[00:00:05.08] So thanks very much for the invitation was no traffic on the way here so [00:00:09.07] [00:00:09.07] I got here radically early so I was expecting traffic but it's a holiday so [00:00:14.22] [00:00:14.22] yeah today I'm going to break I'd like to kind of break up the talk into 2 sections. [00:00:19.17] [00:00:20.18] The 1st is more. [00:00:22.00] [00:00:24.08] Think about some of things I've worked on in the past but we're still thematically [00:00:27.14] [00:00:27.14] interested in in terms of the mechanisms of learning and how subsoil processes [00:00:34.02] [00:00:34.02] are involved with the formation of memories through long term plus the city. [00:00:37.17] [00:00:38.19] And then the 2nd part will be you know the medically completely distinct but [00:00:44.15] [00:00:44.15] I think we're actually we're still think about some of the same type of mechanisms [00:00:48.03] [00:00:48.03] in terms of circuit inhibition So [00:00:53.05] [00:00:53.05] what's how do we think about the neurological basis for learning. [00:00:57.01] [00:00:58.03] And this is kind of how I defined it is that when you're learning [00:01:02.16] [00:01:02.16] something there's a dedicated circuit in a particular part of the brain that's [00:01:06.07] [00:01:06.07] activated are responsible for driving that type of learned behavior and [00:01:12.04] [00:01:12.04] that learning occurs following very simply a change in either the synaptic or [00:01:17.13] [00:01:17.13] signaling properties of neurons within that circuit best known as Plus the city [00:01:21.21] [00:01:23.06] so how might it actually work in real life see if I can get rid of this that. [00:01:28.17] [00:01:36.04] You built take 6 months. [00:01:38.15] [00:01:43.10] Sorry. [00:01:44.00] [00:01:51.21] It's working. [00:01:52.10] [00:01:55.06] Very good so here is. [00:01:57.13] [00:01:59.09] An example of a particular type of learning considered motor learning. [00:02:04.04] [00:02:04.04] So couple years ago about 10 years ago this subway station New York City [00:02:09.18] [00:02:09.18] had an anomaly with its entrance way that really allowed for some kind of real time [00:02:16.14] [00:02:16.14] observation of what a motor learning example might be in humans. [00:02:21.06] [00:02:24.01] You'll notice that some people have a lot of trouble with this step [00:02:28.18] [00:02:28.18] which is about a fraction of an inch difference from the other steps and [00:02:32.19] [00:02:32.19] some people have a really hard time with it so in my mind. [00:02:35.11] [00:02:36.18] I'm thinking that some of these people are tourists getting off the Stop the 1st time [00:02:40.05] [00:02:40.05] some of these people are maybe locals they're used to the step being off [00:02:44.23] [00:02:44.23] I think there's one really good example near the end. [00:02:47.08] [00:02:48.11] That. [00:02:48.23] [00:02:50.21] Really almost bites that. [00:02:51.23] [00:02:54.04] Area. [00:02:54.16] [00:02:56.11] This friend look sort of like what you didn't expect that so [00:02:59.20] [00:02:59.20] how could we study this process. [00:03:01.18] [00:03:04.06] Well there's many different ways that as neuroscience we can think about this we [00:03:07.07] [00:03:07.07] could think about it in big cortical loops or in big circuits centric sort of [00:03:12.00] [00:03:12.00] models but our lab as a theme thinks about these kinds of things or [00:03:17.09] [00:03:17.09] once at least study these types of things and sort of a neuron centric manner so as [00:03:22.18] [00:03:22.18] a lab we kind of want to understand what is it about different subsets of neurons [00:03:27.09] [00:03:27.09] What is the sort of set of signaling functions that they need to perform and [00:03:32.01] [00:03:32.01] how do they do that to you know perform the sort of processes. [00:03:35.18] [00:03:37.07] And even more specifically compartmentalization of signaling within [00:03:41.20] [00:03:41.20] themselves and different types of neurons is sort of a key feature that we look [00:03:46.22] [00:03:46.22] at in terms of learning memory and also in disease models so [00:03:52.07] [00:03:52.07] a really good cartoon example of how compartmentalization of signal it works [00:03:56.19] [00:03:56.19] through the neurons is a single action potential can fire at near the soma [00:04:01.12] [00:04:01.12] actually in the proximal proximal axon and that red compartment [00:04:07.06] [00:04:07.06] is actually the axon you can see the signals much sharper and the signals [00:04:12.16] [00:04:12.16] much wider in the somatic compartment see if I get this laser pointer [00:04:18.14] [00:04:19.15] and then in the dendritic compartment this is the same action potential but [00:04:23.07] [00:04:23.07] it's broadened out so why is it that these signals are sort of expressed differently [00:04:28.21] [00:04:28.21] throughout the neuron what sport purposes do they serve would that serve and [00:04:34.02] [00:04:34.02] our approach is just to give you a little bit of background of sort of the some of [00:04:38.02] [00:04:38.02] the techniques we're working with everything just about everything else show [00:04:42.02] [00:04:42.02] you today is from acute slices from Bill 1000000 circuits so mice. [00:04:48.07] [00:04:49.15] Recordable slices. [00:04:51.11] [00:04:53.00] We use a number of physiological approaches to look at [00:04:57.21] [00:04:57.21] cellular function whole cell Pashka electrophysiology another [00:05:02.09] [00:05:02.09] number of different electrophysiological approaches to photon microscopy [00:05:07.09] [00:05:07.09] to look at sub sailor and cellular processes. [00:05:10.03] [00:05:11.04] A little bit more in depth we use voltage sensitive imaging so sometimes dies and [00:05:18.02] [00:05:18.02] more recently we're now using genetically encoded both Giunta caters [00:05:22.04] [00:05:22.04] fluorescents got a patch clamp which helps us to patch on to very very small regions [00:05:26.15] [00:05:26.15] of neurons and I think I even have the example of ion channel 4 Tulsa's so [00:05:31.08] [00:05:31.08] we can actually block different conductance is a focal matter within their [00:05:35.05] [00:05:35.05] own Socratic dissect out where they exist and what their purpose is. [00:05:38.08] [00:05:39.12] So as I just alluded to. [00:05:41.07] [00:05:42.09] The 1st part of the talk is going to be solely focused into the cerebellar regions [00:05:47.06] [00:05:47.06] of the cerebellum and the reason we use our bones has a fantastic model for [00:05:53.01] [00:05:53.01] plus is the in learning is sort of a it's in terms of mammalian circuits anyway it's [00:05:57.21] [00:05:57.21] a simplified circuit has a lot of advantages to looking at cerebellum its [00:06:03.17] [00:06:03.17] major function as religion well defined and there's a number of motor learning. [00:06:08.23] [00:06:10.23] Pathways that have been identified such as I blink conditioning and [00:06:14.15] [00:06:14.15] this little or ocular reflex or Vo or. [00:06:16.19] [00:06:18.15] There are very well the well defined circuits of the cell types in [00:06:21.15] [00:06:21.15] the cerebellum Perkins' you sell the p.c. [00:06:24.22] [00:06:24.22] is the major output and the old and really the only output of the circuit. [00:06:29.01] [00:06:30.23] These parallel fibers which emanating from the granule So [00:06:36.20] [00:06:36.20] those are the most numerous neuron actually in the 1000000 brain [00:06:42.20] [00:06:42.20] and basically what they are conveying is context sensory motor context so [00:06:46.18] [00:06:46.18] if you're moving your arm there's going to be a certain number of parallel fibers [00:06:49.21] [00:06:49.21] that are sort of firing during that. [00:06:51.06] [00:06:52.20] During that process the climbing fiber and so that is what's thought of [00:06:58.19] [00:06:58.19] as the cell type that's really responsible for conveying error signals so [00:07:03.07] [00:07:03.07] during a movement if you're activating all these parlor fibers and [00:07:06.11] [00:07:06.11] something a sensory motor mismatch happens for example you're on that step and [00:07:12.03] [00:07:12.03] you almost trip then it's thought that those climbing fibers are going to fire. [00:07:16.05] [00:07:17.06] And they they are extraordinarily strong synapse. [00:07:20.01] [00:07:21.03] So it's the parallel fibers in green. [00:07:22.23] [00:07:24.05] That's what the typical sort of so that they can put into a slow but [00:07:28.02] [00:07:28.02] look away from the parallel fiber and the climbing fibers and read. [00:07:31.15] [00:07:33.03] If you're recording from the Kinsey cell that p.c. [00:07:36.17] [00:07:36.17] then you'll get a very strong complex Spike occurring and [00:07:41.23] [00:07:41.23] how does plus this be classically thought to occur within this circuit. [00:07:45.15] [00:07:46.23] So that happens when you have a near coincident pairing of these 2 pathways so [00:07:52.09] [00:07:52.09] you're activating some of those problem fibers perhaps [00:07:55.01] [00:07:55.01] perhaps you're in some sort of motion sequence and you make that error and [00:07:59.13] [00:07:59.13] then you get an error in your environment and when you have the power of a farmer [00:08:03.08] [00:08:03.08] input in the climbing fiber input and in this close coincident in time [00:08:08.07] [00:08:08.07] then that's the trigger plus the city in the circuit. [00:08:11.20] [00:08:13.10] Interestingly the climbing fibers are carrying this plus this city or [00:08:21.06] [00:08:21.06] that convey Plus this is what I think of as a very compartmentalized manner [00:08:26.03] [00:08:26.03] some very intricate dendrite dendritic centric mechanism [00:08:30.20] [00:08:30.20] that's completely subsoil ular excitable phenomenon distinct from the soma and [00:08:35.20] [00:08:35.20] these are just some sort of power for is in from really classic papers in the field [00:08:41.00] [00:08:41.00] and we can show show you that through a single experiment what looks so we can [00:08:47.23] [00:08:47.23] actually electrically stimulate all these pathways record from the park into so. [00:08:52.11] [00:08:53.14] And at the same time also record from that then try so these are whole soul patch [00:08:57.23] [00:08:57.23] point recordings that are happening simultaneously [00:09:00.19] [00:09:00.19] at the 2 different regions of the same neuron wall either. [00:09:04.19] [00:09:06.06] You can electricity believe climate fiber parallel fiber So [00:09:11.06] [00:09:12.10] this is the really striking compartmentalization of the signals here [00:09:15.22] [00:09:15.22] if you see the parkin do so at the Soma. [00:09:18.05] [00:09:19.14] If you fire the climbing Farber just one time [00:09:23.02] [00:09:23.02] you see these rapid sodium spikes that happen. [00:09:25.12] [00:09:26.15] If you look at the recording at the Denver right. [00:09:28.16] [00:09:29.21] The dendrite has this completely different signal. [00:09:33.03] [00:09:34.09] It's almost like a completely separate temporally as well [00:09:38.14] [00:09:38.14] if you overlay the 2 and actually what's happening [00:09:42.17] [00:09:42.17] at the Denver right are these these are actually calcium spikes. [00:09:46.07] [00:09:47.12] As opposed to that then the Soma which are being conveyed by sodium spikes from [00:09:51.18] [00:09:51.18] the x. on. [00:09:52.09] [00:09:56.03] So if we look at a recording now from the kynge still and [00:10:00.06] [00:10:00.06] look at what happens classically with parallel fiber stimulation and [00:10:03.21] [00:10:03.21] close opposition in time to a climbing fiber. [00:10:06.11] [00:10:07.23] There's classic papers that show that this results in l.t.d. so [00:10:12.21] [00:10:12.21] classic cerebellar it l.t.d. and what we know now is that [00:10:17.23] [00:10:17.23] there's an enhancement of calcium entry into the dendrites of the of these [00:10:23.02] [00:10:23.02] Perkin to cells specifically in the spines of these tender rights that allows for [00:10:28.08] [00:10:28.08] the plasticity to occur so what does it look like we can actually do a. [00:10:32.12] [00:10:33.15] Calcium recording from single spines so [00:10:36.14] [00:10:36.14] this is using just a calcium die like a flow 5 f. and with looking [00:10:41.14] [00:10:41.14] at that single spine during a climbing fiber event you get some calcium entry and [00:10:46.08] [00:10:46.08] if you look at the spine during perilous fiber plus climbing fiber You see you get [00:10:51.22] [00:10:51.22] some calcium intruder in the parlor Farber and some during the climbing fiber. [00:10:56.11] [00:10:59.13] If you look at what would be expected from the some of the Parlow fiber in [00:11:03.20] [00:11:03.20] the climbing fiber by themselves that's what this looks like here that's sort of [00:11:08.04] [00:11:08.04] the arithmetic some of the predicted. [00:11:10.02] [00:11:11.07] But when in reality when you have this parallel fiber in climbing 5 or so [00:11:16.00] [00:11:16.00] coming it's nearly simultaneously you have this super linear increase in calcium that [00:11:21.06] [00:11:21.06] happens in the spine and that's what's thought to underlie the expression of l t [00:11:25.04] [00:11:25.04] v So in reality there's a major issue with how this could work. [00:11:31.06] [00:11:32.09] And the reason that is is because climbing fibers are firing [00:11:37.01] [00:11:37.01] spontaneously at about 1.5 hertz so [00:11:40.23] [00:11:40.23] the question becomes why is it that learning mechanisms are not saturated then [00:11:45.22] [00:11:45.22] because you're always getting these complex spikes in the dendrites So [00:11:49.16] [00:11:49.16] how are errors and the smaller learning reliably encoded in this case. [00:11:55.00] [00:12:00.02] So one solution is this active regulation of dendrites [00:12:04.08] [00:12:04.08] right now in an artificial sense we can patch a dendrite and [00:12:08.11] [00:12:08.11] you see we stimulate a climbing fiber like I showed you before and [00:12:13.00] [00:12:13.00] you see this big calcium Spike event actually 3 calcium spikes that happen with [00:12:16.20] [00:12:16.20] a single climbing fiber firing Now if you just hyper polarized that right with [00:12:22.01] [00:12:22.01] your pouch electrode if you've got good wholesale access you actually can reduce [00:12:26.08] [00:12:26.08] the amount of spikes that occur just by hyper polarizing that Android The only [00:12:30.16] [00:12:30.16] problem is that this is very difficult to achieve because our brain so have power to [00:12:35.18] [00:12:35.18] look roads attached every can do so all right so we need a circuit mechanism. [00:12:40.16] [00:12:41.23] To modulator these particular signals if you want to [00:12:46.04] [00:12:46.04] be able to modulator how much learning is occurring in those 10 droids. [00:12:49.07] [00:12:50.23] So that just so [00:12:51.17] [00:12:51.17] happens that there's a potentially perfect circuit mechanism in the serve all in [00:12:56.17] [00:12:56.17] which we can module eat these signals through inhibition on to the dendrites So [00:13:02.08] [00:13:02.08] once I didn't mention is this molecular layer into Iran that exists in the servo [00:13:08.05] [00:13:08.05] So those molecular layer intern or aunts are inhibitory gabardine cells and [00:13:13.06] [00:13:13.06] they make numerous synapses onto the dendritic tree of these super Congi souls. [00:13:17.20] [00:13:20.22] Otherwise known as. [00:13:22.21] [00:13:24.03] There are a number of them that make baskets and apses and [00:13:28.20] [00:13:28.20] a number of them that makes an abscess again along the entire dendritic Arbor and [00:13:33.08] [00:13:33.08] so there's these kind of circuit analog state cortex etc Boma you'll see [00:13:38.15] [00:13:38.15] that inhibition occurs along the somatic axis of the dendritic axis as well so [00:13:44.03] [00:13:44.03] these kind of things exist in Serbo also and [00:13:47.13] [00:13:47.13] we were really fortunate to form this collaboration at the Max Planck with the. [00:13:52.14] [00:13:53.18] Lab who were there looking for drivers of intern or on speed cortex and they had one [00:13:58.20] [00:13:58.20] mouse called The Secret cream house that base it wasn't any good for them but [00:14:04.03] [00:14:04.03] they were looking very very quickly at Surbiton said it looked like there's some [00:14:07.13] [00:14:07.13] something interesting happening there and so we took a look at what. [00:14:11.04] [00:14:12.18] What cell types were actually able to be [00:14:15.22] [00:14:15.22] you know what gene expression we could drive with the smallest in the survey and [00:14:19.17] [00:14:19.17] it turns out it was a completely pure population of intern or [00:14:23.02] [00:14:23.02] aunts which is really fortunate because we want to be able to do all this but [00:14:26.09] [00:14:26.09] also drive the activity of Internet Ron's using up to 6 or chemo genetics [00:14:30.23] [00:14:32.09] and so not only does the conflict whole image look good but [00:14:36.15] [00:14:36.15] you also went in and did all the electrophysiology [00:14:41.23] [00:14:41.23] in this mouse line in molecular layer insurance when you turn the light on. [00:14:46.20] [00:14:48.18] After expressing virally her doubts and [00:14:52.12] [00:14:52.12] in this create a line you see that you get activation and you get you get firing but [00:14:57.23] [00:14:57.23] in every other cell type in the serve all if you were kindred souls gradual souls. [00:15:02.16] [00:15:04.16] That have those parlor fibers attached to them those will never fire so [00:15:09.19] [00:15:09.19] it's a very nice pure. [00:15:11.06] [00:15:13.02] Model that we can use to drive interferon firing [00:15:18.04] [00:15:18.04] during this whole process to kind of model the system so [00:15:23.13] [00:15:24.16] what is the effect of inhibition on these climbing Farber signals and [00:15:29.07] [00:15:29.07] we can ask that by looking again at our dual recording so [00:15:34.10] [00:15:34.10] we have a recording at the Soma in the park if you sell and [00:15:37.18] [00:15:37.18] we'll have also recording going whole so recording going at the. [00:15:40.23] [00:15:42.21] And then we can of again stimulate the climbing fiber to elicit that [00:15:47.15] [00:15:47.15] error signal that we think is occurring during air motor. [00:15:51.20] [00:15:52.22] And again when you click when you're still at that climbing fiber signal [00:15:56.13] [00:15:56.13] you get the complex spike that occurs at the Soma and then. [00:15:59.13] [00:16:01.03] Now the only thing we're going to do on top of this is to coincident pairing [00:16:06.07] [00:16:06.07] of that in turn or on spiking during this whole experiment to see what happens [00:16:10.15] [00:16:12.05] what was interesting to us is that if you did coincident pairing. [00:16:15.23] [00:16:17.16] Of these intramural and look at that somatic signal that it's actually [00:16:21.15] [00:16:21.15] not large differences if you're really crank up the firing an intern or [00:16:25.15] [00:16:25.15] runs you might be able to knock out one of the spike one of the sodium spikelets But [00:16:29.16] [00:16:29.16] often you'll see no difference like from control to light on so [00:16:33.19] [00:16:33.19] this would be with interference firing. [00:16:35.18] [00:16:37.19] Now when we look at the same exact experiment in the same cell but [00:16:43.04] [00:16:43.04] now we're just looking at the dendrite recordings what we see is that [00:16:47.01] [00:16:47.01] those those multiple calcium spikes in the done right are. [00:16:50.22] [00:16:51.23] Largely reduced you can go from 3 calcium spikes down to one calcium Spike [00:16:57.03] [00:16:57.03] just with having coincident. [00:16:58.22] [00:17:01.11] Intern or an input into the den traits. [00:17:03.14] [00:17:05.07] So this is kind of the potential way in which the cerebellum [00:17:10.04] [00:17:10.04] might be able to regulate against average learning essentially. [00:17:14.08] [00:17:15.10] Or excessive plus the city in other words we can also look at this experiment. [00:17:20.13] [00:17:21.19] Completely optically or [00:17:23.01] [00:17:23.01] nearly completely optically by just switching some of the parameters around. [00:17:27.15] [00:17:28.16] So we instead of using electrical recordings now we could look at it using [00:17:33.02] [00:17:33.02] calcium imaging in the spines and we just switched and this is the nice thing about [00:17:38.14] [00:17:38.14] having a good create drive line mounts because we can now use a red activating [00:17:44.12] [00:17:44.12] China Dobson and the reason we use a red this little trick of the trade. [00:17:49.17] [00:17:51.13] But the reason we like to use the red channel tops in here is because if you're [00:17:54.14] [00:17:54.14] doing 2 photon microscopy your p.m.t. is are super sensitive so [00:17:58.23] [00:17:58.23] you would have to shutter out that red top to generic light normally or [00:18:02.14] [00:18:02.14] that up the genetic blue but in this case since we're using this red light we [00:18:06.19] [00:18:06.19] didn't have to shutter at all that. [00:18:08.03] [00:18:09.06] The us we're not losing any of the calcium signal [00:18:12.09] [00:18:12.09] that that we really want to get out of this experiment. [00:18:14.17] [00:18:16.06] And so you can see kind of an analogous experiment to what we just did a lecture [00:18:19.17] [00:18:19.17] clean now we're just looking at it in terms of the calcium imaging [00:18:23.20] [00:18:23.20] at the spines to prove essential the Ok Are we really affecting calcium and [00:18:28.01] [00:18:28.01] treat during this process and so this is just the control traces again so [00:18:32.19] [00:18:32.19] if you see the complex spike that happens at the Soma. [00:18:35.06] [00:18:36.08] And there's that dendritic calcium spike that happens [00:18:39.23] [00:18:39.23] out in those distal Ginger expounds And so [00:18:43.18] [00:18:43.18] this is just after a single climbing fiber input into the into the Den Dr. [00:18:49.01] [00:18:50.13] If we do the same experiment and now we're active in our intern or [00:18:53.23] [00:18:53.23] runs up to genetically in a coincident manner. [00:18:57.20] [00:18:59.12] And we see again this is just another example that with and [00:19:03.10] [00:19:03.10] without inhibition those those somatic calcium signals are not changing. [00:19:08.10] [00:19:09.16] However those dendritic calcium sort of the somatic electrical signal is not [00:19:13.23] [00:19:13.23] changing however that dendritic calcium signal that we think is so important for [00:19:19.01] [00:19:19.01] the expression of plus this city is largely reduced and [00:19:24.03] [00:19:24.03] so what of course what we know about neurons and intern or [00:19:28.17] [00:19:28.17] specifically is that they fire at different rates depending on their input. [00:19:33.18] [00:19:34.23] How strongly their inputs are so [00:19:37.06] [00:19:37.06] we ask the question then in if we change the firing rate of the of those Gabbert [00:19:42.14] [00:19:42.14] you can turn around storing this process can we thus modulator the calcium entry. [00:19:47.14] [00:19:49.14] In basically a stepwise manner. [00:19:51.12] [00:19:52.14] And that's one of the beauties of opt in genetics is that you can actually do that [00:19:56.18] [00:19:56.18] so we did a number of control experiments to show. [00:19:59.06] [00:20:01.02] That we can get reliable firing at different rates with different light power [00:20:05.17] [00:20:05.17] essentially So we were able to make the Internet on so [00:20:09.10] [00:20:09.10] far what we call a liter of moderate rates are high rates like 36300 hertz for [00:20:14.06] [00:20:14.06] example and what you see that is is that if you change the rate at which [00:20:19.20] [00:20:19.20] Internet runs are firing coincident with those climbing fiber vents. [00:20:25.04] [00:20:26.19] For example this is the control trace and then this would be with 30 [00:20:30.07] [00:20:30.07] Hertz in addition and this would be with under Hertz inhibition. [00:20:33.17] [00:20:34.18] Then you actually have a way to essentially titrate the calcium entry [00:20:39.19] [00:20:39.19] during the same electrical input through the use of circuit inhibition and [00:20:45.13] [00:20:45.13] if what's what that immediately starts. [00:20:48.19] [00:20:49.19] When you think about it is if you look at the Serb Eleanore cortex it [00:20:54.07] [00:20:54.07] doesn't really matter it's all about magnitudes of calcium in term [00:20:57.10] [00:20:57.10] in terms of what type of plus this you get or what magnitude of plasticity you get so [00:21:02.09] [00:21:02.09] we're able to modulator the magnitude of calcium and [00:21:06.08] [00:21:06.08] in addition to that although I'm not talking about it in this context. [00:21:09.15] [00:21:10.16] People often think about the magnitude of calcium a tree happening [00:21:13.13] [00:21:13.13] perhaps through an empty air receptor as a trigger for excited toxicity so [00:21:18.08] [00:21:18.08] this is another way to think about why this might be important but [00:21:22.02] [00:21:22.02] this is just a kind of a some schematic from Cosmas at all showing that in in. [00:21:28.02] [00:21:29.18] When you have very high calcium entry or [00:21:31.23] [00:21:31.23] low just slight calcium entry then you tend to get l t p. [00:21:36.02] [00:21:37.09] But if you get very strong that super linear calcium entry I showed you before [00:21:42.07] [00:21:42.07] you get l t d n as a result and so we just basically took this entire environment and [00:21:48.19] [00:21:48.19] switched it to a plus this year it's less this the experiment said Ok depending on [00:21:53.08] [00:21:53.08] the strength of inhibition are we are we going to be able to model it long term [00:21:58.04] [00:21:58.04] plus this in that way and so this is a classic experiment again [00:22:03.11] [00:22:03.11] where now we're just looking at the plasticity instead of calcium. [00:22:06.21] [00:22:07.22] So this is classic cerebellar Ltd remember if you pairing Powell fiber inputs [00:22:13.00] [00:22:13.00] with a single climbing fiber input then that results in l t v in the cerebellum. [00:22:17.15] [00:22:19.11] And this is just sort of the time plot showing that this is [00:22:22.09] [00:22:22.09] during the conjunctive stimulation of parallel far climbing fiber [00:22:26.12] [00:22:26.12] you get this long term effect of the of a depression [00:22:30.20] [00:22:30.20] between that parallel fiber to pretend the cell synapse. [00:22:34.11] [00:22:34.11] Now the only thing we're going to do is add inhibition during that [00:22:39.07] [00:22:39.07] climbing fiber Spike just like I showed you with all those calcium experiments. [00:22:44.04] [00:22:46.12] What I'm showing you 1st is this this inhibition happening at what [00:22:51.11] [00:22:51.11] we're considering moderate firings of 60 hertz firing just during that climbing [00:22:55.23] [00:22:55.23] fiber pairing so we have the same sex experiment the only thing that's different [00:22:59.21] [00:22:59.21] is this inhibition that's occurring coincident with the climbing fiber. [00:23:03.17] [00:23:04.22] Now instead of l.t.d. during this experiment we actually saw no [00:23:09.18] [00:23:09.18] Plus this city on average in the long term this is the lot so this is the time [00:23:14.18] [00:23:14.18] you see that before and after you're having a centrally no difference. [00:23:19.04] [00:23:20.08] So that harkens back to the initial problem we were thinking about which is [00:23:24.15] [00:23:24.15] how is it that if you're getting calcium spikes in dendrites all the time [00:23:28.14] [00:23:28.14] which is true throughout the brain and how is it possible that we can [00:23:33.04] [00:23:33.04] not always undergo plasticity and overwhelm that cellular machinery that's [00:23:37.09] [00:23:37.09] involved with undergoing different forms of long term plus this city and [00:23:41.11] [00:23:41.11] this this is sort of demonstration that with modern inhibition [00:23:46.03] [00:23:46.03] which is happening all the time in circuits feedforward inhibition except for [00:23:49.19] [00:23:49.19] a that you can basically a limb in it that process from happening it's also kind of [00:23:54.15] [00:23:54.15] an important thing to always think about it during many l t [00:23:59.07] [00:23:59.07] l t p protocols people tend to block inhibitions so if you leave inhibition [00:24:04.01] [00:24:04.01] intact in the circuit that's going to result in the something different. [00:24:07.01] [00:24:08.19] Now a couple slides back I told you that actually moderate calcium entry. [00:24:15.05] [00:24:16.22] Actually results in l t p So the next thing we tried was extra [00:24:22.00] [00:24:22.00] very strong inhibition which should essential to block [00:24:27.04] [00:24:27.04] as much calcium entry is we possibly could during that climbing fiber event and [00:24:32.04] [00:24:32.04] now it's interesting you see that you went from no plasticity to actually change [00:24:36.11] [00:24:36.11] the sign of plasticity to l.t.p. and that shown in this graph here [00:24:42.06] [00:24:42.06] actually the grey circles are if you only use parallel fibers so if you [00:24:47.15] [00:24:47.15] just have parallel fiber high frequency input that actually results in l.t.p.. [00:24:52.16] [00:24:53.22] And if you basically use strong inhibition here during the climbing fiber and [00:24:58.13] [00:24:58.13] put what we've basically done is say to the cell ignore that climbing fiber and [00:25:03.19] [00:25:03.19] put because it's the result is exactly the same so [00:25:08.22] [00:25:08.22] in total now what we've what we've demonstrated is that you can have a kind [00:25:14.18] [00:25:14.18] of low high low medium or high calcium entry during the same signal based on [00:25:19.01] [00:25:19.01] the circuit inhibition and the consequence of that is that you can basically [00:25:23.17] [00:25:23.17] titrate that the sign of plasticity in the amount of plasticity you get. [00:25:27.17] [00:25:30.17] So. [00:25:31.11] [00:25:33.23] Basically just include the slide here to say if you're really interested in this [00:25:37.21] [00:25:37.21] you want to see the in vivo experiments we did about it we took all we took this [00:25:42.12] [00:25:42.12] whole slice environment and we brought it to the in vivo level using fibers and [00:25:48.03] [00:25:48.03] up to genetics and a specific behavior called the stability [00:25:52.07] [00:25:52.07] ocular reflex but basically in the interest of time and [00:25:57.00] [00:25:57.00] everyone's attention I think that was enough cerebellum for one thought. [00:25:59.17] [00:26:01.23] But the take home message Cheers essentially that [00:26:04.17] [00:26:04.17] you can do the same thing in the living animal. [00:26:07.05] [00:26:08.09] And you can model late the type of learning that that animal and that. [00:26:12.23] [00:26:14.07] Will express either kind of in one direction of the Elegy other [00:26:19.20] [00:26:19.20] based on the activity of these Intramuros in the circuit. [00:26:22.18] [00:26:26.20] That's just a video of the or. [00:26:28.06] [00:26:30.03] So it happens completely in the dark in this case and we were using infrared light [00:26:34.20] [00:26:34.20] to look at this and so it's a completely beautiful Serb Eller [00:26:38.22] [00:26:38.22] specific behavior that the mouse basically has no choice but to undergo because. [00:26:43.10] [00:26:45.13] It's basically just completely motor. [00:26:48.03] [00:26:50.02] So the 1st take home here is that. [00:26:52.23] [00:26:54.06] Inhibition in the circuit depending on how much you have is going to allow for [00:26:58.04] [00:26:58.04] great expression plus the city in learning and we think that this might occur [00:27:02.17] [00:27:02.17] in different circuits in different contexts as well. [00:27:05.11] [00:27:06.15] One good example beyond that may be that. [00:27:09.12] [00:27:10.18] In for example place cells and if a campus you see that they're undergoing some sort [00:27:15.09] [00:27:15.09] of learning you'll see a plateau potential that happens in that that [00:27:20.07] [00:27:20.07] our hypothesis would be that circuit inhibition or in that event [00:27:25.12] [00:27:25.12] would change the expression of essentially place fields. [00:27:28.23] [00:27:30.08] So it's just kind of a different context but [00:27:32.01] [00:27:32.01] the mech the Soli the mechanisms sort of lining up. [00:27:34.08] [00:27:35.19] So for the 2nd part of the talk I want to. [00:27:38.17] [00:27:40.06] Introduce a some a new a new topic we're looking at in the lab and we're kind [00:27:45.08] [00:27:45.08] of looking at very very similar cell type we're looking at a fest by intern or on. [00:27:49.14] [00:27:51.08] In this case we're moving a cortex and we're we're looking at the physiology of [00:27:56.00] [00:27:56.00] those neurons in the context of oldtimers disease. [00:27:58.18] [00:28:00.15] And let me give you a little bit of background about why we might [00:28:02.18] [00:28:02.18] be interested in doing that. [00:28:03.19] [00:28:05.05] So the prevailing theory. [00:28:07.01] [00:28:08.14] Now switching gears to completely different topic. [00:28:11.17] [00:28:13.02] Very rapidly some a little bit of background [00:28:15.14] [00:28:15.14] you know sort of the prevailing theory underlying etiology of all Simers is that [00:28:20.16] [00:28:20.16] over time these toxic accumulations of protein these. [00:28:24.18] [00:28:27.10] Plaques and then Tao aggregations following the building [00:28:33.22] [00:28:33.22] sort of build up over time and they result in neuronal death and synapse death and [00:28:39.07] [00:28:39.07] eventually of course so it connected cognitive decline that happens. [00:28:43.08] [00:28:44.23] However I think recently as the field it starts to shift and the more and [00:28:49.07] [00:28:49.07] more evidence coming out. [00:28:50.15] [00:28:52.09] Is suggesting that those protein aggregates are not necessarily [00:28:55.15] [00:28:55.15] the causal determinants especially of the see an issue. [00:28:59.11] [00:29:00.15] Of the disease but rather sort of an end effect almost And this is most. [00:29:07.10] [00:29:08.23] Perhaps strongly demonstrated through the failure of some of these [00:29:14.08] [00:29:14.08] recent drug trials that work quite well to reduce soluble amyloid but [00:29:20.06] [00:29:20.06] they they don't really stop cognitive decline except enough some of the some [00:29:23.13] [00:29:23.13] evidence that that's maybe maybe somewhat of it coming out recently. [00:29:26.23] [00:29:28.15] So where we our interest kind of line up to this is that [00:29:31.12] [00:29:31.12] we really want to understand Ok. [00:29:33.07] [00:29:35.09] What's happening really early on in the disease process so what's happening in [00:29:39.13] [00:29:39.13] the so-called priest symptomatic preplan stage of the disease and [00:29:43.07] [00:29:43.07] there's actually quite a bit of literature out there now about what's happening [00:29:47.14] [00:29:47.14] in circuits HIPPA campus and cortical circuits in the in models of a d.n.a. and [00:29:52.04] [00:29:52.04] all it's also humans with mild cognitive problems leading Toles Harmer's And [00:29:58.12] [00:29:58.12] so one of the hallmarks features appears to be that there's a imbalance [00:30:04.05] [00:30:04.05] of excitation inhibition that starts to occur in the circuit and such that you [00:30:08.23] [00:30:08.23] get this over excitation happening in the circuit and so I said not just [00:30:13.18] [00:30:13.18] a hunch there's there's a lot lots more than than here there's tons of literature. [00:30:18.08] [00:30:19.14] And so interesting Lee. [00:30:21.04] [00:30:22.05] It appears that in terms since we're really interested in different neuron [00:30:25.19] [00:30:25.19] types and how they work and how they're conduct one of their conductance is and [00:30:28.18] [00:30:28.18] things like that. [00:30:29.11] [00:30:30.23] There's a lot of literature that's really striking to us showing that in different [00:30:35.18] [00:30:35.18] models of a d. there's a one particular type of Intern her. [00:30:39.06] [00:30:40.09] Inhibitory intern or on again that appears to have a physiological deficit early on [00:30:45.06] [00:30:45.06] and kind of even can spare the other types of Intern runs like [00:30:50.09] [00:30:50.09] some out of that interest for example and so [00:30:53.07] [00:30:53.07] that intern Ron is this this fast spiking or p.v. [00:30:58.10] [00:30:58.10] if you guys are more familiar this p.v. intermural depicted in blue here and so [00:31:04.14] [00:31:04.14] internet runs in cortex are often sort of characterized on their genetics but [00:31:09.14] [00:31:09.14] also their actual targets these gusts tend to target the so [00:31:14.13] [00:31:14.13] now to proximal dendrite and so not a compartment of the principal neurons in [00:31:18.16] [00:31:18.16] the circuit and this is this is now a kind of classic work from [00:31:23.05] [00:31:24.05] power up group showing that in the model of a Deeds a mouse model of a d. [00:31:29.19] [00:31:30.21] That you can get differences in action potential firing in these cortical [00:31:36.13] [00:31:36.13] fs biking interference and [00:31:38.18] [00:31:38.18] all the other groups have now shown in different brain regions. [00:31:41.18] [00:31:42.18] Very very similar phenotypes although there's some disagreement [00:31:46.09] [00:31:46.09] about exactly what happens there seems to be a an agreement that the susceptibility [00:31:50.23] [00:31:50.23] to physiological deficits are really strong in these fast biking interactions. [00:31:55.16] [00:31:56.23] So of course that car to fits into our wheels perfectly [00:32:00.04] [00:32:00.04] because we're really interested in how one of the cellular and [00:32:03.07] [00:32:03.07] subsoil or mechanisms that fit into or that. [00:32:06.20] [00:32:08.10] Are responsible for [00:32:09.16] [00:32:09.16] action potential firing this fast action potential firing in the cell types and so. [00:32:15.01] [00:32:16.19] No doubt the most important thing that's determining the most [00:32:22.02] [00:32:22.02] important factor that's determining this fast spiking phenotype and [00:32:25.09] [00:32:25.09] the cell type so there conductance is there endowed with these really specialize [00:32:29.06] [00:32:29.06] fast on channels like n.a.v. one and k.v. 3 for [00:32:33.19] [00:32:33.19] example we kind of historical interesting k.v. 3 for a lot of reasons so. [00:32:39.04] [00:32:40.05] We were are now a sort of looking into these channels along with the n.a.v. [00:32:45.10] [00:32:45.10] channels as well that and [00:32:49.05] [00:32:49.05] sort of seeing how might this fit into the context of a d. [00:32:53.06] [00:32:53.06] in both sort of a therapeutic men manner and also some of the things [00:32:57.22] [00:32:57.22] some of the mechanisms that deficits that might be occurring in the cell types also. [00:33:01.20] [00:33:02.21] So this is really these these conductance is that Dr spiking in these neurons or [00:33:08.19] [00:33:08.19] are well well at least the general families are well known. [00:33:12.01] [00:33:13.09] For a long time so t.v. 3 channels. [00:33:15.21] [00:33:17.14] Are these sort of fast delayed rectifier channels that [00:33:21.22] [00:33:21.22] are known to play a strong role in the spiking activity of these cells you can [00:33:27.05] [00:33:27.05] see this is from 1909 basically the experiment just dumps. [00:33:32.06] [00:33:33.13] Into the bath up with this slice recording a low concentration of. [00:33:37.10] [00:33:38.14] Which is quite selective for k.v. 3 Not completely but it's pretty good. [00:33:41.18] [00:33:42.21] And so that you know these kind of things have been known for [00:33:44.20] [00:33:44.20] a while like there are certain types of conductance is better over expressed or [00:33:48.14] [00:33:48.14] special expressed in these cell types that allow for that phenotype and so [00:33:52.21] [00:33:52.21] like what's important in the in the context should mention again like why is [00:33:56.08] [00:33:56.08] this important the context of a d is that if you're losing firing in these neurons [00:34:01.14] [00:34:01.14] or other diseases as well if you lose firing frequency if you lose applet to [00:34:05.13] [00:34:05.13] have action potentials then essentially that will disturb the inhibition in [00:34:09.15] [00:34:09.15] the circular world has the potential to lessen the inhibition that [00:34:14.08] [00:34:14.08] those those posts and up that primal neurons are receiving and so [00:34:17.16] [00:34:17.16] that could lead to an over excitable circuit in general which is what is seen. [00:34:22.18] [00:34:24.01] So this is just the results from our lab showing yet [00:34:27.11] [00:34:27.11] 20 years later you can get the same effect which is always good. [00:34:29.21] [00:34:31.16] And so this is kind of dumping a low concentration of k.b. [00:34:35.14] [00:34:35.14] 3 blocker into the back you get a broadening of action potential with [00:34:38.21] [00:34:38.21] you get slowing of spiking so we Ok we know [00:34:43.16] [00:34:43.16] some certain conductance is the responsible for the firing these cells. [00:34:46.21] [00:34:48.14] But also there are other factors that are that sort of fit into this picture that [00:34:54.15] [00:34:54.15] you can't really garner from these kind of global pharmacological experiments and [00:34:59.11] [00:34:59.11] these are things that we've been working on for [00:35:00.23] [00:35:00.23] the Fed past few years is that conductance is. [00:35:04.13] [00:35:05.13] Really important conductance is hard to study in these cells and [00:35:09.03] [00:35:09.03] all neurons because they're localized in these subsidies or [00:35:13.02] [00:35:13.02] compartments of neurons right. [00:35:14.14] [00:35:16.02] So not only is our particular channel types like a v 3 important but also [00:35:21.09] [00:35:21.09] there are localization within the x. on this important or kind of jumped the gun. [00:35:25.23] [00:35:27.01] So the axon initial segment in this case right here is where action [00:35:31.20] [00:35:31.20] potentials are actually starting there that's where they're initiating and [00:35:35.13] [00:35:35.13] this is true for basically all neuron types but not until recently did we [00:35:39.22] [00:35:39.22] kind of confirm that this was also true in these in these fast biking intern or [00:35:44.02] [00:35:44.02] ons and the way that we were able to determine that it's true is through [00:35:49.02] [00:35:49.02] the use of just a regular sort of quiet experiment and [00:35:53.12] [00:35:53.12] simultaneous voltage imaging down into the axon so that allows us to [00:35:58.09] [00:35:58.09] see the signal happening in nearly simultaneously in both locations and [00:36:03.13] [00:36:03.13] what you see is that the actual initial segment the signal in red happens before [00:36:07.06] [00:36:07.06] the somatic signal and if you look at distance and this is this bar is [00:36:12.01] [00:36:12.01] actually standing which is its base this side of skeletal protein showing you where [00:36:16.20] [00:36:16.20] the aggregates of many channels and other proteins happen within the axon. [00:36:20.15] [00:36:22.02] You can see that the somatic is sort of a.p. latency is lowest at [00:36:27.02] [00:36:27.02] around 10 maybe 15 microns 12 microns away from the soma So [00:36:32.16] [00:36:32.16] basically we're hypothesizing that the channels most important the for [00:36:37.17] [00:36:37.17] action potential initiation and maybe even high frequency firing [00:36:42.18] [00:36:42.18] are also are situated at this area and we can actually. [00:36:46.23] [00:36:48.01] Test this which is really fun. [00:36:49.23] [00:36:51.12] Because we're able to focally block ion channels in different regions of neurons [00:36:56.11] [00:36:56.11] so we can use this caged compound. [00:37:00.09] [00:37:00.09] That can block t.v. 3 channels cold Ruthin e m 4 a piece or [00:37:05.07] [00:37:05.07] a thin Ian is actually the cage and the nice thing about this Ruthin Ian Cage is [00:37:09.06] [00:37:09.06] that 2 photon light which is has a very small focal volume. [00:37:13.11] [00:37:14.13] Can actually uncage this this k.b. channel Walker and so [00:37:18.00] [00:37:18.00] if we just then say let's let's situate our own caging. [00:37:22.06] [00:37:23.09] Around this 10 micron stretch of the x. [00:37:25.20] [00:37:25.20] on Will we actually be able to or will we actually affect firing of that x.. [00:37:30.17] [00:37:32.10] And the answer is pretty amazingly Yes if you block just [00:37:37.01] [00:37:37.01] the channels that are situated along that exponential segment region and you see [00:37:41.19] [00:37:41.19] this reduction and action potential firing and these fast spiking your intern or ons. [00:37:46.17] [00:37:48.00] So it's also be very important to look at [00:37:50.23] [00:37:50.23] sort of the conductance is through out the some out of dendritic [00:37:54.05] [00:37:54.05] compartment as well another of the groups I start to do this as well. [00:37:57.06] [00:37:59.08] One thing we're really lacking on. [00:38:01.03] [00:38:03.01] Beyond just knowing what families of channels are in these neurons are actually [00:38:06.11] [00:38:06.11] the true molecular identity of these of these guys and the reason is. [00:38:11.05] [00:38:13.10] You should just it's just really low throughput. [00:38:15.14] [00:38:17.08] Experiments and so it requires that you kind of go through knockouts or [00:38:23.19] [00:38:23.19] some some of the method which you can get molecular identity. [00:38:27.06] [00:38:29.04] And then find it in a localization dependent manner as well but [00:38:33.15] [00:38:33.15] we did we've done some these experiments to by combining knockout with very. [00:38:39.08] [00:38:41.02] Very precise sub Siler recordings of these ion channels. [00:38:45.00] [00:38:47.06] So you can see this is our Axon pipette. [00:38:50.07] [00:38:50.07] The opening open tip diameters about 2 to 300 nanometers so we can actually go and [00:38:55.09] [00:38:55.09] use fluorescents guided to under the 2 photon and [00:38:59.03] [00:38:59.03] then take recordings from these Internet Exxon's at the for [00:39:03.11] [00:39:03.11] instance prison optical or the x. on initial segment and so the take home [00:39:08.11] [00:39:08.11] here is that we were able to identify not only the families of channels but [00:39:13.09] [00:39:13.09] actually some of the sub units that predominate in the accent so [00:39:18.11] [00:39:18.11] knowing the molecular identity of these things are really important if we want to [00:39:22.14] [00:39:22.14] use gene therapeutic methods in the future for example so [00:39:27.05] [00:39:27.05] we see that this particular those 4 subunits of key 3 [00:39:31.23] [00:39:31.23] we went through a few of these things but it looks like a 3.4 [00:39:36.04] [00:39:36.04] This 11 of 4 it's dominating in these fast biking intern or on accidents. [00:39:40.22] [00:39:42.08] And it just so happens that the through biophysical modeling it showing that [00:39:47.02] [00:39:47.02] that particular child seems to be really good at fast spiking as well so [00:39:50.22] [00:39:50.22] it wasn't a big surprise. [00:39:52.07] [00:39:53.16] It looks like it might actually have a mirage as well but once you lose k.b. [00:39:57.13] [00:39:57.13] $3.00 that seems to for whatever reason we don't actually know why knock [00:40:02.22] [00:40:02.22] out all those k.b. channel conductance is preached in Africa Lee or in the axon. [00:40:06.23] [00:40:08.02] So we asked the question Ok we know the molecular identity of the k.v. [00:40:12.14] [00:40:12.14] channel t.v. 3 channel that we think should be involved with high frequency [00:40:16.23] [00:40:16.23] firing the naturalistic firing of the cell types but [00:40:21.08] [00:40:21.08] we actually haven't done that experiment molecularly So what we did next is [00:40:26.09] [00:40:26.09] design an ab crisper So this is got an s. a cast 9 it's like [00:40:31.09] [00:40:31.09] a next generation cast line that you can fit into in a connector with the s.g.r. [00:40:35.14] [00:40:35.14] and against the k.v. 3.4 and then we just injected that into layer 5 cortex and [00:40:41.05] [00:40:41.05] wait a couple weeks and then perform recordings from these Internet. [00:40:45.08] [00:40:46.17] Because their t.v. tomato positive we can actually identify them for [00:40:50.13] [00:40:50.13] recordings that way and the initial data this really exciting I think [00:40:55.17] [00:40:55.17] because it looks like just from the loss of this particular subunit [00:41:01.13] [00:41:01.13] you're getting this dramatic difference in firing frequency in these neurons. [00:41:05.20] [00:41:07.03] A lot of times you have different subject that's for [00:41:09.18] [00:41:09.18] a particular protein that are very similar and one can kind of substitute in for [00:41:13.13] [00:41:13.13] another but it looks like in this case this particular molecular subunit [00:41:18.13] [00:41:18.13] is really important for that phenotype. [00:41:21.00] [00:41:22.19] So going all the way back to a d. and c. and [00:41:26.13] [00:41:26.13] her generation we thought that it would be a good proof of principle to show that if [00:41:31.14] [00:41:31.14] we perturb interactivity through knocking out this gene would that have [00:41:36.19] [00:41:36.19] an effect on a centrally synapse fidelity of the excited turnarounds in the circuit. [00:41:41.13] [00:41:43.08] So the question we asked is essentially if we lose this sub unit in turnarounds [00:41:48.23] [00:41:48.23] does that does that have any effect on cent apses which is essentially I think [00:41:54.07] [00:41:54.07] the most agreed upon early indication of a problem in the circuit in a day and [00:41:59.17] [00:41:59.17] other diseases a sin apps loss so the way that we did that experiment is just to. [00:42:06.00] [00:42:07.10] Especially combine our control experiment or [00:42:11.21] [00:42:11.21] crisper experiment against k.v. 3.4 with a. [00:42:16.18] [00:42:18.06] Marker for the person at that primal Durant's. [00:42:21.02] [00:42:22.06] This was a promoter attempt to that's specific for those cells and [00:42:28.04] [00:42:28.04] then it just expresses why a piece so we can visualize the spot the sun the spines [00:42:32.21] [00:42:32.21] on those dendrites after the experiment and what we found is that. [00:42:37.22] [00:42:39.05] Compared to control injections when we use our k p 33.4 crisper viral crisper method. [00:42:46.21] [00:42:48.01] Just after 2 weeks you get a reduction in post and. [00:42:52.17] [00:42:53.21] Spines and. [00:42:55.22] [00:42:57.07] It's a bit stronger in layer 5 as compared to layer one and [00:43:01.12] [00:43:01.12] also you get some difference in spine length in layer fog but not Layer one [00:43:07.09] [00:43:07.09] the differences in spine length are we don't know exactly why that's happening [00:43:11.17] [00:43:11.17] but all the other groups have shown that synaptic activity changes like through [00:43:16.16] [00:43:16.16] an m.b.a. receptors for example can start to change the shape of the spines. [00:43:20.12] [00:43:23.00] And the reasoning the possible reason why you're getting differences and [00:43:27.15] [00:43:27.15] layers is that we're injecting in layer 5 the primal knew that the pv intern runs [00:43:32.16] [00:43:32.16] in that layer or are contacting the some out of dendritic region so that [00:43:37.05] [00:43:37.05] you might expect a more proximal fact but it's interesting that you're still getting [00:43:41.21] [00:43:41.21] a very distal fact in those distilled underwrites up in Layer one that could be [00:43:46.06] [00:43:46.06] through regulation of spiking of the cell in general or maybe other reasons. [00:43:50.10] [00:43:52.08] So moving forward I guess our hypothesis will be or [00:43:55.13] [00:43:55.13] one of our questions will be of course let's look at this. [00:43:59.01] [00:44:00.01] Let's look at that conductance naturally in models of a diesel that's what we're [00:44:04.03] [00:44:04.03] doing actively now it's been shown that over expression of [00:44:09.14] [00:44:09.14] different sodium channel types can improve some of the. [00:44:13.20] [00:44:14.22] Some of the function in the models except [00:44:17.17] [00:44:17.17] working with sodium channels is very difficult because. [00:44:20.18] [00:44:22.00] Essentially you have to do a cellular therapy in order to get that to work [00:44:25.00] [00:44:25.00] because there are such huge molecules the advantage of using k.v. [00:44:28.18] [00:44:28.18] 3 in this context may be that you can of course over express these channels using [00:44:33.11] [00:44:33.11] A.V.'s as shown here so we're actually able to over express k v 3.4 It's all. [00:44:39.19] [00:44:41.21] In the in fast biking in turn arounds and you see this kind of really interesting [00:44:47.21] [00:44:47.21] effect I didn't really have time to go into today but it does tend to sort [00:44:52.07] [00:44:52.07] of aggregate to different parts of the axon which could have interesting. [00:44:56.19] [00:44:57.23] Sort of consequences 1st for inhibition. [00:45:00.23] [00:45:02.08] So general summary is that these particular sold the units [00:45:06.18] [00:45:06.18] in fast spiking intern or ons appear to be required for [00:45:10.04] [00:45:10.04] that the spiking phenotype in total of the cell and acute knockout of that. [00:45:15.13] [00:45:16.15] Sort of very specialized inductance leads to sit ups loss [00:45:21.23] [00:45:21.23] fairly rapidly in the adult cortical circuit so [00:45:26.11] [00:45:26.11] we kind of want to bring it attempt to look at this in the reverse order and [00:45:30.10] [00:45:30.10] that's what we're doing now is if we over express this channel can we halt [00:45:35.11] [00:45:35.11] some of the phenotypes we're seeing in the model of baby itself. [00:45:39.02] [00:45:41.14] Thanks for attention to take any questions. [00:45:43.12] [00:46:04.05] We will know soon I guess but actually. [00:46:07.19] [00:46:09.09] What we're doing what we're tending to do 1st is recreate the g 20 model but [00:46:16.03] [00:46:16.03] virally in the cute way so that would be the Indiana Swedish mutations but instead [00:46:21.22] [00:46:21.22] of having the mouse grow up with it we're going to over express that ha p.p. and see [00:46:26.10] [00:46:26.10] how that works but I think the alternative to that would be and the reason we [00:46:31.03] [00:46:31.03] started there is because I mean the palace stuff they did they started using that in [00:46:35.13] [00:46:35.13] in that model and they see the Internet or on deficits and that model. [00:46:38.21] [00:46:39.23] So we're just trying to not reinvent the wheel too much. [00:46:42.12] [00:46:43.23] But I think we're weeks weeks away from getting our 1st in information there. [00:46:50.10] [00:46:55.07] Very. [00:46:55.19] [00:46:57.04] Very. [00:46:57.16] [00:47:10.23] Well actually we kind of overdid it with the temporal person because we had [00:47:15.07] [00:47:15.07] we were able to do that but you're right actually normally it's not to be that [00:47:19.19] [00:47:19.19] beautiful in terms of its feed for actually what actually is happening [00:47:23.08] [00:47:23.08] in vivo is that the parallel fibers are activating like a layer in turnarounds [00:47:28.07] [00:47:28.07] which is leading to feed forward inhibition all the time so [00:47:33.03] [00:47:34.06] when we did do experiments in vivo which were kind of naturalistic and then we just [00:47:39.00] [00:47:39.00] turned on or we turn things off than terms of turning off the internet or ons and [00:47:43.11] [00:47:43.11] then you can still perturbed perturbed learning in that way. [00:47:46.18] [00:47:48.01] The reason we were kind of doing it the way we're doing is just to be. [00:47:51.06] [00:47:52.06] You know extreme about it essentially So [00:47:55.09] [00:47:55.09] the interest also goes then too I mean I was just the next layer of complexity but [00:47:59.11] [00:47:59.11] there's a plasticity between the parallel fiber and in turn arounds there and [00:48:03.22] [00:48:03.22] that may play a role in the whole in that whole global system as well. [00:48:07.22] [00:48:31.18] Yeah. [00:48:32.06] [00:48:34.05] So I think most of the studies [00:48:37.21] [00:48:37.21] that look at that tend to be blocking inhibition but. [00:48:40.09] [00:48:42.05] The Ultimately I think the where things occur for example in time has a lot [00:48:49.06] [00:48:49.06] may have a lot to do with electric sort of the electrical nature of the den right and [00:48:54.10] [00:48:54.10] there's some there's some groups that would say Ok there's also a chemical like [00:48:58.22] [00:48:58.22] and glue are but to my mind we've actually looked at some of these experiments where [00:49:03.08] [00:49:03.08] basically how do you get l.t.d. And what's the timing got to do everything for [00:49:07.11] [00:49:07.11] example well the parallel fibers are deep polarizing the dendrite and [00:49:12.18] [00:49:12.18] such that it's sort of it's almost priming the denge right before the climate [00:49:17.13] [00:49:17.13] comes into when they're climbing Farber hits you're getting that massive [00:49:22.18] [00:49:22.18] sort of massive triple triple calcium spike that happens. [00:49:27.05] [00:49:28.20] And we've shown I've actually shown a couple of ways [00:49:31.13] [00:49:31.13] that it could that could be one of the major mechanisms there that would be why [00:49:35.18] [00:49:35.18] you know if you get a climbing fiber 1st you don't have that pre previous [00:49:40.09] [00:49:40.09] deep polarization that's happening that's sort of priming that right and [00:49:45.01] [00:49:45.01] I guess the other side of the card is that some people think that 6 is required. [00:49:49.11] [00:49:52.09] Like the scent group a long time ago in a show that they block that and [00:49:58.07] [00:49:58.07] then they kick it l.t.d. but I think that that's that could be multiple or [00:50:03.18] [00:50:03.18] mechanisms there but I alternately the thing that's causing l.t.d. [00:50:09.06] [00:50:09.06] in cerebellum to happen is this is a is a larger magnitude of calcium [00:50:13.05] [00:50:13.05] which is interesting leave the opposite of cortex which is this. [00:50:16.07] [00:50:17.15] And it kind of makes sense in the way that this or below my cortex speak to each [00:50:21.04] [00:50:21.04] other but if you get this massive entry in cortex you could help t.p.. [00:50:26.10] [00:50:26.10] So ultimately regulation some some way whether through its internal stores or [00:50:32.05] [00:50:32.05] dendritic active properties. [00:50:33.19] [00:50:35.03] That magnitude of calcium seems to be the big That was determining things. [00:50:40.01] [00:50:50.19] Yeah we actually have an interest things only so they're getting. [00:50:56.15] [00:50:57.22] They need an increase in. [00:50:59.23] [00:51:01.13] Spontaneously p.s.e. is happening so what what the mechanisms that [00:51:06.22] [00:51:06.22] you're getting to that point we don't know yet but you're getting that happening. [00:51:10.05] [00:51:11.17] Yeah yeah yeah exactly and we don't know in terms of the crisper test 9 we're [00:51:17.03] [00:51:17.03] not sure what's happening with the spiking at all though we've done the opposite [00:51:21.12] [00:51:21.12] where we've had over expression of the key 3.4 and looked at the primal neurons and [00:51:26.09] [00:51:26.09] they actually spiking a bit less and whether that's like a cell in transit or [00:51:31.17] [00:51:31.17] static like we don't know where that's coming from yet but it looks like things [00:51:35.13] [00:51:35.13] are kind of you know you're over expert if you help regulate those those channel [00:51:39.17] [00:51:39.17] subunits then over all the circuits seems to want to get quieter I guess. [00:51:44.05] [00:51:47.11] Over the years. [00:51:48.05] [00:51:50.20] Where they were. [00:51:52.16] [00:51:54.09] Yeah. [00:51:54.21] [00:51:57.06] Yeah. [00:51:57.18] [00:51:59.06] Yeah. [00:51:59.18] [00:52:01.11] That's great. [00:52:01.23] [00:52:04.11] Now you took the cat out of the bag there because like we did a number of these [00:52:08.00] [00:52:08.00] experiments in and cerebellar into Iran and [00:52:11.10] [00:52:11.10] this is actually a Serb element in Iran and so. [00:52:13.22] [00:52:15.14] We have to actually look at some initial psych we have not looked at that [00:52:20.11] [00:52:20.11] experiment in the cortical that spiking your interference yet but the hypothesis [00:52:25.01] [00:52:25.01] is that they in those cortical 1st buying intern or ons those k.b. $3.00 [00:52:30.07] [00:52:30.07] channels are going to be chock full within the soma and the x. on the full segment. [00:52:35.10] [00:52:37.07] But that's we still have to do that we have done some outside out patches from [00:52:41.01] [00:52:41.01] the Internet on somas and there seems to be some loss of conductance is at the Soma [00:52:46.06] [00:52:46.06] which is kind of its kind interesting like even this is just another example of how [00:52:50.21] [00:52:50.21] within the brain regions neurons that seem to do the same thing and [00:52:53.14] [00:52:53.14] behave similarly they just still have different like a layer and [00:52:59.01] [00:52:59.01] spatial organizations so that they just have to find a dynamic range which they're [00:53:04.13] [00:53:04.13] happy in with with that circuits trying to do and stuff so it's kind of crazy. [00:53:07.20] [00:53:13.09] At. [00:53:13.21] [00:53:32.12] The best thing about this is that I have to grow I think it's all x. Bebo or [00:53:36.13] [00:53:36.13] things from slices some people might think that's bad you know they don't want to [00:53:40.21] [00:53:40.21] do that but I'm just happy not to have to change medium every day instead. [00:53:43.18] [00:53:45.10] It's all ex people. [00:53:46.09] [00:53:49.00] It's all my. [00:53:49.15] [00:53:57.20] Thank you. [00:53:58.08]