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Toker D, Pappas I, Lendner JD, Frohlich J, Mateos DM, Muthukumaraswamy S, Carhart-Harris R, Paff M, Vespa PM, Monti MM, Sommer FT, Knight RT, D'Esposito M. Consciousness is supported by near-critical slow cortical electrodynamics. Proc Natl Acad Sci U S A 2022; 119:e2024455119. [PMID: 35145021 PMCID: PMC8851554 DOI: 10.1073/pnas.2024455119] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 12/20/2021] [Indexed: 12/21/2022] Open
Abstract
Mounting evidence suggests that during conscious states, the electrodynamics of the cortex are poised near a critical point or phase transition and that this near-critical behavior supports the vast flow of information through cortical networks during conscious states. Here, we empirically identify a mathematically specific critical point near which waking cortical oscillatory dynamics operate, which is known as the edge-of-chaos critical point, or the boundary between stability and chaos. We do so by applying the recently developed modified 0-1 chaos test to electrocorticography (ECoG) and magnetoencephalography (MEG) recordings from the cortices of humans and macaques across normal waking, generalized seizure, anesthesia, and psychedelic states. Our evidence suggests that cortical information processing is disrupted during unconscious states because of a transition of low-frequency cortical electric oscillations away from this critical point; conversely, we show that psychedelics may increase the information richness of cortical activity by tuning low-frequency cortical oscillations closer to this critical point. Finally, we analyze clinical electroencephalography (EEG) recordings from patients with disorders of consciousness (DOC) and show that assessing the proximity of slow cortical oscillatory electrodynamics to the edge-of-chaos critical point may be useful as an index of consciousness in the clinical setting.
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Affiliation(s)
- Daniel Toker
- Department of Psychology, University of California, Los Angeles, CA 90095;
| | - Ioannis Pappas
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94704
- Department of Psychology, University of California, Berkeley, CA 94704
- Laboratory of Neuro Imaging, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033
| | - Janna D Lendner
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94704
- Department of Anesthesiology and Intensive Care, University Medical Center, 72076 Tübingen, Germany
| | - Joel Frohlich
- Department of Psychology, University of California, Los Angeles, CA 90095
| | - Diego M Mateos
- Consejo Nacional de Investigaciones Científicas y Técnicas de Argentina, C1425 Buenos Aires, Argentina
- Facultad de Ciencia y Tecnología, Universidad Autónoma de Entre Ríos, E3202 Paraná, Entre Ríos, Argentina
- Grupo de Análisis de Neuroimágenes, Instituo de Matemática Aplicada del Litoral, S3000 Santa Fe, Argentina
| | - Suresh Muthukumaraswamy
- School of Pharmacy, Faculty of Medical and Health Sciences, The University of Auckland, 1010 Auckland, New Zealand
| | - Robin Carhart-Harris
- Neuropsychopharmacology Unit, Centre for Psychiatry, Imperial College London, London SW7 2AZ, United Kingdom
- Centre for Psychedelic Research, Department of Psychiatry, Imperial College London, London SW7 2AZ, United Kingdom
| | - Michelle Paff
- Department of Neurological Surgery, University of California, Irvine, CA 92697
| | - Paul M Vespa
- Brain Injury Research Center, Department of Neurosurgery, University of California, Los Angeles, CA 90095
| | - Martin M Monti
- Department of Psychology, University of California, Los Angeles, CA 90095
- Brain Injury Research Center, Department of Neurosurgery, University of California, Los Angeles, CA 90095
| | - Friedrich T Sommer
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94704
- Redwood Center for Theoretical Neuroscience, University of California, Berkeley, CA 94704
| | - Robert T Knight
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94704
- Department of Psychology, University of California, Berkeley, CA 94704
| | - Mark D'Esposito
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94704
- Department of Psychology, University of California, Berkeley, CA 94704
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Hansson JHS. A hypothesis regarding how sleep can calibrate neuronal excitability in the central nervous system and thereby offer stability, sensitivity and the best possible cognitive function. Med Hypotheses 2019; 131:109307. [PMID: 31443755 DOI: 10.1016/j.mehy.2019.109307] [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: 03/25/2019] [Revised: 06/20/2019] [Accepted: 07/08/2019] [Indexed: 11/17/2022]
Abstract
The function of sleep in mammal and other vertebrates is one of the great mysteries of biology. Many hypotheses have been proposed, but few of these have made even the slightest attempt to explain the essence of sleep - the uncompromising need for reversible unconsciousness. During sleep, epiphenomena - often of a somatic character - occur, but these cannot explain the core function of sleep. One answer could be hidden in the observations made for long periods of time of the function of the central nervous system (CNS). The CNS is faced with conflicting requirements on stability and excitability. A high level of excitability is desirable, and is also a prerequisite for sensitivity and quick reaction times; however, it can also lead to instability and the risk of feedback, with life-threatening epileptic seizures. Activity-dependent negative feedback in neuronal excitability improves stability in the short term, but not to the degree that is required. A hypothesis is presented here demonstrating how calibration of individual neurons - an activity which occurs only during sleep - can establish the balanced and highest possible excitability while also preserving stability in the CNS. One example of a possible mechanism is the observation of slow oscillations in EEGs made on birds and mammals during slow wave sleep. Calibration to a genetically determined level of excitability could take place in individual neurons during the slow oscillation. This is only possible offline, which explains the need for sleep. The hypothesis can explain phenomena such as the need for unconsciousness during sleep, with the disconnection of sensory stimuli, slow EEG oscillations, the relationship of sleep and epilepsy, age, the effects of sleep on neuronal firing rate and the effects of sleep deprivation and sleep homeostasis. This is with regard primarily to mammals, including humans, but also all other vertebrates.
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Maksimov A, Diesmann M, van Albada SJ. Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models. Front Comput Neurosci 2018; 12:44. [PMID: 30042668 PMCID: PMC6048296 DOI: 10.3389/fncom.2018.00044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Accepted: 05/25/2018] [Indexed: 11/13/2022] Open
Abstract
During ongoing and Up state activity, cortical circuits manifest a set of dynamical features that are conserved across these states. The present work systematizes these phenomena by three notions: excitability, the ability to sustain activity without external input; balance, precise coordination of excitatory and inhibitory neuronal inputs; and stability, maintenance of activity at a steady level. Slice preparations exhibiting Up states demonstrate that balanced activity can be maintained by small local circuits. While computational models of cortical circuits have included different combinations of excitability, balance, and stability, they have done so without a systematic quantitative comparison with experimental data. Our study provides quantitative criteria for this purpose, by analyzing in-vitro and in-vivo neuronal activity and characterizing the dynamics on the neuronal and population levels. The criteria are defined with a tolerance that allows for differences between experiments, yet are sufficient to capture commonalities between persistently depolarized cortical network states and to help validate computational models of cortex. As test cases for the derived set of criteria, we analyze three widely used models of cortical circuits and find that each model possesses some of the experimentally observed features, but none satisfies all criteria simultaneously, showing that the criteria are able to identify weak spots in computational models. The criteria described here form a starting point for the systematic validation of cortical neuronal network models, which will help improve the reliability of future models, and render them better building blocks for larger models of the brain.
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Affiliation(s)
- Andrei Maksimov
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I (INM-10), Jülich Research Centre, Jülich, Germany
| | - Markus Diesmann
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I (INM-10), Jülich Research Centre, Jülich, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.,Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany
| | - Sacha J van Albada
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA BRAIN Institute I (INM-10), Jülich Research Centre, Jülich, Germany
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Sykes M, Matheson NA, Brownjohn PW, Tang AD, Rodger J, Shemmell JBH, Reynolds JNJ. Differences in Motor Evoked Potentials Induced in Rats by Transcranial Magnetic Stimulation under Two Separate Anesthetics: Implications for Plasticity Studies. Front Neural Circuits 2016; 10:80. [PMID: 27766073 PMCID: PMC5052269 DOI: 10.3389/fncir.2016.00080] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Accepted: 09/26/2016] [Indexed: 11/25/2022] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is primarily used in humans to change the state of corticospinal excitability. To assess the efficacy of different rTMS stimulation protocols, motor evoked potentials (MEPs) are used as a readout due to their non-invasive nature. Stimulation of the motor cortex produces a response in a targeted muscle, and the amplitude of this twitch provides an indirect measure of the current state of the cortex. When applied to the motor cortex, rTMS can alter MEP amplitude, however, results are variable between participants and across studies. In addition, the mechanisms underlying any change and its locus are poorly understood. In order to better understand these effects, MEPs have been investigated in vivo in animal models, primarily in rats. One major difference in protocols between rats and humans is the use of general anesthesia in animal experiments. Anesthetics are known to affect plasticity-like mechanisms and so may contaminate the effects of an rTMS protocol. In the present study, we explored the effect of anesthetic on MEP amplitude, recorded before and after intermittent theta burst stimulation (iTBS), a patterned rTMS protocol with reported facilitatory effects. MEPs were assessed in the brachioradialis muscle of the upper forelimb under two anesthetics: a xylazine/zoletil combination and urethane. We found MEPs could be induced under both anesthetics, with no differences in the resting motor threshold or the average baseline amplitudes. However, MEPs were highly variable between animals under both anesthetics, with the xylazine/zoletil combination showing higher variability and most prominently a rise in amplitude across the baseline recording period. Interestingly, application of iTBS did not facilitate MEP amplitude under either anesthetic condition. Although it is important to underpin human application of TMS with mechanistic examination of effects in animals, caution must be taken when selecting an anesthetic and in interpreting results during prolonged TMS recording.
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Affiliation(s)
- Matthew Sykes
- Brain Health Research Centre and Brain Research New Zealand Centre of Research ExcellenceDunedin, New Zealand; Department of Anatomy, University of OtagoDunedin, New Zealand; Experimental and Regenerative Neuroscience, School of Animal Biology, University of Western AustraliaPerth, WA, Australia
| | - Natalie A Matheson
- Brain Health Research Centre and Brain Research New Zealand Centre of Research ExcellenceDunedin, New Zealand; Department of Anatomy, University of OtagoDunedin, New Zealand
| | - Philip W Brownjohn
- Brain Health Research Centre and Brain Research New Zealand Centre of Research ExcellenceDunedin, New Zealand; School of Physical Education, Sport and Exercise Sciences, University of OtagoDunedin, New Zealand
| | - Alexander D Tang
- Experimental and Regenerative Neuroscience, School of Animal Biology, University of Western Australia Perth, WA, Australia
| | - Jennifer Rodger
- Experimental and Regenerative Neuroscience, School of Animal Biology, University of Western Australia Perth, WA, Australia
| | - Jonathan B H Shemmell
- Brain Health Research Centre and Brain Research New Zealand Centre of Research ExcellenceDunedin, New Zealand; School of Physical Education, Sport and Exercise Sciences, University of OtagoDunedin, New Zealand
| | - John N J Reynolds
- Brain Health Research Centre and Brain Research New Zealand Centre of Research ExcellenceDunedin, New Zealand; Department of Anatomy, University of OtagoDunedin, New Zealand
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Weigenand A, Schellenberger Costa M, Ngo HVV, Claussen JC, Martinetz T. Characterization of K-complexes and slow wave activity in a neural mass model. PLoS Comput Biol 2014; 10:e1003923. [PMID: 25392991 PMCID: PMC4230734 DOI: 10.1371/journal.pcbi.1003923] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2014] [Accepted: 09/19/2014] [Indexed: 11/18/2022] Open
Abstract
NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep.
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Affiliation(s)
- Arne Weigenand
- Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany
- Graduate School for Computing in Medicine and Life Science, University of Lübeck, Lübeck, Germany
| | - Michael Schellenberger Costa
- Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Hong-Viet Victor Ngo
- Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany
- Graduate School for Computing in Medicine and Life Science, University of Lübeck, Lübeck, Germany
- Institute for Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Jens Christian Claussen
- Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany
- Computational Systems Biology, Jacobs University Bremen, Bremen, Germany
| | - Thomas Martinetz
- Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany
- Graduate School for Computing in Medicine and Life Science, University of Lübeck, Lübeck, Germany
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Garcia-Rodriguez P, Hutt A. Bursting suppression in propofol-induced general anesthesia as bi-stability in a non-linear neural mass model. BMC Neurosci 2014. [PMCID: PMC4125039 DOI: 10.1186/1471-2202-15-s1-p139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Dadok VM, Kirsch HE, Sleigh JW, Lopour BA, Szeri AJ. A probabilistic framework for a physiological representation of dynamically evolving sleep state. J Comput Neurosci 2013; 37:105-24. [PMID: 24363031 DOI: 10.1007/s10827-013-0489-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2013] [Revised: 10/19/2013] [Accepted: 11/14/2013] [Indexed: 12/29/2022]
Abstract
This work presents a probabilistic method for mapping human sleep electroencephalogram (EEG) signals onto a state space based on a biologically plausible mathematical model of the cortex. From a noninvasive EEG signal, this method produces physiologically meaningful pathways of the cortical state over a night of sleep. We propose ways in which these pathways offer insights into sleep-related conditions, functions, and complex pathologies. To address explicitly the noisiness of the EEG signal and the stochastic nature of the mathematical model, we use a probabilistic Bayesian framework to map each EEG epoch to a distribution of likelihoods over all model sleep states. We show that the mapping produced from human data robustly separates rapid eye movement sleep (REM) from slow wave sleep (SWS). A Hidden Markov Model (HMM) is incorporated to improve the path results using the prior knowledge that cortical physiology has temporal continuity.
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Affiliation(s)
- Vera M Dadok
- Department of Mechanical Engineering, University of California, Berkeley, CA, 94720, USA,
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Thalamic activation modulates the responses of neurons in rat primary auditory cortex: an in vivo intracellular recording study. PLoS One 2012; 7:e34837. [PMID: 22514672 PMCID: PMC3325946 DOI: 10.1371/journal.pone.0034837] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2011] [Accepted: 03/06/2012] [Indexed: 11/28/2022] Open
Abstract
Auditory cortical plasticity can be induced through various approaches. The medial geniculate body (MGB) of the auditory thalamus gates the ascending auditory inputs to the cortex. The thalamocortical system has been proposed to play a critical role in the responses of the auditory cortex (AC). In the present study, we investigated the cellular mechanism of the cortical activity, adopting an in vivo intracellular recording technique, recording from the primary auditory cortex (AI) while presenting an acoustic stimulus to the rat and electrically stimulating its MGB. We found that low-frequency stimuli enhanced the amplitudes of sound-evoked excitatory postsynaptic potentials (EPSPs) in AI neurons, whereas high-frequency stimuli depressed these auditory responses. The degree of this modulation depended on the intensities of the train stimuli as well as the intervals between the electrical stimulations and their paired sound stimulations. These findings may have implications regarding the basic mechanisms of MGB activation of auditory cortical plasticity and cortical signal processing.
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