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<div class="block title" style="margin-top: 35px;"><h3 style="text-align: left;" id="Nerve">Gold-coated membranes</h3></div> | <div class="block title" style="margin-top: 35px;"><h3 style="text-align: left;" id="Nerve">Gold-coated membranes</h3></div> | ||
<div class="block full"> | <div class="block full"> | ||
− | <p>One of the goals of NeuronArch is to use or even develop a neural signal collection solution that is both non-invasive for the nerve and highly selective.In this context, we seek to develop an innovative architecture to significantly improve the selectivity of extraneural electrodes. In order to be able to develop such a solution, we must be able to estimate the electrical potential created on the surface of the nerve by the propagation of transmembrane currents at the level of the axons.</p> | + | <p>One of the goals of NeuronArch is to use or even develop a neural signal collection solution that is both non-invasive for the nerve and highly selective. In this context, we seek to develop an innovative architecture to significantly improve the selectivity of extraneural electrodes. In order to be able to develop such a solution, we must be able to estimate the electrical potential created on the surface of the nerve by the propagation of transmembrane currents at the level of the axons.</p> |
− | <p>For this study, we are only interested in | + | <p>For this study, we are only interested in myelinated axons present in the peripheral nervous system. Models that represent the extracellular voltage produced by the passage of an action potential for this type of fiber already exist. The evolution of the extracellular voltage in the space separating two nodes of Ranvier can be described by these models.</p> |
− | <p>First, we are going to detail the physiological characteristics of the human nervous system. Then, we are going to | + | <p>First, we are going to detail the physiological characteristics of the human nervous system. Then, we are going to model the electrical currents of an axon. Finally, we will estimate the influence of such currents at the surface of a nerve and model an entire nerve. </p> |
</div> | </div> | ||
<div class="block title"><h1>I. physiological characteristics of the human nervous system<sup>[1]</sup></h1></div> | <div class="block title"><h1>I. physiological characteristics of the human nervous system<sup>[1]</sup></h1></div> | ||
<div class="block full"> | <div class="block full"> | ||
− | <p>The nervous system is divided in two different parts: the central nervous system (CNS) and the peripheral nervous system (PNS). We will | + | <p>The nervous system is divided in two different parts: the central nervous system (CNS) and the peripheral nervous system (PNS). We will focus on the peripheral nervous system as it transports the information between the rest of the body and the central nervous system. Moreover, it includes the somatic nervous system which consists of afferent nerves, also called sensory nerves, and efferent nerves, also called motor nerves. Afferent nerves are responsible for relaying sensation from the body to the central nervous system; efferent nerves are responsible for sending out commands from the CNS to the body, stimulating muscle contraction; they include all the non-sensory neurons connected with skeletal muscles and skin. Generally, the fibers of the somatic nervous system have an insulating sheath called a myelin sheath.</p> |
+ | |||
<img src="https://static.igem.org/mediawiki/2018/c/c2/T--Pasteur_Paris--InterfaceNerveFigure1.jpg" style="width:300px"> | <img src="https://static.igem.org/mediawiki/2018/c/c2/T--Pasteur_Paris--InterfaceNerveFigure1.jpg" style="width:300px"> | ||
<div class="legend"><b>Figure 1: </b>Structure of nerves<sup>[2]</sup></div> | <div class="legend"><b>Figure 1: </b>Structure of nerves<sup>[2]</sup></div> | ||
− | <p>Nerve fibers, consisting of axons and associated Schwann cells are grouped together in fascicles, sheathed by the perineurium. | + | <p>Nerve fibers, consisting of axons and associated Schwann cells are grouped together in fascicles, sheathed by the perineurium (Cf. Figure 1). It is composed of layers of perineural cells. About half of the fascicular surface is occupied by the fibers, the rest is composed of the endoneurium which segment the inside of the fascicle into several groups of nerve fibers which will then form new fascicles.</p> |
− | <p>The fascicles are | + | <p>The fascicles are contained in an isolated connective tissue called the epineurium that contains fibroblasts, collagen and fat in different proportions. This envelope allows the fixation of the nerve on the surrounding structures. It contains the lymphatic and vascular network which crosses the perineurium to communicate with the network of arterioles and venula of the endoneurium. The epineurium constitutes 30 to 70% of the total area of a nerve.</p> |
− | <p>The fascicular architecture is ordered only distally, close to the emergence of a nerve trunk.Going up to the proximal part, | + | <p>The fascicular architecture is ordered only distally, close to the emergence of a nerve trunk. Going up to the proximal part, fascicles divide and some fibers change their fascicles, the size of the fascicles decreases and their number increases. An orderly organization relative to the target organ is found only in the final branches that innervate a muscle, a group of muscles or sensory receptors.</p> |
</div> | </div> | ||
<div class="block title"><h1>II. Propagation of nerve impulses:</h1></div> | <div class="block title"><h1>II. Propagation of nerve impulses:</h1></div> | ||
<div class="block full"> | <div class="block full"> | ||
− | <p>The nerve impulse is initiated by action potentials that are created by successive openings and closings of the ion channels. The membrane current due to ionic flux creates an electric field in the nerve that produces a potential difference outside the nerve called extracellular voltage. It is this extracellular voltage that a measuring electrode will perceive. For a myelinated axon these ionic currents appear only at the nodes of Ranvier.</p> | + | <p>The nerve impulse is initiated by action potentials that are created by successive openings and closings of the ion channels. The membrane current due to ionic flux creates an electric field in the nerve that produces a potential difference outside the nerve called extracellular voltage. It is this extracellular voltage that a measuring electrode will perceive. For a myelinated axon, these ionic currents appear only at the nodes of Ranvier.</p> |
</div> | </div> | ||
<div class="block title"><h1>III. Modelisation of the currents of a axon’s membrane</h1></div> | <div class="block title"><h1>III. Modelisation of the currents of a axon’s membrane</h1></div> | ||
<div class="block full"> | <div class="block full"> | ||
− | <p>Although our objective is the | + | <p>Although our objective is the measurement of the extracellular action potential, it is necessary to know the currents produced at the level of an axon. </p> |
<p>From an electrical point of view, the myelin sheath of the axon acts as an insulator, preventing the appearance of transmembrane currents elsewhere than at Ranvier's nodes. In fact, seen from the outside of the axon, the action potential seems to jump from one node of Ranvier to the other. Let us now consider how to model this propagation, in order to extract the transmembrane currents at the nodes of Ranvier.</p> | <p>From an electrical point of view, the myelin sheath of the axon acts as an insulator, preventing the appearance of transmembrane currents elsewhere than at Ranvier's nodes. In fact, seen from the outside of the axon, the action potential seems to jump from one node of Ranvier to the other. Let us now consider how to model this propagation, in order to extract the transmembrane currents at the nodes of Ranvier.</p> | ||
</div> | </div> | ||
<div class="block title"><h3 style="text-align: left;">1. Electric model of an axon</h3></div> | <div class="block title"><h3 style="text-align: left;">1. Electric model of an axon</h3></div> | ||
− | <div class="block full"><p>We used the model of Hodgkin-Huxley to describe the flow of electric current through the surface membrane of a giant nerve fiber. The electrical | + | <div class="block full"><p>We used the model of Hodgkin-Huxley to describe the flow of electric current through the surface membrane of a giant nerve fiber. The electrical behavior of the membrane may be represented by the network shown in Figure 2. Current can be carried through the membrane either by charging the membrane capacity or by movement of ions through the resistance in parallel with the capacity. The influence of membrane potential on permeability can be summarized by stating: first, that depolarization causes a transient increase in sodium conductance and a slower, but maintained, increase in potassium conductance; secondly, that these changes are graded and that they can be reversed by repolarizing the membrane. </p></div> |
<img src="https://static.igem.org/mediawiki/2018/4/4c/T--Pasteur_Paris--InterfaceNerveFigure2.jpg" style="width:300px"> | <img src="https://static.igem.org/mediawiki/2018/4/4c/T--Pasteur_Paris--InterfaceNerveFigure2.jpg" style="width:300px"> | ||
<div class="legend"><b>Figure 2: </b>Electrical circuit representing membrane. RNa = 1/g<sub>Na</sub>; R<sub>k</sub> = 1/g<sub>k</sub>; R<sub>l</sub> = 1/ḡ<sub>l</sub>. R<sub>Na</sub> and R<sub>k</sub> vary with time and membrane potential; the other components are constant.<sup>[3]</sup></div> | <div class="legend"><b>Figure 2: </b>Electrical circuit representing membrane. RNa = 1/g<sub>Na</sub>; R<sub>k</sub> = 1/g<sub>k</sub>; R<sub>l</sub> = 1/ḡ<sub>l</sub>. R<sub>Na</sub> and R<sub>k</sub> vary with time and membrane potential; the other components are constant.<sup>[3]</sup></div> | ||
− | <p>Thanks to this model, we are able to determine the evolution of the potential | + | <p>Thanks to this model, we are able to determine the evolution of the membrane’s potential (V), ionic current (J<sub>i</sub>) and capacitive (J<sub>CM</sub>) densities as a function of time (Cf. Figure 3).</p> |
<img src="https://static.igem.org/mediawiki/2018/e/ef/T--Pasteur_Paris--InterfaceNerveFigure3.jpg" style="width:300px"> | <img src="https://static.igem.org/mediawiki/2018/e/ef/T--Pasteur_Paris--InterfaceNerveFigure3.jpg" style="width:300px"> | ||
<div class="legend"><b>Figure 3 </b>: Components of membrane current during propagated action potential. A, membrane potential. B, ionic current density (I<sub>i</sub>), capacity current density and total membrane current density I. C, ionic current density (I<sub>i</sub>), sodium current density (I<sub>Na</sub>) and potassium current density (I<sub>K</sub>).<sup>[3]</sup></div> | <div class="legend"><b>Figure 3 </b>: Components of membrane current during propagated action potential. A, membrane potential. B, ionic current density (I<sub>i</sub>), capacity current density and total membrane current density I. C, ionic current density (I<sub>i</sub>), sodium current density (I<sub>Na</sub>) and potassium current density (I<sub>K</sub>).<sup>[3]</sup></div> | ||
<div class="block title"><h3 style="text-align: left;">2. Simulation of the transmembrane nodal currents</h3></div> | <div class="block title"><h3 style="text-align: left;">2. Simulation of the transmembrane nodal currents</h3></div> | ||
<div class="block full"> | <div class="block full"> | ||
− | <p>It is possible to implement this model in the NEURON software (http://www.neuron.yale.edu/neuron/) to be able to simulate | + | <p>It is possible to implement this model in the NEURON software (http://www.neuron.yale.edu/neuron/) to be able to simulate transmembrane nodal currents (Cf. Figure 4). This software calculates the density of the currents presented previously.</p> |
<img src="https://static.igem.org/mediawiki/2018/b/b6/T--Pasteur_Paris--InterfaceNerveFigure4.jpg" style="width:300px"> | <img src="https://static.igem.org/mediawiki/2018/b/b6/T--Pasteur_Paris--InterfaceNerveFigure4.jpg" style="width:300px"> | ||
<div class="legend"><b>Figure 4: </b>Result of the NEURON simulation of the electrical activity (evolution as a function of the time of the transmembrane current) of a Ranvier node of a typical axon of 8.7 <FONT face="Raleway">μ</FONT>m diameter.<sup>[4]</sup></div> | <div class="legend"><b>Figure 4: </b>Result of the NEURON simulation of the electrical activity (evolution as a function of the time of the transmembrane current) of a Ranvier node of a typical axon of 8.7 <FONT face="Raleway">μ</FONT>m diameter.<sup>[4]</sup></div> | ||
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<div class="block title"><h3 style="text-align: left;">2. Medium transfer function </h3></div> | <div class="block title"><h3 style="text-align: left;">2. Medium transfer function </h3></div> | ||
<div class="block full"> | <div class="block full"> | ||
− | <p>J. H. Meier and al. developed a nonhomogeneous and anisotropic model of a nerve [6]. We consider a cylindrical nerve of radius a and an axon at a distance r from the axis of the nerve (figure 6). The nodes of Ranvier are separated by a distance | + | <p>J. H. Meier and al. developed a nonhomogeneous and anisotropic model of a nerve <sup>[6]</sup>. We consider a cylindrical nerve of radius a and an axon at a distance r from the axis of the nerve (figure 6). The nodes of Ranvier are separated by a distance l<sub>my</sub>. The point M, where the extracellular potential will be calculated, is located at a distance d = <FONT face="Raleway">ρ</FONT> - a from the surface of the nerve and at a distance <FONT face="Raleway">ρ</FONT>0 from the axon considered. The angle <FONT face="Raleway">θ</FONT> is the angle constructed from the radial position of the axon and the observation point M. The conductivity inside the nerve is different (<FONT face="Raleway">σ</FONT>z and <FONT face="Raleway">σ</FONT><FONT face="Raleway">ρ</FONT>) depending on the direction, longitudinal or radial. We consider two media other than the interior of the nerve: the perineural sheath that surrounds the nerve, of conductivity <FONT face="Raleway">σ</FONT>s, and the outside of the nerve of conductivity <FONT face="Raleway">σ</FONT>e.</p> |
<img src="https://static.igem.org/mediawiki/2018/7/76/T--Pasteur_Paris--InterfaceNerveFigure6.jpg" style="width:300px"> | <img src="https://static.igem.org/mediawiki/2018/7/76/T--Pasteur_Paris--InterfaceNerveFigure6.jpg" style="width:300px"> | ||
<div class="legend"><b>Figure 6: </b>Model of the nerve fascicle, with perineural sheath labeled “s” and external surroundings labeled “e”.<sup>[6]</sup></div> | <div class="legend"><b>Figure 6: </b>Model of the nerve fascicle, with perineural sheath labeled “s” and external surroundings labeled “e”.<sup>[6]</sup></div> | ||
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<img src="https://static.igem.org/mediawiki/2018/3/30/T--Pasteur_Paris--InterfaceNerveFigure7.jpg" style="width:300px"> | <img src="https://static.igem.org/mediawiki/2018/3/30/T--Pasteur_Paris--InterfaceNerveFigure7.jpg" style="width:300px"> | ||
<div class="legend"><b>Figure 7: </b>The line represents the nodal current and the bars represent the currents of the active nodes. Each bar corresponds to one node.<sup>[6]</sup></div> | <div class="legend"><b>Figure 7: </b>The line represents the nodal current and the bars represent the currents of the active nodes. Each bar corresponds to one node.<sup>[6]</sup></div> | ||
− | <p>From this model, the calculation of the extracellular potential is based on the calculation of the electric field in a cylindrical medium. J. H. MEIER and al. established an analytic expression of the extracellular action potential using the medium transfer function in the spatio-frequency domain[6]. With the simplifications we have chosen, this transfer function is the sum of the series presented below by separating, for each term, a factor depending on the respective positions of the axon and the point of observation, and two factors dependent on the physical characteristics of the nerve considered.</p> | + | <p>From this model, the calculation of the extracellular potential is based on the calculation of the electric field in a cylindrical medium. J. H. MEIER and al. established an analytic expression of the extracellular action potential using the medium transfer function in the spatio-frequency domain <sup>[6]</sup>. With the simplifications we have chosen, this transfer function is the sum of the series presented below by separating, for each term, a factor depending on the respective positions of the axon and the point of observation, and two factors dependent on the physical characteristics of the nerve considered.</p> |
− | <p>From this expression, it is possible to determine the "spatial" transfer function h2(z). To do this, it suffices to calculate the inverse Fourier transform of H<FONT face="Raleway">ω</FONT>2, which is done numerically as it can not be practiced analytically[4]. The behavior of these two views of the transfer function is shown in Figure 8 for two reference distances <FONT face="Raleway">ρ</FONT>0 between the observation point M and the axon.</p> | + | <p>From this expression, it is possible to determine the "spatial" transfer function h2(z). To do this, it suffices to calculate the inverse Fourier transform of H<FONT face="Raleway">ω</FONT>2, which is done numerically as it can not be practiced analytically <sup>[4]</sup>. The behavior of these two views of the transfer function is shown in Figure 8 for two reference distances <FONT face="Raleway">ρ</FONT>0 between the observation point M and the axon.</p> |
− | + | ||
<img src="https://static.igem.org/mediawiki/2018/d/dc/T--Pasteur_Paris--InterfaceNerveFigure8.jpg" style="width:400px"> | <img src="https://static.igem.org/mediawiki/2018/d/dc/T--Pasteur_Paris--InterfaceNerveFigure8.jpg" style="width:400px"> | ||
− | <div class="legend"><b>Figure 8: </b>Spatial transfer function h2(z) and space-frequency H2(k) of the nonhomogeneous and anisotropic medium for two distances <FONT face="Raleway">ρ</FONT>0 = 200 and 500 <FONT face="Raleway">μ</FONT>m between the observation point and the axon (depth of the axon in the nerve).<sup>6]</sup></div> | + | <div class="legend"><b>Figure 8: </b>Spatial transfer function h2(z) and space-frequency H2(k) of the nonhomogeneous and anisotropic medium for two distances <FONT face="Raleway">ρ</FONT>0 = 200 and 500 <FONT face="Raleway">μ</FONT>m between the observation point and the axon (depth of the axon in the nerve).<sup>[6]</sup></div> |
<p>It is of course possible to go from the nonhomogeneous and anisotropic model to the homogeneous isotropic model by considering in the nonhomogeneous and anisotropic model that the conductivities of the media are equal to each other and that the perineurium is infinite. It is clear that the nonhomogeneous and anisotropic model is more realistic but the two models give relatively close medium transfer function variation trends.</p> | <p>It is of course possible to go from the nonhomogeneous and anisotropic model to the homogeneous isotropic model by considering in the nonhomogeneous and anisotropic model that the conductivities of the media are equal to each other and that the perineurium is infinite. It is clear that the nonhomogeneous and anisotropic model is more realistic but the two models give relatively close medium transfer function variation trends.</p> | ||
<p>We have described the two models in order to calculate the potential extracellular created by the presence of nodal currents generated at Ranvier nodes. This extracellular potential at a point M and at a time t can be expressed as the convolution product in the spatial domain between the nodal current i(z, t) and the transfer function of the medium h(z)<sup>[4]</sup>:</p> | <p>We have described the two models in order to calculate the potential extracellular created by the presence of nodal currents generated at Ranvier nodes. This extracellular potential at a point M and at a time t can be expressed as the convolution product in the spatial domain between the nodal current i(z, t) and the transfer function of the medium h(z)<sup>[4]</sup>:</p> | ||
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<p>We consider the typical case of a 8.7 <FONT face="Raleway">μ</FONT>m diameter axon near myelin gains (length lmy=1000 <FONT face="Raleway">μ</FONT>m) and diameter 2.8 <FONT face="Raleway">μ</FONT>m near the Ranvier’s nodes.</p> | <p>We consider the typical case of a 8.7 <FONT face="Raleway">μ</FONT>m diameter axon near myelin gains (length lmy=1000 <FONT face="Raleway">μ</FONT>m) and diameter 2.8 <FONT face="Raleway">μ</FONT>m near the Ranvier’s nodes.</p> | ||
<p>The objective of this part is to study the spatial and spatio-frequency properties of the extracellular potential created by such an axon.</p> | <p>The objective of this part is to study the spatial and spatio-frequency properties of the extracellular potential created by such an axon.</p> | ||
− | <p>Two reference distances (<FONT face="Raleway">ρ</FONT>'=200 <FONT face="Raleway">μ</FONT>m and <FONT face="Raleway">ρ</FONT>'=500 <FONT face="Raleway">μ</FONT>m) are considered between the observation point and the axon. The action potential at the surface and along the nerve is represented figure 9 for the two previous models. Whatever the model used, the low-frequency component - space current envelope (see Figure 9) - is found on the action potential generated. It can be concluded that the action potential has the same wavelength as the nodal currents at Ranvier's node. The nonhomogeneous and anisotropic model, closer to reality, gives a greater amplitude than the homogeneous isotropic model. This phenomenon - due partly to the insulating effect of the extraneural electrode - allows to expect a more easily measurable amplitude at the electrode. We also note that the extracellular action potential has a high frequency ripple, we will call this ripple | + | <p>Two reference distances (<FONT face="Raleway">ρ</FONT>'=200 <FONT face="Raleway">μ</FONT>m and <FONT face="Raleway">ρ</FONT>'=500 <FONT face="Raleway">μ</FONT>m) are considered between the observation point and the axon. The action potential at the surface and along the nerve is represented figure 9 for the two previous models. Whatever the model used, the low-frequency component - space current envelope (see Figure 9) - is found on the action potential generated. It can be concluded that the action potential has the same wavelength as the nodal currents at Ranvier's node. The nonhomogeneous and anisotropic model, closer to reality, gives a greater amplitude than the homogeneous isotropic model. This phenomenon - due partly to the insulating effect of the extraneural electrode - allows to expect a more easily measurable amplitude at the electrode. We also note that the extracellular action potential has a high frequency ripple, we will call this ripple a High Spatial Frequency component (HSF). This ripple is due to the spatial discretization of transmembrane current sources due to the nodes of Ranvier. The position of each peak is related to the location of a Ranvier node and the period of the ripple is directly related to the distance between two Ranvier nodes. Finally, it is interesting to note that the amplitude of these peaks is significant for the low <FONT face="Raleway">ρ</FONT>' distances, that is to say when the axon is close to the surface of the nerve, and this whatever the model used. </p> |
<img src="https://static.igem.org/mediawiki/2018/8/8f/T--Pasteur_Paris--InterfaceNerveFigure9.jpg" style="width:400px"> | <img src="https://static.igem.org/mediawiki/2018/8/8f/T--Pasteur_Paris--InterfaceNerveFigure9.jpg" style="width:400px"> | ||
<div class="legend"><b>Figure 9: </b>Example of calculation of the extracellular action potential at the surface of the nerve for two reference distances (<FONT face="Raleway">ρ</FONT>0=200<FONT face="Raleway">μ</FONT>m and <FONT face="Raleway">ρ</FONT>0=500<FONT face="Raleway">μ</FONT>m) between the observation point and the axon. (1a and 1b) Distribution of nodal currents along the axon (identical). (2a and 2b) Transfer function of the medium according to models homogeneous isotropic model (2a) and nonhomogeneous anisotropic model (2b). (3a and 3b) Distribution of the extracellular action potential as a function of the position of the observation point along the nerve<sup>[4]</sup>. </div> | <div class="legend"><b>Figure 9: </b>Example of calculation of the extracellular action potential at the surface of the nerve for two reference distances (<FONT face="Raleway">ρ</FONT>0=200<FONT face="Raleway">μ</FONT>m and <FONT face="Raleway">ρ</FONT>0=500<FONT face="Raleway">μ</FONT>m) between the observation point and the axon. (1a and 1b) Distribution of nodal currents along the axon (identical). (2a and 2b) Transfer function of the medium according to models homogeneous isotropic model (2a) and nonhomogeneous anisotropic model (2b). (3a and 3b) Distribution of the extracellular action potential as a function of the position of the observation point along the nerve<sup>[4]</sup>. </div> | ||
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<div class="legend"><b>Figure 12: </b>Example of spatial extracellular action potential along a fascicle. For two distances: <FONT face="Raleway">ρ</FONT>0=200 <FONT face="Raleway">μ</FONT>m (solid line) and <FONT face="Raleway">ρ</FONT>0=500 <FONT face="Raleway">μ</FONT>m (dotted line)<sup>[9]</sup>.</div> | <div class="legend"><b>Figure 12: </b>Example of spatial extracellular action potential along a fascicle. For two distances: <FONT face="Raleway">ρ</FONT>0=200 <FONT face="Raleway">μ</FONT>m (solid line) and <FONT face="Raleway">ρ</FONT>0=500 <FONT face="Raleway">μ</FONT>m (dotted line)<sup>[9]</sup>.</div> | ||
<p>The extracellular action potentials for the configuration described in figure 11 are presented in figure 12 for observation sites (M1 and M2). One being close to the fascicle (<FONT face="Raleway">ρ</FONT>0=200 <FONT face="Raleway">μ</FONT>m), and the other being further away (<FONT face="Raleway">ρ</FONT>0=500 <FONT face="Raleway">μ</FONT>m).</p> | <p>The extracellular action potentials for the configuration described in figure 11 are presented in figure 12 for observation sites (M1 and M2). One being close to the fascicle (<FONT face="Raleway">ρ</FONT>0=200 <FONT face="Raleway">μ</FONT>m), and the other being further away (<FONT face="Raleway">ρ</FONT>0=500 <FONT face="Raleway">μ</FONT>m).</p> | ||
− | <p> | + | <p>We can verify some similarities with the study done on a single fiber. We can first see the existence of high spatial frequency components for small distances (<FONT face="Raleway">ρ</FONT>0 = 200 <FONT face="Raleway">μ</FONT>m). Then at greater distances (<FONT face="Raleway">ρ</FONT>0=500 <FONT face="Raleway">μ</FONT>m), these variations are substantially attenuated, and to a lesser extent the low frequency component of the action potential. This observation validates our proposal to observe the effect of Ranvier nodes for action potentials of fascicles. We can see that the peak-to-peak amplitude of the HSF component of this signal is of the order of 10 <FONT face="Raleway">μ</FONT>V (noted VppHF in figure 12). These considerations lead us to believe that this HSF component, a consequence of the activity of the fascicles, will be measurable on the surface of the nerve.</p> |
</div> | </div> | ||
<div class="block title"><h1>VI. Neural information:</h1></div> | <div class="block title"><h1>VI. Neural information:</h1></div> | ||
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<p>We presented the calculation of the spatial action potential at the surface of the nerve. Based on these results, we exposed the construction of a nerve model for which the fascicles are generated randomly. This model allows us to represent a fascicular activity on the surface of the nerve. We show that the high spatial frequency component can be present at the surface of the nerve, but only for fascicles close to the point of measurement.</p> | <p>We presented the calculation of the spatial action potential at the surface of the nerve. Based on these results, we exposed the construction of a nerve model for which the fascicles are generated randomly. This model allows us to represent a fascicular activity on the surface of the nerve. We show that the high spatial frequency component can be present at the surface of the nerve, but only for fascicles close to the point of measurement.</p> | ||
<p>Finally, we have shown that the amplitude of this component is of the order of ten microvolts.</p> | <p>Finally, we have shown that the amplitude of this component is of the order of ten microvolts.</p> | ||
+ | <p> All the information presented can be used to realize an extraneural electrode having the desired performances.</p> | ||
<p></p> | <p></p> | ||
</div> | </div> | ||
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<div class="block full"> | <div class="block full"> | ||
<ul style="text-align: left;"> | <ul style="text-align: left;"> | ||
− | <li style="list-style-type: decimal;">P. | + | <li style="list-style-type: decimal;">Rigoard, P., Buffenoir, K., Wager, M., Bauche, S., Giot, J.-P., Robert, R., and Lapierre, F. (2009). Organisation anatomique et physiologique du nerf périphérique. /data/revues/00283770/v55sS1/S0028377008004025/.<br><br></li> |
− | <li style="list-style-type: decimal;">https://www.studyblue.com/notes/note/n/chapter-11-nervous-system-ii-divisions-of-the-nervous-system/deck/8819508 | + | <li style="list-style-type: decimal;"> https://www.studyblue.com/notes/note/n/chapter-11-nervous-system-ii-divisions-of-the-nervous-system/deck/8819508 <br><br></li> |
− | <li style="list-style-type: decimal;"> | + | <li style="list-style-type: decimal;">Hodgkin, A.L., and Huxley, A.F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. J Physiol 117, 500–544.<br><br></li> |
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Revision as of 19:14, 16 October 2018
Membrane
When manipulating genetically engineered organisms, it is crucial to guarantee the confinement of these organisms. In our case, we want genetically modified bacteria to stay at the interface between the prosthesis and the external organic medium. At the same time, one of the main issues our project wants to tackle is the conduction of the neuron influx to the prosthesis. The answer to these questions came as a double solution: confinement of the bacteria by conductive nanoporous membranes. The membrane’s nanoporosity allows substances produced by our modified biofilm to pass through the membrane, but the bacteria remain confined. We tested the conductivity and biocompatibility of two types of membranes.
Membrane
Nerve and electrodes
As seen in the other parts of this wiki, we chose to use a nanoporous membrane in our device. The first goal of the membrane was to confine our biofilm, so it does not escape the prosthesis. Moreover, we also used our membrane as a conductive electrode. This solution was interesting since we didn’t have enough time to develop an entire electrical device which collects and treat the signal of the nerves. However, we know we still need to improve our interface if we want the patient to fully control his prosthesis. That is why we decided to look at what is already made in this field. So, first, we detailed how it is possible to model the electrical characteristics of a nerve. Then, we searched for information on electrodes and signal treatment.
This section is principaly based on the thesis of Olivier Rossel: Dispositifs de mesure et d’interprétation de l’activité d’un nerf. Electronique. Université Montpellier II - Sciences et Techniques du Languedoc, 2012. Français.