Showing papers by "Giulio Tononi published in 2022"

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

Abstract: Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an explainable consciousness indicator (ECI) using deep learning to disentangle the components of consciousness. We employ electroencephalographic (EEG) responses to transcranial magnetic stimulation under various conditions, including sleep (n = 6), general anesthesia (n = 16), and severe brain injury (n = 34). We also test our framework using resting-state EEG under general anesthesia (n = 15) and severe brain injury (n = 34). ECI simultaneously quantifies arousal and awareness under physiological, pharmacological, and pathological conditions. Particularly, ketamine-induced anesthesia and rapid eye movement sleep with low arousal and high awareness are clearly distinguished from other states. In addition, parietal regions appear most relevant for quantifying arousal and awareness. This indicator provides insights into the neural correlates of altered states of consciousness.

Lucid Dreaming Occurs in Activated REM Sleep, Not a Mixture of Sleep and Wakefulness.

Abstract: STUDY OBJECTIVES 1) To replicate the finding that lucid dreams are associated with physiological activation, including heightened REM density, during REM sleep. 2) To critically test whether a previously reported increase in frontolateral 40 Hz power in lucid REM sleep, used to justify the claim that lucid dreaming is a "hybrid state" mixing sleep and wakefulness, is attributable to the saccadic spike potential (SP) artifact as a corollary of heightened REM density. 3) To conduct an exploratory analysis of changes in EEG features during lucid REM sleep. METHODS We analyzed 14 signal-verified lucid dreams (SVLDs) and baseline REM sleep segments from the same REM periods from six participants derived from the Stanford SVLD database. Participants marked lucidity onset with standard left-right-left-right-center (LR2c) eye-movement signals in polysomnography recordings. RESULTS Compared to baseline REM sleep, lucid REM sleep had higher REM density (p=0.002). Bayesian analysis supported the null hypothesis of no differences in frontolateral 40 Hz power after removal of the SP artifact (BH=0.18) and ICA correction (BH=0.01). Compared to the entire REM sleep period, lucid REM sleep showed small reductions in low-frequency and beta band spectral power as well as increased signal complexity (all p<0.05), which were within the normal variance of baseline REM sleep. CONCLUSIONS Lucid dreams are associated with higher-than-average levels of physiological activation during REM sleep, including measures of both subcortical and cortical activation. Increases in 40 Hz power in periorbital channels reflect saccadic and microsaccadic SPs as a result of higher REM density accompanying heightened activation.

Lucid dreaming occurs in activated rapid eye movement sleep, not a mixture of sleep and wakefulness.

Abstract: STUDY OBJECTIVES (1) To critically test whether a previously reported increase in frontolateral 40 Hz power in lucid REM sleep, used to justify the claim that lucid dreaming is a "hybrid state" mixing sleep and wakefulness, is attributable to the saccadic spike potential (SP) artifact as a corollary of heightened REM density. (2) To replicate the finding that lucid dreams are associated with physiological activation, including heightened eye movement density, during REM sleep. (3) To conduct an exploratory analysis of changes in EEG features during lucid REM sleep. METHODS We analyzed 14 signal-verified lucid dreams (SVLDs) and baseline REM sleep segments from the same REM periods from six participants derived from the Stanford SVLD database. Participants marked lucidity onset with standard left-right-left-right-center (LR2c) eye-movement signals in polysomnography recordings. RESULTS Compared to baseline REM sleep, lucid REM sleep had higher REM density (β = 0.85, p = 0.002). Bayesian analysis supported the null hypothesis of no differences in frontolateral 40 Hz power after removal of the SP artifact (BH = 0.18) and ICA correction (BH = 0.01). Compared to the entire REM sleep period, lucid REM sleep showed small reductions in low-frequency and beta band spectral power as well as increased signal complexity (all p < 0.05), which were within the normal variance of baseline REM sleep. CONCLUSIONS Lucid dreams are associated with higher-than-average levels of physiological activation during REM sleep, including measures of both subcortical and cortical activation. Increases in 40 Hz power in periorbital channels reflect saccadic and microsaccadic SPs as a result of higher REM density accompanying heightened activation.

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

Abstract: 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, and permits inferences and extrapolations. IIT 4.0 incorporates several developments of the past ten years, including a more accurate translation of axioms into 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.

Restricted truncal sagittal movements of rapid eye movement behaviour disorder

Abstract: Unlike sleep-walkers, patients with rapid-eye-movement-behaviour disorder (RBD) rarely leave the bed during the re-enactment of their dreams. RBD movements may be independent of spatial co-ordinates of the 'outside-world', and instead rely on (allocentric) brain-generated virtual space-maps, as evident by patients' limited truncal/axial movements. To confirm this, a semiology analysis of video-polysomnography records of 38 RBD patients was undertaken and paradoxically restricted truncal/thoraco-lumbar movements during complex dream re-enactments demonstrated.

Restricted truncal sagittal movements of rapid eye movement behaviour disorder

Abstract: Unlike sleep-walkers, patients with rapid-eye-movement-behaviour disorder (RBD) rarely leave the bed during the re-enactment of their dreams. RBD movements may be independent of spatial co-ordinates of the 'outside-world', and instead rely on (allocentric) brain-generated virtual space-maps, as evident by patients' limited truncal/axial movements. To confirm this, a semiology analysis of video-polysomnography records of 38 RBD patients was undertaken and paradoxically restricted truncal/thoraco-lumbar movements during complex dream re-enactments demonstrated.

System Integrated Information

Abstract: 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.

IIT, half masked and half disfigured

Abstract: Abstract The target article misrepresents the foundations of integrated information theory (IIT) and ignores many essential publications. It, thus, falls to this lead commentary to outline the axioms and postulates of IIT and correct major misconceptions. The commentary also explains why IIT starts from phenomenology and why it predicts that only select physical substrates can support consciousness. Finally, it highlights that IIT's account of experience – a cause–effect structure quantified by integrated information – has nothing to do with “information transfer.”

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

Abstract: 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.

Only what exists can cause: An intrinsic view of free will

Abstract: This essay addresses the implications of integrated information theory (IIT) for free will. IIT is a theory of what consciousness is and what it takes to have it. According to IIT, the presence of consciousness is accounted for by a maximum of cause-effect power in the brain. Moreover, the way specific experiences feel is accounted for by how that cause-effect power is structured. If IIT is right, we do have free will in the fundamental sense: we have true alternatives, we make true decisions, and we - not our neurons or atoms - are the true cause of our willed actions and bear true responsibility for them. IIT's argument for true free will hinges on the proper understanding of consciousness as true existence, as captured by its intrinsic powers ontology: what truly exists, in physical terms, are intrinsic entities, and only what truly exists can cause.

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

Abstract: Significance How do the neural correlates of recognition change over time? We study natural scene image recognition spanning a year with 7-Tesla functional magnetic resonance imaging (fMRI) of the human brain. We find that the medial temporal lobe (MTL) contribution to recognition persists over 200 d, supporting multiple-trace theory and contradicting a trace transfer (from MTL to cortex) point of view. We then test the hypothesis that the signal-to-noise ratio of traces increases over time, presumably a consequence of synaptic “desaturation” in the weeks following learning. The fMRI trace signature associates with the rate of removal of competing traces and reflects a time-related enhancement of image-feature selectivity. We conclude that multiple MTL traces and improved signal-to-noise may underlie systems-level memory consolidation.

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

Abstract: 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.

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

Abstract: 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 7,000 spines and their parallel fiber synapses in the mouse posterior vermis. We find that most Purkinje cell spines carry a synapse, but some do not. The latter, which we call “naked” spines, are ∼5% of all spines after wake but grow to ∼10% of all spines after sleep. Further analysis shows that the changes in the number of naked synapses with wake and sleep can be accounted for by a change in the number of “branched” synapses, which are housed in two or more spines sharing the same neck. Thus, during sleep branched spines may lose one or more synapses or convert to single spines, while the opposite changes occur after wake. Because branched synapses almost always contact different parallel fibers, these results also 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 at driving the soma of Purkinje cells. Sleep, on the other hand, may promote the pruning of branched synapses that were formed due to spurious coincidences.

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

Abstract: 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 due to 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. 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 during sleep that challenge previous models, including low and skewed firing rates 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 slow wave activity on synaptic strength. Overall, this work points to a role for presynaptic inhibition by MaCs in the generation of DOWN states during sleep.

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

Abstract: Neurophysiological differentiation (ND), a metric that quantifies the number of distinct activity states that the brain or its part visits over a period of time, 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 populations of spiking neurons rather than the whole brain. Therefore, in this study, we use Neuropixels recordings from the mouse brain to characterize the ND metric 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 as well as 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 as well. 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. Analysis of spiking activity allows us to characterize the ND metric across a wide range of timescales from 10s of milliseconds to a few seconds. This analysis reveals that although ND of activity of single neurons is often maximized at an optimal timescale around 100 ms, the optimum shifts to under 5 ms for ND of neuronal ensembles. Finally, we find that the ND of activations in convolutional neural networks (CNNs) trained on an image classification task shows distinct trends relative to the mouse visual system: ND is often higher for less naturalistic stimuli and varies by orders of magnitude across the hierarchy, compared to modest variation in the mouse brain. Together, these results suggest that ND computed on cellular-level neural recordings can be a useful tool highlighting cell populations that may be involved in subjective perception. Summary Advances in our understanding on neural coding has revealed that information about visual stimuli is represented across several brain regions. However, availability of information does not imply that it is necessarily utilized by the brain, much less that it is subjectively perceived. Since percepts originate in neural activity, distinct percepts must be associated with distinct ‘states’ of neural activity, at least within the brain region that supports the percepts. Thus, one approach developed in this direction is to quantify the number of distinct ‘states’ that the activity of the brain goes through, called neurophysiological differentiation (ND). ND of the entire brain has been shown to reflect subjective reports of visual stimulus meaningfulness. But what specific subpopulations within the brain could be supporting conscious perception, and what is the correct timescale on which states should be quantified? In this study, we analyze ND of spiking neural activity in the mouse visual cortex recorded using Neuropixels probes, allowing us to characterize the ND metric across a wide range of timescales all the way down from 5 ms to a few seconds. It also allows us to understand the ND of neural activity of different ensembles of neurons, from individual thalamic or cortical ensembles to those spanning across multiple visual areas in the mouse brain.