During the falling-asleep process, the low-frequency oscillation first appeared in the thalamus, then the posterior cortex, and lastly the frontal cortex, while the high-frequency oscillation first appeared in the midbrain, then the frontal cortex, and lastly the posterior cortex. During the waking-up process, both oscillations disappeared first from the thalamus, then the frontal cortex, and lastly the posterior cortex. The BOLD oscillations provide local signatures of spindle and slow wave activity. They may be employed to monitor the regional occurrence of sleep or wakefulness, track which regions are the first to fall asleep or wake up at the wake-sleep transitions, and investigate local homeostatic sleep processes.

Identification of ultrastructural signatures of sleep and wake in the fly brain.

The cellular consequences of sleep loss are poorly characterized. In the pyramidal neurons of mouse frontal cortex, we found that mitochondria and secondary lysosomes occupy a larger proportion of the cytoplasm after chronic sleep restriction compared to sleep, consistent with increased cellular burden due to extended wake. For each morphological parameter, the within-animal variance was high, suggesting that the effects of sleep and sleep loss vary greatly among neurons. However, the analysis was based on 4-5 mice/group and a single section/cell. Here, we applied serial block-face scanning electron microscopy to identify signatures of sleep and sleep loss in the Drosophila brain. Stacks of images were acquired and used to obtain full 3D reconstructions of the cytoplasm and nucleus of 263 Kenyon cells from adult flies collected after a night of sleep (S) or after 11 h (SD11) or 35 h (SD35) of sleep deprivation (9 flies/group). Relative to S flies, SD35 flies showed increased density of dark clusters of chromatin and Golgi apparata and a trend increase in the percent of cell volume occupied by mitochondria, consistent with increased need for energy and protein supply during extended wake. Logistic regression models could assign each neuron to the correct experimental group with good accuracy, but in each cell, nuclear and cytoplasmic changes were poorly correlated, and within-fly variance was substantial in all experimental groups. Together, these results support the presence of ultrastructural signatures of sleep and sleep loss but underscore the complexity of their effects at the single-cell level.