1
|
Gaggio B, Jan A, Muller M, Salonikidou B, Bakhit B, Hellenbrand M, Di Martino G, Yildiz B, MacManus-Driscoll JL. Sodium-Controlled Interfacial Resistive Switching in Thin Film Niobium Oxide for Neuromorphic Applications. CHEMISTRY OF MATERIALS : A PUBLICATION OF THE AMERICAN CHEMICAL SOCIETY 2024; 36:5764-5774. [PMID: 38883429 PMCID: PMC11170940 DOI: 10.1021/acs.chemmater.4c00965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 05/24/2024] [Accepted: 05/24/2024] [Indexed: 06/18/2024]
Abstract
A double layer 2-terminal device is employed to show Na-controlled interfacial resistive switching and neuromorphic behavior. The bilayer is based on interfacing biocompatible NaNbO3 and Nb2O5, which allows the reversible uptake of Na+ in the Nb2O5 layer. We demonstrate voltage-controlled interfacial barrier tuning via Na+ transfer, enabling conductivity modulation and spike-amplitude- and spike-timing-dependent plasticity. The neuromorphic behavior controlled by Na+ ion dynamics in biocompatible materials shows potential for future low-power sensing electronics and smart wearables with local processing.
Collapse
Affiliation(s)
- Benedetta Gaggio
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
| | - Atif Jan
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
| | - Moritz Muller
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
| | - Barbara Salonikidou
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
| | - Babak Bakhit
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
- Electrical Engineering Division, Department of Engineering, University of Cambridge, JJ Thomson Avenue, Cambridge CB3 0FA, U.K
- Thin Film Physics Division, Department of Physics, Chemistry and Biology (IFM), Linköping University, Linköping SE-581 83, Sweden
| | - Markus Hellenbrand
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
| | - Giuliana Di Martino
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
| | - Bilge Yildiz
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States
| | - Judith L MacManus-Driscoll
- Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K
| |
Collapse
|
2
|
Pauls KAM, Salmela E, Korsun O, Kujala J, Salmelin R, Renvall H. Human Sensorimotor Beta Event Characteristics and Aperiodic Signal Are Highly Heritable. J Neurosci 2024; 44:e0265232023. [PMID: 37973377 PMCID: PMC10860623 DOI: 10.1523/jneurosci.0265-23.2023] [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: 02/13/2023] [Revised: 10/24/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023] Open
Abstract
Individuals' phenotypes, including the brain's structure and function, are largely determined by genes and their interplay. The resting brain generates salient rhythmic patterns that can be characterized noninvasively using functional neuroimaging such as magnetoencephalography (MEG). One of these rhythms, the somatomotor (rolandic) beta rhythm, shows intermittent high amplitude "events" that predict behavior across tasks and species. Beta rhythm is altered in neurological disease. The aperiodic (1/f) signal present in electrophysiological recordings is also modulated by some neurological conditions and aging. Both sensorimotor beta and aperiodic signal could thus serve as biomarkers of sensorimotor function. Knowledge about the extent to which these brain functional measures are heritable could shed light on the mechanisms underlying their generation. We investigated the heritability and variability of human spontaneous sensorimotor beta rhythm events and aperiodic activity in 210 healthy male and female adult siblings' spontaneous MEG activity. The most heritable trait was the aperiodic 1/f signal, with a heritability of 0.87 in the right hemisphere. Time-resolved beta event amplitude parameters were also highly heritable, whereas the heritabilities for overall beta power, peak frequency, and measures of event duration remained nonsignificant. Human sensorimotor neural activity can thus be dissected into different components with variable heritability. We postulate that these differences partially reflect different underlying signal-generating mechanisms. The 1/f signal and beta event amplitude measures may depend more on fixed, anatomical parameters, whereas beta event duration and its modulation reflect dynamic characteristics, guiding their use as potential disease biomarkers.
Collapse
Affiliation(s)
- K Amande M Pauls
- Department of Neurology, Helsinki University Hospital, and Department of Clinical Neurosciences, University of Helsinki, 00029 Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, 00290 Helsinki, Finland
| | - Elina Salmela
- Organismal and Evolutionary Biology Research Programme, Faculty of Biological and Environmental Sciences, University of Helsinki, 00014 Helsinki, Finland
- Department of Biology, University of Turku, 20014 Turku, Finland
| | - Olesia Korsun
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, 00290 Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, 02150 Espoo, Finland
| | - Jan Kujala
- Department of Psychology, University of Jyväskylä, 40014 Jyväskylä, Finland
| | - Riitta Salmelin
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, 02150 Espoo, Finland
| | - Hanna Renvall
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Hospital, 00290 Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, 02150 Espoo, Finland
| |
Collapse
|
3
|
Noor MS, Howell B, McIntyre CC. Role of the volume conductor on simulations of local field potential recordings from deep brain stimulation electrodes. PLoS One 2023; 18:e0294512. [PMID: 38011104 PMCID: PMC10681243 DOI: 10.1371/journal.pone.0294512] [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: 04/20/2023] [Accepted: 11/02/2023] [Indexed: 11/29/2023] Open
Abstract
OBJECTIVE Local field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are commonly used in research analyses, and are beginning to be used in clinical practice. Computational models of DBS LFPs provide tools for investigating the biophysics and neural synchronization that underlie LFP signals. However, technical standards for DBS LFP model parameterization remain to be established. Therefore, the goal of this study was to evaluate the role of the volume conductor (VC) model complexity on simulated LFP signals in the subthalamic nucleus (STN). APPROACH We created a detailed human head VC model that explicitly represented the inhomogeneity and anisotropy associated with 12 different tissue structures. This VC model represented our "gold standard" for technical detail and electrical realism. We then incrementally decreased the complexity of the VC model and quantified the impact on the simulated LFP recordings. Identical STN neural source activity was used when comparing the different VC model variants. Results Ignoring tissue anisotropy reduced the simulated LFP amplitude by ~12%, while eliminating soft tissue heterogeneity had a negligible effect on the recordings. Simplification of the VC model to consist of a single homogenous isotropic tissue medium with a conductivity of 0.215 S/m contributed an additional ~3% to the error. SIGNIFICANCE Highly detailed VC models do generate different results than simplified VC models. However, with errors in the range of ~15%, the use of a well-parameterized simple VC model is likely to be acceptable in most contexts for DBS LFP modeling.
Collapse
Affiliation(s)
- M. Sohail Noor
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Bryan Howell
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Cameron C. McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- Department of Neurosurgery, Duke University, Durham, NC, United States of America
| |
Collapse
|
4
|
Herrera B, Sajad A, Errington SP, Schall JD, Riera JJ. Cortical origin of theta error signals. Cereb Cortex 2023; 33:11300-11319. [PMID: 37804250 PMCID: PMC10690871 DOI: 10.1093/cercor/bhad367] [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: 06/23/2023] [Revised: 09/13/2023] [Accepted: 09/14/2023] [Indexed: 10/09/2023] Open
Abstract
A multi-scale approach elucidated the origin of the error-related-negativity (ERN), with its associated theta-rhythm, and the post-error-positivity (Pe) in macaque supplementary eye field (SEF). Using biophysical modeling, synaptic inputs to a subpopulation of layer-3 (L3) and layer-5 (L5) pyramidal cells (PCs) were optimized to reproduce error-related spiking modulation and inter-spike intervals. The intrinsic dynamics of dendrites in L5 but not L3 error PCs generate theta rhythmicity with random phases. Saccades synchronized the phases of the theta-rhythm, which was magnified on errors. Contributions from error PCs to the laminar current source density (CSD) observed in SEF were negligible and could not explain the observed association between error-related spiking modulation in L3 PCs and scalp-EEG. CSD from recorded laminar field potentials in SEF was comprised of multipolar components, with monopoles indicating strong electro-diffusion, dendritic/axonal electrotonic current leakage outside SEF, or violations of the model assumptions. Our results also demonstrate the involvement of secondary cortical regions, in addition to SEF, particularly for the later Pe component. The dipolar component from the observed CSD paralleled the ERN dynamics, while the quadrupolar component paralleled the Pe. These results provide the most advanced explanation to date of the cellular mechanisms generating the ERN.
Collapse
Affiliation(s)
- Beatriz Herrera
- Department of Biomedical Engineering, Florida International University, Miami, FL 33174, United States
| | - Amirsaman Sajad
- Department of Psychology, Vanderbilt Vision Research Center, Center for Integrative & Cognitive Neuroscience, Vanderbilt University, Nashville, TN 37203, United States
| | - Steven P Errington
- Department of Psychology, Vanderbilt Vision Research Center, Center for Integrative & Cognitive Neuroscience, Vanderbilt University, Nashville, TN 37203, United States
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, United States
| | - Jeffrey D Schall
- Centre for Vision Research, Vision: Science to Applications Program, Departments of Biology and Psychology, York University, Toronto, ON M3J 1P3, Canada
| | - Jorge J Riera
- Department of Biomedical Engineering, Florida International University, Miami, FL 33174, United States
| |
Collapse
|
5
|
Sætra MJ, Ellingsrud AJ, Rognes ME. Neural activity induces strongly coupled electro-chemo-mechanical interactions and fluid flow in astrocyte networks and extracellular space-A computational study. PLoS Comput Biol 2023; 19:e1010996. [PMID: 37478153 PMCID: PMC10396022 DOI: 10.1371/journal.pcbi.1010996] [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: 03/03/2023] [Revised: 08/02/2023] [Accepted: 06/28/2023] [Indexed: 07/23/2023] Open
Abstract
The complex interplay between chemical, electrical, and mechanical factors is fundamental to the function and homeostasis of the brain, but the effect of electrochemical gradients on brain interstitial fluid flow, solute transport, and clearance remains poorly quantified. Here, via in-silico experiments based on biophysical modeling, we estimate water movement across astrocyte cell membranes, within astrocyte networks, and within the extracellular space (ECS) induced by neuronal activity, and quantify the relative role of different forces (osmotic, hydrostatic, and electrical) on transport and fluid flow under such conditions. We find that neuronal activity alone may induce intracellular fluid velocities in astrocyte networks of up to 14μm/min, and fluid velocities in the ECS of similar magnitude. These velocities are dominated by an osmotic contribution in the intracellular compartment; without it, the estimated fluid velocities drop by a factor of ×34-45. Further, the compartmental fluid flow has a pronounced effect on transport: advection accelerates ionic transport within astrocytic networks by a factor of ×1-5 compared to diffusion alone.
Collapse
Affiliation(s)
- Marte J. Sætra
- Department of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, Norway
| | - Ada J. Ellingsrud
- Department of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, Norway
| | - Marie E. Rognes
- Department of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, Norway
| |
Collapse
|
6
|
Darmani G, Drummond NM, Ramezanpour H, Saha U, Hoque T, Udupa K, Sarica C, Zeng K, Cortez Grippe T, Nankoo JF, Bergmann TO, Hodaie M, Kalia SK, Lozano AM, Hutchison WD, Fasano A, Chen R. Long-Term Recording of Subthalamic Aperiodic Activities and Beta Bursts in Parkinson's Disease. Mov Disord 2023; 38:232-243. [PMID: 36424835 DOI: 10.1002/mds.29276] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 10/19/2022] [Accepted: 10/25/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Local field potentials (LFPs) represent the summation of periodic (oscillations) and aperiodic (fractal) signals. Although previous studies showed changes in beta band oscillations and burst characteristics of the subthalamic nucleus (STN) in Parkinson's disease (PD), how aperiodic activity in the STN is related to PD pathophysiology is unknown. OBJECTIVES The study aimed to characterize the long-term effects of STN-deep brain stimulation (DBS) and dopaminergic medications on aperiodic activities and beta bursts. METHODS A total of 10 patients with PD participated in this longitudinal study. Simultaneous bilateral STN-LFP recordings were conducted in six separate visits during a period of 18 months using the Activa PC + S device in the off and on dopaminergic medication states. We used irregular-resampling auto-spectral analysis to separate oscillations and aperiodic components (exponent and offset) in the power spectrum of STN-LFP signals in beta band. RESULTS Our results revealed a systematic increase in both the exponent and the offset of the aperiodic spectrum over 18 months following the DBS implantation, independent of the dopaminergic medication state of patients with PD. In contrast, beta burst durations and amplitudes were stable over time and were suppressed by dopaminergic medications. CONCLUSIONS These findings indicate that oscillations and aperiodic activities reflect at least partially distinct yet complementary neural mechanisms, which should be considered in the design of robust biomarkers to optimize adaptive DBS. Given the link between increased gamma-aminobutyric acidergic (GABAergic) transmission and higher aperiodic activity, our findings suggest that long-term STN-DBS may relate to increased inhibition in the basal ganglia. © 2022 International Parkinson and Movement Disorder Society.
Collapse
Affiliation(s)
- Ghazaleh Darmani
- Krembil Research Institute, University Health Network, Toronto, Canada
| | - Neil M Drummond
- Krembil Research Institute, University Health Network, Toronto, Canada
| | | | - Utpal Saha
- Krembil Research Institute, University Health Network, Toronto, Canada
| | - Tasnuva Hoque
- Krembil Research Institute, University Health Network, Toronto, Canada
| | - Kaviraja Udupa
- Department of Neurophysiology, National Institute of Mental Health & Neurosciences, Bengaluru, India
| | - Can Sarica
- Krembil Research Institute, University Health Network, Toronto, Canada
| | - Ke Zeng
- Krembil Research Institute, University Health Network, Toronto, Canada
| | | | | | - Til Ole Bergmann
- Neuroimaging Center, Johannes Gutenberg University Medical Center, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Mojgan Hodaie
- Krembil Research Institute, University Health Network, Toronto, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Canada
| | - Suneil K Kalia
- Krembil Research Institute, University Health Network, Toronto, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Canada
| | - Andres M Lozano
- Krembil Research Institute, University Health Network, Toronto, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Canada
| | - William D Hutchison
- Krembil Research Institute, University Health Network, Toronto, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Canada
| | - Alfonso Fasano
- Krembil Research Institute, University Health Network, Toronto, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Toronto, Canada
| | - Robert Chen
- Krembil Research Institute, University Health Network, Toronto, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Toronto, Canada
| |
Collapse
|
7
|
Spatio-temporal modeling of saltatory conduction in neurons using Poisson-Nernst–Planck treatment and estimation of conduction velocity. BRAIN MULTIPHYSICS 2022. [DOI: 10.1016/j.brain.2022.100061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
|
8
|
Multiscale co-simulation of deep brain stimulation with brain networks in neurodegenerative disorders. BRAIN MULTIPHYSICS 2022. [DOI: 10.1016/j.brain.2022.100058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
|
9
|
Kim D, Lee JS. Emulating the Signal Transmission in a Neural System Using Polymer Membranes. ACS APPLIED MATERIALS & INTERFACES 2022; 14:42308-42316. [PMID: 36069456 DOI: 10.1021/acsami.2c12166] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Neurons are vital components of the brain. When stimulated by neurotransmitters at the dendrites, neurons deliver signals as changes in the membrane potential by ion movement. The signal transmission of a nervous system exhibits a high energy efficiency. These characteristics of neurons are being exploited to develop efficient neuromorphic computing systems. In this study, we develop chemical synapses for neuromorphic devices and emulate the signaling processes in a nervous system using a polymer membrane, in which the ionic permeability can be controlled. The polymer membrane comprises poly(diallyl-dimethylammonium chloride) and poly(3-sulfopropyl acrylate potassium salt), which have positive and negative charges, respectively. The ionic permeability of the polymer membrane is controlled by the injection of a neurotransmitter solution. This device emulates the signal transmission behavior of biological neurons depending on the concentration of the injected neurotransmitter solution. The proposed artificial neuronal signaling device can facilitate the development of bio-realistic neuromorphic devices.
Collapse
Affiliation(s)
- Dongshin Kim
- Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea
| | - Jang-Sik Lee
- Department of Materials Science and Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, Korea
| |
Collapse
|
10
|
Membrane electrical properties of mouse hippocampal CA1 pyramidal neurons during strong inputs. Biophys J 2022; 121:644-657. [PMID: 34999132 PMCID: PMC8873947 DOI: 10.1016/j.bpj.2022.01.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 09/21/2021] [Accepted: 01/05/2022] [Indexed: 11/24/2022] Open
Abstract
In this work, we highlight an electrophysiological feature often observed in recordings from mouse CA1 pyramidal cells that has so far been ignored by experimentalists and modelers. It consists of a large and dynamic increase in the depolarization baseline (i.e., the minimum value of the membrane potential between successive action potentials during a sustained input) in response to strong somatic current injections. Such an increase can directly affect neurotransmitter release properties and, more generally, the efficacy of synaptic transmission. However, it cannot be explained by any currently available conductance-based computational model. Here we present a model addressing this issue, demonstrating that experimental recordings can be reproduced by assuming that an input current modifies, in a time-dependent manner, the electrical and permeability properties of the neuron membrane by shifting the ionic reversal potentials and channel kinetics. For this reason, we propose that any detailed model of ion channel kinetics for neurons exhibiting this characteristic should be adapted to correctly represent the response and the synaptic integration process during strong and sustained inputs.
Collapse
|
11
|
Computing Extracellular Electric Potentials from Neuronal Simulations. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1359:179-199. [DOI: 10.1007/978-3-030-89439-9_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
12
|
Ellingsrud AJ, Boullé N, Farrell PE, Rognes ME. Accurate numerical simulation of electrodiffusion and water movement in brain tissue. MATHEMATICAL MEDICINE AND BIOLOGY-A JOURNAL OF THE IMA 2021; 38:516-551. [PMID: 34791309 DOI: 10.1093/imammb/dqab016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 08/09/2021] [Accepted: 10/19/2021] [Indexed: 12/19/2022]
Abstract
Mathematical modelling of ionic electrodiffusion and water movement is emerging as a powerful avenue of investigation to provide a new physiological insight into brain homeostasis. However, in order to provide solid answers and resolve controversies, the accuracy of the predictions is essential. Ionic electrodiffusion models typically comprise non-trivial systems of non-linear and highly coupled partial and ordinary differential equations that govern phenomena on disparate time scales. Here, we study numerical challenges related to approximating these systems. We consider a homogenized model for electrodiffusion and osmosis in brain tissue and present and evaluate different associated finite element-based splitting schemes in terms of their numerical properties, including accuracy, convergence and computational efficiency for both idealized scenarios and for the physiologically relevant setting of cortical spreading depression (CSD). We find that the schemes display optimal convergence rates in space for problems with smooth manufactured solutions. However, the physiological CSD setting is challenging: we find that the accurate computation of CSD wave characteristics (wave speed and wave width) requires a very fine spatial and fine temporal resolution.
Collapse
Affiliation(s)
| | - Nicolas Boullé
- Mathematical Institute, University of Oxford, Oxford, UK
| | | | | |
Collapse
|
13
|
Sætra MJ, Einevoll GT, Halnes G. An electrodiffusive neuron-extracellular-glia model for exploring the genesis of slow potentials in the brain. PLoS Comput Biol 2021; 17:e1008143. [PMID: 34270543 PMCID: PMC8318289 DOI: 10.1371/journal.pcbi.1008143] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 07/28/2021] [Accepted: 06/28/2021] [Indexed: 11/29/2022] Open
Abstract
Within the computational neuroscience community, there has been a focus on simulating the electrical activity of neurons, while other components of brain tissue, such as glia cells and the extracellular space, are often neglected. Standard models of extracellular potentials are based on a combination of multicompartmental models describing neural electrodynamics and volume conductor theory. Such models cannot be used to simulate the slow components of extracellular potentials, which depend on ion concentration dynamics, and the effect that this has on extracellular diffusion potentials and glial buffering currents. We here present the electrodiffusive neuron-extracellular-glia (edNEG) model, which we believe is the first model to combine compartmental neuron modeling with an electrodiffusive framework for intra- and extracellular ion concentration dynamics in a local piece of neuro-glial brain tissue. The edNEG model (i) keeps track of all intraneuronal, intraglial, and extracellular ion concentrations and electrical potentials, (ii) accounts for action potentials and dendritic calcium spikes in neurons, (iii) contains a neuronal and glial homeostatic machinery that gives physiologically realistic ion concentration dynamics, (iv) accounts for electrodiffusive transmembrane, intracellular, and extracellular ionic movements, and (v) accounts for glial and neuronal swelling caused by osmotic transmembrane pressure gradients. The edNEG model accounts for the concentration-dependent effects on ECS potentials that the standard models neglect. Using the edNEG model, we analyze these effects by splitting the extracellular potential into three components: one due to neural sink/source configurations, one due to glial sink/source configurations, and one due to extracellular diffusive currents. Through a series of simulations, we analyze the roles played by the various components and how they interact in generating the total slow potential. We conclude that the three components are of comparable magnitude and that the stimulus conditions determine which of the components that dominate.
Collapse
Affiliation(s)
- Marte J. Sætra
- Department of Numerical Analysis and Scientific Computing, Simula Research Laboratory, Oslo, Norway
| | - Gaute T. Einevoll
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
- Department of Physics, Norwegian University of Life Sciences, Ås, Norway
| | - Geir Halnes
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Physics, Norwegian University of Life Sciences, Ås, Norway
| |
Collapse
|
14
|
Abstract
This work is aimed to give an electrochemical insight into the ionic transport phenomena in the cellular environment of organized brain tissue. The Nernst–Planck–Poisson (NPP) model is presented, and its applications in the description of electrodiffusion phenomena relevant in nanoscale neurophysiology are reviewed. These phenomena include: the signal propagation in neurons, the liquid junction potential in extracellular space, electrochemical transport in ion channels, the electrical potential distortions invisible to patch-clamp technique, and calcium transport through mitochondrial membrane. The limitations, as well as the extensions of the NPP model that allow us to overcome these limitations, are also discussed.
Collapse
|
15
|
Semenova U, Popov V, Tomskiy A, Shaikh AG, Sedov A. Pallidal 1/f asymmetry in patients with cervical dystonia. Eur J Neurosci 2020; 53:2214-2219. [PMID: 32237251 DOI: 10.1111/ejn.14729] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 03/19/2020] [Accepted: 03/22/2020] [Indexed: 01/20/2023]
Abstract
Lateralized differences in pallidal outflow are putatively linked to asymmetric tonic contractions of the neck muscles in cervical dystonia (CD). At the population level, the interhemispheric asymmetry has been traditionally studied for the estimation of the spectral power in specified frequency bands. Broadband spectral features, however, were not taken into consideration. The contemporary analysis revealed that the aperiodic (1/f) broadband activity could be a neurophysiological marker of the excitation/inhibition ratio. During deep brain stimulation (DBS) surgery, we measured bilateral pallidal local field potentials (LFP) in nine CD patients, examining the effects of lateralized asymmetry on 1/f broadband activity. All patients showed a trend towards an asymmetric difference in the 1/f broadband activity. The ipsilateral 1/f slope was significantly higher in internal (GPi) segment of the globus pallidus that is on the contralateral side of the direction of the dystonia. We also found lateralized differences in the beta oscillations for GPi and in the alpha oscillations for GPe. Our findings emphasize the importance of mainstreaming broadband activity in the estimation of LFP spectral features together with periodic features and provide further evidence for the pallidal asymmetry in CD patients.
Collapse
Affiliation(s)
- Ulia Semenova
- Laboratory of Human Cell Neurophysiology, Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Valentin Popov
- Laboratory of Human Cell Neurophysiology, Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, Russia.,Department of Functional Neurosurgery, N.N. Burdenko National Scientific and Practical Center for Neurosurgery of the Ministry of Healthcare of the Russian Federation, Moscow, Russia
| | - Alexey Tomskiy
- Department of Functional Neurosurgery, N.N. Burdenko National Scientific and Practical Center for Neurosurgery of the Ministry of Healthcare of the Russian Federation, Moscow, Russia
| | - Aasef G Shaikh
- Department of Neurology, Case Western Reserve University, Cleveland, OH, USA.,Neurological Institute, University Hospitals, Cleveland, OH, USA.,Neurology Service, Louis Stokes Cleveland VA Medical Centre, Cleveland, OH, USA
| | - Alexey Sedov
- Laboratory of Human Cell Neurophysiology, Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow, Russia.,Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia
| |
Collapse
|
16
|
An electrodiffusive, ion conserving Pinsky-Rinzel model with homeostatic mechanisms. PLoS Comput Biol 2020; 16:e1007661. [PMID: 32348299 PMCID: PMC7213750 DOI: 10.1371/journal.pcbi.1007661] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 05/11/2020] [Accepted: 04/07/2020] [Indexed: 02/05/2023] Open
Abstract
In most neuronal models, ion concentrations are assumed to be constant, and effects of concentration variations on ionic reversal potentials, or of ionic diffusion on electrical potentials are not accounted for. Here, we present the electrodiffusive Pinsky-Rinzel (edPR) model, which we believe is the first multicompartmental neuron model that accounts for electrodiffusive ion concentration dynamics in a way that ensures a biophysically consistent relationship between ion concentrations, electrical charge, and electrical potentials in both the intra- and extracellular space. The edPR model is an expanded version of the two-compartment Pinsky-Rinzel (PR) model of a hippocampal CA3 neuron. Unlike the PR model, the edPR model includes homeostatic mechanisms and ion-specific leakage currents, and keeps track of all ion concentrations (Na+, K+, Ca2+, and Cl−), electrical potentials, and electrical conductivities in the intra- and extracellular space. The edPR model reproduces the membrane potential dynamics of the PR model for moderate firing activity. For higher activity levels, or when homeostatic mechanisms are impaired, the homeostatic mechanisms fail in maintaining ion concentrations close to baseline, and the edPR model diverges from the PR model as it accounts for effects of concentration changes on neuronal firing. We envision that the edPR model will be useful for the field in three main ways. Firstly, as it relaxes commonly made modeling assumptions, the edPR model can be used to test the validity of these assumptions under various firing conditions, as we show here for a few selected cases. Secondly, the edPR model should supplement the PR model when simulating scenarios where ion concentrations are expected to vary over time. Thirdly, being applicable to conditions with failed homeostasis, the edPR model opens up for simulating a range of pathological conditions, such as spreading depression or epilepsy. Neurons generate their electrical signals by letting ions pass through their membranes. Despite this fact, most models of neurons apply the simplifying assumption that ion concentrations remain effectively constant during neural activity. This assumption is often quite good, as neurons contain a set of homeostatic mechanisms that make sure that ion concentrations vary quite little under normal circumstances. However, under some conditions, these mechanisms can fail, and ion concentrations can vary quite dramatically. Standard models are thus not able to simulate such conditions. Here, we present what to our knowledge is the first multicompartmental neuron model that accounts for ion concentration variations in a way that ensures complete and consistent ion concentration and charge conservation. In this work, we use the model to explore under which activity conditions the ion concentration variations become important for predicting the neurodynamics. We expect the model to be of great value for the field of neuroscience, as it can be used to simulate a range of pathological conditions, such as spreading depression or epilepsy, which are associated with large changes in extracellular ion concentrations.
Collapse
|
17
|
Ellingsrud AJ, Solbrå A, Einevoll GT, Halnes G, Rognes ME. Finite Element Simulation of Ionic Electrodiffusion in Cellular Geometries. Front Neuroinform 2020; 14:11. [PMID: 32269519 PMCID: PMC7109287 DOI: 10.3389/fninf.2020.00011] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 03/05/2020] [Indexed: 12/31/2022] Open
Abstract
Mathematical models for excitable cells are commonly based on cable theory, which considers a homogenized domain and spatially constant ionic concentrations. Although such models provide valuable insight, the effect of altered ion concentrations or detailed cell morphology on the electrical potentials cannot be captured. In this paper, we discuss an alternative approach to detailed modeling of electrodiffusion in neural tissue. The mathematical model describes the distribution and evolution of ion concentrations in a geometrically-explicit representation of the intra- and extracellular domains. As a combination of the electroneutral Kirchhoff-Nernst-Planck (KNP) model and the Extracellular-Membrane-Intracellular (EMI) framework, we refer to this model as the KNP-EMI model. Here, we introduce and numerically evaluate a new, finite element-based numerical scheme for the KNP-EMI model, capable of efficiently and flexibly handling geometries of arbitrary dimension and arbitrary polynomial degree. Moreover, we compare the electrical potentials predicted by the KNP-EMI and EMI models. Finally, we study ephaptic coupling induced in an unmyelinated axon bundle and demonstrate how the KNP-EMI framework can give new insights in this setting.
Collapse
Affiliation(s)
- Ada J Ellingsrud
- Department for Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway
| | - Andreas Solbrå
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Gaute T Einevoll
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.,Department of Physics, University of Oslo, Oslo, Norway.,Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Geir Halnes
- Centre for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.,Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Marie E Rognes
- Department for Scientific Computing and Numerical Analysis, Simula Research Laboratory, Oslo, Norway
| |
Collapse
|
18
|
Martinez-Banaclocha M. Astroglial Isopotentiality and Calcium-Associated Biomagnetic Field Effects on Cortical Neuronal Coupling. Cells 2020; 9:cells9020439. [PMID: 32069981 PMCID: PMC7073214 DOI: 10.3390/cells9020439] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2020] [Revised: 02/07/2020] [Accepted: 02/10/2020] [Indexed: 01/01/2023] Open
Abstract
Synaptic neurotransmission is necessary but does not sufficiently explain superior cognitive faculties. Growing evidence has shown that neuron-astroglial chemical crosstalk plays a critical role in the processing of information, computation, and memory. In addition to chemical and electrical communication among neurons and between neurons and astrocytes, other nonsynaptic mechanisms called ephaptic interactions can contribute to the neuronal synchronization from different brain regions involved in the processing of information. New research on brain astrocytes has clearly shown that the membrane potential of these cells remains very stable among neighboring and distant astrocytes due to the marked bioelectric coupling between them through gap junctions. This finding raises the possibility that the neocortical astroglial network exerts a guiding template modulating the excitability and synchronization of trillions of neurons by astroglial Ca2+-associated bioelectromagnetic interactions. We propose that bioelectric and biomagnetic fields of the astroglial network equalize extracellular local field potentials (LFPs) and associated local magnetic field potentials (LMFPs) in the cortical layers of the brain areas involved in the processing of information, contributing to the adequate and coherent integration of external and internal signals. This article reviews the current knowledge of ephaptic interactions in the cerebral cortex and proposes that the isopotentiality of cortical astrocytes is a prerequisite for the maintenance of the bioelectromagnetic crosstalk between neurons and astrocytes in the neocortex.
Collapse
|
19
|
Depannemaecker D, Canton Santos LE, Rodrigues AM, Scorza CA, Scorza FA, Almeida ACGD. Realistic spiking neural network: Non-synaptic mechanisms improve convergence in cell assembly. Neural Netw 2019; 122:420-433. [PMID: 31841876 DOI: 10.1016/j.neunet.2019.09.038] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 09/17/2019] [Accepted: 09/23/2019] [Indexed: 01/26/2023]
Abstract
Learning in neural networks inspired by brain tissue has been studied for machine learning applications. However, existing works primarily focused on the concept of synaptic weight modulation, and other aspects of neuronal interactions, such as non-synaptic mechanisms, have been neglected. Non-synaptic interaction mechanisms have been shown to play significant roles in the brain, and four classes of these mechanisms can be highlighted: (i) electrotonic coupling; (ii) ephaptic interactions; (iii) electric field effects; and iv) extracellular ionic fluctuations. In this work, we proposed simple rules for learning inspired by recent findings in machine learning adapted to a realistic spiking neural network. We show that the inclusion of non-synaptic interaction mechanisms improves cell assembly convergence. By including extracellular ionic fluctuation represented by the extracellular electrodiffusion in the network, we showed the importance of these mechanisms to improve cell assembly convergence. Additionally, we observed a variety of electrophysiological patterns of neuronal activity, particularly bursting and synchronism when the convergence is improved.
Collapse
Affiliation(s)
- Damien Depannemaecker
- Laboratório de Neurociência Experimental e Computacional, Departamento de Engenharia de Biossistemas, Universidade Federal de São João del-Rei (UFSJ), Brazil; Disciplina de Neurociência, Departamento de Neurologia e Neurocirurgia, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
| | - Luiz Eduardo Canton Santos
- Laboratório de Neurociência Experimental e Computacional, Departamento de Engenharia de Biossistemas, Universidade Federal de São João del-Rei (UFSJ), Brazil; Disciplina de Neurociência, Departamento de Neurologia e Neurocirurgia, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
| | - Antônio Márcio Rodrigues
- Laboratório de Neurociência Experimental e Computacional, Departamento de Engenharia de Biossistemas, Universidade Federal de São João del-Rei (UFSJ), Brazil
| | - Carla Alessandra Scorza
- Laboratório de Neurociência Experimental e Computacional, Departamento de Engenharia de Biossistemas, Universidade Federal de São João del-Rei (UFSJ), Brazil
| | - Fulvio Alexandre Scorza
- Disciplina de Neurociência, Departamento de Neurologia e Neurocirurgia, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil
| | - Antônio-Carlos Guimarães de Almeida
- Laboratório de Neurociência Experimental e Computacional, Departamento de Engenharia de Biossistemas, Universidade Federal de São João del-Rei (UFSJ), Brazil.
| |
Collapse
|
20
|
Veerakumar A, Tiruvadi V, Howell B, Waters AC, Crowell AL, Voytek B, Riva-Posse P, Denison L, Rajendra JK, Edwards JA, Bijanki KR, Choi KS, Mayberg HS. Field potential 1/ f activity in the subcallosal cingulate region as a candidate signal for monitoring deep brain stimulation for treatment-resistant depression. J Neurophysiol 2019; 122:1023-1035. [PMID: 31314668 PMCID: PMC6766743 DOI: 10.1152/jn.00875.2018] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Revised: 07/02/2019] [Accepted: 07/02/2019] [Indexed: 01/22/2023] Open
Abstract
Subcallosal cingulate cortex deep brain stimulation (SCC-DBS) is an experimental therapy for treatment-resistant depression (TRD). Refinement and optimization of SCC-DBS will benefit from increased study of SCC electrophysiology in context of ongoing high-frequency SCC-DBS therapy. The study objective was a 7-mo observation of frequency-domain 1/f slope in off-stimulation local field potentials (SCC-LFPs) alongside standardized measurements of depression severity in 4 patients undergoing SCC-DBS. SCC was implanted bilaterally with a combined neurostimulation-LFP recording system. Following a 1-mo off-stimulation postoperative phase with multiple daily recordings, patients received bilateral SCC-DBS therapy (130 Hz, 90 μs) and weekly resting-state SCC-LFP recordings over a 6-mo treatment phase. 1/f slopes for each time point were estimated via linear regression of log-transformed Welch periodograms. General linear mixed-effects models were constructed to estimate pretreatment sources of 1/f slope variance, and 95% bootstrap confidence intervals were constructed to estimate treatment phase 1/f slope association with treatment response (50% decrease in preimplantation symptom severity). Results show the time of recording was a prominent source of pretreatment 1/f slope variance bilaterally, with increased 1/f slope magnitude observed during night hours (2300-0659). Increase in right 1/f slope was observed in the setting of treatment response, with bootstrap analysis supporting this observation in 3 of 4 subjects. We conclude that 1/f slope can be measured longitudinally in a combined SCC-DBS/LFP recording system and likely conforms to known 1/f circadian variability. The preliminary evidence of 1/f slope increase during treatment response suggests a potential utility as a candidate biomarker for ongoing development of adaptive TRD-neuromodulation strategies.NEW & NOTEWORTHY In four patients with treatment-resistant depression undergoing therapeutic deep brain stimulation (DBS), we present the first longitudinal observations of local field potentials (LFP) from the subcallosal cingulate region outside the postoperative period. Specifically, our results demonstrate that frequency-domain 1/f activity is measurable in a combined DBS-LFP recording system and that right hemisphere recordings appear sensitive to mood state, thus suggesting a potential readout suitable for consideration in ongoing efforts to develop adaptive DBS delivery systems.
Collapse
Affiliation(s)
- Ashan Veerakumar
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
| | - Vineet Tiruvadi
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia
| | - Bryan Howell
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Allison C Waters
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Andrea L Crowell
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
| | - Bradley Voytek
- Department of Cognitive Science, University of California San Diego, La Jolla, California
| | - Patricio Riva-Posse
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
| | - Lydia Denison
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
| | - Justin K Rajendra
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Scientific and Statistical Computational Core. National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland
| | - Johnathan A Edwards
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Department of Biomedical Informatics, Emory University, Atlanta, Georgia
| | - Kelly R Bijanki
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Department of Neurosurgery, Emory University, Atlanta, Georgia
| | - Ki Sueng Choi
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Helen S Mayberg
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, Georgia
- Center for Advanced Circuit Therapeutics, Icahn School of Medicine at Mount Sinai, New York, New York
| |
Collapse
|
21
|
Lubba CH, Le Guen Y, Jarvis S, Jones NS, Cork SC, Eftekhar A, Schultz SR. PyPNS: Multiscale Simulation of a Peripheral Nerve in Python. Neuroinformatics 2019; 17:63-81. [PMID: 29948844 PMCID: PMC6394768 DOI: 10.1007/s12021-018-9383-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Bioelectronic Medicines that modulate the activity patterns on peripheral nerves have promise as a new way of treating diverse medical conditions from epilepsy to rheumatism. Progress in the field builds upon time consuming and expensive experiments in living organisms. To reduce experimentation load and allow for a faster, more detailed analysis of peripheral nerve stimulation and recording, computational models incorporating experimental insights will be of great help. We present a peripheral nerve simulator that combines biophysical axon models and numerically solved and idealised extracellular space models in one environment. We modelled the extracellular space as a three-dimensional resistive continuum governed by the electro-quasistatic approximation of the Maxwell equations. Potential distributions were precomputed in finite element models for different media (homogeneous, nerve in saline, nerve in cuff) and imported into our simulator. Axons, on the other hand, were modelled more abstractly as one-dimensional chains of compartments. Unmyelinated fibres were based on the Hodgkin-Huxley model; for myelinated fibres, we adapted the model proposed by McIntyre et al. in 2002 to smaller diameters. To obtain realistic axon shapes, an iterative algorithm positioned fibres along the nerve with a variable tortuosity fit to imaged trajectories. We validated our model with data from the stimulated rat vagus nerve. Simulation results predicted that tortuosity alters recorded signal shapes and increases stimulation thresholds. The model we developed can easily be adapted to different nerves, and may be of use for Bioelectronic Medicine research in the future.
Collapse
Affiliation(s)
- Carl H Lubba
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK.
| | - Yann Le Guen
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Sarah Jarvis
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Nick S Jones
- Department of Mathematics, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Simon C Cork
- Department of Medicine, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Amir Eftekhar
- Department of Electrical and Electronic Engineering, Imperial College London, South Kensington, London, SW7 2AZ, UK
| | - Simon R Schultz
- Department of Bioengineering, Imperial College London, South Kensington, London, SW7 2AZ, UK.
| |
Collapse
|
22
|
Electrodiffusion models of synaptic potentials in dendritic spines. J Comput Neurosci 2019; 47:77-89. [PMID: 31410632 DOI: 10.1007/s10827-019-00725-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 07/29/2019] [Accepted: 08/01/2019] [Indexed: 12/17/2022]
Abstract
The biophysical properties of dendritic spines play a critical role in neuronal integration but are still poorly understood, due to experimental difficulties in accessing them. Spine biophysics has been traditionally explored using theoretical models based on cable theory. However, cable theory generally assumes that concentration changes associated with ionic currents are negligible and, therefore, ignores electrodiffusion, i.e. the interaction between electric fields and ionic diffusion. This assumption, while true for large neuronal compartments, could be incorrect when applied to femto-liter size structures such as dendritic spines. To extend cable theory and explore electrodiffusion effects, we use here the Poisson (P) and Nernst-Planck (NP) equations, which relate electric field to charge and Fick's law of diffusion, to model ion concentration dynamics in spines receiving excitatory synaptic potentials (EPSPs). We use experimentally measured voltage transients from spines with nanoelectrodes to explore these dynamics with realistic parameters. We find that (i) passive diffusion and electrodiffusion jointly affect the dynamics of spine EPSPs; (ii) spine geometry plays a key role in shaping EPSPs; and, (iii) the spine-neck resistance dynamically decreases during EPSPs, leading to short-term synaptic facilitation. Our formulation, which complements and extends cable theory, can be easily adapted to model ionic biophysics in other nanoscale bio-compartments.
Collapse
|
23
|
Qu G, Fan B, Fu X, Yu Y. The Impact of Frequency Scale on the Response Sensitivity and Reliability of Cortical Neurons to 1/f β Input Signals. Front Cell Neurosci 2019; 13:311. [PMID: 31354432 PMCID: PMC6637762 DOI: 10.3389/fncel.2019.00311] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 06/25/2019] [Indexed: 12/16/2022] Open
Abstract
What type of principle features intrinsic inside of the fluctuated input signals could drive neurons with the maximal excitations is one of the crucial neural coding issues. In this article, we examined both experimentally and theoretically the cortical neuronal responsivity (including firing rate and spike timing reliability) to input signals with different intrinsic correlational statistics (e.g., white-type noise, showed 1/f0 power spectrum, pink noise 1/f, and brown noises 1/f2) and different frequency ranges. Our results revealed that the response sensitivity and reliability of cortical neurons is much higher in response to 1/f noise stimuli with long-term correlations than 1/f0 with short-term correlations for a broad frequency range, and also higher than 1/f2 for all frequency ranges. In addition, we found that neuronal sensitivity diverges to opposite directions for 1/f noise comparing with 1/f0 white noise as a function of cutoff frequency of input signal. As the cutoff frequency is progressively increased from 50 to 1,000 Hz, the neuronal responsiveness increased gradually for 1/f noise, while decreased exponentially for white noise. Computational simulations of a general cortical model revealed that, neuronal sensitivity and reliability to input signal statistics was majorly dominated by fast sodium inactivation, potassium activation, and membrane time constants.
Collapse
Affiliation(s)
- Guojie Qu
- State Key Laboratory of Medical Neurobiology, School of Life Science, Human Phenome Institute, Institute of Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Boqiang Fan
- State Key Laboratory of Medical Neurobiology, School of Life Science, Human Phenome Institute, Institute of Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Xin Fu
- State Key Laboratory of Medical Neurobiology, School of Life Science, Human Phenome Institute, Institute of Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yuguo Yu
- State Key Laboratory of Medical Neurobiology, School of Life Science, Human Phenome Institute, Institute of Brain Science, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| |
Collapse
|
24
|
Hagen E, Næss S, Ness TV, Einevoll GT. Multimodal Modeling of Neural Network Activity: Computing LFP, ECoG, EEG, and MEG Signals With LFPy 2.0. Front Neuroinform 2018; 12:92. [PMID: 30618697 PMCID: PMC6305460 DOI: 10.3389/fninf.2018.00092] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Accepted: 11/21/2018] [Indexed: 11/13/2022] Open
Abstract
Recordings of extracellular electrical, and later also magnetic, brain signals have been the dominant technique for measuring brain activity for decades. The interpretation of such signals is however nontrivial, as the measured signals result from both local and distant neuronal activity. In volume-conductor theory the extracellular potentials can be calculated from a distance-weighted sum of contributions from transmembrane currents of neurons. Given the same transmembrane currents, the contributions to the magnetic field recorded both inside and outside the brain can also be computed. This allows for the development of computational tools implementing forward models grounded in the biophysics underlying electrical and magnetic measurement modalities. LFPy (LFPy.readthedocs.io) incorporated a well-established scheme for predicting extracellular potentials of individual neurons with arbitrary levels of biological detail. It relies on NEURON (neuron.yale.edu) to compute transmembrane currents of multicompartment neurons which is then used in combination with an electrostatic forward model. Its functionality is now extended to allow for modeling of networks of multicompartment neurons with concurrent calculations of extracellular potentials and current dipole moments. The current dipole moments are then, in combination with suitable volume-conductor head models, used to compute non-invasive measures of neuronal activity, like scalp potentials (electroencephalographic recordings; EEG) and magnetic fields outside the head (magnetoencephalographic recordings; MEG). One such built-in head model is the four-sphere head model incorporating the different electric conductivities of brain, cerebrospinal fluid, skull and scalp. We demonstrate the new functionality of the software by constructing a network of biophysically detailed multicompartment neuron models from the Neocortical Microcircuit Collaboration (NMC) Portal (bbp.epfl.ch/nmc-portal) with corresponding statistics of connections and synapses, and compute in vivo-like extracellular potentials (local field potentials, LFP; electrocorticographical signals, ECoG) and corresponding current dipole moments. From the current dipole moments we estimate corresponding EEG and MEG signals using the four-sphere head model. We also show strong scaling performance of LFPy with different numbers of message-passing interface (MPI) processes, and for different network sizes with different density of connections. The open-source software LFPy is equally suitable for execution on laptops and in parallel on high-performance computing (HPC) facilities and is publicly available on GitHub.com.
Collapse
Affiliation(s)
- Espen Hagen
- Department of Physics, University of Oslo, Oslo, Norway.,Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Solveig Næss
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Torbjørn V Ness
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Gaute T Einevoll
- Department of Physics, University of Oslo, Oslo, Norway.,Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
| |
Collapse
|
25
|
Solbrå A, Bergersen AW, van den Brink J, Malthe-Sørenssen A, Einevoll GT, Halnes G. A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons. PLoS Comput Biol 2018; 14:e1006510. [PMID: 30286073 PMCID: PMC6191143 DOI: 10.1371/journal.pcbi.1006510] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 10/16/2018] [Accepted: 09/12/2018] [Indexed: 11/30/2022] Open
Abstract
Many pathological conditions, such as seizures, stroke, and spreading depression, are associated with substantial changes in ion concentrations in the extracellular space (ECS) of the brain. An understanding of the mechanisms that govern ECS concentration dynamics may be a prerequisite for understanding such pathologies. To estimate the transport of ions due to electrodiffusive effects, one must keep track of both the ion concentrations and the electric potential simultaneously in the relevant regions of the brain. Although this is currently unfeasible experimentally, it is in principle achievable with computational models based on biophysical principles and constraints. Previous computational models of extracellular ion-concentration dynamics have required extensive computing power, and therefore have been limited to either phenomena on very small spatiotemporal scales (micrometers and milliseconds), or simplified and idealized 1-dimensional (1-D) transport processes on a larger scale. Here, we present the 3-D Kirchhoff-Nernst-Planck (KNP) framework, tailored to explore electrodiffusive effects on large spatiotemporal scales. By assuming electroneutrality, the KNP-framework circumvents charge-relaxation processes on the spatiotemporal scales of nanometers and nanoseconds, and makes it feasible to run simulations on the spatiotemporal scales of millimeters and seconds on a standard desktop computer. In the present work, we use the 3-D KNP framework to simulate the dynamics of ion concentrations and the electrical potential surrounding a morphologically detailed pyramidal cell. In addition to elucidating the single neuron contribution to electrodiffusive effects in the ECS, the simulation demonstrates the efficiency of the 3-D KNP framework. We envision that future applications of the framework to more complex and biologically realistic systems will be useful in exploring pathological conditions associated with large concentration variations in the ECS.
Collapse
Affiliation(s)
- Andreas Solbrå
- Center for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
| | | | | | - Anders Malthe-Sørenssen
- Center for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
| | - Gaute T. Einevoll
- Center for Integrative Neuroplasticity, University of Oslo, Oslo, Norway
- Department of Physics, University of Oslo, Oslo, Norway
- Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway
| | - Geir Halnes
- Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Ås, Norway
| |
Collapse
|
26
|
Michalikova M, Remme MWH, Kempter R. Extracellular waveforms reveal an axonal origin of spikelets in pyramidal neurons. J Neurophysiol 2018; 120:1484-1495. [PMID: 29947587 DOI: 10.1152/jn.00463.2017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
Spikelets are small spike-like membrane depolarizations measured at the soma whose origin in pyramidal neurons is still unresolved. We investigated the mechanism of spikelet generation using detailed models of pyramidal neurons. We simulated extracellular waveforms associated with action potentials and spikelets and compared these with experimental data obtained by Chorev and Brecht ( J Neurophysiol 108: 1584-1593, 2012) from hippocampal pyramidal neurons in vivo. We considered spikelets originating in the axon of a single cell as well as spikelets generated in two cells coupled with gap junctions. We found that in both cases the experimental data can be explained by an axonal origin of spikelets: in the single-cell case, action potentials are generated in the axon but fail to activate the soma. Such spikelets can be evoked by dendritic input. Alternatively, spikelets resulting from axoaxonal gap junction coupling with a large (greater than several hundred μm) distance between the somata of the coupled cells are also consistent with the data. Our results demonstrate that a cell firing a somatic spikelet generates a detectable extracellular potential that is different from the action potential-correlated extracellular waveform generated by the same cell and recorded at the same location. This, together with the absence of a refractory period between action potentials and spikelets, implies that spikelets and action potentials generated in one cell may easily get misclassified in extracellular recordings as two different cells, albeit they both constitute the output of a single pyramidal neuron. NEW & NOTEWORTHY We addressed the origin of spikelets, using compartmental models of pyramidal neurons. Comparing our simulation results with published extracellular spikelet recordings revealed an axonal origin of spikelets. Our results imply that action potential- and spikelet-associated extracellular waveforms may easily get misclassified as two different cells, albeit they both constitute the output of a single pyramidal cell.
Collapse
Affiliation(s)
- Martina Michalikova
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin , Germany
| | - Michiel W H Remme
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin , Germany
| | - Richard Kempter
- Institute for Theoretical Biology, Department of Biology, Humboldt-Universität zu Berlin, Berlin , Germany.,Bernstein Center for Computational Neuroscience Berlin , Berlin , Germany.,Einstein Center for Neurosciences Berlin , Berlin , Germany
| |
Collapse
|
27
|
Moshkforoush A, Valdes-Hernandez PA, Rivera-Espada DE, Mori Y, Riera J. waveCSD: A method for estimating transmembrane currents originated from propagating neuronal activity in the neocortex: Application to study cortical spreading depression. J Neurosci Methods 2018; 307:106-124. [PMID: 29997062 PMCID: PMC6086575 DOI: 10.1016/j.jneumeth.2018.06.024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Revised: 06/25/2018] [Accepted: 06/26/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND Recent years have witnessed an upsurge in the development of methods for estimating current source densities (CSDs) in the neocortical tissue from their recorded local field potential (LFP) reflections using microelectrode arrays. Among these, methods utilizing linear arrays work under the assumption that CSDs vary as a function of cortical depth; whereas they are constant in the tangential direction, infinitely or in a confined cylinder. This assumption is violated in the analysis of neuronal activity propagating along the neocortical sheet, e.g. propagation of alpha waves or cortical spreading depression. NEW METHOD Here, we developed a novel mathematical method (waveCSD) for CSD analysis of LFPs associated with a planar wave of neocortical neuronal activity propagating at a constant velocity towards a linear probe. RESULTS Results show that the algorithm is robust to the presence of noise in LFP data and uncertainties in knowledge of propagation velocity. Also, results show high level of accuracy of the method in a wide range of electrode resolutions. Using in vivo experimental recordings from the rat neocortex, we employed waveCSD to characterize transmembrane currents associated with cortical spreading depressions. COMPARISON WITH EXISTING METHOD(S) Simulation results indicate that waveCSD has a significantly higher reconstruction accuracy compared to the widely-used inverse CSD method (iCSD), and the regularized kernel CSD method (kCSD), in the analysis of CSDs originating from propagating neuronal activity. CONCLUSIONS The waveCSD method provides a theoretical platform for estimation of transmembrane currents from their LFPs in experimental paradigms involving wave propagation.
Collapse
Affiliation(s)
- Arash Moshkforoush
- Department Biomedical Engineering, Florida International University, United States
| | | | | | - Yoichiro Mori
- Department of Mathematics, University of Minnesota Twin Cities, United States
| | - Jorge Riera
- Department Biomedical Engineering, Florida International University, United States.
| |
Collapse
|
28
|
Newton AJH, McDougal RA, Hines ML, Lytton WW. Using NEURON for Reaction-Diffusion Modeling of Extracellular Dynamics. Front Neuroinform 2018; 12:41. [PMID: 30042670 PMCID: PMC6049079 DOI: 10.3389/fninf.2018.00041] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2018] [Accepted: 06/12/2018] [Indexed: 11/13/2022] Open
Abstract
Development of credible clinically-relevant brain simulations has been slowed due to a focus on electrophysiology in computational neuroscience, neglecting the multiscale whole-tissue modeling approach used for simulation in most other organ systems. We have now begun to extend the NEURON simulation platform in this direction by adding extracellular modeling. The extracellular medium of neural tissue is an active medium of neuromodulators, ions, inflammatory cells, oxygen, NO and other gases, with additional physiological, pharmacological and pathological agents. These extracellular agents influence, and are influenced by, cellular electrophysiology, and cellular chemophysiology-the complex internal cellular milieu of second-messenger signaling and cascades. NEURON's extracellular reaction-diffusion is supported by an intuitive Python-based where/who/what command sequence, derived from that used for intracellular reaction diffusion, to support coarse-grained macroscopic extracellular models. This simulation specification separates the expression of the conceptual model and parameters from the underlying numerical methods. In the volume-averaging approach used, the macroscopic model of tissue is characterized by free volume fraction-the proportion of space in which species are able to diffuse, and tortuosity-the average increase in path length due to obstacles. These tissue characteristics can be defined within particular spatial regions, enabling the modeler to account for regional differences, due either to intrinsic organization, particularly gray vs. white matter, or to pathology such as edema. We illustrate simulation development using spreading depression, a pathological phenomenon thought to play roles in migraine, epilepsy and stroke. Simulation results were verified against analytic results and against the extracellular portion of the simulation run under FiPy. The creation of this NEURON interface provides a pathway for interoperability that can be used to automatically export this class of models into complex intracellular/extracellular simulations and future cross-simulator standardization.
Collapse
Affiliation(s)
- Adam J. H. Newton
- Department of Neuroscience, Yale University, New Haven, CT, United States
- SUNY Downstate Medical Center, The State University of New York, New York, NY, United States
| | - Robert A. McDougal
- Department of Neuroscience, Yale University, New Haven, CT, United States
- Center for Medical Informatics, Yale University, New Haven, CT, United States
| | - Michael L. Hines
- Department of Neuroscience, Yale University, New Haven, CT, United States
| | - William W. Lytton
- SUNY Downstate Medical Center, The State University of New York, New York, NY, United States
- Neurology, Kings County Hospital Center, Brooklyn, NY, United States
| |
Collapse
|
29
|
Pesaran B, Vinck M, Einevoll GT, Sirota A, Fries P, Siegel M, Truccolo W, Schroeder CE, Srinivasan R. Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation. Nat Neurosci 2018; 21:903-919. [PMID: 29942039 DOI: 10.1038/s41593-018-0171-8] [Citation(s) in RCA: 203] [Impact Index Per Article: 33.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 05/01/2018] [Indexed: 11/09/2022]
Abstract
New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.
Collapse
Affiliation(s)
- Bijan Pesaran
- Center for Neural Science, New York University, New York, NY, USA. .,NYU Neuroscience Institute, New York University Langone Health, New York, NY, USA.
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany
| | - Gaute T Einevoll
- Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Anton Sirota
- Bernstein Center for Computational Neuroscience Munich, Munich Cluster of Systems Neurology (SyNergy), Faculty of Medicine, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt, Germany.,Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Markus Siegel
- Centre for Integrative Neuroscience & MEG Center, University of Tübingen, Tübingen, Germany
| | - Wilson Truccolo
- Department of Neuroscience and Institute for Brain Science, Brown University, Providence, RI, USA.,Center for Neurorestoration and Neurotechnology, U.S. Department of Veterans Affairs, Providence, RI, USA
| | - Charles E Schroeder
- Translational Neuroscience Division, Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.,Department of Neurosurgery, Columbia College of Physicians and Surgeons, New York, NY, USA
| | - Ramesh Srinivasan
- Department of Cognitive Sciences, Department of Biomedical Engineering, University of California, Irvine, CA, USA
| |
Collapse
|
30
|
Maex R. An Interneuron Circuit Reproducing Essential Spectral Features of Field Potentials. Neural Comput 2018; 30:1296-1322. [PMID: 29566349 DOI: 10.1162/neco_a_01068] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Recent advances in engineering and signal processing have renewed the interest in invasive and surface brain recordings, yet many features of cortical field potentials remain incompletely understood. In the computational study that follows, we show that a model circuit of interneurons, coupled via both GABAA receptor synapses and electrical synapses, reproduces many essential features of the power spectrum of local field potential (LFP) recordings, such as 1/ f power scaling at low frequency (below 10 Hz), power accumulation in the γ-frequency band (30-100 Hz), and a robust α rhythm in the absence of stimulation. The low-frequency 1/ f power scaling depends on strong reciprocal inhibition, whereas the α rhythm is generated by electrical coupling of intrinsically active neurons. As in previous studies, the γ power arises through the amplification of single-neuron spectral properties, owing to the refractory period, by parameters that favor neuronal synchrony, such as delayed inhibition. This study also confirms that both synaptic and voltage-gated membrane currents contribute substantially to the LFP and that high-frequency signals such as action potentials quickly taper off with distance. Given the ubiquity of electrically coupled interneuron circuits in the mammalian brain, they may be major determinants of the recorded potentials.
Collapse
Affiliation(s)
- Reinoud Maex
- École Normale Supérieure, Paris 75005, France, and School of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, U.K.
| |
Collapse
|
31
|
Correction: Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue. PLoS Comput Biol 2018. [PMID: 29513665 PMCID: PMC5841638 DOI: 10.1371/journal.pcbi.1006050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
|
32
|
Ephaptic Coupling of Cortical Neurons: Possible Contribution of Astroglial Magnetic Fields? Neuroscience 2017; 370:37-45. [PMID: 28793233 DOI: 10.1016/j.neuroscience.2017.07.072] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2017] [Revised: 06/17/2017] [Accepted: 07/31/2017] [Indexed: 02/08/2023]
Abstract
The close anatomical and functional relationship between neuronal circuits and the astroglial network in the neocortex has been demonstrated at several organization levels supporting the idea that neuron-astroglial crosstalk can play a key role in information processing. In addition to chemical and electrical neurotransmission, other non-synaptic mechanisms called ephaptic interactions seem to be important to understand neuronal coupling and cognitive functions. Recent interest in this issue comes from the fact that extra-cranial electric and magnetic field stimulations have shown therapeutic actions in the clinical practice. The present paper reviews the current knowledge regarding the ephaptic effects in mammalian neocortex and proposes that astroglial bio-magnetic fields associated with Ca2+ transients could be implicated in the ephaptic coupling of neurons by a direct magnetic modulation of the intercellular local field potentials.
Collapse
|
33
|
Tveito A, Jæger KH, Lines GT, Paszkowski Ł, Sundnes J, Edwards AG, Māki-Marttunen T, Halnes G, Einevoll GT. An Evaluation of the Accuracy of Classical Models for Computing the Membrane Potential and Extracellular Potential for Neurons. Front Comput Neurosci 2017; 11:27. [PMID: 28484385 PMCID: PMC5401906 DOI: 10.3389/fncom.2017.00027] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Accepted: 03/31/2017] [Indexed: 11/20/2022] Open
Abstract
Two mathematical models are part of the foundation of Computational neurophysiology; (a) the Cable equation is used to compute the membrane potential of neurons, and, (b) volume-conductor theory describes the extracellular potential around neurons. In the standard procedure for computing extracellular potentials, the transmembrane currents are computed by means of (a) and the extracellular potentials are computed using an explicit sum over analytical point-current source solutions as prescribed by volume conductor theory. Both models are extremely useful as they allow huge simplifications of the computational efforts involved in computing extracellular potentials. However, there are more accurate, though computationally very expensive, models available where the potentials inside and outside the neurons are computed simultaneously in a self-consistent scheme. In the present work we explore the accuracy of the classical models (a) and (b) by comparing them to these more accurate schemes. The main assumption of (a) is that the ephaptic current can be ignored in the derivation of the Cable equation. We find, however, for our examples with stylized neurons, that the ephaptic current is comparable in magnitude to other currents involved in the computations, suggesting that it may be significant-at least in parts of the simulation. The magnitude of the error introduced in the membrane potential is several millivolts, and this error also translates into errors in the predicted extracellular potentials. While the error becomes negligible if we assume the extracellular conductivity to be very large, this assumption is, unfortunately, not easy to justify a priori for all situations of interest.
Collapse
Affiliation(s)
- Aslak Tveito
- Simula Research Laboratory, Center for Biomedical ComputingOslo, Norway
- Department of Informatics, University of OsloOslo, Norway
| | - Karoline H. Jæger
- Simula Research Laboratory, Center for Biomedical ComputingOslo, Norway
| | - Glenn T. Lines
- Simula Research Laboratory, Center for Biomedical ComputingOslo, Norway
| | | | - Joakim Sundnes
- Simula Research Laboratory, Center for Biomedical ComputingOslo, Norway
- Department of Informatics, University of OsloOslo, Norway
| | - Andrew G. Edwards
- Simula Research Laboratory, Center for Biomedical ComputingOslo, Norway
- Department of Biosciences, University of OsloOslo, Norway
| | - Tuomo Māki-Marttunen
- NORMENT, K.G. Jebsen Center for Psychosis Research, Institute of Clinical Medicine, University of OsloOslo, Norway
| | - Geir Halnes
- Department of Mathematical Sciences and Technology, Norwegian University of Life SciencesÅs, Norway
| | - Gaute T. Einevoll
- Department of Mathematical Sciences and Technology, Norwegian University of Life SciencesÅs, Norway
- Department of Physics, University of OsloOslo, Norway
| |
Collapse
|
34
|
Gratiy SL, Halnes G, Denman D, Hawrylycz MJ, Koch C, Einevoll GT, Anastassiou CA. From Maxwell's equations to the theory of current-source density analysis. Eur J Neurosci 2017; 45:1013-1023. [PMID: 28177156 PMCID: PMC5413824 DOI: 10.1111/ejn.13534] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2016] [Revised: 01/17/2017] [Accepted: 01/30/2017] [Indexed: 12/31/2022]
Abstract
Despite the widespread use of current‐source density (CSD) analysis of extracellular potential recordings in the brain, the physical mechanisms responsible for the generation of the signal are still debated. While the extracellular potential is thought to be exclusively generated by the transmembrane currents, recent studies suggest that extracellular diffusive, advective and displacement currents—traditionally neglected—may also contribute considerably toward extracellular potential recordings. Here, we first justify the application of the electro‐quasistatic approximation of Maxwell's equations to describe the electromagnetic field of physiological origin. Subsequently, we perform spatial averaging of currents in neural tissue to arrive at the notion of the CSD and derive an equation relating it to the extracellular potential. We show that, in general, the extracellular potential is determined by the CSD of membrane currents as well as the gradients of the putative extracellular diffusion current. The diffusion current can contribute significantly to the extracellular potential at frequencies less than a few Hertz; in which case it must be subtracted to obtain correct CSD estimates. We also show that the advective and displacement currents in the extracellular space are negligible for physiological frequencies while, within cellular membrane, displacement current contributes toward the CSD as a capacitive current. Taken together, these findings elucidate the relationship between electric currents and the extracellular potential in brain tissue and form the necessary foundation for the analysis of extracellular recordings.
Collapse
Affiliation(s)
| | - Geir Halnes
- Faculty of Science and Technology, Norwegian University of Life Sciences, Aas, Norway
| | - Daniel Denman
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | | | - Christof Koch
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
| | - Gaute T Einevoll
- Faculty of Science and Technology, Norwegian University of Life Sciences, Aas, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Costas A Anastassiou
- Allen Institute for Brain Science, Seattle, WA, 98109, USA.,Department of Neurology, University of British Columbia, Vancouver, BC, Canada
| |
Collapse
|
35
|
Halnes G, Mäki-Marttunen T, Pettersen KH, Andreassen OA, Einevoll GT. Ion diffusion may introduce spurious current sources in current-source density (CSD) analysis. J Neurophysiol 2017; 118:114-120. [PMID: 28298307 PMCID: PMC5494370 DOI: 10.1152/jn.00976.2016] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2016] [Revised: 03/13/2017] [Accepted: 03/13/2017] [Indexed: 11/22/2022] Open
Abstract
Standard CSD analysis does not account for ionic diffusion. Using biophysically realistic computer simulations, we show that unaccounted-for diffusive currents can lead to the prediction of spurious current sources. This finding may be of strong interest for in vivo electrophysiologists doing extracellular recordings in general, and CSD analysis in particular. Current-source density (CSD) analysis is a well-established method for analyzing recorded local field potentials (LFPs), that is, the low-frequency part of extracellular potentials. Standard CSD theory is based on the assumption that all extracellular currents are purely ohmic, and thus neglects the possible impact from ionic diffusion on recorded potentials. However, it has previously been shown that in physiological conditions with large ion-concentration gradients, diffusive currents can evoke slow shifts in extracellular potentials. Using computer simulations, we here show that diffusion-evoked potential shifts can introduce errors in standard CSD analysis, and can lead to prediction of spurious current sources. Further, we here show that the diffusion-evoked prediction errors can be removed by using an improved CSD estimator which accounts for concentration-dependent effects. NEW & NOTEWORTHY Standard CSD analysis does not account for ionic diffusion. Using biophysically realistic computer simulations, we show that unaccounted-for diffusive currents can lead to the prediction of spurious current sources. This finding may be of strong interest for in vivo electrophysiologists doing extracellular recordings in general, and CSD analysis in particular.
Collapse
Affiliation(s)
- Geir Halnes
- Faculty for Science and Technology, Norwegian University of Life Sciences, Ås, Norway;
| | - Tuomo Mäki-Marttunen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Klas H Pettersen
- Letten Centre and GliaLab, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway; and
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Gaute T Einevoll
- Faculty for Science and Technology, Norwegian University of Life Sciences, Ås, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| |
Collapse
|
36
|
Affiliation(s)
- Reinoud Maex
- Ecole Normale Supérieure, rue d’Ulm 29, Paris 75005, France. E-mail:
| |
Collapse
|
37
|
Miceli S, Ness TV, Einevoll GT, Schubert D. Impedance Spectrum in Cortical Tissue: Implications for Propagation of LFP Signals on the Microscopic Level. eNeuro 2017; 4:ENEURO.0291-16.2016. [PMID: 28197543 PMCID: PMC5282548 DOI: 10.1523/eneuro.0291-16.2016] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 12/19/2016] [Accepted: 12/30/2016] [Indexed: 01/23/2023] Open
Abstract
Brain research investigating electrical activity within neural tissue is producing an increasing amount of physiological data including local field potentials (LFPs) obtained via extracellular in vivo and in vitro recordings. In order to correctly interpret such electrophysiological data, it is vital to adequately understand the electrical properties of neural tissue itself. An ongoing controversy in the field of neuroscience is whether such frequency-dependent effects bias LFP recordings and affect the proper interpretation of the signal. On macroscopic scales and with large injected currents, previous studies have found various grades of frequency dependence of cortical tissue, ranging from negligible to strong, within the frequency band typically considered relevant for neuroscience (less than a few thousand hertz). Here, we performed a detailed investigation of the frequency dependence of the conductivity within cortical tissue at microscopic distances using small current amplitudes within the typical (neuro)physiological micrometer and sub-nanoampere range. We investigated the propagation of LFPs, induced by extracellular electrical current injections via patch-pipettes, in acute rat brain slice preparations containing the somatosensory cortex in vitro using multielectrode arrays. Based on our data, we determined the cortical tissue conductivity over a 100-fold increase in signal frequency (5-500 Hz). Our results imply at most very weak frequency-dependent effects within the frequency range of physiological LFPs. Using biophysical modeling, we estimated the impact of different putative impedance spectra. Our results indicate that frequency dependencies of the order measured here and in most other studies have negligible impact on the typical analysis and modeling of LFP signals from extracellular brain recordings.
Collapse
Affiliation(s)
- Stéphanie Miceli
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre Nijmegen, 6500 HB, Nijmegen, The Netherlands
- Department of Neural Networks, Center of Advanced European Studies and Research (caesar), Max Planck Society
| | - Torbjørn V. Ness
- Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, 1432 ÅS, Norway
| | - Gaute T. Einevoll
- Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, 1432 ÅS, Norway
- Department of Physics, University of Oslo, 0316 Oslo, Norway
| | - Dirk Schubert
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre Nijmegen, 6500 HB, Nijmegen, The Netherlands
| |
Collapse
|
38
|
Herreras O. Local Field Potentials: Myths and Misunderstandings. Front Neural Circuits 2016; 10:101. [PMID: 28018180 PMCID: PMC5156830 DOI: 10.3389/fncir.2016.00101] [Citation(s) in RCA: 171] [Impact Index Per Article: 21.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2016] [Accepted: 11/28/2016] [Indexed: 12/02/2022] Open
Abstract
The intracerebral local field potential (LFP) is a measure of brain activity that reflects the highly dynamic flow of information across neural networks. This is a composite signal that receives contributions from multiple neural sources, yet interpreting its nature and significance may be hindered by several confounding factors and technical limitations. By and large, the main factor defining the amplitude of LFPs is the geometry of the current sources, over and above the degree of synchronization or the properties of the media. As such, similar levels of activity may result in potentials that differ in several orders of magnitude in different populations. The geometry of these sources has been experimentally inaccessible until intracerebral high density recordings enabled the co-activating sources to be revealed. Without this information, it has proven difficult to interpret a century's worth of recordings that used temporal cues alone, such as event or spike related potentials and frequency bands. Meanwhile, a collection of biophysically ill-founded concepts have been considered legitimate, which can now be corrected in the light of recent advances. The relationship of LFPs to their sources is often counterintuitive. For instance, most LFP activity is not local but remote, it may be larger further from rather than close to the source, the polarity does not define its excitatory or inhibitory nature, and the amplitude may increase when source's activity is reduced. As technological developments foster the use of LFPs, the time is now ripe to raise awareness of the need to take into account spatial aspects of these signals and of the errors derived from neglecting to do so.
Collapse
Affiliation(s)
- Oscar Herreras
- Department of Translational Neuroscience, Cajal Institute-CSICMadrid, Spain
| |
Collapse
|