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Zhang L, Fang K, Tao S, Deng L, Li H, Cao Y, Wang L, Yu F, Gu E. Electroencephalography-demonstrated mechanisms of dexmedetomidine-mediated deepening of propofol anesthesia: an observational study. Perioper Med (Lond) 2021; 10:44. [PMID: 34879867 PMCID: PMC8656083 DOI: 10.1186/s13741-021-00213-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 08/08/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Although dexmedetomidine (Dex) is known to reduce bispectral index (BIS) values and propofol dosage, there is little information regarding raw electroencephalography (EEG) changes related to Dex deepening of propofol general anesthesia (GA). This study investigated the Dex effects on propofol GA via analysis of EEG changes. METHODS A study cohort of 21 surgical patients (age range, 20-60 years) categorized as American Society of Anesthesiologists (ASA) class I or II was enrolled. We used time-varying spectral and bicoherence methods to compare electroencephalogram signatures 5 min before versus 10 min after intravenous Dex injection under propofol GA. The means and medians are reported with 95% confidence intervals (CIs) and inter-quartile ranges (IQRs), respectively. RESULTS Dex augmented the slow waves power and theta (θ) oscillation bicoherence peak from a mean (95% CI) of 22.1% (19.0, 25.2) to 25.2% (21.8, 28.6). Meanwhile, Dex reduced alpha (α) peak power and bicoherence from 3.5 dB (1.0, 6.0) and 41.5% (34.0, 49.0) to 1.7 dB (- 0.6, 4.0) and 35.4% (29.0, 41.8), respectively, while diminishing the median frequency of α oscillation peak values and the mean frequency of α peaks in bicoherence spectra from 12.0 Hz (IQR 11.2, 12.6) and 11.7 Hz (11.3, 12.2) to 11.1 Hz (IQR 10.3, 11.8) and 11.2 Hz (10.9, 11.6), respectively. CONCLUSIONS Profound EEG changes support the supposition that Dex enhances propofol-induced GA from a moderate to a deeper state. The present findings provide a theoretical basis and reference regarding protocols aimed at reducing anesthetic/sedative dosage while maintaining sufficient depth of GA. CLINICAL TRIAL REGISTRATION ChiCTR, ChiCTR1900026955 . Registered on 27 October 2019.
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Affiliation(s)
- Lei Zhang
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China
| | - Kun Fang
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.,First School of Clinical Medicine, Anhui Medical University, Hefei, Anhui, China
| | - Shengwei Tao
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.,First School of Clinical Medicine, Anhui Medical University, Hefei, Anhui, China
| | - Liyun Deng
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.,First School of Clinical Medicine, Anhui Medical University, Hefei, Anhui, China
| | - Hua Li
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.,First School of Clinical Medicine, Anhui Medical University, Hefei, Anhui, China
| | - Yuanyuan Cao
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China
| | - Lei Wang
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China
| | - Fengqiong Yu
- School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei, Anhui, China
| | - Erwei Gu
- Department of Anesthesiology, The First Affiliated Hospital of Anhui Medical University, Anhui Medical University, Hefei, Anhui, China.
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Sinha N, Wang Y, Dauwels J, Kaiser M, Thesen T, Forsyth R, Taylor PN. Computer modelling of connectivity change suggests epileptogenesis mechanisms in idiopathic generalised epilepsy. NEUROIMAGE-CLINICAL 2019; 21:101655. [PMID: 30685702 PMCID: PMC6356007 DOI: 10.1016/j.nicl.2019.101655] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 12/21/2018] [Accepted: 01/03/2019] [Indexed: 12/14/2022]
Abstract
Patients with idiopathic generalised epilepsy (IGE) typically have normal conventional magnetic resonance imaging (MRI), hence diagnosis based on MRI is challenging. Anatomical abnormalities underlying brain dysfunctions in IGE are unclear and their relation to the pathomechanisms of epileptogenesis is poorly understood. In this study, we applied connectometry, an advanced quantitative neuroimaging technique for investigating localised changes in white-matter tissues in vivo. Analysing white matter structures of 32 subjects we incorporated our in vivo findings in a computational model of seizure dynamics to suggest a plausible mechanism of epileptogenesis. Patients with IGE have significant bilateral alterations in major white-matter fascicles. In the cingulum, fornix, and superior longitudinal fasciculus, tract integrity is compromised, whereas in specific parts of tracts between thalamus and the precentral gyrus, tract integrity is enhanced in patients. Combining these alterations in a logistic regression model, we computed the decision boundary that discriminated patients and controls. The computational model, informed with the findings on the tract abnormalities, specifically highlighted the importance of enhanced cortico-reticular connections along with impaired cortico-cortical connections in inducing pathological seizure-like dynamics. We emphasise taking directionality of brain connectivity into consideration towards understanding the pathological mechanisms; this is possible by combining neuroimaging and computational modelling. Our imaging evidence of structural alterations suggest the loss of cortico-cortical and enhancement of cortico-thalamic fibre integrity in IGE. We further suggest that impaired connectivity from cortical regions to the thalamic reticular nucleus offers a therapeutic target for selectively modifying the brain circuit for reversing the mechanisms leading to epileptogenesis. Significant focal alterations along major white-matter fascicles in IGE patients are characterised. Increased white matter integrity found in thalamo-cortical connections. Decreased white matter integrity found in cortico-cortical connections. Disease mechanism is investigated by combining the neuroimaging findings with a dynamical model of seizure activity. Model implicates cortical projections to the thalamic reticular nucleus in IGE.
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Affiliation(s)
- Nishant Sinha
- Institute of Neuroscience, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.
| | - Yujiang Wang
- Institute of Neuroscience, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK; Institute of Neurology, University College London, UK
| | - Justin Dauwels
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore
| | - Marcus Kaiser
- Institute of Neuroscience, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK
| | - Thomas Thesen
- Department of Neurology, School of Medicine, New York University, NY, USA; Department of Physiology and Neuroscience, St. Georges University, Grenada, West Indies
| | - Rob Forsyth
- Institute of Neuroscience, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Peter Neal Taylor
- Institute of Neuroscience, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK; Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, UK; Institute of Neurology, University College London, UK.
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Fan D, Wang Q, Su J, Xi H. Stimulus-induced transitions between spike-wave discharges and spindles with the modulation of thalamic reticular nucleus. J Comput Neurosci 2017; 43:203-225. [PMID: 28939929 DOI: 10.1007/s10827-017-0658-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2017] [Revised: 08/11/2017] [Accepted: 09/04/2017] [Indexed: 12/19/2022]
Abstract
It is believed that thalamic reticular nucleus (TRN) controls spindles and spike-wave discharges (SWD) in seizure or sleeping processes. The dynamical mechanisms of spatiotemporal evolutions between these two types of activity, however, are not well understood. In light of this, we first use a single-compartment thalamocortical neural field model to investigate the effects of TRN on occurrence of SWD and its transition. Results show that the increasing inhibition from TRN to specific relay nuclei (SRN) can lead to the transition of system from SWD to slow-wave oscillation. Specially, it is shown that stimulations applied in the cortical neuronal populations can also initiate the SWD and slow-wave oscillation from the resting states under the typical inhibitory intensity from TRN to SRN. Then, we expand into a 3-compartment coupled thalamocortical model network in linear and circular structures, respectively, to explore the spatiotemporal evolutions of wave states in different compartments. The main results are: (i) for the open-ended model network, SWD induced by stimulus in the first compartment can be transformed into sleep-like slow UP-DOWN and spindle states as it propagates into the downstream compartments; (ii) for the close-ended model network, weak stimulations performed in the first compartment can result in the consistent experimentally observed spindle oscillations in all three compartments; in contrast, stronger periodic single-pulse stimulations applied in the first compartment can induce periodic transitions between SWD and spindle oscillations. Detailed investigations reveal that multi-attractor coexistence mechanism composed of SWD, spindles and background state underlies these state evolutions. What's more, in order to demonstrate the state evolution stability with respect to the topological structures of neural network, we further expand the 3-compartment coupled network into 10-compartment coupled one, with linear and circular structures, and nearest-neighbor (NN) coupled network as well as its realization of small-world (SW) topology via random rewiring, respectively. Interestingly, for the cases of linear and circular connetivities, qualitatively similar results were obtained in addition to the more irregularity of firings. However, SWD can be eventually transformed into the consistent low-amplitude oscillations for both NN and SW networks. In particular, SWD evolves into the slow spindling oscillations and background tonic oscillations within the NN and SW network, respectively. Our modeling and simulation studies highlight the effect of network topology in the evolutions of SWD and spindling oscillations, which provides new insights into the mechanisms of cortical seizures development.
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Affiliation(s)
- Denggui Fan
- School of Mathematics and Physics, University of Science and Technology Beijing, Beijing, 100083, China
| | - Qingyun Wang
- Department of Dynamics and Control, Beihang University, Beijing, 100191, China.
| | - Jianzhong Su
- Department of Mathematics, University of Texas at Arlington, Arlington, TX, 76019-0408, USA
| | - Hongguang Xi
- Department of Mathematics, University of Texas at Arlington, Arlington, TX, 76019-0408, USA
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Wang Y, Trevelyan AJ, Valentin A, Alarcon G, Taylor PN, Kaiser M. Mechanisms underlying different onset patterns of focal seizures. PLoS Comput Biol 2017; 13:e1005475. [PMID: 28472032 PMCID: PMC5417416 DOI: 10.1371/journal.pcbi.1005475] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Accepted: 03/23/2017] [Indexed: 02/07/2023] Open
Abstract
Focal seizures are episodes of pathological brain activity that appear to arise from a localised area of the brain. The onset patterns of focal seizure activity have been studied intensively, and they have largely been distinguished into two types-low amplitude fast oscillations (LAF), or high amplitude spikes (HAS). Here we explore whether these two patterns arise from fundamentally different mechanisms. Here, we use a previously established computational model of neocortical tissue, and validate it as an adequate model using clinical recordings of focal seizures. We then reproduce the two onset patterns in their most defining properties and investigate the possible mechanisms underlying the different focal seizure onset patterns in the model. We show that the two patterns are associated with different mechanisms at the spatial scale of a single ECoG electrode. The LAF onset is initiated by independent patches of localised activity, which slowly invade the surrounding tissue and coalesce over time. In contrast, the HAS onset is a global, systemic transition to a coexisting seizure state triggered by a local event. We find that such a global transition is enabled by an increase in the excitability of the "healthy" surrounding tissue, which by itself does not generate seizures, but can support seizure activity when incited. In our simulations, the difference in surrounding tissue excitability also offers a simple explanation of the clinically reported difference in surgical outcomes. Finally, we demonstrate in the model how changes in tissue excitability could be elucidated, in principle, using active stimulation. Taken together, our modelling results suggest that the excitability of the tissue surrounding the seizure core may play a determining role in the seizure onset pattern, as well as in the surgical outcome.
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Affiliation(s)
- Yujiang Wang
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neurology, University College London, London, United Kingdom
| | - Andrew J Trevelyan
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Antonio Valentin
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Gonzalo Alarcon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Comprehensive Epilepsy Center, Neuroscience Institute, Academic Health Systems, Hamad Medical Corporation, Doha, Qatar
| | - Peter N Taylor
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Kaiser
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, United Kingdom
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5
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Baier G, Taylor PN, Wang Y. Understanding Epileptiform After-Discharges as Rhythmic Oscillatory Transients. Front Comput Neurosci 2017; 11:25. [PMID: 28458634 PMCID: PMC5394159 DOI: 10.3389/fncom.2017.00025] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2017] [Accepted: 03/29/2017] [Indexed: 01/24/2023] Open
Abstract
Electro-cortical activity in patients with epilepsy may show abnormal rhythmic transients in response to stimulation. Even when using the same stimulation parameters in the same patient, wide variability in the duration of transient response has been reported. These transients have long been considered important for the mapping of the excitability levels in the epileptic brain but their dynamic mechanism is still not well understood. To investigate the occurrence of abnormal transients dynamically, we use a thalamo-cortical neural population model of epileptic spike-wave activity and study the interaction between slow and fast subsystems. In a reduced version of the thalamo-cortical model, slow wave oscillations arise from a fold of cycles (FoC) bifurcation. This marks the onset of a region of bistability between a high amplitude oscillatory rhythm and the background state. In vicinity of the bistability in parameter space, the model has excitable dynamics, showing prolonged rhythmic transients in response to suprathreshold pulse stimulation. We analyse the state space geometry of the bistable and excitable states, and find that the rhythmic transient arises when the impending FoC bifurcation deforms the state space and creates an area of locally reduced attraction to the fixed point. This area essentially allows trajectories to dwell there before escaping to the stable steady state, thus creating rhythmic transients. In the full thalamo-cortical model, we find a similar FoC bifurcation structure. Based on the analysis, we propose an explanation of why stimulation induced epileptiform activity may vary between trials, and predict how the variability could be related to ongoing oscillatory background activity. We compare our dynamic mechanism with other mechanisms (such as a slow parameter change) to generate excitable transients, and we discuss the proposed excitability mechanism in the context of stimulation responses in the epileptic cortex.
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Affiliation(s)
- Gerold Baier
- Cell and Developmental Biology, University College LondonLondon, UK
| | - Peter N Taylor
- Institute of Neuroscience, Newcastle UniversityNewcastle upon Tyne, UK.,Interdisciplinary Computing and Complex BioSystems (ICOS), School of Computing Science, Newcastle UniversityNewcastle, UK.,Institute of Neurology, University College LondonLondon, UK
| | - Yujiang Wang
- Institute of Neuroscience, Newcastle UniversityNewcastle upon Tyne, UK.,Interdisciplinary Computing and Complex BioSystems (ICOS), School of Computing Science, Newcastle UniversityNewcastle, UK.,Institute of Neurology, University College LondonLondon, UK
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6
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Yousif N, Mace M, Pavese N, Borisyuk R, Nandi D, Bain P. A Network Model of Local Field Potential Activity in Essential Tremor and the Impact of Deep Brain Stimulation. PLoS Comput Biol 2017; 13:e1005326. [PMID: 28068428 PMCID: PMC5261813 DOI: 10.1371/journal.pcbi.1005326] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 01/24/2017] [Accepted: 12/20/2016] [Indexed: 11/27/2022] Open
Abstract
Essential tremor (ET), a movement disorder characterised by an uncontrollable shaking of the affected body part, is often professed to be the most common movement disorder, affecting up to one percent of adults over 40 years of age. The precise cause of ET is unknown, however pathological oscillations of a network of a number of brain regions are implicated in leading to the disorder. Deep brain stimulation (DBS) is a clinical therapy used to alleviate the symptoms of a number of movement disorders. DBS involves the surgical implantation of electrodes into specific nuclei in the brain. For ET the targeted region is the ventralis intermedius (Vim) nucleus of the thalamus. Though DBS is effective for treating ET, the mechanism through which the therapeutic effect is obtained is not understood. To elucidate the mechanism underlying the pathological network activity and the effect of DBS on such activity, we take a computational modelling approach combined with electrophysiological data. The pathological brain activity was recorded intra-operatively via implanted DBS electrodes, whilst simultaneously recording muscle activity of the affected limbs. We modelled the network hypothesised to underlie ET using the Wilson-Cowan approach. The modelled network exhibited oscillatory behaviour within the tremor frequency range, as did our electrophysiological data. By applying a DBS-like input we suppressed these oscillations. This study shows that the dynamics of the ET network support oscillations at the tremor frequency and the application of a DBS-like input disrupts this activity, which could be one mechanism underlying the therapeutic benefit. Essential tremor (ET) is acknowledged to be the most common movement disorder affecting 1% of the population. Although the underlying mechanisms remain elusive, the thalamus, cortex and cerebellum are implicated in the underlying pathology. More recently, it has been shown that ET can be successfully treated by deep brain stimulation (DBS). This clinical treatment involves the surgical implantation of electrodes into the brain, through which current is applied. However, the mechanisms of how DBS achieves clinical benefit continue to be debated. A key question is whether ET can be modeled as a pathological network behavior as has been suggested previously. If so, we can then ask how DBS would modulate this brain activity. Our study combines: (i) simultaneous electrophysiological recordings from the brain and muscle; (ii) computational modelling; (iii) mathematical analysis. We found that the network supports oscillations in the tremor range, and the application of high frequency DBS switches this to low amplitude, high-frequency activity. We propose that our model can be used to predict DBS parameter settings that suppress pathological network activity and consequently tremor. In summary, we provide the first population level model of essential tremor including the effect of DBS on network behaviour.
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Affiliation(s)
- Nada Yousif
- Division of Brain Sciences, Imperial College London, London, United Kingdom
- School of Engineering and Technology, University of Hertfordshire, Hatfield, United Kingdom
- * E-mail:
| | - Michael Mace
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Nicola Pavese
- Division of Brain Sciences, Imperial College London, London, United Kingdom
| | - Roman Borisyuk
- School of Computing and Mathematics, University of Plymouth, Plymouth, United Kingdom
- Institute of Mathematical Problems of Biology of RAS, The Branch of Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Moscow, Russia
| | - Dipankar Nandi
- Division of Brain Sciences, Imperial College London, London, United Kingdom
| | - Peter Bain
- Division of Brain Sciences, Imperial College London, London, United Kingdom
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Taylor PN, Wang Y, Goodfellow M, Dauwels J, Moeller F, Stephani U, Baier G. A computational study of stimulus driven epileptic seizure abatement. PLoS One 2014; 9:e114316. [PMID: 25531883 PMCID: PMC4273970 DOI: 10.1371/journal.pone.0114316] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2014] [Accepted: 11/05/2014] [Indexed: 01/24/2023] Open
Abstract
Active brain stimulation to abate epileptic seizures has shown mixed success. In spike-wave (SW) seizures, where the seizure and background state were proposed to coexist, single-pulse stimulations have been suggested to be able to terminate the seizure prematurely. However, several factors can impact success in such a bistable setting. The factors contributing to this have not been fully investigated on a theoretical and mechanistic basis. Our aim is to elucidate mechanisms that influence the success of single-pulse stimulation in noise-induced SW seizures. In this work, we study a neural population model of SW seizures that allows the reconstruction of the basin of attraction of the background activity as a four dimensional geometric object. For the deterministic (noise-free) case, we show how the success of response to stimuli depends on the amplitude and phase of the SW cycle, in addition to the direction of the stimulus in state space. In the case of spontaneous noise-induced seizures, the basin becomes probabilistic introducing some degree of uncertainty to the stimulation outcome while maintaining qualitative features of the noise-free case. Additionally, due to the different time scales involved in SW generation, there is substantial variation between SW cycles, implying that there may not be a fixed set of optimal stimulation parameters for SW seizures. In contrast, the model suggests an adaptive approach to find optimal stimulation parameters patient-specifically, based on real-time estimation of the position in state space. We discuss how the modelling work can be exploited to rationally design a successful stimulation protocol for the abatement of SW seizures using real-time SW detection.
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Affiliation(s)
- Peter Neal Taylor
- School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Yujiang Wang
- School of Computing Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Marc Goodfellow
- College of Engineering, University of Exeter, Exeter, United Kingdom
| | - Justin Dauwels
- School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore
| | - Friederike Moeller
- Department of Neuropediatrics, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Ulrich Stephani
- Department of Neuropediatrics, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Gerold Baier
- Cell and Developmental Biology, University College London, London, United Kingdom
- * E-mail:
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Srinivasan R, Thorpe S, Nunez PL. Top-down influences on local networks: basic theory with experimental implications. Front Comput Neurosci 2013; 7:29. [PMID: 23616762 PMCID: PMC3629312 DOI: 10.3389/fncom.2013.00029] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2012] [Accepted: 03/19/2013] [Indexed: 11/25/2022] Open
Abstract
The response of a population of cortical neurons to an external stimulus depends not only on the receptive field properties of the neurons, but also the level of arousal and attention or goal-oriented cognitive biases that guide information processing. These top-down effects on cortical neurons bias the output of the neurons and affect behavioral outcomes such as stimulus detection, discrimination, and response time. In any physiological study, neural dynamics are observed in a specific brain state; the background state partly determines neuronal excitability. Experimental studies in humans and animal models have also demonstrated that slow oscillations (typically in the alpha or theta bands) modulate the fast oscillations (gamma band) associated with local networks of neurons. Cross-frequency interaction is of interest as a mechanism for top-down or bottom up interactions between systems at different spatial scales. We develop a generic model of top-down influences on local networks appropriate for comparison with EEG. EEG provides excellent temporal resolution to investigate neuronal oscillations but is space-averaged on the cm scale. Thus, appropriate EEG models are developed in terms of population synaptic activity. We used the Wilson–Cowan population model to investigate fast (gamma band) oscillations generated by a local network of excitatory and inhibitory neurons. We modified the Wilson–Cowan equations to make them more physiologically realistic by explicitly incorporating background state variables into the model. We found that the population response is strongly influenced by the background state. We apply the model to reproduce the modulation of gamma rhythms by theta rhythms as has been observed in animal models and human ECoG and EEG studies. The concept of a dynamic background state presented here using the Wilson–Cowan model can be readily applied to incorporate top-down modulation in more detailed models of specific cortical systems.
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Affiliation(s)
- Ramesh Srinivasan
- Department of Cognitive Sciences, University of California Irvine, CA, USA ; Department of Biomedical Engineering, University of California Irvine, CA, USA ; Institute for Mathematical Behavioral Sciences, University of California Irvine, CA, USA
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Pikov V, McCreery DB. Spinal hyperexcitability and bladder hyperreflexia during reversible frontal cortical inactivation induced by low-frequency electrical stimulation in the cat. J Neurotrauma 2009; 26:109-19. [PMID: 19119915 DOI: 10.1089/neu.2008.0584] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Spinal hyperexcitability and hyperreflexia gradually develop in the majority of stroke patients. These pathologies develop as a result of reduced cortical modulation of spinal reflexes, mediated largely indirectly via relays in the brainstem and other subcortical structures. Cortical control of spinal reflexes is markedly different in small animals, such as rodents, while in some larger species, such as cats, it is more comparable to that in humans. In this study, we developed a novel model of stroke in the cat, with controllable and reversible inhibition of cortical neuronal activity appearing approximately 1h after initiation of low-frequency electrical stimulation in the frontal cerebral cortex, evidenced by a large increase in the alpha frequency band (7-14 Hz) of the frontal electrocorticographic signal. Hyperreflexia of the urinary bladder developed 3h or more after induction of reversible cortical inactivation with optimized stimulation parameters (frequency of 1-2 Hz, amplitude of 10 mA, applied for 30 min). The bladder hyperreflexia persisted for at least 8h, and disappeared within 24h. At the S2 level of the spinal cord, where neural circuits mediating micturition and other pelvic reflexes reside, we have recorded an increase in neuronal activity correlated with the development of hyperreflexia. The low-frequency stimulation-induced reversible cortical inactivation model of stroke is highly reproducible and allows evaluation of spinal hyperexcitability and hyperreflexia using within-animal comparisons across experimental conditions, which can be of great value in examination of mechanisms of spinal hyperreflexia following stroke or brain trauma, and for developing more effective treatments for these conditions.
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Affiliation(s)
- Victor Pikov
- Neural Engineering Program, Huntington Medical Research Institutes, Pasadena, CA 91105, USA.
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Humphries MD, Gurney K, Prescott TJ. Is there a brainstem substrate for action selection? Philos Trans R Soc Lond B Biol Sci 2007; 362:1627-39. [PMID: 17428776 PMCID: PMC2440776 DOI: 10.1098/rstb.2007.2057] [Citation(s) in RCA: 51] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The search for the neural substrate of vertebrate action selection has focused on structures in the forebrain and midbrain, and particularly on the group of sub-cortical nuclei known as the basal ganglia. Yet, the behavioural repertoire of decerebrate and neonatal animals suggests the existence of a relatively self-contained neural substrate for action selection in the brainstem. We propose that the medial reticular formation (mRF) is the substrate's main component and review evidence showing that the mRF's inputs, outputs and intrinsic organization are consistent with the requirements of an action-selection system. The internal architecture of the mRF is composed of interconnected neuron clusters. We present an anatomical model which suggests that the mRF's intrinsic circuitry constitutes a small-world network and extend this result to show that it may have evolved to reduce axonal wiring. Potential configurations of action representation within the internal circuitry of the mRF are then assessed by computational modelling. We present new results demonstrating that each cluster's output is most likely to represent activation of a component action; thus, coactivation of a set of these clusters would lead to the coordinated behavioural response observed in the animal. Finally, we consider the potential integration of the basal ganglia and mRF substrates for selection and suggest that they may collectively form a layered/hierarchical control system.
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Affiliation(s)
- M D Humphries
- Adaptive Behaviour Research Group, Department of Psychology, University of Sheffield, Sheffield S10 2TP, UK.
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Yousif N, Denham M. The role of cortical feedback in the generation of the temporal receptive field responses of lateral geniculate nucleus neurons: a computational modelling study. BIOLOGICAL CYBERNETICS 2007; 97:269-77. [PMID: 17657507 DOI: 10.1007/s00422-007-0171-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2006] [Accepted: 07/02/2007] [Indexed: 05/16/2023]
Abstract
The influence of cortical feedback on thalamic visual responses has been a source of much discussion in recent years. In this study we examine the possible role of cortical feedback in shaping the spatiotemporal receptive field (STRF) responses of thalamocortical (TC) cells in the lateral geniculate nucleus (LGN) of the thalamus. A population-based computational model of the thalamocortical network is used to generate a representation of the STRF response of LGN TC cells within the corticothalamic feedback circuit. The cortical feedback is shown to have little influence on the spatial response properties of the STRF organization. However, the model suggests that cortical feedback may play a key role in modifying the experimentally observed biphasic temporal response property of the STRF, that is, the reversal over time of the polarity of ON and OFF responses of the centre and surround of the receptive field, in particular accounting for the experimentally observed mismatch between retinal cells and TC cells in respect of the magnitude of the second (rebound) phase of the temporal response. The model results also show that this mismatch may result from an anti-phase corticothalamic feedback mechanism.
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Affiliation(s)
- Nada Yousif
- Centre for Computational and Theoretical Neuroscience, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK.
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Hayashi K, Tsuda N, Sawa T, Hagihira S. Ketamine increases the frequency of electroencephalographic bicoherence peak on the alpha spindle area induced with propofol. Br J Anaesth 2007; 99:389-95. [PMID: 17621599 DOI: 10.1093/bja/aem175] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The reticular and thalamocortical system is known to play a prominent role in spindle wave activity, and the spindle wave is related to the sedative effects of anaesthetics. Recently, bispectral analysis of the EEG has been developed as a better method to indicate nonlinear regulation including the thalamocortical system linking to the cortical area. In the present study, in order to explore the interference of ketamine with the nonlinear regulation of the sub-cortical system, we examined the effect of ketamine on spindle alpha waves through the bispectral analysis. METHODS The study included 21 patients. Anaesthesia was induced and maintained using a propofol-TCI system (target-controlled infusion, with target concentration 3.5 microg ml(-1)). An A-2000 BIS monitor was used and the raw EEG signals were collected via an RS232 interface on a personal computer. Bicoherence, the normalized bispectrum, and power spectrum were analysed before and after i.v. administration of 1 mg kg(-1) racemic ketamine. RESULTS Propofol caused alpha peaks in both power and bicoherence spectra, with average frequencies of 10.6 (SD 0.9) Hz and 10.7 (1.0) Hz, respectively. The addition of ketamine significantly shifted each peak to frequencies of 14.4 (1.4) Hz and 13.6 (1.5) Hz, respectively [P < 0.05, mean (SD)]. CONCLUSIONS Ketamine shifted the alpha peaks of bicoherence induced by propofol to higher frequencies. This suggests that ketamine changes the alpha spindle rhythms through the modulation of the nonlinear sub-cortical reverberating network.
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Affiliation(s)
- K Hayashi
- Department of Anesthesiology, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan.
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