Biology subjects

Tononi, G.

Publications and source records attributed to Tononi, G..

At least 19 recordsLinked to original sources

bioRxiv2026

Neural Signatures of Conscious Experience During Sleep: A Serial Awakening Study Using High-Density EEG

Identifying neural signatures of consciousness remains a central challenge in neuroscience. Sleep offers a tractable model for comparing brain activity in the presence or absence of subjective experience while minimizing behavioral responsiveness confounds. Using overnight 256 electrode high-density EEG in 140 participants and a serial-awakening paradigm, we analyzed 699 non-rapid eye movement (NREM) sleep stage 2 and 3 awakenings (351 dreaming experience, 348 no experience). Features from the 60s preceding awakening included regional spectral power, lagged-coherence connectivity, graph-theoretic metrics and gamma-to-alpha power ratios. Dreaming experiences were associated with shifts in posterior spectral balance, particularly reduced alpha and delta power and increased gamma-related measures, together with altered large scale network organization. In participant-level cross-validated machine-learning analyses, all classifiers performed above chance, with the best ensemble model reaching an ROC-AUC of 0.80 and average precision of 0.80. These findings identify reproducible posterior electrophysiological and network-level signatures of conscious states during NREM sleep.

neuroscience↗

bioRxiv2025

TI-Toolbox: An Open-Source Software for Temporal Interference Stimulation Research

BackgroundTemporal interference stimulation is a novel non-invasive brain stimulation approach that promises selective targeting of deep brain structures while minimizing off-target cortical stimulation. Despite a growing interest in temporal interference applications, there is a need for integrated computational tools that seamlessly connect neuroimaging data preprocessing through montage optimization, field simulation, and analysis within a unified framework designed for translational and clinical research. MethodsWe developed TI-Toolbox, an open-source software platform that integrates established neuroimaging tools (dcm2niix, SimNIBS, FreeSurfer) with specialized algorithms for temporal interference research. The platform provides end-to-end workflows encompassing structural MRI preprocessing, volume conduction modeling, montage optimization, electric field simulation, and region-of-interest analysis. Both graphical user interface and command-line interface implementations ensure accessibility across user expertise levels. The platform employs containerized deployment via Docker to ensure reproducibility and cross-platform compatibility. ResultsTI-Toolbox successfully automates the complete temporal interference research pipeline, from DICOM conversion through final field analysis. The platform demonstrates robust performance across operating systems and provides standardized workflows that enhance reproducibility. Furthermore, our case studies support the validity of our HD-EEG mapping approach for montage standardization and the need for individualized modeling for exposure assessment. ConclusionsTI-Toolbox addresses critical infrastructure gaps in temporal interference research by providing researchers with a unified, validated platform that reduces technical barriers and accelerates translational research in non-invasive deep brain stimulation. HighlightsO_LIOpen-source platform unifying TI stimulation workflow end-to-end C_LIO_LIDocker deployment ensures reproducibility across operating systems C_LIO_LIHD-EEG electrode mapping preserves field characteristics C_LIO_LIStandardized model is sufficient for montage optimization C_LIO_LIAnatomical differences explain >40% of inter-individual variability C_LI

neuroscience↗

bioRxiv2025

Induction of cortical ON/OFF periods in awake mice fulfills sleep functions

Can animals obtain core benefits of sleep while remaining awake? In mammals, slow-wave sleep is characterized by synchronized neuronal activity alternating between ON and OFF periods. Slow-wave activity and synchrony reflect sleep need, are correlated with synaptic strength in cortical circuits, and promote synaptic down-selection and memory consolidation. To address the above question, we locally induced alternating ON/OFF periods during wakefulness using optogenetics in mice. This led to a local, ipsilateral reduction of slow-wave activity and synchrony during subsequent sleep and to reduced markers of synaptic strength. Moreover, bilateral induction of OFF periods over sensorimotor cortex during sleep deprivation restored memory consolidation. Thus, inducing ON/OFF activity during wakefulness is sufficient to reduce local sleep need and fulfills core functions of sleep.

neuroscience↗

bioRxiv2025

Temporal Interference Stimulation Can Enhance or Disrupt Human Memory Encoding as a Function of Brain Location and Frequency

Visual memory relies on synchronized interactions and rhythms between the medial temporal lobes and neocortical brain regions. Non-invasive manipulation of memory-related brain regions, specifically deeper temporal lobe regions, has been limited by the lack of precision of non-invasive neuromodulation - when targeting deeper structures, the cortex is always stimulated, never deeper structures in isolation. Temporal Interference (TI) stimulation, a novel non-invasive technique, uses high-frequency carrier fields to deliver targeted, physiologically relevant neuromodulation via amplitude-modulated envelopes at specific brain regions. Here, we investigate TIs impact on figure memory encoding in 70 healthy participants using the Rey-Osterrieth and Taylor Complex Figure tasks, with TI applied in several brain regions independently and simultaneously - allowing investigation of combinations of medial temporal lobe and neocortical brain regions. Interestingly, higher frequency TI envelopes (130 Hz offset) targeting bilateral hippocampi and temporal cortices significantly impair recall (p = 6.54e-04), while lower frequency TI envelopes (5 Hz offset) targeting only the bilateral hippocampi significantly enhance recall (p = 0.0447). Stimulation using other combinations of medial temporal lobe and neocortical regions showed no effect, underscoring the critical role of frequency and focality of non-invasive brain stimulation and correct target selection. Finally, functional MRI reveals strong differences between the effects of 130 Hz and 5 Hz envelopes, specifically in hippocampal BOLD signals, brain connectivity, default mode, and attentional networks. These findings demonstrate TIs ability to bidirectionally modulate memory encoding through precise frequency and target tuning, offering a powerful tool for cognitive neuroscience and potential therapeutic applications for memory disorders. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/677714v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@8e9db3org.highwire.dtl.DTLVardef@1135a3corg.highwire.dtl.DTLVardef@189345dorg.highwire.dtl.DTLVardef@ccca8f_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract:C_FLOATNO Temporal Interference stimulation for bidirectional memory modulation assessed via behavioral testing and MRI scanning. C_FIG

neuroscience↗

bioRxiv2024

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. However, while several studies have demonstrated that stimulation of subcortical nuclei can produce EEG activation and restore consciousness, so far no direct causal evidence has been available for the cortex itself. 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.

neuroscience↗

bioRxiv2024

Neural correlates of pure presence

Pure presence (PP) is described in several meditative traditions as an experience of a vast, vivid space devoid of perceptual objects, thoughts, and self. Integrated information theory (IIT) predicts that such vivid experiences may occur when the cortical substrate of consciousness is virtually silent. To test this, we analyzed high-quality 256-electrode high-density electroencephalography (hdEEG) from twenty-two long-term Vajrayana and Zen meditators who reported reaching PP during a week-long retreat. Because neural activity typically increases gamma power, we predicted PP would show widespread gamma reductions. Across both traditions, PP was associated with broadband power decrease compared to within-meditation mind-wandering, most consistent in the gamma range (30- 45 Hz). Source reconstruction revealed widespread gamma decreases, strongest in posteromedial cortex. PP gamma power was lower than in all other control states, including watching or imagining a movie, active thinking, and open-monitoring. PP delta power (1-4Hz) was also markedly reduced compared to dreamless sleep. Meditative states resembling PP--with minimal perceptual contents or accompanied by bliss-- showed similar signatures. Overall, PP appears to be a state of vivid consciousness during which the cortex is highly awake (low delta) yet widely quiescent (low gamma), in line with IITs predictions.

neuroscience↗

bioRxiv2024

From micro to macro units: a mathematical framework for identifying the causal grain of a system from its intrinsic perspective

Integrated information theory (IIT) aims to account for the quality and quantity of consciousness in physical terms. According to IIT, a substrate of consciousness must be a system of units that is a maximum of intrinsic, irreducible cause-effect power, quantified by integrated information ({varphi}s). Moreover, the grain of each unit must be the one-- from micro (finer) to macro (coarser)--that maximizes the systems intrinsic irreducibility (i.e., maximizes{varphi} s). The units that maximize{varphi} s are called the intrinsic units of the system. This work extends the mathematical framework of IIT 4.0 to assess cause-effect power at different grains and thereby determine a systems intrinsic units. Using simple, simulated systems, we show that the cause-effect power of a system of macro units can be higher than the cause-effect power of the corresponding micro units. Two examples highlight specific kinds of macro units, and how each kind can increase cause-effect power. The implications of the framework are discussed in the broader context of IIT, including how it provides a foundation for tests and inferences about consciousness.

systems biology↗

bioRxiv2023

An adversarial collaboration to critically evaluate theories of consciousness

Different theories explain how subjective experience arises from brain activity1,2. These theories have independently accrued evidence, yet, confirmation bias and dependence on design choices hamper progress in the field3. Here, we present an open science adversarial collaboration which directly juxtaposes Integrated Information Theory (IIT)4,5 and Global Neuronal Workspace Theory (GNWT)6-10, employing a theory-neutral consortium approach11,12. We investigate neural correlates of the content and duration of visual experience. The theory proponents and the consortium developed and preregistered the experimental design, divergent predictions, expected outcomes, and their interpretation12. 256 human subjects viewed suprathreshold stimuli for variable durations while neural activity was measured with functional magnetic resonance imaging, magnetoencephalography, and electrocorticography. We find information about conscious content in visual, ventro-temporal and inferior frontal cortex, with sustained responses in occipital and lateral temporal cortex reflecting stimulus duration, and content-specific synchronization between frontal and early visual areas. These results confirm some predictions of IIT and GNWT, while substantially challenging both theories: for IIT, a lack of sustained synchronization within posterior cortex contradicts the claim that network connectivity specifies consciousness. GNWT is challenged by the general lack of ignition at stimulus offset and limited representation of certain conscious dimensions in prefrontal cortex. Beyond challenging the theories themselves, we present an alternative approach to advance cognitive neuroscience through a principled, theory-driven, collaborative effort. We highlight the challenges to change peoples mind 13 and the need for a quantitative framework integrating evidence for systematic theory testing and building.

neuroscience↗

bioRxiv2022

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 brains 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.

neuroscience↗

bioRxiv2022

Sleep/wake changes in perturbational complexity in rats and mice

In humans, the level of consciousness can be assessed by quantifying the spatiotemporal complexity of cortical responses using the Perturbational Complexity Index (PCI) and related PCIst (st, state transitions). These measures are consistently high in wake and rapid eye movement (REM) sleep and low in dreamless non-REM (NREM) sleep, deep slow wave anesthesia, and coma. The neuronal mechanisms underlying the reduction of PCI/PCIst in unconscious states remain largely unexplored. The extent to which different cortical areas or layers contribute to these measures is also unknown. To address these questions, here we first validate the use of PCIst in freely moving rats (8 males) and mice (12, 4 females) by showing that its values are lower in NREM sleep and slow wave anesthesia than in wake or REM sleep, as in humans. We then show that low PCIst is associated with the occurrence of an OFF period of neuronal silence. Moreover, the stimulation of deep, but not superficial, cortical layers leads to reliable changes in PCIst across sleep/wake and anesthesia. Finally, consistent changes in PCIst can be measured independent of which single area is being stimulated or recorded, except for recordings in mouse prefrontal cortex. These experiments directly support the hypothesis that PCIst is low when an OFF period disrupts causal interactions in cortical networks. Moreover, they demonstrate that, as in humans, PCIst can be used for the reliable assessment of vigilance states in unresponsive animals, without the need to rely on behavioral outputs such as the righting reflex. Significance StatementThe level of consciousness can be assessed in humans by measuring the spatiotemporal complexity of cortical responses using the Perturbational Complexity Index (PCI) and related PCIst. These measures discriminate between conscious and unconscious conditions with high sensitivity and specificity and work in unresponsive patients. However, the neuronal mechanisms underlying PCI/ PCIst are largely unexplored. Moreover, since they reflect evoked responses from many cortical regions, it is unclear whether some areas or layers are more informative than others. Here we validate PCIst in rodents, provide direct evidence for the underlying neuronal mechanisms, and show that reliable changes in PCIst can almost always be obtained independent of which single area is stimulated or recorded, but only after stimulation of deep layers.

neuroscience↗

bioRxiv2022

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

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. SummaryAdvances 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.

neuroscience↗

bioRxiv2021

Distinct signatures of loss of consciousness during Focal Impaired Awareness (FIA) versus Focal to Bilateral Tonic-Clonic (FBTC) seizures

Loss of consciousness (LOC) is a hallmark of many epileptic seizures and carries risks of serious injury and sudden death. While cortical sleep-like activities accompany LOC during focal impaired awareness (FIA) seizures, the mechanisms of LOC during focal to bilateral tonic-clonic (FBTC) seizures remain unclear. Quantifying differences in markers of cortical activation and ictal recruitment between FIA and FBTC seizures may also help to understand their different consequences for clinical outcomes and to optimize neuromodulation therapies. We quantified clinical signs of LOC and intracranial EEG (iEEG) activity during 129 FIA and 50 FBTC from 41 patients. We characterized iEEG changes both in the seizure onset zone (SOZ) and in areas remote from SOZ with a total of 3386 electrodes distributed across brain areas. First, we compared the dynamics of iEEG sleep-like activities: slow-wave activity (SWA; 1-4 Hz) and beta/delta ratio (B/D; a validated marker of cortical activation) during FIA vs. FBTC. Second, we quantified differences between FBTC and FIA for a marker validated to detect ictal cross-frequency coupling: phase-locked high-gamma (PLHG; high gamma phased locked to low frequencies) and a marker of ictal recruitment: the epileptogenicity index (i.e. the number of channels crossing an energy ratio threshold for high vs. low frequency power). Third, we assessed changes in iEEG activity preceding and accompanying behavioral generalization onset and their correlation with electromyogram (EMG) channels. In addition, we analyzed human cortical multi-unit activity recorded with Utah arrays during three FBTC. Compared to FIA, FBTC seizures were characterized by deeper LOC and by stronger increases in SWA in parieto-occipital cortex. FBTC also displayed more widespread increases in cortical activation (B/D), ictal cross-frequency coupling (PLHG) and ictal recruitment (epileptogenicity index). Even before generalization, FBTC displayed deeper LOC; this early LOC was accompanied by a paradoxical increase in B/D in fronto-parietal cortex. Behavioral generalization coincided with complete loss of responsiveness and a subsequent increase in high-gamma in the whole brain, which was especially synchronous in deep sources and could not be explained by EMG. Similarly, multi-unit activity analysis of FBTC revealed sustained increases in cortical firing rates during and after generalization onset in areas remote from the SOZ. Unlike during FIA, LOC during FBTC is characterized by a paradoxical increase in cortical activation and neuronal firing. These findings suggest differences in the mechanisms of ictal LOC between FIA and FBTC and may account for the more negative prognostic consequences of FBTC.

neuroscience↗

bioRxiv2020

Measuring stimulus-evoked neurophysiological differentiation in distinct populations of neurons in mouse visual cortex

Despite significant progress in understanding neural coding, it remains unclear how the coordinated activity of large populations of neurons relates to what an observer actually perceives. Since neurophysiological differences must underlie differences among percepts, differentiation analysis--quantifying distinct patterns of neurophysiological activity--is an "inside out" approach that addresses this question. We used two-photon calcium imaging in mice to systematically survey stimulus-evoked neurophysiological differentiation in excitatory populations across 3 cortical layers (L2/3, L4, and L5) in each of 5 visual cortical areas (primary, lateral, anterolateral, posteromedial, and anteromedial) in response to naturalistic and phase-scrambled movie stimuli. We find that unscrambled stimuli evoke greater neurophysiological differentiation than scrambled stimuli specifically in L2/3 of the anterolateral and anteromedial areas, and that this effect is modulated by arousal state and locomotion. Contrariwise, decoding performance was far above chance and did not vary substantially across areas and layers. Differentiation also differed within the unscrambled stimulus set, suggesting that differentiation analysis may be used to probe the ethological relevance of individual stimuli.

neuroscience↗

bioRxiv2019

Integrity of corpus callosum is essential for the cross-hemispheric propagation of sleep slow waves: a high-density EEG study in split-brain patients

The slow waves of NREM-sleep (0.5-4Hz) reflect experience-dependent plasticity and play a direct role in the restorative functions of sleep. Importantly, slow waves behave as traveling waves and their propagation is assumed to reflect the structural properties of white matter connections. Based on this assumption, the corpus callosum (CC) may represent the main responsible for cross-hemispheric slow wave propagation. To verify this hypothesis, here we studied a group of patients who underwent total callosotomy due to drug-resistant epilepsy. Overnight high-density (hd)-EEG recordings (256 electrodes) were performed in five totally callosotomized in-patients (CP; 40-53y, 2F), in three control non-callosotomized neurological in-patients (NP; 44-66y, 2F, 1M epileptic), and in an additional sample of 24 healthy adult subjects (HS; 20-47y, 13F). Data were inspected to select NREM-sleep epochs and artefactual or non-physiological activity was rejected. Slow waves were detected using an automated algorithm and their properties and propagation patterns were computed. For each slow wave parameter and for each patient, the relative z-score and the corresponding p-value were calculated with respect to the distribution represented by the HS-group. Group differences were considered significant only when a Bonferroni corrected P < 0.05 was observed in all the CP and in none of the NP. A regression-based adjustment was used to exclude potential confounding effects of age. Slow wave density, amplitude, slope and propagation speed did not differ across CP and HS. In all CP slow waves displayed a significantly reduced probability of cross-hemispheric propagation and a stronger inter-hemispheric asymmetry. Moreover, we found that the incidence of large slow waves tended to differ across hemispheres within individual NREM epochs, with a relative predominance of the right over the left hemisphere in both CP and HS. The absolute magnitude of this inter-hemispheric difference was significantly greater in CP relative to HS. This effect did not depend on differences in slow wave origin within each hemisphere across groups. Present results indicate that the integrity of the CC is essential for the cross-hemispheric traveling of sleep slow waves, supporting the assumption of a direct relationship between white matter structural integrity and cross-hemispheric slow wave propagation. Our findings also imply a prominent role of cortico-cortical connections, rather than cortico-subcortico-cortical loops, in slow wave cross-hemispheric synchronization. Finally, this data indicate that the lack of the CC does not lead to differences in sleep depth, in terms of slow wave generation/origin, across brain hemispheres.

neuroscience↗

bioRxiv2019

Fear in dreams and in wakefulness: evidence for day/night affective homeostasis

Despite partial experimental evidence, it is a long-standing and common belief that dreams serve an emotion regulation function. Revisiting this idea, recent neuroscientific theories have proposed that emotions experienced in dreams contribute to the resolution of emotional distress (e.g. fear extinction) and preparation for future waking affective reactions. Here we addressed one emerging common prediction from these theoretical accounts, namely that experiencing fear in dreams is associated with more adapted responses to threatening signals during wakefulness. Using a stepwise approach across two studies, we first identified brain regions activated when experiencing fear in dreams and then showed that frightening dreams modulated the response of these same regions to threatening stimuli during wakefulness. As predicted, more fear in dreams was associated with reduced activation of those fear-responsive regions during wakefulness. Specifically, in Study 1, we performed serial awakenings in 18 participants recorded throughout the night with high-density EEG and asked them whether they experienced any fear in their dreams. Insula activity increased (i.e. decreased delta and increased gamma power) for dreams containing fear. In Study 2, we tested 89 participants and found that those with higher incidence of fear in their dreams showed reduced fMRI response to fear-eliciting stimuli in the insula, amygdala and midcingulate cortex, while awake. Consistent with better emotion regulation processes, the same participants also displayed increased medial prefrontal cortex activity. These findings support that emotions in dreams and wakefulness engage similar neural substrates, and substantiate a link between emotional processes occurring during sleep and emotional brain functions during wakefulness.

neuroscience↗

bioRxiv2019

Visual imagery and visual perception induce similar changes in occipital slow waves of sleep

Previous studies have shown that regional slow wave activity (SWA) during NREM-sleep is modulated by prior experience and learning. While this effect has been convincingly demonstrated for the sensorimotor domain, attempts to extend these findings to the visual system have provided mixed results. Here we asked whether depriving subjects of external visual stimuli during daytime would lead to regional changes in slow waves during sleep and whether the degree of internal visual stimulation (spontaneous imagery) would influence such changes. In two 8h-long sessions spaced one-week apart, twelve healthy volunteers either were blindfolded while listening to audiobooks or watched movies (control condition), after which their sleep was recorded with high-density EEG. We found that during NREM-sleep the number of small, local slow waves in the occipital cortex decreased after listening with blindfolding relative to movie watching in a way that depended on the degree of visual imagery subjects reported during blindfolding: subjects with low visual imagery showed a significant reduction of occipital sleep slow waves, while those who reported a high degree of visual imagery did not. We also found a positive relationship between the reliance on visual imagery during blindfolding and audiobook listening and the degree of correlation in sleep SWA between visual areas and language-related areas. These preliminary results demonstrate that short-term alterations in visual experience may trigger slow wave changes in cortical visual areas. Furthermore, they suggest that plasticity-related EEG changes during sleep may reflect externally induced ( bottom-up) visual experiences, as well as internally generated ( top-down) processes.

neuroscience↗

bioRxiv2019

BOLD signatures of sleep

Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of non-rapid-eye-movement sleep are two major EEG events: slow waves and spindles. Here we sought to identify possible signatures of sleep in brain hemodynamic activity, using simultaneous fMRI-EEG. We found that, during the transition from wake to sleep, blood-oxygen-level-dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (~0.05Hz) oscillation prominent in light sleep and a high-frequency (~0.17Hz) oscillation in deep sleep. The two BOLD oscillations correlated with the occurrences of spindles and slow waves, respectively. They were detectable across the whole brain, cortically and subcortically, but had different regional distributions and opposite onset patterns. These spontaneous BOLD oscillations provide fMRI signatures of basic sleep processes, which may be employed to study human sleep at spatial resolution and brain coverage not achievable using EEG. HIGHLIGHTSspontaneous BOLD oscillations differentiate sleep from wake low-frequency BOLD oscillation tracks sleep spindles high-frequency BOLD oscillation tracks sleep slow waves BOLD oscillations provide fMRI signatures of key sleep processes

neuroscience↗

bioRxiv2018

A fast and general method to empirically estimate the complexity of distributed causal interactions in the brain

BackgroundThe Perturbational Complexity Index (PCI) was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain injured patients, PCI depends on elaborate experimental setups and offline processing and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG) recordings. ObjectiveWe aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. MethodsPCIST is based on dimensionality reduction and state transitions (ST) quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain injured patients, and tested on sparse intracranial recordings (SEEG) of 9 patients undergoing intra-cerebral single-pulse electrical stimulation (SPES). ResultsWhen calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracerebral complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. ConclusionsPCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.

neuroscience↗