 Welcome back to the lecture series on bioelectricity. So, this will be the 24th lecture what I will be delegating or delivering to you. So, as of now, we have talked in depth about bioelectrical phenomena in the animal world. We talked about action potentials, we talked about the stress reflex arc, ion channels, patch clamp measurements, microelectrode arrays, helping circuits, then we talked about spinal cord injuries, special senses like eyes, ears, nose, alfaction, gastation, then we talked about memory acquisition, different diseases involved in memory acquisition process, spinal cord injuries and so forth. So, in the animal bioelectricity, especially in the nervous system, I have left out some very few small techniques which are not very regularly used, but it is good to know about the power of some of these techniques. So, this lecture will be those small bits and pieces of different techniques which could be utilized and apart from it, I will be highlighting two aspect of at the, because it is a very complex network. So, there are certain aspects of inhibitory and excitatory circuits which I will be kind of highlighting in this talk and how this kind of network behavior kind of you know regulate all those things. So, let us start the lecture 24 and let us enumerate what all I will be touching in this particular lecture. So, in lecture 24 and what I will be touching is first I will be talking about capacitance measurement. If you are treating cell as cell membrane as a capacitor, capacitance measurements, this is the first thing I will be dealing with. So, if you remember, while I was talking to you about the membrane, it is something like a lipid bilayer. It is almost like a two plate capacitor. So, here you have the proteins which are sitting out there. So, now you can treat this membrane as a capacitor membrane. So, what happens during, so if you go back to the basics, if you understand the basics, basics of capacitor is basically you see the formula. See if C stands for capacitance, then Q is the charge, P is the voltage and C is your capacitance. So, this is how we define capacitance and further you can actually derive capacitance by 0, A by D, where D is the, this is essentially is the D and in this case, A is the area of the whole membrane and this is the permittivity constant, permittivity of the membrane as well as, so in the free space, your epsilon 0 in the free space will be 8.85, 10 to the power of minus 12. So, if it is a parallel plate capacitor and specific capacitance will be around 1 micro farad and pure bilayers slightly higher than the pure bilayer which is approximately around, this is around 0.8 micro farad per centimeter square. Now, what I essentially wanted you to highlight is this component area. See for example, if there are two neurons like this, here is another neuron, let me just kind of you know, these are the dendritic processes likewise and of course, this one also will have whole range of dendritic processes likewise, so on and so forth. So, now, this one is neuron one, this one is neuron two. Now, this neuron is sending an electrical impulse and assume that this neuron is receiving the electrical impulse. So, at the zone of synapse, this is where is the synaptic cleft and the zone of synapse, there are couple of things which are happening. The most important thing which is happening out here is this, once this electrical signal reaches out here. So, synapse is basically two neurons are in closest contact, but there is a small gap out there, which is called the synaptic cleft, which I mentioned here. So, at this level, there are the first thing which happens is that, this signal directly does not jump into this next neuron. So, from neuron one, there are neurotransmitters which are secreted. Those neurotransmitters could be excitatory or inhibitory. So, if it is an excitatory, because the next thing will be coming that is why I kind of left it out for later. Excitatory NTs or neurotransmitter or inhibitory NTs. Among the inhibitory NTs are like something like GABA, something like glycine, whereas among excitatory neurotransmitter, you have glutamate, acetyl, choline. So, now how these neurotransmitters are secreted? So, if I kind of blow up this zone, what essentially happens? So, if I blow up the whole synaptic zone, synaptic zone looks like this. So, this is the presynaptic or neuron one. This one is the receiving neuron which is with its dendritic processes, multiple dendritic processes like this. Now, this is N1 and this is your N2. So, the electrical impulse reaches out here and travelling in this direction as shown by the arrow. Out here, there are neurotransmitter vesicles in the form like this. They are attached into it like this. These are membranous sacs, these circle ones what I am drawing here which are filled with neurotransmitters, a part of the membrane like this. Huge, huge buttons of neurotransmitters sitting out here and these are all filled with. So, I am just representing it with you know this green molecule. These are the molecules of neurotransmitters what is what has filled up all these things. Now, when the electrical impulse reaches here, it leads to the influx of calcium out here. This can calcium ions binds here and helps this particular neurotransmitter pocket to be released. So, the way it works is this, this part of the membrane gets detached and this part of it gets detached. So, let me just put it make it slightly dark, it gets detached and what you see in transiently what happens this membrane loses part of the membrane and they become like this. So, a part of the membrane is lost in this process. So, when the part of the membrane, so let me complete I will come back to this stage. So, then these neurotransmitter comes here and goes and binds to these you know to the postsynaptic membrane and then this leads to the opening of the ion channels and automatically there will be huge flux of sodium out here, sodium ions. These sodium ions eventually carry it further. If this neurotransmitter is inhibitory, then this neurotransmitter could secrete something like a GABA or glycine. When these GABA and glycine binds to this particular postsynaptic neuron, this may lead to the opening of the say chloride. So, when the chloride is coming from minus 80 millivolt, where the cell is setting, it becomes more negative, it becomes minus 90 millivolt. So, these kind of neurotransmitter does not allow the electrical signal to proceed further, it could stop here. So, those kind of synapses where it leads to the opening of the chloride or which makes the cell much more negative are called inhibitory neurotransmitter or inhibitory circuits. Something like you know when the GABA binds here, GABA leads to the entry of the chloride ions through the chloride channels, which are inhibitory entities leading to inhibitory circuits. But out here there is something else which is happening. So, you see part of the membrane is lost. So, now if you go back to the previous picture out here, I told you. So, it means there is a change in the area and because if original area is A, because part of the membrane is lost. So, there is a next area which is form which is say for example, A slash, which essentially is A slash will be less than A original area. This change in area could help in determining the capacitance change in the capacitance. And based on the change in capacitance, you can actually back calculate how much current must have flown here. So, this is how the capacitance measurement is very comes very handy, but these kind of measurements use very huge cells, where the change between two neurons is very distinctly seen. So, for capacitance measurement you need very huge cells and mostly these are done with you know something like chromaphen cells and likewise. There are several other cells which could do this. So, you need really huge cells for this. So, this is one of the very potentially very powerful technique of capacitance measurement, which is followed by different people who work with bovine pituitary and neuroendocrine cells. Mostly these are neuroendocrine cells which are involved in it. Just to give you an idea that what all different electrical techniques could be used. That is why I kind of hold it here there and I came back to this circuit now to tell you like you know these kind of measurements also can be done to understand the electrical changes which are taking place. So, this is very briefly about the capacitance measurement. I promised you that I will be talking about the field effect transistors. So, what I will be doing because that is kindly slightly out of the I will be giving a hand out at the end of the course. You can go through it and I will give you a very simple hand out which will kind of give you an idea how field effect transistors are being used. It will be in a form of a power point or in a PDF file which will be attached with along the question papers which I will be providing for the course. You can go through that and that will give you a fairly good idea. So, this is something I am just for your record let it be there. So, for the FET refer to the hand outs and at the end I will I will be discussing certain things about it. It is a very upcoming technology refer to the hand out and refer to the reference material to be provided. So, this is about the FETs. Now, from here I come little bit about the neuronal computation of excitatory and inhibitory neurotransmitters. So, this is something which I have not really discussed in depth, but back and forth we have kind of you know touched upon it, but I will specifically devote few minutes for you to realize how the computation takes place. Say for example, so let us draw a simple network first to you know understand this process. So, these are the individual neurons with their cell body in circular a and you know let us you know draw something like this little bit more like say for example, now let us name them N 1 N 2 N 3 N 4. These are the different name different neurons N 5 N 6 N 7 N 8 likewise. Now, let us assume N 4 and we know all the cells set at a resting membrane potential of minus 70 millivolt. Let us assume N 4 is a inhibitory neuron I N. And N 3 is a excitatory neuron N 2 is an excitatory neuron N 1 is an excitatory neuron N 5 is an inhibitory neuron N 6 N 8 is an inhibitory neuron N 7 is an excitatory neuron N 6 is an inhibitory is an excitatory neuron and 6 is an inhibitory neuron. So, when I talk about inhibitory and excitatory neuron what I mean essentially is the neurotransmitter they are secreting. So, among the classification they could be when we are talking about I n's and then you have e n's e n's could be let us assume as glutamate glutamatergic neuron these are called glutamatergic neuron acetylcholine or cholinergic neuron which are essentially the major chunk of the motor neurons except drosophila where they are glutamatergic and among the inhibitory neurons you have GABA GABAergic neurons you have glycinergic neuron GABA are the ones which promote the entry of the chloride glutamate are the ones which are providing the entry of the sodium. So, now this is how a hypothetical network looks like what I have drawn. So, now this neuron say for example, this I n is receiving a n p and which is also excited in neuron. So, say for example, from n p electrical impulse is traveling all the way to all the way excitatory signal all the way out here. So, now if there is an inhibitory signal coming from this neuron say for example, an inhibitory signal coming from this neuron. So, there will be an algebraic addition out here. So, if this sends say 5 units of signal and this sent 2 units of signal essentially n 3 will have 3 units of signal realize. So, what it will be passing on here will be 3 unit I am just giving hypothetical numbers here if you have a way to quantify it. Now, n 7 out here is receiving an input from say for example, let us make it little bit more a 3 unit from n 3 and another sum x y z unit from n 2. So, this one is also sending a excitatory signal to this one. So, now 3 unit plus whatsoever unit is coming from n 2, but then there is an inhibitory signal coming from this one. Now, these 3 signals so if say for example, this is 5 unit. So, essentially if this negative signal is coming 5 unit and there is a positive signal of 3 unit and then this signal has to be somewhere or other bigger than minus because there is already minus 3 plus 3 minus 5. So, this is minus 2. So, this signal which is coming should be greater than minus 2 in order to ensure that the signal does not end at n 7 otherwise signal will end at n 7 realizing how this whole computation work. So, now with the simplistic situation if this is the most simplistic thing I can think of now imagine there are thousands of neuron and each neuron each one of this I am just showing two connectivity each one of them are receiving input from say 10,000 different sources or they are sending signal to 10,000 different sources at one point of time. Imagine the complexity of the network it is a complexity which is fairly unfathomable by the logical or the logics or mathematics what we know it is a very very high level of computation what is happening in the brain because your amount of the brain area is limited it is within that limited area of the brain all this complete circuit has to be embedded and this. So, I mean think of it this is the total area of your brain and this is where all the neurons have to be there if it is not there then the completion will not take place. So, within this all this connectivity has to be accommodated it is a exceptionally complex and multi level computation which is taking place out in the brain this is absolutely an amazing feed what nature has acquired over a period of time. So, this is the reason why I wanted to highlight. So, this is a whole range of computation which is taking place and regarding the feed of these different kind of you know GABA RJ glycinergy. So, initially it is believe initially when I cannot when the nervous system was forming probably all the neurons say for example, it is in the formative phase all the initially all the neurons have the ability you know to synthesize all the different neurotransmitters they could do a multitasking, but then slowly slowly they specialize themselves they become you know depending on the location depending on the developmental role they become either you know glutamate major one they will be they are secreting then could be glutamate neurotransmitter or you know acetylcholine which is when acetylcholine goes and binds it kind of you know opens up the cation channels it could be you know GABA it could be glycine it could be you know which directly passes through the membrane could be in CO 2. So, this ability of or this plethora of different neurotransmitter adds further complexity to the nervous system because on one hand you have these voltage gated channels then this voltage gated channels then you have this ligand gated channels ligand gated channels are essentially the neurotransmitter driven channels then you have spatial and temporal computation something like this. See for example, let us again get back to the circuit. So, imagine a circuit like this now a set of signal is coming. So, these are different neurons let me just 1 2 3 4 5 6 now say for example, a signal is coming from here part of the signal going say here. Now, at time t 1 the signal is started at time 2 it is here whereas, with a slight delay at t 4 it is here. So, simultaneously another signal may be coming say for example, from one of these processes or like this. So, may be this signal is coming with a slight delay with respect to t 2. So, what is happening followed by t 2 if another signal they will add up. So, if this is the first signal coming followed by another signal something like this. So, there will be an addition out here like this or if there is a inhibitory signal say for example, one signal is coming like this and there is another signal which is coming on the rivers like this. So, what will happen the summation will be something like this. So, what is essentially I am trying to tell you there is a temporal summation keyword with respect to the time the signal could be inhibitory as well as excitatory and then there is something called spatial summation. Spatial summation means where in the space within this it could be stored here it could be stored here it could be stored here likewise there are several zones where it could be stored at different space. So, if you see the different diversities we are talking about we are talking about voltage gated ion channels voltage gated ICs 1, then you have ligand gated ICs 2, then you have neurotransmitters 3, then you have temporal and spatial summation in the network that is the fourth. Then you have different morphologies of neuron and within the neurotransmitters you have inhibitory and excitatory within the voltage gated channels you have sodium potassium and within that there are multiple sub types within the ligand gated channels you have N T neurotransmitter driven channels which on binding then we have talked about the temporal summation over a period of time the summation is taking place. Then at different places within the space of the network there is a summation taking place. Then there are different morphologies of the neuron there are morphologies something like a huge cell body of a motor neuron kind of morphology with dense network yet there are cells which has extremely high you know dendritic tree like something like this. Then yet there are cells this is the huge dendritic tree what you observe out here this is the huge cell body what you observe here then you have the pyramidal neurons what we describe yesterday in the hippocampus. Then similarly you have neurons which has no axons only that dendritic tree which you see in the amacrine cells in the retina. Then you have a hair cells and apart from it just coming back then out here adding few more complexity here voltage negated then just to add up the complexity here mechano, light, odor and the taste neurons or channels. So, what essentially I wanted to the reason to you know enumerate this whole thing is to highlight the possibilities all the different possibilities the nervous system can deal with I mean it is a library of wide variations. So, it can do several kind of permutation and combination in storing information in your in this whole circuit of the brain. And whenever you explore this kind of system you have to explore it with a very open mind you cannot really afford to be kind of rigid you know like you know this is it this cannot happen. There are lot of possibilities and more and more we are understanding like one of the techniques which currently is underway people are trying to develop is. So, for example, whenever we talked about a neuron. So, imagine this is the neuronal cell body you know and this is the whole process if you could. So, whenever there is an action potential getting generated or electrical pulses generated you have the sodium ions which are moving through and sodium ions eventually leads to an action potential which you have already discussed. So, essentially people are trying to you know fluorescently image the action potential fluorescent is fluorescent imaging of action potential or is another very powerful technique which people are trying which they are doing for a long period of time is called calcium imaging where the calcium waves because calcium is playing a very critical role as I was telling you the calcium waves which are coming through. So, calcium imaging imaging calcium flux in order to figure out the you know electrical activity. So, there are different tools which are either very well developed or in the process of getting developed in order to decipher the electrical code within our system and of the day what is most important is that where I was starting the whole thing. And we predict that you know if this is your eye and this is your brain what is that electrical signal which tells the eye that this is an apple and this is where lies our neural code. What makes you know that this is an apple not an orange or this is an apple not a you know human being. So, both of them have one commonality they are all driven by the electrical impulses which are sent to the brain. And that is why this whole field of bioelectricity at of the animal system is. So, very interesting that these are small ionic fluxes ensures who we are and what we are. So, I mean this is never ending story I mean this can go on and on forever. So, I will close in here about the animal bioelectricity fragment this module go through it and I will be giving as I have told you I will be giving a lot of reference material which you should go through. And there is another area of bioelectricity what will be dealing next after this nothing to be the brain, but with the heart the one which ensures that we are alive. So, I will close in here the next two classes or. So, we will be talking about the bioelectrical phenomena of the heart and that will pretty much will you know complete the bigger animal electricity aspects what we are supposed to deal with. Thank you.