| 00:02 | This is cellular neuroscience lecture seven. we're covering today the material from lecture |
|
| 00:11 | . Actually I'm excited to inhibit their if I just wanted to remind you |
|
| 00:17 | there's a variety of what we talked i on a tropic receptors and the |
|
| 00:26 | glutamate receptors that we discussed in detail and M. D. A. |
|
| 00:31 | also talked about meta tropic receptor And when we talked about medical tropical |
|
| 00:39 | receptor signaling, we actually didn't talk about numbering deep polarization. Zor current |
|
| 00:46 | is but we we rather focused we focused on the cellular cascades or cellular |
|
| 00:59 | . And so if we look again the physiology um these uh signals that |
|
| 01:10 | talked about. So when we talked glutamate signaling an excitation of glutamate we |
|
| 01:20 | about the PSP and this gPS speed produced by a combination of Tampa and |
|
| 01:31 | M. B. A receptors. ? But we never said anything about |
|
| 01:43 | medical tropic component of this signaling And we never said anything about the |
|
| 01:51 | of the tropic component here. Let turn down the lights a little bit |
|
| 01:56 | much clear for before. Maybe this show up there 61. Yeah so |
|
| 02:18 | is our PPE sp but when we about ideas piece Yeah this would be |
|
| 02:29 | with Gaba when we talked about I speeds we talked about two elected physiological |
|
| 02:39 | , gather a component. It is mediated and gather be component that is |
|
| 02:54 | immediately. So when we discuss minimal glutamate receptors, we actually discuss them |
|
| 03:04 | the context of cellular signaling. And may have had this question. So |
|
| 03:12 | that mean that medical tropic glutamate receptors affect ionic channels like minimal tropic Gaba |
|
| 03:24 | . Gaba B is medical tropic and affects potassium channels. It opens potassium |
|
| 03:35 | that are otherwise sculpted by gated by . And so when you look at |
|
| 03:42 | , tropic glutamate signaling, what we discussed is that there are several classes |
|
| 03:48 | we won't have time to do There are several classes of another protropin |
|
| 03:52 | receptors and post synaptic lee. They affect both educated calcium channels. Both |
|
| 04:00 | potassium channels, they can have an effect on the south in some situations |
|
| 04:11 | other situations measurable tropical intimate receptors through calcium cal modulates signaling through other intracellular |
|
| 04:20 | map Kane signaling. They can actually eight an MD a receptors And potentially |
|
| 04:29 | or increased excitation in the synapse. so this is probably the biggest difference |
|
| 04:37 | when you talk about deep polarization and talk about glutamate, we technically you're |
|
| 04:45 | talking about happen MD A receptors. a variety of medical, tropical intimate |
|
| 04:54 | they're downstream, you don't typically record car uh membrane potential and you record |
|
| 05:04 | it's different for Gavin and Gaba effect am on the clocks and ionic signaling |
|
| 05:15 | the synopsis and also Mhm. Within great diagram that summarizes everything everything we |
|
| 05:26 | about excitation actually there's not as much less than what we learned about excitation |
|
| 05:33 | , as much as we learned about addition. So just recall that excited |
|
| 05:40 | inhibit their synopsis can be localized, localized that can be close to each |
|
| 05:50 | that you have Gaba A. Signaling chloride receptors, parson optically and Gaba |
|
| 05:57 | signaling through potassium channels parson optical that you uh if you look at the |
|
| 06:10 | levels of Gaba, the receptor release neurotransmitter release these molecules will activate but |
|
| 06:20 | receptors and also auto receptors Gaba B that are located pre synaptic away and |
|
| 06:32 | Gaba B receptor is present optically will both educated calcium channels and thereby well |
|
| 06:42 | this negative feedback loop, auto negative loop can control the release of its |
|
| 06:50 | inhibit their neurotransmitter Gaba, nearby glutamate you'll see you'll have Ample and in |
|
| 06:59 | eight the signaling that we talked about of deep polarization and influx of calcium |
|
| 07:08 | through an MD. A receptors which downstream cascades through calcium module and kinda |
|
| 07:17 | can okay influence. And the fact gabby receptors that are located post synaptic |
|
| 07:24 | the excitatory synopsis and those Gaba B can now open potassium channels and by |
|
| 07:33 | potassium channels that will hyper polarize the synopsis. So now if you have |
|
| 07:46 | of Gaba from the inhibitory synapses here the left that spill over it was |
|
| 07:56 | Gaba combined to Gabba B receptors that located prison optically on excitatory cells as |
|
| 08:10 | . So you have gathered to be the pre synaptic excitatory terminals and gather |
|
| 08:17 | the post synaptic excited to synopsis and . And optically Gaba B can control |
|
| 08:26 | release of both Gaba and glutamate and synaptic lee Gaba and Gaba B will |
|
| 08:35 | polarize the south and then hit a synopsis. And and the excitatory synopsis |
|
| 08:43 | can act through Gaba B receptors also hyper polarization of the excitatory synapses. |
|
| 08:52 | so this is where we put all our knowledge together about the excitation about |
|
| 08:59 | inhibitions. And today we're gonna talk the excited to inhibitor circuits and how |
|
| 09:05 | circuits generate the diversity of the brain which represent functional diversity of the |
|
| 09:14 | And these brain rhythms and interactions of between neurons. Synaptic transmission and electrochemical |
|
| 09:26 | transmission represents different different behavioral states, attitude. Different states of being |
|
| 09:36 | asleep and such and interactions between the I Editori and inhibitory cells. So |
|
| 09:46 | is our excitatory parameter cell in This is an inhibitory basket cell from |
|
| 09:53 | . This is another inhibitory oh a south from hippocampus that we also had |
|
| 09:58 | our previous charge and these cells and the glial cells that are intricate parts |
|
| 10:12 | this network not just passive support but controlling especially glutamate ergic neural transmission they |
|
| 10:21 | through periods of activity. Where are activity peaks. And then when the |
|
| 10:30 | goes down. And this preordered phenomena they create or the brain rhythms that |
|
| 10:38 | create in nature. uh in the there's no is no exception. You |
|
| 10:44 | these periodic phenomenon in nature, I on the right here the tide |
|
| 10:52 | it goes up and down and goes and down and it depends on the |
|
| 10:55 | cycle. And sometimes it will have high tides during the day and two |
|
| 11:02 | tides and sometimes it's just one. so in the brain, what we're |
|
| 11:12 | is that structure determines the function, there is a certain structural architectural design |
|
| 11:20 | the macro scale and also on a scale. So when you talk about |
|
| 11:26 | scale, you're talking about networks, talking about circuits, parts of the |
|
| 11:33 | nuclei. When you're talking about micro , you're talking about some things that |
|
| 11:38 | need a microscope to visualize individual South molecules within these sin absence. And |
|
| 11:48 | are certain rules that govern interactions in . These rules a lot of times |
|
| 11:57 | on what neurons can do. Some can produce action potentials at the highest |
|
| 12:04 | of 10 hertz, 10 cycles. action potentials per second. Either neurons |
|
| 12:10 | produce 600 action potentials a second and much higher frequencies. But they also |
|
| 12:20 | finite stores of energy. They need recover the number of potential cannot stay |
|
| 12:29 | polarized forever. It has to re in order for the self to rebuild |
|
| 12:36 | intracellular composition protein member in pod The cells are wired precisely in a |
|
| 12:45 | way and these are also the Certain rules but which there there going |
|
| 12:52 | be governed by. So there are circuits and loops within the circuits that |
|
| 12:57 | known. The brain is super complex when you talk about, when we |
|
| 13:06 | about cellular level and circuit level interactions order to understand the complete brain |
|
| 13:17 | when you're sitting, talking, studying, learning, thinking something, |
|
| 13:22 | something, moving, something, it's encompassing. It's really complex. And |
|
| 13:30 | involves billions of cells, billions of that form trillions of synapses, trillions |
|
| 13:37 | connections. So in order to understand brain circuits on a larger scale, |
|
| 13:49 | have to understand them on some basic principles that then will help you scale |
|
| 13:59 | your understanding to billions of cells maybe theoretical computational neuroscience, maybe through analytical |
|
| 14:09 | , analytical signal detection and analysis. the diversity of cortical function and the |
|
| 14:22 | in these rhythms, these periodic fluctuations you would see in the brain is |
|
| 14:29 | by inhibition. In particular by the of the inhibitory cells that you find |
|
| 14:37 | cortical or hippocampal sub cortical circuits are circuits that we're talking about and recall |
|
| 14:47 | inhibit theirselves inhibit their into neurons in cortex or in hippocampus. The only |
|
| 14:57 | 10-20% of the total neuronal populations. there are not that many of the |
|
| 15:07 | sells the excitatory projection cells branded ourselves comprise 80 to 90% of the total |
|
| 15:18 | populations in the new york cortical and hippocampal circuits. There's a question whether |
|
| 15:28 | projection inhibition, Why is there a rule in the brain that when we |
|
| 15:36 | about excitatory surface and excitatory phenomenal they're mostly projection cells. How come |
|
| 15:43 | is no projection inhibitory cells? How that change the brain function if we |
|
| 15:50 | that? Everything we've learned so far we talked about, inhibited into neurons |
|
| 15:57 | are local and they exert their effect then train activity of the parameter cells |
|
| 16:03 | within the circuits. And then the cells can then communicate that information to |
|
| 16:09 | adjacent interconnected brain regions. So we these inhibitor loops, we have the |
|
| 16:18 | forward inhibitor loops. We have the inhibitory loops that will all contribute to |
|
| 16:27 | complexity of signaling and what the excitatory project where most of the inter neurons |
|
| 16:36 | really still be talked about as local cells. This is a book that |
|
| 16:45 | highly recommend by. You're g you're . Uh Professor Princeton, I believe |
|
| 16:57 | studies intricately neuronal networks and neuronal It's called rhythms of the brain. |
|
| 17:09 | what he has here is in this one from this book and there's some |
|
| 17:15 | and some quotes that I used from book. I put a link there |
|
| 17:20 | you which will lead you to the link to that book. I have |
|
| 17:25 | affiliation with the book. I just like it. Uh Figure 1.1, |
|
| 17:34 | illustrate orthogonal relationship between frequency and time space and time. An event can |
|
| 17:42 | over and over giving the impression of change like circle of life Birth. |
|
| 17:50 | sort of a living death mosquitoes slip like 10 days. So that's their |
|
| 17:57 | cycle, that's their circle of There's of course some phases in that |
|
| 18:04 | it repeats and alternatively the event evolves time, like Panta rei on the |
|
| 18:12 | . But the forward order of succession the main argument for causality. Everything |
|
| 18:21 | forward that line and Monterey, the is moving forward. The time doesn't |
|
| 18:25 | back unless we get into a time or communicate to aliens and get there |
|
| 18:31 | or something. But other than that time is moving forward. The events |
|
| 18:36 | happened. They fluctuate over time. period corresponds to the perimeter of the |
|
| 18:44 | . So one period on the right you can see this is the |
|
| 18:49 | this is the phase, this is amplitude of the signal and then this |
|
| 18:53 | the period. Right? The complete which is can be represented also as |
|
| 18:59 | circle on the left. The sinus fluctuation. So you have this intimate |
|
| 19:06 | between space time and its packages into of space time, X, |
|
| 19:10 | Z. Time dimensions. So how dimensions are we talking about? four |
|
| 19:20 | ? What's the 5th dimension? The dimension would be the black holes in |
|
| 19:27 | event horizon where the space and time collapse. I guess there's no those |
|
| 19:35 | collapse and then there's something else. we know that both observation aly and |
|
| 19:44 | these oscillations can be conceived of and displayed in terms of space time, |
|
| 19:51 | can walk the perimeter of the circle twice ability of times. And yet |
|
| 19:55 | always get back to our starting What has been is what will be |
|
| 19:59 | what has been done is what will done and there's nothing new under the |
|
| 20:04 | . This is the circle of life our walk in its perimeter is measured |
|
| 20:07 | dislocation. Yeah. As an alternative the periodicity view, the universe is |
|
| 20:14 | display periodicity as a series of sine . Now we can walk along the |
|
| 20:19 | and peaks at the line without ever to the starting point. Which is |
|
| 20:27 | completely always true at some point. think use physically in space you can |
|
| 20:33 | to the same point but in time what is happening in space at that |
|
| 20:39 | point. And maybe even the shoes you're wearing, it's not going to |
|
| 20:43 | the same. Okay, so it's be a little bit different. The |
|
| 20:52 | are identical in shape and the start end points of the cycle form an |
|
| 20:56 | path into the seemingly endless universe. this this meandering. So we walked |
|
| 21:04 | , this fluctuation and we behave like and our brains behave in the sinus |
|
| 21:12 | activity and we can pick up this using electrons of holograms and when we |
|
| 21:19 | these E. G. Caps that containing electrodes on the surface of the |
|
| 21:26 | we can pick up some of the brain activity. And when we measure |
|
| 21:33 | behavioral different activity we pick up different with these electors. During different behavioral |
|
| 21:41 | we realized that there are dominant frequencies which these networks oscillator and walk this |
|
| 21:52 | your soil all line. And these frequencies are alpha, beta, |
|
| 21:59 | beta gamma and sharp waves. That's they're called. So for example if |
|
| 22:05 | look at the occipital cortex in the of the brain that processes visual information |
|
| 22:10 | eyes are open, the cortex will dominated in the back by the alpha |
|
| 22:20 | that have quite a large amplitude. have a frequency of about 8-10 Hz |
|
| 22:30 | 8 to 10 oscillations per second. once a person opens their eyes the |
|
| 22:38 | that gets picked up by the electrodes the exhibit alone will display predominantly beta |
|
| 22:47 | . And those beta waves are different , higher frequency And now what you're |
|
| 23:00 | on the right when the person again his eyes, the brain again gets |
|
| 23:07 | by alfa weights in this experiment is invasive. This experiments doesn't represent any |
|
| 23:17 | activity. This is normal brain activity how the brain circuits in this case |
|
| 23:24 | visual circuits in the occipital cortex switch one frequency into the next frequency and |
|
| 23:33 | is related to whether they're receiving visual or not person. So alpha is |
|
| 23:44 | with relaxed wakefulness, eyes closed. sleep data is intense mental activity. |
|
| 23:54 | you're looking at something engaged and this rhythm. So you'll say does that |
|
| 24:01 | that you'll only see these rhythms in part of the brain? And the |
|
| 24:07 | is you'll see them in different parts the brain depending on what those parts |
|
| 24:15 | the brain are doing at the You see somebody who has their hand |
|
| 24:22 | . Go ahead, Michael and uh dr Hubertus. Um So looking at |
|
| 24:29 | classification, the sharp waves, are saying those are Like the high frequency |
|
| 24:34 | like past the gamma. Is that per Yes. So we'll we'll get |
|
| 24:39 | that. Very good question. We'll to the next few slides. We'll |
|
| 24:43 | talk about them. But so you slower waves, delta waves, theta |
|
| 24:50 | and then you have faster waves, and sharp waves. And then the |
|
| 24:55 | waves I have drowsiness or pathology during wakefulness data waves but data is also |
|
| 25:02 | important rhythm for the circuits to be new information and through creating memories. |
|
| 25:09 | stay to gamma and sharp waves are important in these processes. And sharp |
|
| 25:15 | often referred to as ripples Are That circuits not just individual cells but |
|
| 25:23 | circuits can produce upwards to 400, even 600 cycles per second. This |
|
| 25:33 | another representation of uh of the left oscillations. Sometimes you will see that |
|
| 25:47 | overlap. So also in different These frequencies could be within different |
|
| 26:02 | So instead of Data 4-7 it could 7-9 that is dominating. So just |
|
| 26:12 | of a defense. But once again see that one of these traces that |
|
| 26:19 | seeing here on the right represents a electorate recorder. And you can see |
|
| 26:26 | between excited, relaxed, drowsy asleep deep sleeps states. The brain circuits |
|
| 26:36 | produce these various oscillations. Now when talk about each year recordings that our |
|
| 26:46 | and that means that the patient is the conscious awake it's a cap of |
|
| 26:54 | that's placed on the skull and it's up the electrical activity from the surface |
|
| 27:02 | the cortex but that electrical activity gets through the skull. And on the |
|
| 27:12 | child on the top is wearing an . G. Cap. From the |
|
| 27:16 | to pictures detects and grid of electrodes is actually placed on the surface of |
|
| 27:26 | brain. And you can see that skull, the scalp and the skull |
|
| 27:33 | the meninges. The dura. The Modern the adenoid have been cut and |
|
| 27:40 | brain surface has been exposed and an of electrodes will be placed on the |
|
| 27:46 | surface and these are intra cortical recordings still going to be extra cellular. |
|
| 27:57 | in this case they're a little and a lot more specific spatially And the |
|
| 28:05 | why you would do these kind of intro operatively is to determine exactly where |
|
| 28:14 | side of the pathology may be where neuronal function may be impaired or |
|
| 28:23 | the parts of regions of the brain are infected or otherwise affected, that |
|
| 28:31 | responsible for really crucial basic functions. in cases of neurosurgery. So if |
|
| 28:40 | have a resection of the brain, means the neurosurgeon will be removing, |
|
| 28:48 | a piece of your brain out. really want to take out as little |
|
| 28:53 | possible. And so in cases, example of cancer growth gliomas which are |
|
| 29:06 | common cancers of the brain that come glial cells called also glioblastoma sauce. |
|
| 29:15 | would want to do a surgery in case. But in other instances these |
|
| 29:22 | surgeries are done in the cases of and epileptic patients. And those are |
|
| 29:29 | cases where patients do not respond to when they do not respond to |
|
| 29:37 | the overactive areas of the brain produce electrical activity and can literally burn those |
|
| 29:44 | of the brain and can also turn abnormal synchronized activity in the interconnected brain |
|
| 29:52 | , slowly burning the interconnected brain In that case you want to remove |
|
| 29:59 | is called the focal point or the the part of the brain one spot |
|
| 30:05 | maybe two spots that are responsible for that abnormal activity or maybe that are |
|
| 30:13 | for having abnormal pathology in that pathology a spreading type of pathology and so |
|
| 30:19 | want to eliminate it and cut it . So you would do these great |
|
| 30:25 | of recordings. In fact, D. S quite often would work |
|
| 30:32 | ph D. S in the operating for these types of recordings. PhD |
|
| 30:40 | be responsible for the grid and the of the electrode signal and helping neurosurgeon |
|
| 30:49 | the specific regions of the brain that active and active. Pathologically affected or |
|
| 30:54 | for really important functions. A neurosurgeon going to be doing the work of |
|
| 31:00 | the skull of doing the surgery after recording. Now it's still is extra |
|
| 31:10 | it still is network activity but now specially a lot more precise. |
|
| 31:19 | And that's why you would use that operatively or inter operatively when we talk |
|
| 31:28 | the signals that get picked up by . G a single electrode. And |
|
| 31:34 | electrode caps can contain hundreds of electrodes they can contain 32 electors. It |
|
| 31:42 | kind of what country you live How advanced technologically it is some of |
|
| 31:50 | caps will we have the equipment that sample hundreds of electorates with very fast |
|
| 31:58 | rates, kilohertz and other types of equipment. And second to third world |
|
| 32:06 | may have fewer electrodes and slower sampling and it's all very much depends on |
|
| 32:14 | on the technology that is being used a single electorate when it's placed on |
|
| 32:19 | brain, the more electorates you have greater spatial specificity you can get for |
|
| 32:25 | abnormality that you're looking for. But general what the electrodes are picking up |
|
| 32:32 | the surface of off the skull is surface cortical activity from the parameter signal |
|
| 32:40 | signal sources from the parameter cells. parameter cells in the cortex, which |
|
| 32:47 | the sixth layer structure illustrated here on top right? 1234, A. |
|
| 32:53 | . C. Five and six. you can see that the parameter cells |
|
| 33:01 | layers 23 and layer five and layer will project these massive A pickle damn |
|
| 33:08 | to the very surface of the Cortex Layer one. and these 10 rights |
|
| 33:16 | where there's going to be a lot flux of the currents and deep |
|
| 33:26 | There's going to be activity on the here that gets picked up from layer |
|
| 33:34 | from letter to but from those ethical of the parameter south of projected the |
|
| 33:42 | of the cortex. So when you're E. G. You're mostly recording |
|
| 33:50 | polarities of an exchange of the And this is what we call the |
|
| 33:59 | and source of the currents. The will sink in the current and they'll |
|
| 34:04 | be the source of the current. so this is the signal that will |
|
| 34:12 | get picked up in a single trace representing a single electrode. Okay, |
|
| 34:24 | is the structure that we are learning . And you actually learned a lot |
|
| 34:29 | the function of hippocampus. When we at the circuit and we'll come back |
|
| 34:32 | look at the circuit again. What you see here on the bottom left |
|
| 34:38 | shows one through 16. That means taking a recording from 16 electrodes. |
|
| 34:45 | when you're taking an easy you're recording comparing activity an electrode, one versus |
|
| 34:51 | to, it's almost like a You take the difference between the two |
|
| 34:57 | that's what you're seeing and then between and three you take the difference and |
|
| 35:04 | is the each one of these black represents a recording of comparative recording from |
|
| 35:11 | of the selectors in the cap. you have some on the left, |
|
| 35:16 | on the left and you have eight the right left and right. And |
|
| 35:23 | the top. You see a picture a lady and she has this |
|
| 35:27 | G. Cap that is tied onto head and you can see that she |
|
| 35:34 | to be exhibiting somewhat of a normal and then be she seems to be |
|
| 35:45 | and is maybe having already an insight something to happen. This is usually |
|
| 35:53 | aura of the preceding seizure epileptic And so you can see in b |
|
| 36:01 | already occurrence on the right side of brain of synchronized activity that synchronized activity |
|
| 36:09 | not just in one electrode but it to spread across all of the right |
|
| 36:14 | of the brain and and see this is actually experiencing an epileptic seizure. |
|
| 36:23 | of the some of the features, many different types of epileptic seizures, |
|
| 36:27 | some of them may have an emotional even a screaming component when the person |
|
| 36:33 | having a seizure and you've seen see that activity has spread from the |
|
| 36:38 | side of the brain and to the side of the brain. And there |
|
| 36:41 | a generalized synchrony where all of the lectures across the entire surface of the |
|
| 36:50 | seeing very similar synchronized activity. So is also to say that there is |
|
| 37:00 | synchrony and there are these normal the normal frequencies and there's abnormal pathological |
|
| 37:11 | and pathological oscillations. And if these oscillations, if these seizures are repeated |
|
| 37:20 | if these seizures have a focus or sides such as hippocampus, it will |
|
| 37:27 | cause neuro degeneration. They will kill and they will kill eventually the brain |
|
| 37:36 | . You will have death and neuro and effects on hippocampus and alzheimer's |
|
| 37:44 | The hippocampus is also affected by schizophrenia when you look at the hippocampus, |
|
| 37:52 | is the structure of the hippocampus on , on the macro scale. This |
|
| 37:57 | wide arrows on the left and on right. It's basically showing a significant |
|
| 38:04 | to the hippocampus on the right and can have that significant damage in the |
|
| 38:10 | that are written up here. So only the abnormal electrical activity, but |
|
| 38:16 | the senile plaque growth and inflammation in and Alzheimer's disease, inflammation and breakdown |
|
| 38:24 | circuits in schizophrenia, abnormal signaling and oscillations and abnormal synchrony will lead to |
|
| 38:35 | will lead to abnormal release of glutamate will lead to toxicity. So abnormal |
|
| 38:42 | will set up, will upset the inhibitory balance. And if it favors |
|
| 38:49 | , it will cause neuro degeneration through toxicity, calcium and glutamate. So |
|
| 39:01 | are the rhythms created? How come is a variety of these rhythms? |
|
| 39:06 | you can see uh Table here on right from the article about 20 years |
|
| 39:13 | by sentiment and sake that have tried systematically tried to explain and mathematically tried |
|
| 39:22 | explain these different rhythms. And if look here, you can see that |
|
| 39:28 | of these rhythms are very slow there seconds. In fact, we have |
|
| 39:34 | rhythms that are underwater of day and . It's a circadian brain rhythm. |
|
| 39:42 | awake cycle, that's a day, cycle. Then we have a minute |
|
| 39:46 | cycles, rhythms. But when we're about the functional rhythms that influence activity |
|
| 39:53 | oscillations and synchrony, we're talking about the slowest rhythms being in seconds and |
|
| 39:58 | fastest rhythms being up to 600 And so these are the dominant rhythms |
|
| 40:06 | we talked about? The slow What's the delta data data? Gamma |
|
| 40:10 | and ultra fast rhythms. Why so facility regimes. If you think that |
|
| 40:17 | one of these facility regimes represents a behavior or a task that you can |
|
| 40:26 | well, it would be great if have many. It also would be |
|
| 40:31 | if they can overlap in time. that you can have fast rhythms riding |
|
| 40:36 | top of slow rhythms. And that happens. So you have very fast |
|
| 40:41 | and you need that precise and fast Because action potential also won two |
|
| 40:49 | The bear is coming at you and only have a half a second to |
|
| 40:53 | how you're going to behave. Everything very fast. It's happening around the |
|
| 40:58 | . The cars are zooming by fast the street. So you also have |
|
| 41:03 | answer questions, react emotionally in a fast manner. And these different frequencies |
|
| 41:12 | four distinct levels of computation. So looked at these rhythms and on the |
|
| 41:24 | scale you have natural log of And if you take the natural log |
|
| 41:33 | these dominant frequencies 1.5 to 44 to , 10 to 30. These beta |
|
| 41:40 | delta ranges of frequencies Make sort of fall within one integer apart from each |
|
| 41:49 | on the top. So on scale you're seeing. So that's a mathematicians |
|
| 41:58 | of trying to explain mathematically and computational these different rhythms from a cellular |
|
| 42:06 | We have all of these different cell that we talked about that will contribute |
|
| 42:11 | creating these different rhythms neurotransmitters and ion . Some of them are fast. |
|
| 42:17 | of them are slower. And of you have these rhythms that are created |
|
| 42:24 | li so you don't have to have exogenous input. You don't have to |
|
| 42:29 | can close your eyes, you can asleep, the brain will still have |
|
| 42:32 | rhythms. There will be just different . But the rhythms in our brain |
|
| 42:37 | even the sleep rhythms will be entrained what we're seeing in the outside environment |
|
| 42:43 | the stimuli that you're seeing in the environment. So E. G. |
|
| 42:53 | and modern day electrode recordings and localization the source signal are very important. |
|
| 43:01 | when you do E. G. your recording potentially from 1000 of neurons |
|
| 43:07 | the optical dendrites from parameter layer five layer two. But you don't know |
|
| 43:14 | sell exactly fired. When and so localization by triangulation for determining heart's electrical |
|
| 43:23 | . Voltage measurements are made to clean right and left arms. Mhm. |
|
| 43:30 | left arm and left leg. Top photograph, top left illustrates William Eindhoven's |
|
| 43:38 | . The subject places environment lagged in salt water connected to saldanha. Meaner |
|
| 43:44 | the voltage deflection. In each The voltage vector can be calculated and |
|
| 43:51 | this was used for E. G. For heartbeat recordings. This |
|
| 43:57 | of a triangulation and in the bottom strangulation of the three dimensionally position of |
|
| 44:06 | by tetro measurements. So Tetro diz electrode that actually has four electrodes in |
|
| 44:13 | that you would insert inside the So this is not surface reporting the |
|
| 44:19 | differences between the wires of the tetra . Of the recorded spikes from individual |
|
| 44:25 | allow the calculation of the unique position each neuron. So basically by knowing |
|
| 44:35 | tetro structure where it's sitting in the , the amplitude of the signal you're |
|
| 44:42 | up and the speed at which that is electrode. One located the |
|
| 44:48 | We'll pick up the signal first from parameter cell and the electrode in the |
|
| 44:52 | will pick it up last right You know that if the cell fired |
|
| 45:02 | , that's the closest to this electrode the Tetreault, it's located on this |
|
| 45:07 | of the tet road. If the in the back, if the electorate |
|
| 45:11 | the tetra in the back first reacted the signal and then the second electorate |
|
| 45:16 | then this last elector. Then you'll that the cell is located on that |
|
| 45:21 | of the road. Now you basically a spatial localization on a cell level |
|
| 45:29 | a microscopic level. And textures will you to pick up individual spiking activity |
|
| 45:35 | actual potential activity from the south will you to triangulate Where those cells are |
|
| 45:41 | which Sauce Fire 1st and in which which is also important for the frequency |
|
| 45:49 | foreigners are rhythms. This is uh connectivity within local micro circuits of the |
|
| 45:59 | cortex of the rat. So these the experimental neuroscience recording from the |
|
| 46:07 | Mhm. And you would insert these film like stripes. You can see |
|
| 46:16 | stripes in the middle have wires running them and each one of these wires |
|
| 46:22 | conducted to tiny little micro electrodes. now you can have one stripe that |
|
| 46:28 | have 123-456-78. There's even higher number electrodes if this stripe electrodes are very |
|
| 46:37 | so you can implant them without damaging brain structure's very much synaptic connections between |
|
| 46:45 | parameter cells. Triangles in this diagram parameter cells and putative into neurons suspected |
|
| 46:54 | neurons are circles. Mhm can be by the temporal relationship. Where are |
|
| 47:05 | circles are pointing to the, to to the circles here as putative into |
|
| 47:11 | for example decreased discharge of a partner immediately after the spike of the reference |
|
| 47:18 | . Time zero in the upper wide a gram reveals the inhibiting age of |
|
| 47:24 | reference neuron. Conversely, a consistent lengthens the discharge of the partner of |
|
| 47:29 | after the reference spike. Lower instagram excitatory nature of the reference self. |
|
| 47:37 | you can see that they're talking about hissed a gram here of activity and |
|
| 47:42 | can see a break here and when is a break here there's something going |
|
| 47:48 | here that is excitatory. So what happening is now you can start inferring |
|
| 47:56 | or an inhibitory activity In general Her parameter cells, they will not |
|
| 48:02 | higher than 20 hertz per second. the inhibitory cells will hire will fire |
|
| 48:09 | to 600 hertz a second. so this is the circuit that we |
|
| 48:17 | at on a microscopic scale. Now gonna go back and look at the |
|
| 48:22 | on the macroscopic scale. That's the system that contains our infamous hippocampus. |
|
| 48:33 | . James tape says In 1937 described Olympic system as cortical machinery fulfilling the |
|
| 48:47 | involves limbic lobe a regional identified by . So you have different structures that |
|
| 48:57 | shown in green that all participate in olympic system and they have communication between |
|
| 49:04 | different structures in a certain way. you have the singular gyrus here. |
|
| 49:12 | . Corpus callosum is gonna be the that is going in to connect the |
|
| 49:16 | hemispheres and this is how activity and epileptic or seizure activity will spread from |
|
| 49:23 | hemisphere left to right or right to . You have entering final cortex. |
|
| 49:34 | you have para hippocampal gyrus, you hippocampal formation which contains our hippocampus, |
|
| 49:46 | dental gyrus, subic gulum area, cervical um and parasitic element interim neocortex |
|
| 49:53 | interacts with the hippocampal formation. There also several nuclei hypothalamus, mammal, |
|
| 50:02 | ethel thomas. That's all basil wow there's a lot of stuff involved |
|
| 50:11 | on top of that there's a big structure called the medulla where you have |
|
| 50:17 | lot of emotional fear processing centers as as facial recognition centers. The memory |
|
| 50:24 | these facial recognitions. So it's a complex system the limbic system hippocampus is |
|
| 50:34 | very important part of it. And in particular has its own distinct |
|
| 50:43 | If the campus is called after hippocampus are on the losses because in |
|
| 50:51 | because it actually has a shape that a bent like shape that reminds anonymous |
|
| 51:00 | the seahorse and in hippocampus the major , it's called corner simone or see |
|
| 51:11 | areas and it is named after Horny demon was an ancient Egyptian |
|
| 51:18 | He was depicted as human with a head. So that's the Egyptian |
|
| 51:25 | one of the chief god's latest supreme . And he was then adopted by |
|
| 51:32 | Zeus on the on the it's served and romans is jupiter still containing the |
|
| 51:43 | , the ram's horns. So that shape of hippocampus and the ram's horns |
|
| 51:49 | what gave hippocampus its its name and the different hippocampal areas their names to |
|
| 51:57 | a one of the most famed and structures in the brain. This is |
|
| 52:04 | nestle stain missile stain will stain all the cells in the brain and so |
|
| 52:09 | you're seeing these blue punk tape. seeing neurons. You also can stain |
|
| 52:14 | and neurons all of the south using stain. And you can see here |
|
| 52:20 | is the rodent brain. So in human brain hippocampus is located here toward |
|
| 52:27 | temporal lobe. Okay towards the base the brain is in this diagram. |
|
| 52:32 | in rodents you can see that it located on the on the superior side |
|
| 52:40 | of cortical and you can see these dark bands and these dark bands represent |
|
| 52:47 | cell populations. Typically actually excitatory cell . The hippocampus has this distinct and |
|
| 52:57 | identifiable growth structure and histological appearance. has laminate structure with one very distinct |
|
| 53:05 | layer that very dense band but it's three layer structure. It's plays a |
|
| 53:11 | important role in learning and memory and may have read or heard or it's |
|
| 53:17 | . I would encourage you on your time to read about the case of |
|
| 53:22 | . M. And the treating physician and milner from Canada in the 1950s |
|
| 53:30 | described the case of Hmm that had to hippocampus and had damage to the |
|
| 53:36 | areas of the brain And could not anything. And that's how in the |
|
| 53:42 | and 60s we determined that Hippocampus played very important role in memory information. |
|
| 53:50 | is perhaps the second most famous patient their science following finesse gauge except that |
|
| 53:59 | don't have medical notes of Phineas gauge we do on a judge and |
|
| 54:06 | He would introduce himself to his treating every day because he wouldn't remember who |
|
| 54:12 | were and that tells me that the is important in encoding the memory and |
|
| 54:20 | of the memory and in particular the memory places, dates, advanced |
|
| 54:26 | names not procedural memory like doing things motor actions. Hippocampus is a part |
|
| 54:36 | the brain that is susceptible to seizures susceptible to epilepsy and also other neuro |
|
| 54:43 | that we've already discussed. Alzheimer's Schizophrenia because it is relegated supported cle |
|
| 54:50 | is very, very sensitive. Two changes and therefore small ischemia or anoxia |
|
| 55:00 | of oxygen. Uh two neurons and sub cortical hippocampal areas will cause neuronal |
|
| 55:09 | within minutes. So you know that need oxygen and they need nutrients. |
|
| 55:17 | if the brain is derived deprived of For two minutes or more neurons start |
|
| 55:30 | when somebody has a stroke or they and have a clinical death, their |
|
| 55:37 | stops. The first thing that the physicians want to know is how long |
|
| 55:46 | the heart stopped for? If the stops, that means there's no |
|
| 55:51 | That means that there's no pumping of oxygenated blood. But the hard |
|
| 55:58 | This is the difference really between the uh duration divers then actually go and |
|
| 56:08 | and keep the air For how long five minutes. Why do their neurons |
|
| 56:15 | die? Because their heart doesn't stop . They're alive. But if you |
|
| 56:22 | clinical death, somebody is no pulse two minutes neurons start dying. That |
|
| 56:31 | there's no oxygen, there's no residual that's being pumped through the blood |
|
| 56:36 | That's it. And within 10 minutes person is likely to be brain dead |
|
| 56:43 | certain parts of the brain brain stem sub cortical regions are exquisitely sensitive, |
|
| 56:50 | losses of oxygen. This is the precise circuit of the hippocampus and hippocampal |
|
| 56:58 | . When we talk about corner this is the sea a region and |
|
| 57:02 | are the parameter cells that will be in the parameter layer. This is |
|
| 57:07 | dental age iris. That will contain cells that are excited to re granule |
|
| 57:13 | is the second type of the excitatory and it's going to receive most of |
|
| 57:19 | input through the perforated pathway that will from the cortex. So you can |
|
| 57:25 | Ec here in this diagram is entering cortex that is going to project into |
|
| 57:30 | dental gyrus. The Hippocampus. There's to be a small pathway from ec |
|
| 57:36 | bypasses DDG and goes directly into the . A. three area too. |
|
| 57:42 | the major pathway into hippocampus input is the preference pathway into the dental page |
|
| 57:48 | . The excitatory cells and dente gyros the granule cells so they're different from |
|
| 57:54 | cells but there's still projection excitatory They're flying and survived it by different |
|
| 58:01 | of interneuron simple you'll find in G. And the major fiber bundle |
|
| 58:07 | but they will come out from dented from the granule cells is called the |
|
| 58:11 | fibers that will Synapse onto the Parameter of the sea. A three region |
|
| 58:17 | the Hippocampus. The major C. . Three outputs into the sea. |
|
| 58:24 | one region of the hippocampus that we've discussing. and we discussed the complex |
|
| 58:29 | and excitatory circuit. This is the A. Collaterals, the shopper |
|
| 58:34 | So project out of C. Three into C. A. One |
|
| 58:38 | the optical done drives of the parameter . And if the cells are excited |
|
| 58:45 | this excitation is regulated in a certain by the inhibitor inter neurons then the |
|
| 58:51 | of the hippocampus is going to be area C. A. One into |
|
| 58:56 | sib Picula ma'am. From C. into the civic Yalom as well as |
|
| 59:02 | the frontal cortical areas. So now can see that you have within even |
|
| 59:10 | very simple structure. Simple because it has three layers. You have these |
|
| 59:18 | dominant pathways. And I could ask to label those pathways in the exam |
|
| 59:23 | recognizing them because this builds really a complex understanding of what a circuit excited |
|
| 59:32 | inhibitors circuits looks in one structure that's simple structure. Other representations of this |
|
| 59:52 | you're seeing. Yeah okay dont gyros . G. C. Three C |
|
| 60:00 | cervical. Um This isn't a The cuts that you're looking at are |
|
| 60:07 | transverse cuts there in the transverse There's sort of a cross cut through |
|
| 60:14 | but they're not in your typical cross that you would see through the entire |
|
| 60:21 | and then you have PP preference Major impotent to hippocampus. Mossy |
|
| 60:29 | they're called mossy fibers because the granule outputs excitatory fiber output looks like |
|
| 60:37 | Under a microscope. It's very widely with very small synaptic differentiations. And |
|
| 60:47 | fibers will contact criminal cells and Three S. C. Stands for |
|
| 60:53 | collaterals will contact C. One And from C. A. One |
|
| 60:59 | into the civic Yalom. You have this Kathleen # four. The projection |
|
| 61:07 | this ridiculous. You can see that difference between the granule cells and the |
|
| 61:17 | cells. These excitatory cells but granule don't project out of the hippocampus. |
|
| 61:24 | project within the hippocampus granule cells have dendritic projections unlike gravity. All sauce |
|
| 61:31 | have both basil and a pickled Granule cells have only a pickle. |
|
| 61:41 | right? So this is a granule and this is the brahmin. All |
|
| 61:51 | really personally. Okay So you have cells that are manipulative little projections monta |
|
| 62:16 | or external projections to see a. . These mossy fibers. Okay. |
|
| 62:21 | . Three C two C. A stratum for a mandala is the parameter |
|
| 62:26 | layer. They will have bipolar. then drives here in the parameters of |
|
| 62:33 | large cell bodies. See a two a C A two region. So |
|
| 62:38 | say like how come you forgot Ch ch two is not very well studied |
|
| 62:43 | not very well connected. But this input that comes from Grandal sauce will |
|
| 62:48 | only see three cells and C. cells will have very large. So |
|
| 62:54 | of the parameter cells densely located So this is our favorite slide and |
|
| 63:01 | favorite circuit. This is you can C. three virus. Okay. |
|
| 63:08 | types of parameter cells and uh at 21 classes of inter neurons in |
|
| 63:15 | See in one area how are parameters ? Different. They're different because some |
|
| 63:20 | them live in stratum ready autumn. in stratum orient. Most of them |
|
| 63:25 | in stratum pyramidal, give that cell very high density when you're staying for |
|
| 63:32 | stand for example they stained for Kalb or they do not and that's |
|
| 63:40 | So they inhibit their inter neurons. already discussed. You can see that |
|
| 63:44 | have different morphology. They can target their synapses where there's yellow cops different |
|
| 63:51 | of the exhaust, somatic axis, , somatic dendritic access on the parameter |
|
| 64:01 | and some of them are located in layers. Some of them are located |
|
| 64:05 | pyramidal and some of them are located Ready Adam the two cells that we |
|
| 64:13 | earlier for these functional circuits of the cells and the old lamb cells. |
|
| 64:20 | as you will see basket cells are in the feedback and in the feed |
|
| 64:25 | inhibitor inhibition and the alarms also involved the feedback inhibition. So here are |
|
| 64:34 | of the ways in which you would feedback feed forward or even lateral |
|
| 64:40 | These are some of the learning rules the rules by which the brain operates |
|
| 64:46 | you get an excited to input on parameter cells. Those parameter cells that |
|
| 64:50 | flying by inhibitor cells that will also only project their axons out of the |
|
| 64:57 | . So also excited nearby inhibitory cells by exciting nearby inhibitory selves. They |
|
| 65:03 | cause an inhibition onto themselves. So is a feedback negative started of feedback |
|
| 65:10 | , feed forward inhibition. Is that inputs that are coming in, These |
|
| 65:17 | that are coming in, let's say c. three. They're not only |
|
| 65:20 | to target the parameter cells but they're as you can see going to target |
|
| 65:26 | dendrites of the inhibitor into neurons. when they come in and they target |
|
| 65:33 | salsas inhibitory. South could be located of the excitatory cells and so they |
|
| 65:41 | receive an excitatory input. Inhibit ourselves inhibit these cells in the feed forward |
|
| 65:48 | because they will be receiving the same input from the C. Three region |
|
| 65:53 | C. One region excited for inventory , lateral inhibition. It provides for |
|
| 66:00 | is called autonomy or segregation of So if you have excitation of the |
|
| 66:07 | cell and you have excitation of the into neurons that surround this parameter will |
|
| 66:15 | . Then these surrounding inhibitory cells can activity from the nearby circuits from the |
|
| 66:23 | excitatory cells and strengthen the activity of cells that are receiving the original |
|
| 66:31 | So this is the lateral inhibition rule exists exists in the brain. This |
|
| 66:42 | the basket cell that we talked about hmm. And into neurons can target |
|
| 66:51 | proximal and distal synopsis but most of inhibition that happens happens in this |
|
| 66:58 | Somatic regions around the selma. The of the inhibitory projections affect excitatory |
|
| 67:04 | Integrative properties feed forward inhibition, feed inhibition can have a huge input. |
|
| 67:13 | the cell is going to produce an potential or not because it's going to |
|
| 67:18 | polarized. The self feedback inhibition can tame the activity of the cell after |
|
| 67:23 | cell already fired this action potential to feed forward our basket cells. In |
|
| 67:31 | previous diagrams feedback would be an Alarm cell because it doesn't receive much |
|
| 67:38 | to input from C. Three. rather from the parameter cells and the |
|
| 67:43 | parameter one parameter cells are active. will activate all alarms cells that stands |
|
| 67:48 | orients like an awesome a local larry . And those will respond by targeting |
|
| 67:55 | optical dendrites of parameter cells and inhibiting optical done dried activity. So now |
|
| 68:05 | you look at these abbreviations in the , it reminds you of something something |
|
| 68:10 | you know. S. O. for stratum orients sp stardom for a |
|
| 68:14 | . A. S. R. already autumn. That's a long time |
|
| 68:17 | looking also my local route relative. addition strength of different compartments of |
|
| 68:23 | A one parameter salt during theta oscillations sharp wave ripples. So you can |
|
| 68:30 | that these data oscillations. At first will have strong parameter will sell activity |
|
| 68:37 | the brahma dolly layer where you have lot of red here and then that |
|
| 68:43 | is going to shift into the optical and basil areas here in the orients |
|
| 68:51 | Rommedahl, a layer is going to dominated by inhibition here, creating the |
|
| 68:57 | and the opposite direction and then coming of it. You will have again |
|
| 69:01 | dominating around stratum from adala layer in the opposite side of that oscillation, |
|
| 69:09 | opposite wave. You can see how wave ripples would be then superimposed over |
|
| 69:16 | hippocampal structure. And these sharp wave and data rhythms are both very important |
|
| 69:23 | for learning and memory. You'll also hear about spindle rhythms. These rhythms |
|
| 69:31 | ride on top of each other. you can have slower rhythms and on |
|
| 69:39 | of the slower the rhythms, you have much faster rhythms. So for |
|
| 69:47 | , this could be a sharp oscillation is writing And this is 200 Hz |
|
| 69:58 | is riding on top of this That is 20 Hz. And so |
|
| 70:05 | can have overlap of multiple redos in same circuits and you can see that |
|
| 70:14 | there will be affecting different players differently different temporal sections of this ongoing |
|
| 70:27 | So for example, this is a cell and on top and blues a |
|
| 70:34 | cell and green is a basket Now, when you have this precise |
|
| 70:41 | anatomy and inhibit the excitatory cells. can ask the question which sells fire |
|
| 70:47 | the peak or the highest frequency and highest amplitude of the ripples. And |
|
| 70:52 | answer is criminal cells, basket And this other cell called the stratified |
|
| 70:58 | . What about the alarm sells? about the other cells? These are |
|
| 71:01 | the hissed a grams. And the of firing for firing probability. So |
|
| 71:08 | higher the peak here the more likely type of cell is going to |
|
| 71:13 | It's more probable that cell is going fire. And so now you can |
|
| 71:18 | that to create this ripple rhythm. have 123456 different types of cells firing |
|
| 71:25 | different phases of this ongoing rhythm, or inhibitory cells providing for their peak |
|
| 71:33 | in different phases of this overall network them. And so you would have |
|
| 71:41 | kind of readouts that are called spectrograms local field potential. So you can |
|
| 71:47 | spectrograms of E. G. Recordings their frequency spectral analysis. This is |
|
| 71:54 | E E. G. And you see in the top the darker the |
|
| 72:01 | the lines that you're seeing, the axis is time and seconds. The |
|
| 72:08 | axis is frequency. This is rem . It's a slow wave sleep. |
|
| 72:13 | can see how the frequencies shift. then in exploratory mode exploration is dominated |
|
| 72:21 | the state of rhythms and also by frequency gamma rhythms. And so now |
|
| 72:28 | can find the dominant frequencies during different states and now you can understand that |
|
| 72:36 | different behavioral states will be created by subtypes of inhibitor and excitatory cells contributing |
|
| 72:47 | exhibitor inhibitory excitatory signals within space and . Using certain rules and using the |
|
| 72:58 | of cellular subtypes that will provide for complexity of behavioral states and complexity of |
|
| 73:05 | capabilities that we have in my So this is all good stuff that |
|
| 73:10 | going to get covered on on the one. And I'm happy to take |
|
| 73:16 | questions on Wednesday because I think I've my time today to the maximum. |
|
| 73:21 | don't want to hold you guys Thank you all for being here in |
|
| 73:26 | today. Just a reminder on Wednesday can be here in class but I |
|
| 73:31 | only be on zoom but you can to use the class. Nobody should |
|
| 73:36 | here and you can tell them to away it's their classroom if they're |
|
| 73:42 | So see you on Wednesday on zoom your review session then. Thank you |
|
