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Burlando B, Mucci V, Browne CJ, Losacco S, Indovina I, Marinelli L, Blanchini F, Giordano G. Mal de Debarquement Syndrome explained by a vestibulo-cerebellar oscillator. MATHEMATICAL MEDICINE AND BIOLOGY : A JOURNAL OF THE IMA 2023; 40:96-110. [PMID: 36469499 DOI: 10.1093/imammb/dqac016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 10/25/2022] [Indexed: 12/12/2022]
Abstract
Mal de Debarquement Syndrome (MdDS) is a puzzling central vestibular disorder characterized by a long-lasting perception of oscillatory postural instability that may occur after sea travels or flights. We have postulated that MdDS originates from the post-disembarking persistence of an adaptive internal oscillator consisting of a loop system, involving the right and left vestibular nuclei, and the Purkinje cells of the right and left flocculonodular cerebellar cortex, connected by GABAergic and glutamatergic fibers. We have formulated here a mathematical model of the vestibulo-cerebellar loop system and carried out a computational analysis based on a set of differential equations describing the interactions among the loop elements and containing Hill functions that model input-output firing rates relationships among neurons. The analysis indicates that the system acquires a spontaneous and permanent oscillatory behavior for a decrease of threshold and an increase of sensitivity in neuronal input-output responses. These results suggest a role for synaptic plasticity in MdDS pathophysiology, thus reinforcing our previous hypothesis that MdDS may be the result of excessive synaptic plasticity acting on the vestibulo-cerebellar network during its entraining to an oscillatory environment. Hence, our study points to neuroendocrine pathways that lead to increased synaptic response as possible new therapeutic targets for the clinical treatment of the disorder.
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Affiliation(s)
- Bruno Burlando
- Department of Pharmacy, University of Genova, Viale Benedetto XV 3, 16132 Genova, Italy
| | - Viviana Mucci
- School of Science, Western Sydney University, Penrith NSW 2560, Australia
| | - Cherylea J Browne
- School of Science, Western Sydney University, Penrith NSW 2560, Australia
- Translational Neuroscience Facility, School of Medical Sciences, UNSW Sydney, NSW 2052, Australia
| | - Serena Losacco
- Department of Pharmacy, University of Genova, Viale Benedetto XV 3, 16132 Genova, Italy
| | - Iole Indovina
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, 98125 Messina, Italy
- Neuromotor Physiology Lab, IRCCS Foundation Santa Lucia, via Ardeatina 354, 00179 Rome, Italy
| | - Lucio Marinelli
- DINOGMI University of Genova, Largo Daneo 3, 16132, Genova, Italy
- IRCCS Ospedale Policlinico San Martino, Division of Clinical Neurophysiology, Department of Neuroscience, Largo R. Benzi 10, 16132 Genova, Italy
| | - Franco Blanchini
- Department of Mathematics, Computer Science and Physics, University of Udine, Via delle Scienze 208, 33100 Udine, Italy
| | - Giulia Giordano
- Department of Industrial Engineering, University of Trento, Via Sommarive 9, 38123 Povo (TN), Italy
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2
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Thalamocortical bistable switch as a theoretical model of fibromyalgia pathogenesis inferred from a literature survey. J Comput Neurosci 2022; 50:471-484. [PMID: 35816263 PMCID: PMC9666334 DOI: 10.1007/s10827-022-00826-8] [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: 09/07/2021] [Revised: 05/17/2022] [Accepted: 06/22/2022] [Indexed: 11/25/2022]
Abstract
Fibromyalgia (FM) is an unsolved central pain processing disturbance. We aim to provide a unifying model for FM pathogenesis based on a loop network involving thalamocortical regions, i.e., the ventroposterior lateral thalamus (VPL), the somatosensory cortex (SC), and the thalamic reticular nucleus (TRN). The dynamics of the loop have been described by three differential equations having neuron mean firing rates as variables and containing Hill functions to model mutual interactions among the loop elements. A computational analysis conducted with MATLAB has shown a transition from monostability to bistability of the loop behavior for a weakening of GABAergic transmission between TRN and VPL. This involves the appearance of a high-firing-rate steady state, which becomes dominant and is assumed to represent pathogenic pain processing giving rise to chronic pain. Our model is consistent with a bulk of literature evidence, such as neuroimaging and pharmacological data collected on FM patients, and with correlations between FM and immunoendocrine conditions, such as stress, perimenopause, chronic inflammation, obesity, and chronic dizziness. The model suggests that critical targets for FM treatment are to be found among immunoendocrine pathways leading to GABA/glutamate imbalance having an impact on the thalamocortical system.
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Saponati M, Garcia-Ojalvo J, Cataldo E, Mazzoni A. Thalamocortical Spectral Transmission Relies on Balanced Input Strengths. Brain Topogr 2021; 35:4-18. [PMID: 34089121 PMCID: PMC8813837 DOI: 10.1007/s10548-021-00851-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 05/05/2021] [Indexed: 12/27/2022]
Abstract
The thalamus is a key element of sensory transmission in the brain, as it gates and selects sensory streams through a modulation of its internal activity. A preponderant role in these functions is played by its internal activity in the alpha range ([8–14] Hz), but the mechanism underlying this process is not completely understood. In particular, how do thalamocortical connections convey stimulus driven information selectively over the back-ground of thalamic internally generated activity? Here we investigate this issue with a spiking network model of feedforward connectivity between thalamus and primary sensory cortex reproducing the local field potential of both areas. We found that in a feedforward network, thalamic oscillations in the alpha range do not entrain cortical activity for two reasons: (i) alpha range oscillations are weaker in neurons projecting to the cortex, (ii) the gamma resonance dynamics of cortical networks hampers oscillations over the 10–20 Hz range thus weakening alpha range oscillations. This latter mechanism depends on the balance of the strength of thalamocortical connections toward excitatory and inhibitory neurons in the cortex. Our results highlight the relevance of corticothalamic feedback to sustain alpha range oscillations and pave the way toward an integrated understanding of the sensory streams traveling between the periphery and the cortex.
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Affiliation(s)
- Matteo Saponati
- The Biorobotics Institute, Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, IT, Italy.,Dipartimento di Fisica "E. Fermi", Largo Bruno Pontecorvo 3, 56127, Pisa, IT, Italy
| | - Jordi Garcia-Ojalvo
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park Dr. Aiguader 88, 08003, Barcelona, ES, Spain
| | - Enrico Cataldo
- Dipartimento di Fisica "E. Fermi", Largo Bruno Pontecorvo 3, 56127, Pisa, IT, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025, Pontedera, IT, Italy.
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4
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Glomb K, Cabral J, Cattani A, Mazzoni A, Raj A, Franceschiello B. Computational Models in Electroencephalography. Brain Topogr 2021; 35:142-161. [PMID: 33779888 PMCID: PMC8813814 DOI: 10.1007/s10548-021-00828-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Accepted: 02/19/2021] [Indexed: 12/17/2022]
Abstract
Computational models lie at the intersection of basic neuroscience and healthcare applications because they allow researchers to test hypotheses in silico and predict the outcome of experiments and interactions that are very hard to test in reality. Yet, what is meant by “computational model” is understood in many different ways by researchers in different fields of neuroscience and psychology, hindering communication and collaboration. In this review, we point out the state of the art of computational modeling in Electroencephalography (EEG) and outline how these models can be used to integrate findings from electrophysiology, network-level models, and behavior. On the one hand, computational models serve to investigate the mechanisms that generate brain activity, for example measured with EEG, such as the transient emergence of oscillations at different frequency bands and/or with different spatial topographies. On the other hand, computational models serve to design experiments and test hypotheses in silico. The final purpose of computational models of EEG is to obtain a comprehensive understanding of the mechanisms that underlie the EEG signal. This is crucial for an accurate interpretation of EEG measurements that may ultimately serve in the development of novel clinical applications.
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Affiliation(s)
- Katharina Glomb
- Connectomics Lab, Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland.
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), University of Minho, Braga, Portugal
| | - Anna Cattani
- Department of Psychiatry, University of Wisconsin-Madison, Madison, USA.,Department of Biomedical and Clinical Sciences 'Luigi Sacco', University of Milan, Milan, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Ashish Raj
- School of Medicine, UCSF, San Francisco, USA
| | - Benedetta Franceschiello
- Department of Ophthalmology, Hopital Ophthalmic Jules Gonin, FAA, Lausanne, Switzerland.,CIBM Centre for Biomedical Imaging, EEG Section CHUV-UNIL, Lausanne, Switzerland.,Laboratory for Investigative Neurophysiology, Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), Lausanne, Switzerland
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Usami K, Milsap GW, Korzeniewska A, Collard MJ, Wang Y, Lesser RP, Anderson WS, Crone NE. Cortical Responses to Input From Distant Areas are Modulated by Local Spontaneous Alpha/Beta Oscillations. Cereb Cortex 2020; 29:777-787. [PMID: 29373641 DOI: 10.1093/cercor/bhx361] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Indexed: 01/13/2023] Open
Abstract
Any given area in human cortex may receive input from multiple, functionally heterogeneous areas, potentially representing different processing threads. Alpha (8-13 Hz) and beta oscillations (13-20 Hz) have been hypothesized by other investigators to gate local cortical processing, but their influence on cortical responses to input from other cortical areas is unknown. To study this, we measured the effect of local oscillatory power and phase on cortical responses elicited by single-pulse electrical stimulation (SPES) at distant cortical sites, in awake human subjects implanted with intracranial electrodes for epilepsy surgery. In 4 out of 5 subjects, the amplitudes of corticocortical evoked potentials (CCEPs) elicited by distant SPES were reproducibly modulated by the power, but not the phase, of local oscillations in alpha and beta frequencies. Specifically, CCEP amplitudes were higher when average oscillatory power just before distant SPES (-110 to -10 ms) was high. This effect was observed in only a subset (0-33%) of sites with CCEPs and, like the CCEPs themselves, varied with stimulation at different distant sites. Our results suggest that although alpha and beta oscillations may gate local processing, they may also enhance the responsiveness of cortex to input from distant cortical sites.
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Affiliation(s)
- Kiyohide Usami
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Griffin W Milsap
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Anna Korzeniewska
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Maxwell J Collard
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Yujing Wang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA
| | - Ronald P Lesser
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - William S Anderson
- Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Saponati M, Garcia-Ojalvo J, Cataldo E, Mazzoni A. Integrate-and-fire network model of activity propagation from thalamus to cortex. Biosystems 2019; 183:103978. [PMID: 31152773 DOI: 10.1016/j.biosystems.2019.103978] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 04/24/2019] [Accepted: 05/27/2019] [Indexed: 01/16/2023]
Abstract
The thalamus plays a crucial role in modulating the cortical activity underlying sensory and cognitive processes. In particular, recent experimental findings highlighted that the thalamus does not merely act as a binary gate for sensory stimuli, but rather participates to the processing of sensory information. Clarifying such thalamic influence on cortical dynamics is also important as the thalamus is the target of therapies such as DBS for Tourette patients. In this perspective, various computational models have been proposed in the last decades. However, a detailed description of the propagation of thalamic activity to the cortex is missing. Here we present a simple computational model of thalamocortical connectivity accounting for the propagation of activity from the thalamus to the cortex. The model includes both the single-neuron scale and the mesoscopic level of Local Field Potential (LFP) signals. Numerical simulations at both levels reproduce typical thalamocortical dynamics which are consistent with experimental measurements and robust to parameters changes. In particular, our model correctly reproduces locally generated rhythms as spindle oscillations in the thalamus and gamma oscillations in the cortex. Our model paves the way to deeper investigations of the thalamic influence on cortical dynamics, with and without sensory inputs or therapeutic electrical stimulation.
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Affiliation(s)
- Matteo Saponati
- The Biorobotics Institute, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025 Pontedera (PI), Italy; Department of Physics, University of Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy
| | - Jordi Garcia-Ojalvo
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
| | - Enrico Cataldo
- Department of Physics, University of Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy
| | - Alberto Mazzoni
- The Biorobotics Institute, Sant'Anna School of Advanced Studies, Viale Rinaldo Piaggio 34, 56025 Pontedera (PI), Italy.
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7
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Jacob T, Lillis KP, Wang Z, Swiercz W, Rahmati N, Staley KJ. A Proposed Mechanism for Spontaneous Transitions between Interictal and Ictal Activity. J Neurosci 2019; 39:557-575. [PMID: 30446533 PMCID: PMC6335741 DOI: 10.1523/jneurosci.0719-17.2018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Revised: 10/23/2018] [Accepted: 10/31/2018] [Indexed: 11/21/2022] Open
Abstract
Epileptic networks are characterized by two outputs: brief interictal spikes and rarer, more prolonged seizures. Although either output state is readily modeled in silico and induced experimentally, the transition mechanisms are unknown, in part because no models exhibit both output states spontaneously. In silico small-world neural networks were built using single-compartment neurons whose physiological parameters were derived from dual whole-cell recordings of pyramidal cells in organotypic hippocampal slice cultures that were generating spontaneous seizure-like activity. In silico, neurons were connected by abundant local synapses and rare long-distance synapses. Activity-dependent synaptic depression and gradual recovery delimited synchronous activity. Full synaptic recovery engendered interictal population spikes that spread via long-distance synapses. When synaptic recovery was incomplete, postsynaptic neurons required coincident activation of multiple presynaptic terminals to reach firing threshold. Only local connections were sufficiently dense to spread activity under these conditions. This coalesced network activity into traveling waves whose velocity varied with synaptic recovery. Seizures were comprised of sustained traveling waves that were similar to those recorded during experimental and human neocortical seizures. Sustained traveling waves occurred only when wave velocity, network dimensions, and the rate of synaptic recovery enabled wave reentry into previously depressed areas at precisely ictogenic levels of synaptic recovery. Wide-field, cellular-resolution GCamP7b calcium imaging demonstrated similar initial patterns of activation in the hippocampus, although the anatomical distribution of traveling waves of synaptic activation was altered by the pattern of synaptic connectivity in the organotypic hippocampal cultures.SIGNIFICANCE STATEMENT When computerized distributed neural network models are required to generate both features of epileptic networks (i.e., spontaneous interictal population spikes and seizures), the network structure is substantially constrained. These constraints provide important new hypotheses regarding the nature of epileptic networks and mechanisms of seizure onset.
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Affiliation(s)
- Theju Jacob
- Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, MA 02115
| | - Kyle P Lillis
- Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, MA 02115
| | - Zemin Wang
- Brigham and Women's Hospital, Boston, MA 02115, and
- Harvard Medical School, Boston, MA 02115
| | - Waldemar Swiercz
- Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, MA 02115
| | - Negah Rahmati
- Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, MA 02115
| | - Kevin J Staley
- Massachusetts General Hospital, Boston, Massachusetts 02114,
- Harvard Medical School, Boston, MA 02115
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8
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Mobarhan MH, Halnes G, Martínez-Cañada P, Hafting T, Fyhn M, Einevoll GT. Firing-rate based network modeling of the dLGN circuit: Effects of cortical feedback on spatiotemporal response properties of relay cells. PLoS Comput Biol 2018; 14:e1006156. [PMID: 29771919 PMCID: PMC5976212 DOI: 10.1371/journal.pcbi.1006156] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 05/30/2018] [Accepted: 04/23/2018] [Indexed: 12/01/2022] Open
Abstract
Visually evoked signals in the retina pass through the dorsal geniculate nucleus (dLGN) on the way to the visual cortex. This is however not a simple feedforward flow of information: there is a significant feedback from cortical cells back to both relay cells and interneurons in the dLGN. Despite four decades of experimental and theoretical studies, the functional role of this feedback is still debated. Here we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. For this model the responses are found by direct evaluation of two- or three-dimensional integrals allowing for fast and comprehensive studies of putative effects of different candidate organizations of the cortical feedback. Our analysis identifies a special mixed configuration of excitatory and inhibitory cortical feedback which seems to best account for available experimental data. This configuration consists of (i) a slow (long-delay) and spatially widespread inhibitory feedback, combined with (ii) a fast (short-delayed) and spatially narrow excitatory feedback, where (iii) the excitatory/inhibitory ON-ON connections are accompanied respectively by inhibitory/excitatory OFF-ON connections, i.e. following a phase-reversed arrangement. The recent development of optogenetic and pharmacogenetic methods has provided new tools for more precise manipulation and investigation of the thalamocortical circuit, in particular for mice. Such data will expectedly allow the eDOG model to be better constrained by data from specific animal model systems than has been possible until now for cat. We have therefore made the Python tool pyLGN which allows for easy adaptation of the eDOG model to new situations. On route from the retina to primary visual cortex, visually evoked signals have to pass through the dorsal lateral geniculate nucleus (dLGN). However, this is not an exclusive feedforward flow of information as feedback exists from neurons in the cortex back to both relay cells and interneurons in the dLGN. The functional role of this feedback remains mostly unresolved. Here, we use a firing-rate model, the extended difference-of-Gaussians (eDOG) model, to explore cortical feedback effects on visual responses of dLGN relay cells. Our analysis indicates that a particular mix of excitatory and inhibitory cortical feedback agrees best with available experimental observations. In this configuration ON-center relay cells receive both excitatory and (indirect) inhibitory feedback from ON-center cortical cells (ON-ON feedback) where the excitatory feedback is fast and spatially narrow while the inhibitory feedback is slow and spatially widespread. In addition to the ON-ON feedback, the connections are accompanied by OFF-ON connections following a so-called phase-reversed (push-pull) arrangement. To facilitate further applications of the model, we have made the Python tool pyLGN which allows for easy modification and evaluation of the a priori quite general eDOG model to new situations.
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Affiliation(s)
- Milad Hobbi Mobarhan
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Geir Halnes
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Pablo Martínez-Cañada
- Centro de Investigación en Tecnologías de la Información y de las Comunicaciones (CITIC), University of Granada, Granada, Spain
| | - Torkel Hafting
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Marianne Fyhn
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Biosciences, University of Oslo, Oslo, Norway
| | - Gaute T. Einevoll
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway
- Department of Physics, University of Oslo, Oslo, Norway
- * E-mail:
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