1
|
Van De Poll M, Tainton-Heap L, Troup M, van Swinderen B. Whole-Brain Electrophysiology and Calcium Imaging in Drosophila during Sleep and Wake. Cold Spring Harb Protoc 2024; 2024:pdb.top108394. [PMID: 38148172 DOI: 10.1101/pdb.top108394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
Sleep is likely a whole-brain phenomenon, with most of the brain probably benefiting from this state of decreased arousal. Recent advances in our understanding of some potential sleep functions, such as metabolite clearance and synaptic homeostasis, make it evident why the whole brain is likely impacted by sleep: All neurons have synapses, and all neurons produce waste metabolites. Sleep experiments in the fly Drosophila melanogaster suggest that diverse sleep functions appear to be conserved across all animals. Studies of brain activity during sleep in humans typically involve multidimensional data sets, such as those acquired by electroencephalograms (EEGs) or functional magnetic resonance imaging (fMRI), and these whole-brain read-outs often reveal important qualities of different sleep stages, such as changes in frequency dynamics or connectivity. Recently, various techniques have been developed that allow for the recording of neural activity simultaneously across multiple regions of the fly brain. These whole-brain-recording approaches will be important for better understanding sleep physiology and function, as they provide a more comprehensive view of neural dynamics during sleep and wake in a relevant model system. Here, we present a brief summary of some of the findings derived from sleep activity recording studies in sleeping Drosophila flies and discuss the value of electrophysiological versus calcium imaging techniques. Although these involve very different preparations, they both highlight the value of multidimensional data for studying sleep in this model system, like the use of both EEG and fMRI in humans.
Collapse
Affiliation(s)
- Matthew Van De Poll
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Lucy Tainton-Heap
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Michael Troup
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Bruno van Swinderen
- Queensland Brain Institute, The University of Queensland, Brisbane, Queensland 4072, Australia
| |
Collapse
|
2
|
Junges L, Galvis D, Winsor A, Treadwell G, Richards C, Seri S, Johnson S, Terry JR, Bagshaw AP. The impact of paediatric epilepsy and co-occurring neurodevelopmental disorders on functional brain networks in wake and sleep. PLoS One 2024; 19:e0309243. [PMID: 39186749 PMCID: PMC11346934 DOI: 10.1371/journal.pone.0309243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 08/07/2024] [Indexed: 08/28/2024] Open
Abstract
Epilepsy is one of the most common neurological disorders in children. Diagnosing epilepsy in children can be very challenging, especially as it often coexists with neurodevelopmental conditions like autism and ADHD. Functional brain networks obtained from neuroimaging and electrophysiological data in wakefulness and sleep have been shown to contain signatures of neurological disorders, and can potentially support the diagnosis and management of co-occurring neurodevelopmental conditions. In this work, we use electroencephalography (EEG) recordings from children, in restful wakefulness and sleep, to extract functional connectivity networks in different frequency bands. We explore the relationship of these networks with epilepsy diagnosis and with measures of neurodevelopmental traits, obtained from questionnaires used as screening tools for autism and ADHD. We explore differences in network markers between children with and without epilepsy in wake and sleep, and quantify the correlation between such markers and measures of neurodevelopmental traits. Our findings highlight the importance of considering the interplay between epilepsy and neurodevelopmental traits when exploring network markers of epilepsy.
Collapse
Affiliation(s)
- Leandro Junges
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
| | - Daniel Galvis
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
| | - Alice Winsor
- Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Grace Treadwell
- Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, Keele University, Staffordshire, United Kingdom
| | - Caroline Richards
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Centre for Developmental Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Stefano Seri
- Aston Institute of Health and Neurodevelopment, Aston University, Birmingham, United Kingdom
- Department of Clinical Neurophysiology, Birmingham Women’s and Children’s Hospital, Birmingham, United Kingdom
| | - Samuel Johnson
- School of Mathematics, University of Birmingham, Birmingham, United Kingdom
- The Alan Turing Institute, London, United Kingdom
| | - John R. Terry
- Centre for Systems Modelling and Quantitative Biomedicine, University of Birmingham, Birmingham, United Kingdom
- Institute for Metabolism and Systems Research, University of Birmingham, Birmingham, United Kingdom
- Neuronostics Ltd, Engine Shed, Station Approach, Bristol, United Kingdom
| | - Andrew P. Bagshaw
- Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
| |
Collapse
|
3
|
Luppi AI, Rosas FE, Mediano PAM, Demertzi A, Menon DK, Stamatakis EA. Unravelling consciousness and brain function through the lens of time, space, and information. Trends Neurosci 2024; 47:551-568. [PMID: 38824075 DOI: 10.1016/j.tins.2024.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/29/2024] [Accepted: 05/09/2024] [Indexed: 06/03/2024]
Abstract
Disentangling how cognitive functions emerge from the interplay of brain dynamics and network architecture is among the major challenges that neuroscientists face. Pharmacological and pathological perturbations of consciousness provide a lens to investigate these complex challenges. Here, we review how recent advances about consciousness and the brain's functional organisation have been driven by a common denominator: decomposing brain function into fundamental constituents of time, space, and information. Whereas unconsciousness increases structure-function coupling across scales, psychedelics may decouple brain function from structure. Convergent effects also emerge: anaesthetics, psychedelics, and disorders of consciousness can exhibit similar reconfigurations of the brain's unimodal-transmodal functional axis. Decomposition approaches reveal the potential to translate discoveries across species, with computational modelling providing a path towards mechanistic integration.
Collapse
Affiliation(s)
- Andrea I Luppi
- Division of Anaesthesia, University of Cambridge, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Montreal Neurological Institute, McGill University, Montreal, QC, Canada; St John's College, University of Cambridge, Cambridge, UK; Center for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK.
| | - Fernando E Rosas
- Center for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Department of Informatics, University of Sussex, Brighton, UK; Center for Psychedelic Research, Imperial College London, London, UK
| | | | - Athena Demertzi
- Physiology of Cognition Lab, GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium; Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège 4000, Belgium; National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
| | - David K Menon
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
| | - Emmanuel A Stamatakis
- Division of Anaesthesia, University of Cambridge, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| |
Collapse
|
4
|
Lee J, Hussain S, Warnick R, Vannucci M, Menchaca I, Seitz AR, Hu X, Peters MAK, Guindani M. A predictor-informed multi-subject bayesian approach for dynamic functional connectivity. PLoS One 2024; 19:e0298651. [PMID: 38753655 PMCID: PMC11098372 DOI: 10.1371/journal.pone.0298651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 01/30/2024] [Indexed: 05/18/2024] Open
Abstract
Dynamic functional connectivity investigates how the interactions among brain regions vary over the course of an fMRI experiment. Such transitions between different individual connectivity states can be modulated by changes in underlying physiological mechanisms that drive functional network dynamics, e.g., changes in attention or cognitive effort. In this paper, we develop a multi-subject Bayesian framework where the estimation of dynamic functional networks is informed by time-varying exogenous physiological covariates that are simultaneously recorded in each subject during the fMRI experiment. More specifically, we consider a dynamic Gaussian graphical model approach where a non-homogeneous hidden Markov model is employed to classify the fMRI time series into latent neurological states. We assume the state-transition probabilities to vary over time and across subjects as a function of the underlying covariates, allowing for the estimation of recurrent connectivity patterns and the sharing of networks among the subjects. We further assume sparsity in the network structures via shrinkage priors, and achieve edge selection in the estimated graph structures by introducing a multi-comparison procedure for shrinkage-based inferences with Bayesian false discovery rate control. We evaluate the performances of our method vs alternative approaches on synthetic data. We apply our modeling framework on a resting-state experiment where fMRI data have been collected concurrently with pupillometry measurements, as a proxy of cognitive processing, and assess the heterogeneity of the effects of changes in pupil dilation on the subjects' propensity to change connectivity states. The heterogeneity of state occupancy across subjects provides an understanding of the relationship between increased pupil dilation and transitions toward different cognitive states.
Collapse
Affiliation(s)
- Jaylen Lee
- Department of Statistics, University of California, Irvine, Irvine, California, United States of America
| | - Sana Hussain
- Department of Bioengineering, University of California, Riverside, Riverside, California, United States of America
| | - Ryan Warnick
- Microsoft Security Research, Microsoft, Redmond, Washington, United States of America
| | - Marina Vannucci
- Department of Statistics, Rice University, Houston, Texas, United States of America
| | - Isaac Menchaca
- Department of Bioengineering, University of California, Riverside, Riverside, California, United States of America
| | - Aaron R. Seitz
- Department of Psychology, University of California, Riverside, Riverside, California, United States of America
| | - Xiaoping Hu
- Department of Bioengineering, University of California, Riverside, Riverside, California, United States of America
| | - Megan A. K. Peters
- Department of Bioengineering, University of California, Riverside, Riverside, California, United States of America
- Department of Cognitive Sciences, University of California, Irvine, Irvine, California, United States of America
| | - Michele Guindani
- Department of Biostatistics, University of California, Los Angeles, Los Angeles, California, United States of America
| |
Collapse
|
5
|
Joliot M, Cremona S, Tzourio C, Etard O. Modulate the impact of the drowsiness on the resting state functional connectivity. Sci Rep 2024; 14:8652. [PMID: 38622265 PMCID: PMC11018752 DOI: 10.1038/s41598-024-59476-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 04/11/2024] [Indexed: 04/17/2024] Open
Abstract
This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN.
Collapse
Affiliation(s)
- Marc Joliot
- GIN, IMN UMR5293, CEA, CNRS, Université de Bordeaux, Bordeaux, France.
| | - Sandrine Cremona
- GIN, IMN UMR5293, CEA, CNRS, Université de Bordeaux, Bordeaux, France
| | | | - Olivier Etard
- Normandie Université, UNICAEN, INSERM, COMETE U1075, CYCERON, CHU Caen, 14000, Caen, France
| |
Collapse
|
6
|
Boulakis PA, Mortaheb S, van Calster L, Majerus S, Demertzi A. Whole-Brain Deactivations Precede Uninduced Mind-Blanking Reports. J Neurosci 2023; 43:6807-6815. [PMID: 37643862 PMCID: PMC10552942 DOI: 10.1523/jneurosci.0696-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 07/11/2023] [Accepted: 08/07/2023] [Indexed: 08/31/2023] Open
Abstract
Mind-blanking (MB) is termed as the inability to report our immediate-past mental content. In contrast to mental states with reportable content, such as mind-wandering or sensory perceptions, the neural correlates of MB started getting elucidated only recently. A notable particularity that pertains to MB studies is the way MB is instructed for reporting, like by deliberately asking participants to "empty their minds." Such instructions were shown to induce fMRI activations in frontal brain regions, typically associated with metacognition and self-evaluative processes, suggesting that MB may be a result of intentional mental content suppression. Here, we aim at examining this hypothesis by determining the neural correlates of MB without induction. Using fMRI combined with experience-sampling in 31 participants (22 female), univariate analysis of MB reports revealed deactivations in occipital, frontal, parietal, and thalamic areas, but no activations in prefrontal regions. These findings were confirmed using Bayesian region-of-interest analysis on areas previously shown to be implicated in induced MB, where we report evidence for frontal deactivations during MB reports compared with other mental states. Contrast analysis between reports of MB and content-oriented mental states also revealed deactivations in the left angular gyrus. We propose that these effects characterize a neuronal profile of MB, where key thalamocortical nodes are unable to communicate and formulate reportable content. Collectively, we show that study instructions for MB lead to differential neural activation. These results provide mechanistic insights linked to the phenomenology of MB and point to the possibility of MB being expressed in different forms.SIGNIFICANCE STATEMENT This study explores how brain activity changes when individuals report unidentifiable thoughts, a phenomenon known as mind-blanking (MB). It aims to detect changes in brain activations and deactivations when MB is reported spontaneously, as opposed to the neural responses that have been previously reported when MB is induced. By means of brain imaging and experience-sampling, the study points to reduced brain activity in a wide number of regions, including those mesio-frontally which were previously detected as activated during induced MB. These results enhance our understanding of the complexity of spontaneous thinking and contribute to broader discussions on consciousness and reportable experience.
Collapse
Affiliation(s)
- Paradeisios Alexandros Boulakis
- Physiology of Cognition Lab, GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
| | - Sepehr Mortaheb
- Physiology of Cognition Lab, GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
| | - Laurens van Calster
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège 4000, Belgium
- GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels 1200, Belgium
| | - Steve Majerus
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège 4000, Belgium
- GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
| | - Athena Demertzi
- Physiology of Cognition Lab, GIGA-Cyclotron Research Center In Vivo Imaging, University of Liège, Liège 4000, Belgium
- National Fund for Scientific Research (FNRS), Brussels 1000, Belgium
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège 4000, Belgium
| |
Collapse
|
7
|
Rafi H, Delavari F, Perroud N, Derome M, Debbané M. The continuum of attention dysfunction: Evidence from dynamic functional network connectivity analysis in neurotypical adolescents. PLoS One 2023; 18:e0279260. [PMID: 36662797 PMCID: PMC9858399 DOI: 10.1371/journal.pone.0279260] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 12/04/2022] [Indexed: 01/21/2023] Open
Abstract
The question of whether attention-related disorders such as attention-deficit/hyperactivity disorder (ADHD) are best understood as clinical categories or as extreme ends of a spectrum is an ongoing debate. Assessing individuals with varying degrees of attention problems and utilizing novel methodologies to assess relationships between attention and brain activity may provide key information to support the spectrum hypothesis. We scanned 91 neurotypical adolescents during rest using functional magnetic resonance imaging. We conducted static and dynamic functional network connectivity (FNC) analysis and correlated findings to behavioral metrics of ADHD, attention problems, and impulsivity. We found that dynamic FNC analysis detects significant differences in large-scale neural connectivity as a function of individual differences in attention and impulsivity that are obscured in static analysis. We show ADHD manifestations and attention problems are associated with diminished Salience Network-centered FNC and that ADHD manifestations and impulsivity are associated with prolonged periods of dynamically hyperconnected states. Importantly, our meta-state analysis results reveal a relationship between ADHD manifestations and exhibiting variable and volatile dynamic behavior such as changing meta-states more often and traveling over a greater dynamic range. These findings in non-clinical adolescents provide support for the continuum model of attention disorders.
Collapse
Affiliation(s)
- Halima Rafi
- Faculty of Psychology and Educational Sciences, Developmental Clinical Psychology Research Unit, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
| | - Farnaz Delavari
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
- Medical Image Processing Lab, Institute of Bioengineering, EPFL, Lausanne, Switzerland
| | - Nader Perroud
- Department of Psychiatry, Service of Psychiatric Specialties, University Hospitals of Geneva, Geneva, Switzerland
| | - Mélodie Derome
- Faculty of Psychology and Educational Sciences, Developmental Clinical Psychology Research Unit, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
| | - Martin Debbané
- Faculty of Psychology and Educational Sciences, Developmental Clinical Psychology Research Unit, University of Geneva, Geneva, Switzerland
- Department of Psychiatry, Developmental Neuroimaging and Psychopathology Laboratory, University of Geneva, Geneva, Switzerland
- Research Department of Clinical, Educational & Health Psychology, University College London, London, United Kingdom
| |
Collapse
|
8
|
Mind blanking is a distinct mental state linked to a recurrent brain profile of globally positive connectivity during ongoing mentation. Proc Natl Acad Sci U S A 2022; 119:e2200511119. [PMID: 36194631 PMCID: PMC9564098 DOI: 10.1073/pnas.2200511119] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Mind blanking (MB) is a waking state during which we do not report any mental content. The phenomenology of MB challenges the view of a constantly thinking mind. Here, we comprehensively characterize the MB's neurobehavioral profile with the aim to delineate its role during ongoing mentation. Using functional MRI experience sampling, we show that the reportability of MB is less frequent, faster, and with lower transitional dynamics than other mental states, pointing to its role as a transient mental relay. Regarding its neural underpinnings, we observed higher global signal amplitude during MB reports, indicating a distinct physiological state. Using the time-varying functional connectome, we show that MB reports can be classified with high accuracy, suggesting that MB has a unique neural composition. Indeed, a pattern of global positive-phase coherence shows the highest similarity to the connectivity patterns associated with MB reports. We interpret this pattern's rigid signal architecture as hindering content reportability due to the brain's inability to differentiate signals in an informative way. Collectively, we show that MB has a unique neurobehavioral profile, indicating that nonreportable mental events can happen during wakefulness. Our results add to the characterization of spontaneous mentation and pave the way for more mechanistic investigations of MB's phenomenology.
Collapse
|
9
|
Rabuffo G, Fousek J, Bernard C, Jirsa V. Neuronal Cascades Shape Whole-Brain Functional Dynamics at Rest. eNeuro 2021; 8:ENEURO.0283-21.2021. [PMID: 34583933 PMCID: PMC8555887 DOI: 10.1523/eneuro.0283-21.2021] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/11/2021] [Accepted: 09/15/2021] [Indexed: 01/20/2023] Open
Abstract
At rest, mammalian brains display remarkable spatiotemporal complexity, evolving through recurrent functional connectivity (FC) states on a slow timescale of the order of tens of seconds. While the phenomenology of the resting state dynamics is valuable in distinguishing healthy and pathologic brains, little is known about its underlying mechanisms. Here, we identify neuronal cascades as a potential mechanism. Using full-brain network modeling, we show that neuronal populations, coupled via a detailed structural connectome, give rise to large-scale cascades of firing rate fluctuations evolving at the same time scale of resting-state networks (RSNs). The ignition and subsequent propagation of cascades depend on the brain state and connectivity of each region. The largest cascades produce bursts of blood oxygen level-dependent (BOLD) co-fluctuations at pairs of regions across the brain, which shape the simulated RSN dynamics. We experimentally confirm these theoretical predictions. We demonstrate the existence and stability of intermittent epochs of FC comprising BOLD co-activation (CA) bursts in mice and human functional magnetic resonance imaging (fMRI). We then provide evidence for the existence and leading role of the neuronal cascades in humans with simultaneous EEG/fMRI recordings. These results show that neuronal cascades are a major determinant of spontaneous fluctuations in brain dynamics at rest.
Collapse
Affiliation(s)
- Giovanni Rabuffo
- Aix Marseille University, INSERM, INS, Institut de Neurosciences des Systèmes, 13005 Marseille, France
| | - Jan Fousek
- Aix Marseille University, INSERM, INS, Institut de Neurosciences des Systèmes, 13005 Marseille, France
| | - Christophe Bernard
- Aix Marseille University, INSERM, INS, Institut de Neurosciences des Systèmes, 13005 Marseille, France
| | - Viktor Jirsa
- Aix Marseille University, INSERM, INS, Institut de Neurosciences des Systèmes, 13005 Marseille, France
| |
Collapse
|
10
|
Houldin E, Fang Z, Ray LB, Stojanoski B, Owen AM, Fogel SM. Reversed and increased functional connectivity in non-REM sleep suggests an altered rather than reduced state of consciousness relative to wake. Sci Rep 2021; 11:11943. [PMID: 34099771 PMCID: PMC8184935 DOI: 10.1038/s41598-021-91211-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 05/18/2021] [Indexed: 12/02/2022] Open
Abstract
Sleep resting state network (RSN) functional connectivity (FC) is poorly understood, particularly for rapid eye movement (REM), and in non-sleep deprived subjects. REM and non-REM (NREM) sleep involve competing drives; towards hypersynchronous cortical oscillations in NREM; and towards wake-like desynchronized oscillations in REM. This study employed simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) to explore whether sleep RSN FC reflects these opposing drives. As hypothesized, this was confirmed for the majority of functional connections modulated by sleep. Further, changes were directional: e.g., positive wake correlations trended towards negative correlations in NREM and back towards positive correlations in REM. Moreover, the majority did not merely reduce magnitude, but actually either reversed and strengthened in the opposite direction, or increased in magnitude during NREM. This finding supports the notion that NREM is best expressed as having altered, rather than reduced FC. Further, as many of these functional connections comprised “higher-order” RSNs (which have been previously linked to cognition and consciousness), such as the default mode network, this finding is suggestive of possibly concomitant alterations to cognition and consciousness.
Collapse
Affiliation(s)
- Evan Houldin
- Brain & Mind Institute, Western Interdisciplinary Research Building, Western University, London, N6A 5B7, Canada.,Department of Neuroscience, Western University, 1151 Richmond St. N., London, N6A 3K7, Canada.,Queensland Brain Institute, University of Queensland, Brisbane, 4072, Australia
| | - Zhuo Fang
- Brain & Mind Institute, Western Interdisciplinary Research Building, Western University, London, N6A 5B7, Canada.,University of Ottawa Brain and Mind Research Institute, 451 Smyth Rd, Ottawa, K1H 8M5, Canada
| | - Laura B Ray
- Brain & Mind Institute, Western Interdisciplinary Research Building, Western University, London, N6A 5B7, Canada.,The Royal's Institute for Mental Health Research, University of Ottawa, 1145 Carling Ave, Ottawa, K1Z 7K4, Canada
| | - Bobby Stojanoski
- Brain & Mind Institute, Western Interdisciplinary Research Building, Western University, London, N6A 5B7, Canada
| | - Adrian M Owen
- Brain & Mind Institute, Western Interdisciplinary Research Building, Western University, London, N6A 5B7, Canada.,Department of Psychology, Western University, London, N6A 5C2, Canada
| | - Stuart M Fogel
- Brain & Mind Institute, Western Interdisciplinary Research Building, Western University, London, N6A 5B7, Canada. .,University of Ottawa Brain and Mind Research Institute, 451 Smyth Rd, Ottawa, K1H 8M5, Canada. .,The Royal's Institute for Mental Health Research, University of Ottawa, 1145 Carling Ave, Ottawa, K1Z 7K4, Canada. .,Department of Psychology, Western University, London, N6A 5C2, Canada. .,School of Psychology, University of Ottawa, 136 Jean-Jacques Lussier, Ottawa, K1N 6N5, Canada.
| |
Collapse
|
11
|
Differential classification of states of consciousness using envelope- and phase-based functional connectivity. Neuroimage 2021; 237:118171. [PMID: 34000405 DOI: 10.1016/j.neuroimage.2021.118171] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 05/06/2021] [Accepted: 05/09/2021] [Indexed: 12/14/2022] Open
Abstract
The development of sophisticated computational tools to quantify changes in the brain's oscillatory dynamics across states of consciousness have included both envelope- and phase-based measures of functional connectivity (FC), but there are very few direct comparisons of these techniques using the same dataset. The goal of this study was to compare an envelope-based (i.e. Amplitude Envelope Correlation, AEC) and a phase-based (i.e. weighted Phase Lag Index, wPLI) measure of FC in their classification of states of consciousness. Nine healthy participants underwent a three-hour experimental anesthetic protocol with propofol induction and isoflurane maintenance, in which five minutes of 128-channel electroencephalography were recorded before, during, and after anesthetic-induced unconsciousness, at the following time points: Baseline; light sedation with propofol (Light Sedation); deep unconsciousness following three hours of surgical levels of anesthesia with isoflurane (Unconscious); five minutes prior to the recovery of consciousness (Pre-ROC); and three hours following the recovery of consciousness (Recovery). Support vector machine classification was applied to the source-localized EEG in the alpha (8-13 Hz) frequency band in order to investigate the ability of AEC and wPLI (separately and together) to discriminate i) the four states from Baseline; ii) Unconscious ("deep" unconsciousness) vs. Pre-ROC ("light" unconsciousness); and iii) responsiveness (Baseline, Light Sedation, Recovery) vs. unresponsiveness (Unconscious, Pre-ROC). AEC and wPLI yielded different patterns of global connectivity across states of consciousness, with AEC showing the strongest network connectivity during the Unconscious epoch, and wPLI showing the strongest connectivity during full consciousness (i.e., Baseline and Recovery). Both measures also demonstrated differential predictive contributions across participants and used different brain regions for classification. AEC showed higher classification accuracy overall, particularly for distinguishing anesthetic-induced unconsciousness from Baseline (83.7 ± 0.8%). AEC also showed stronger classification accuracy than wPLI when distinguishing Unconscious from Pre-ROC (i.e., "deep" from "light" unconsciousness) (AEC: 66.3 ± 1.2%; wPLI: 56.2 ± 1.3%), and when distinguishing between responsiveness and unresponsiveness (AEC: 76.0 ± 1.3%; wPLI: 63.6 ± 1.8%). Classification accuracy was not improved compared to AEC when both AEC and wPLI were combined. This analysis of source-localized EEG data demonstrates that envelope- and phase-based FC provide different information about states of consciousness but that, on a group level, AEC is better able to detect relative alterations in brain FC across levels of anesthetic-induced unconsciousness compared to wPLI.
Collapse
|
12
|
Ke M, Li J, Wang L. Alteration in Resting-State EEG Microstates Following 24 Hours of Total Sleep Deprivation in Healthy Young Male Subjects. Front Hum Neurosci 2021; 15:636252. [PMID: 33912019 PMCID: PMC8075097 DOI: 10.3389/fnhum.2021.636252] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 03/15/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: The cognitive effects of total sleep deprivation (TSD) on the brain remain poorly understood. Electroencephalography (EEG) is a very useful tool for detecting spontaneous brain activity in the resting state. Quasi-stable electrical distributions, known as microstates, carry useful information about the dynamics of large-scale brain networks. In this study, microstate analysis was used to study changes in brain activity after 24 h of total sleep deprivation. Participants and Methods: Twenty-seven healthy volunteers were recruited and underwent EEG scans before and after 24 h of TSD. Microstate analysis was applied, and six microstate classes (A–F) were identified. Topographies and temporal parameters of the microstates were compared between the rested wakefulness (RW) and TSD conditions. Results: Microstate class A (a right-anterior to left-posterior orientation of the mapped field) showed lower global explained variance (GEV), frequency of occurrence, and time coverage in TSD than RW, whereas microstate class D (a fronto-central extreme location of the mapped field) displayed higher GEV, frequency of occurrence, and time coverage in TSD compared to RW. Moreover, subjective sleepiness was significantly negatively correlated with the microstate parameters of class A and positively correlated with the microstate parameters of class D. Transition analysis revealed that class B exhibited a higher probability of transition than did classes D and F in TSD compared to RW. Conclusion: The observation suggests alterations of the dynamic brain-state properties of TSD in healthy young male subjects, which may serve as system-level neural underpinnings for cognitive declines in sleep-deprived subjects.
Collapse
Affiliation(s)
- Ming Ke
- College of Computer and Communication, Lanzhou University of Technology, Gansu, China
| | - Jianpan Li
- College of Computer and Communication, Lanzhou University of Technology, Gansu, China.,Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, China
| | - Lubin Wang
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing, China
| |
Collapse
|
13
|
Lombardo D, Cassé-Perrot C, Ranjeva JP, Le Troter A, Guye M, Wirsich J, Payoux P, Bartrés-Faz D, Bordet R, Richardson JC, Felician O, Jirsa V, Blin O, Didic M, Battaglia D. Modular slowing of resting-state dynamic functional connectivity as a marker of cognitive dysfunction induced by sleep deprivation. Neuroimage 2020; 222:117155. [PMID: 32736002 DOI: 10.1016/j.neuroimage.2020.117155] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2020] [Revised: 05/25/2020] [Accepted: 07/07/2020] [Indexed: 11/29/2022] Open
Abstract
Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks -including Rapid Visual Processing (RVP, assessing sustained visual attention)- and dFC speed quantified at the level of functional sub-networks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module.
Collapse
Affiliation(s)
- Diego Lombardo
- Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes (INS) UMR_S 1106, 13005, Marseille, France
| | - Catherine Cassé-Perrot
- Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes (INS) UMR_S 1106, 13005, Marseille, France; Service de Pharmacologie Clinique et Pharmacovigilance, AP-HM, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, CNRS, Centre de Résonance Magnétique et Biologique et Médicale (CRMBM, 7339), Medical School of Marseille, 13005, Marseille, France; Assistance Publique - Hôpitaux de Marseille, Hôpital de la Timone, CEMEREM, Pôle d'Imagerie Médicale, CHU, 13005, Marseille, France
| | - Arnaud Le Troter
- Aix-Marseille Université, CNRS, Centre de Résonance Magnétique et Biologique et Médicale (CRMBM, 7339), Medical School of Marseille, 13005, Marseille, France; Assistance Publique - Hôpitaux de Marseille, Hôpital de la Timone, CEMEREM, Pôle d'Imagerie Médicale, CHU, 13005, Marseille, France
| | - Maxime Guye
- Aix-Marseille Université, CNRS, Centre de Résonance Magnétique et Biologique et Médicale (CRMBM, 7339), Medical School of Marseille, 13005, Marseille, France; Assistance Publique - Hôpitaux de Marseille, Hôpital de la Timone, CEMEREM, Pôle d'Imagerie Médicale, CHU, 13005, Marseille, France
| | - Jonathan Wirsich
- Aix-Marseille Université, CNRS, Centre de Résonance Magnétique et Biologique et Médicale (CRMBM, 7339), Medical School of Marseille, 13005, Marseille, France
| | - Pierre Payoux
- UMR 825 Inserm, Imagerie Cérébrale et Handicaps Neurologiques, Université Toulouse III Paul Sabatier, Toulouse, France
| | - David Bartrés-Faz
- Department of Psychiatry and Clinical Psychobiology, Faculty of Medicine, University of Barcelona and Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Catalunya, Spain
| | - Régis Bordet
- U1171 Inserm, CHU Lille, Degenerative and Vascular Cognitive Disorders, University of Lille, Lille, France
| | - Jill C Richardson
- Neurosciences Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage, UK
| | - Olivier Felician
- Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes (INS) UMR_S 1106, 13005, Marseille, France; APHM, Timone, Service de Neurologie et Neuropsychologie, Hôpital Timone Adultes, Marseille, France
| | - Viktor Jirsa
- Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes (INS) UMR_S 1106, 13005, Marseille, France
| | - Olivier Blin
- Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes (INS) UMR_S 1106, 13005, Marseille, France; Service de Pharmacologie Clinique et Pharmacovigilance, AP-HM, France
| | - Mira Didic
- Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes (INS) UMR_S 1106, 13005, Marseille, France; APHM, Timone, Service de Neurologie et Neuropsychologie, Hôpital Timone Adultes, Marseille, France
| | - Demian Battaglia
- Aix-Marseille Université, Inserm, Institut de Neurosciences des Systèmes (INS) UMR_S 1106, 13005, Marseille, France.
| |
Collapse
|