CNSP: Sorry, Mick, I just accidentally stopped your video instead of making you a panelist.
CNSP: Show yourself.
Mick Crosse: I can't start my video now, because you stopped it, apparently
CNSP: sorry about that
CNSP: fixing it. I'm fixing it. Too many people are joining.
Hmm.
CNSP: so does that have everyone.
CNSP: Steph, you co-host
CNSP: should be. Now.
CNSP: Okay, so this should be the final session of Cnsb, this should be pretty. I'll just be honest. I don't have anything prepared for this. I thought this would just be something like
CNSP: you. All can come in and bring us your questions, and we'll do our best to answer it, or if you have things that you thought might have might be interested and interesting to talk about. Maybe some of us have like something prepared. I don't know, but nothing is prepared on my end. So
CNSP: we tried that one time, but
CNSP: we I don't think we'd we'd try that again.
CNSP: This is my cat that looks like the cat in all this picture.
giorgia cantisani: His name's Cosmo, and he's really stupid.
CNSP: He's actually really smart, but he looks really dumb.
giorgia cantisani: He was there all the time
CNSP: he came in yesterday during the tutorial, I think because he could hear me talking the whole time. He wasn't in here today.
giorgia cantisani: No, he just came in today.
Giovanni Di Liberto: Darren. I mean, there are a couple of things that we can tip for the end. because maybe about the you know what's next.
Giovanni Di Liberto: Sure. But maybe let's see if someone has more specific questions before before we got into that.
CNSP: I don't know if this is gonna help. But there might be questions for Ola or malice. So I'm gonna make you all co host as well. just in case
CNSP: no, everyone understood everything perfectly. That's great.
Stephanie Haro: See? I wasn't in track. Oh, go ahead.
Marlies Gillis: Yeah. I was just not to ask a question or so. But I noticed that the cohere email, they asked to
Marlies Gillis: handing or or make like an overview of all available natural speech data sets. And I think, like making a good overview is a very, very nice and good start. So maybe because we have, we have added our or the details of our data set. It might be cool just to make sure that everyone who knows like data sets
Marlies Gillis: that the overview is is full. So then go to the go here, stop. And there's a Google form where you can.
Marlies Gillis: If all the details of your data set might also be good to keep track of
CNSP: how do you think we would be able to find that in just like your data set.
Marlies Gillis: yeah, i'll i'll,
Marlies Gillis: so i'll, i'll put the the link in the chat.
Marlies Gillis: And this is to
Marlies Gillis: yeah, to add your data sets, and I if you want to join the Co here, sessions, then you should Re, send a request to this email, for probably you're all in there already, but
Marlies Gillis: just for people who want to join. It's very like it will be turn this Thursday, I guess, and it's always super nice seminars. So just as a general remark or so.
CNSP: and I would double that. I like cog here. It's one of my favorite online conferences. Aside from Cnsvi, I guess
CNSP: Lucas Farah told us yesterday in the practice session, not to be afraid of silence, because silence makes people talk.
Giovanni Di Liberto: Does anyone want to bring up any
Giovanni Di Liberto: points? Any questions?
Stephanie Haro: I wasn't in track number one.
Stephanie Haro: What anyone from track number one want to say like something cool they learned
Stephanie Haro: in that track.
CNSP: Well, I'm not a python person. I'm slowly learning, and I learned that
CNSP: it's not as hard as I. You know you, you might think it is I was able to keep so it's nothing to do with the tutorial.
CNSP: But well, aside from maybe like how well it was organized in the code. Or maybe that's just Co lab, or something, but props to Marlene's for using Co lab, I guess.
CNSP: but I was able to follow along just just fine.
CNSP: Also learned that the ill brain.
CNSP: some pretty cool features, too, that are kind of embedded already.
CNSP: giving me some ideas.
CNSP: Nick.
CNSP: Oh, Mick, also I there's
CNSP: or other interior people. you know, the onset and offset artifacts that we sometimes get.
CNSP: It's it's not just us. It's it was also in Marley State. I
CNSP: er at least in the analysis that she showed some of some of the Trf. She showed had those same onset offset like spikes.
CNSP: And she gave an explanation that's pretty much in line with
CNSP: at least my thinking in that it's like trying to predict things that are like off out just outside the window.
Mick Crosse: Yeah, II think, including the bias term is supposed to help that a bit. But
Mick Crosse: I think it's more to do with how you condition your data.
Ole: I'm not sure how much the 5 sorry, Hola, I think. Can that also be due to the due to the time lags when you z score your data. Isn't that you remember that we just like I have one plot in the
Ole: in my tutorial track, where you can see that if you say you z score the envelope you'll you'll you'll end up with like a baseline that's below 0. And then if you if you introduce.
Ole: if you 0 pad, you'll get like a step function at the beginning and and I've tried it once. The same analysis on the envelope trf with them without z scoring. And so with Z scoring, you're getting this step because you're pushing the baseline below 0, and then, without z scoring, you see it like on the same level. And then, without c scoring, I didn't see this like rise to the end, and with Z scoring I saw it. So I figured it might be due to this like step that you're creating.
CNSP: Yeah, drf, has a hard time with those discontinuities.
Marlies Gillis: Umhm. But in ill brain there's no padding or so involved. So
CNSP: and also an ill brain. there's not really an issue with
Ole: getting a weight. That's not 0 because it all starts at 0. And then it's the kernel is added on top of it. Yeah, that's true.
CNSP: but it's it's weird, though, like the the I'm gonna maybe I'll just show my screen
CNSP: just to illustrate like what I was seeing.
CNSP: But they they have this th. These were clipped from 0 to 500. So the way I'm interpreting this is that you've got a an artifact here and an artifact here just before 500, or maybe these are offset a little bit.
CNSP: and maybe this is actually for 500. But it it does a little bit of fitting before your team in, I guess, because you have to introduce that like
CNSP: that, like the other side of the kernel. But yeah.
Marlies Gillis: yeah, indeed.
CNSP: Alright.
CNSP: just to show everyone what we're talking about.
CNSP: So it's not just us that sucks
CNSP: a yeah. And she also had a pretty much the same
CNSP: like W. Solution that we do is we fit a little bit beyond what we want, and then shrink it down.
Giovanni Di Liberto: So everyone, otherwise pretty happy with the and the Rf.
Giovanni Di Liberto: Matters we have at the moment.
Giovanni Di Liberto: Nobody wants something better like, I got particularly frustrated with the time invariance, assumption. So this
Giovanni Di Liberto: assumption that basically every time you you hear a sound like you hear a click, or whatever the response is, you know, is is going to have the exact same
Giovanni Di Liberto: timing, let's say, which is also, what causes that? Those those big
Giovanni Di Liberto: large responses for the N. 400. So, you know, I've been thinking about having a model that you know in the Trf, basically, if you say, Oh, 400 ms.
Giovanni Di Liberto: that is the log.
Giovanni Di Liberto: But that is, that is always. That's I mean, you assume that 400 ms response the same across time. Right? It's always at 400 ms, while I mean, add with
Giovanni Di Liberto: Dennis?
Oh, what's Nanny's surname? Mick?
Giovanni Di Liberto: mit Ctl. And Dennis Dennis Drennan he showed I mean, it was known already, but in the context of continuous sounds. He showed how that's absolutely not true. So you got
Giovanni Di Liberto: he did this cool study where basically, we're having this this this envelope.
Giovanni Di Liberto: I don't know if some of you have seen that, but basically it was taking. It was splitting the envelope into different different envelopes.
Giovanni Di Liberto: One was capturing the loud sounds, and the other the less loud and less loud and less loud portion of the of the sound, and basically showing that you know the louder it is the earlier the responses. Is that right?
Giovanni Di Liberto: So the latency changes for different levels of.
Giovanni Di Liberto: you know, magnitude of the of the envelope. not to say loudness
Giovanni Di Liberto: and but in the same way, for for different words of different length. you know, you would have response to different latencies. So was considering looking into models like
Giovanni Di Liberto: mixed models, or something like that. I don't know some sort of kernel models that that. Don't have this time invariance. That's exactly the paper. Yeah.
Giovanni Di Liberto: The figure looks ugly, but but the concept was clear, I think, where he shows the actual colorful. Trf.
yeah, there.
Giovanni Di Liberto: basically, for different amplitude beans. The response changes latency.
Giovanni Di Liberto: And so with the normal. Trf, you just get a large component when in reality for different loudness, you will have small.
Giovanni Di Liberto: small different components, different latencies so pretty frustrating.
CNSP: I mentioned this yesterday, but Jen has also been using deepmail notes to
CNSP: fit the timing of like when an in 400 should be
CNSP: like, for example, based on.
Giovanni Di Liberto: I mean ability.
CNSP: II think it the the I, the thinking behind it is that like as we're like listening to words, we like gain an understanding of what that word is at different points in the word.
CNSP: And so the the Michael Broderick paper puts an impulse at the start of the word, but that's not necessarily where we.
CNSP: And then also all the old in in 400 papers. They do like time aligning to the beginning of the surprising or not surprising words. So we're assuming the beginning of the word is like when the comprehension is yet like yoke to, and that there's some like
CNSP: single like one lag after the word onset, when we understand the word.
CNSP: but it could be like toward the end of the word or middle of the word, depending on how long the word is so like is known. That model like
CNSP: is fitting
CNSP: the in 400 and allowing it to like change across time to get the best fit. And we do find that like I don't know that the details, but it does improve the the fit, and there does seem to be some relationship between something to do with the words and and the the latency of which the in 400 appears so.
Ole: But I think I think this doesn't address Jovani's problem right? Because I think what Jen does. I mean he does like somehow, like warp the trf around with his deep learning. But you still end up with like one trf.
Ole: so so that that Drf. Still would would say that if you have like one stimulus, it is the response. And then, if you have the same stimulus again, it is still the same response, while I think what Giovanni is
Ole: suggesting is that the response, like playing the same stimulus twice in a row, should have like the second one should have somehow a response. That depends on the first one. And I'm not sure if Jin's model incorporates that.
CNSP: No, yeah, you're right.
Giovanni Di Liberto: Yeah. I suppose I mean, my question is more of a general method that would apply in any case. But II get your point, darren. I mean I got it as a comment when it submitted the paper. I can't remember when. Maybe I think there's speech. And the reviewer was like, Oh, but why did you use the onset? Why don't use the uniqueness
Giovanni Di Liberto: point and that sort of stuff which?
Giovanni Di Liberto: Yeah, it's it's a different question. But it's
Giovanni Di Liberto: I wonder if there is a solution
Marlies Gillis: we have wrapped our heads around that issue as well. But it's not tricky. It's not easy to solve. II think the solution. And we have tried to, but not
Marlies Gillis: successfully like it's really completely new. Way of calculating or predicting your your neural responses by
Marlies Gillis: by, for example, allowing, like like you said, allowing also latency. So first, you need to learn the peak, and then you need to also learn that the latency can move, depending on the value. That that's
Marlies Gillis: very, very tricky.
Giovanni Di Liberto: yeah, I mean, because II was thinking, I mean, if you drop one assumption, you may have to introduce more. So more problems, of course. But let's say that you assume because the Trf, the current Trf doesn't assume.
Giovanni Di Liberto: How many peaks we have? But, as you say, let's assume that there are 3 peaks there is, I don't know. There is a the the I know, and one and and yeah, and let's say that you fit the Trf normally. And you say we know that this center there.
Giovanni Di Liberto: So on average, is there? But then we we tolerate some
Giovanni Di Liberto: some variability due to certain parameters.
Giovanni Di Liberto: We need to. We need to write the math. That's the problem now. But maybe Lucas has some ideas, since it's so into
Giovanni Di Liberto: month. Part
Giovanni Di Liberto: but II can see there could be a couple of formulations. The question is, would it be worth it or not? Cause overall? I mean, Eeg is rubbish, anyway. So are we going to to be able to do anything better. I don't know but the but using Lucas methods. If we assume consistency, maybe across participants.
Giovanni Di Liberto: you see rather than across, like, if you assume the like. The uniqueness point of Aaron was mentioning there.
Giovanni Di Liberto: Maybe, if you use, like, the the method that the Lucas is using like into the subject correlation Ioc there, or maybe maybe using, you know, Mcca, which is the same thing, really getting this ground truth, this basically component across participants.
Giovanni Di Liberto: Maybe then we could try to fit these models. But
Giovanni Di Liberto: does. Anyone has hands to do that.
Giovanni Di Liberto: I don't have a mathematician at the moment in the team, so can't do that.
Giovanni Di Liberto: Maybe Ola Ole, how do you pronounce your name? Ole Ola? Ola. Ole.
Ole: Yeah. First first try was good, ole and nice to meet you. Finally. By the way.
Giovanni Di Liberto: I've been using exchange emails as well. I've been using your work and all. So that's that's that's great stuff.
Giovanni Di Liberto: maybe you have some math background, or
CNSP: this is all magic to us, Joe. Did you know that?
Giovanni Di Liberto: And it works
Giovanni Di Liberto: any other funky question?
Giovanni Di Liberto: Thank you, Mick, for spotting the the type on the title of the paper, by the way.
Mick Crosse: and also
CNSP: shared that with me.
Mick Crosse: II also caused it.
Giovanni Di Liberto: Ed caused it, and he fixed one thing and and created another issue. okay, let Ca, can I just repeat to something that you said already, Aaron?
Giovanni Di Liberto: If any of the people in the in the room, you know, would like to to get involved in any you know, at any level.
Giovanni Di Liberto: Just give us a shout.
Giovanni Di Liberto: You know we've been doing this for what? 3 years. Now we'll keep doing this.
Giovanni Di Liberto: we need to figure out in which format but I mean, I'll keep doing this stuff, anyway. So
Giovanni Di Liberto: your involvement can be like
Giovanni Di Liberto: anything. You have a data set, and you want to to share it.
Giovanni Di Liberto: or you have shared it, anyway. And you want to say, Oh, I have shared this data, said, do you want to put it in a website? And they have a function? There is a bug. There is anything. you know that that's that's
Giovanni Di Liberto: any level of involvement. The thing is that of course, we have limited
Giovanni Di Liberto: number of hands. So when there is, sometimes we receive back reports, and we just don't have
Giovanni Di Liberto: particular person correcting bugs at the moment.
Giovanni Di Liberto: so we'll we'll aim to apply for for for grants for that.
Giovanni Di Liberto: So that's one of the things that we'll discuss.
Giovanni Di Liberto: you know, later on. I was looking around into into grants for
Giovanni Di Liberto: supporting the the yeah. the development of scientific software. So there are some. There are particular applications that are not the usual grant applications we will go for.
Giovanni Di Liberto: So I might get in touch in in a month or 2, when when
Giovanni Di Liberto: I have more bandwidth, and we can, we can talk about some beating something, for, you know, getting a richer's assistant on this
Giovanni Di Liberto: for a couple of years would be incredible, you know, to to fix all the bugs and and bring some some things to completion.
CNSP: Are you? Are those grants going through like an Irish thing, or is it euro council, or is
Giovanni Di Liberto: variety of things? I've seen some companies. They give some
Giovanni Di Liberto: free money, basically. For for encouraging this kind of stuff. I think there was
Giovanni Di Liberto: from the classic Google thing to to other, to to to foundations that that that support these kind of activities.
Giovanni Di Liberto: Th, there is. Yeah, the the bigger ones I have. I haven't found any of the of the Irish things. Yet if anyone has any ideas, you know, let us know what happened to the
CNSP: The dude who contacted Ed about putting the Mtf. Tool box on Matlab. I know it's a I know it's an add-on on Matlab now that you can get through Matlab. But I thought they were gonna
CNSP: help us with
CNSP: the code at some.
Giovanni Di Liberto: True true, they had mentioned that
Mick Crosse: they contact us a few times about gone in for a grant or something like that, but never. never already went anywhere.
CNSP: Hmm!
Mick Crosse: Actually, one thing II meant to ask all I about regarding the
Mick Crosse: the tutorial. So he was talking about how?
Mick Crosse: when you're doing your statistical inference, you know you can kind of test whether or not the
Mick Crosse: correlation you get, the performance value you get is significant or not by doing a permutation test on the data
Mick Crosse: and
Mick Crosse: obviously doing doing that correctly takes a lot of time right? Because you have to.
Mick Crosse: you know, scramble the order of your how your data is is matched, prepared.
Mick Crosse: and on the the analysis we've talked about
Mick Crosse: a kind of a slightly
Mick Crosse: act way of doing that where, instead of
Mick Crosse: mismatching your data and trying to compute the mapping, you just
Mick Crosse: calculate the correlation between your prediction.
Mick Crosse: and a different trial.
Mick Crosse: And I was just wondering is, is is that in any way valid? Or would you get this? Do you know if you. Have you tried that? We recently had a very similar discussion
Ole: erez agmoni in the in our lab meeting, and I don't know I'm I'm planning on testing that out. Also, one suggestion ad recently had is, for if you do this for a decoder, of course, the amount is like massively increased that it
Ole: computation time? Yeah.
Ole: that this would be yeah. It would be would be really, really useful to to
Ole: Do this this approach. Ii think, what? What did you? You said? You you wanna you're comparing the correlation on the
Ole: to any other trial?
Mick Crosse: Yeah, exactly. So you you you fit all.
Mick Crosse: Yeah, you fit, you fit all of your correct models.
Mick Crosse: and then the prediction of those models is compared
Mick Crosse: to the wrong trial.
Mick Crosse: Instead of mismatching the stimulus and Eeg at the training stage.
Mick Crosse: because obviously, it's the training stage that takes yeah. but I'm not sure if if if that they necessarily kind of give you the same null distribution.
CNSP: I don't think they're going to give you the same distribution, I mean numerically, they might be very similar, and I think that was the
Mick Crosse: yeah.
CNSP: In point of, like, our, all of my talks about this is that probably gonna be the same like ultimate distribution numbers wise, but conceptually I think
CNSP: it's not the same at all, and one you're trying to fit a shit model, and the other you're trying to use a good model to do shit.
Ole: Yeah, I mean, of course, you're doing something else. But I think the important question is whether this gives you like a good approximation of the true permutation distribution, right? And it's a good approximation. But I think, yeah, it's step definitely something worth testing. I think
CNSP: I think it's would be important to like vary the conditions in which you're testing that. Because I think under
CNSP: like optimal conditions, you're gonna get pretty much the same distribution.
Mick Crosse: But I think there might be some like edge cases
CNSP: where that doesn't work, maybe not even edge cases, but like
CNSP: like th, the thing that pops out immediately is what Nate was trying to do is trying to use permute like tracking for music.
CNSP: And if you have multiple, like different styles of music, for example. and you fit
CNSP: like it's it's not really a fair comparison to try to get a good model to predict the wrong kind of music, because the wrong kind of music has all kinds of different
CNSP: statistics like it. It moves slower or could move faster, so that distribution might not be
CNSP: applicable. And that's why he would use, like the circular shift to keep the the statistics in the same
CNSP: fit and train in the model. because his other trials he couldn't actually shuffle the trials, because
CNSP: it would like not be a good null distribution. So you would still have the same distribution when you're predicting a different trial. No, that that different trial would still have the correct sort of overall statistics of the stimulus. Yeah, except you wouldn't try to predict a different trial the way I would do a permutation test is
CNSP: to shuffle on the train
CNSP: and then try to predict the right trial with that bad model.
CNSP: Yeah. But then you have to do all the training right. The idea like, avoid having to do all the training. I mean, I think, in the optimal situation you can avoid that. But
CNSP: I think to be like careful in in those edge cases. I'm not sure if you can avoid that.
Giovanni Di Liberto: Yeah, the the risk increases with the complexity of the features in the stimulus.
Giovanni Di Liberto: So that is the problem we we had dealt with with Nate, I think, or or make.
Giovanni Di Liberto: It's just. Instead of of correlating a different trial, you correlate you, you use a different stimulus for your prediction, which is the same thing.
Giovanni Di Liberto: but the the difference is whether
Giovanni Di Liberto: you know, if you, if your model is particularly sensitive to the lambda in sense, that if you have a shied
Giovanni Di Liberto: model fit like you. You shuffle your your training.
Giovanni Di Liberto: And the question, is there? Okay, I had an optimal lambda one with the correct order. Now I'm shuffling and I get an optimal lambda. 1,000
Giovanni Di Liberto: right? Does that 1,000 give me more? And of course your baseline is going to be higher.
Giovanni Di Liberto: marginally higher. Remember, we just have one
Giovanni Di Liberto: hyper parameter. So if we were talking about Cca, I would tell you. Don't do that because it would be a tragedy. You're missing all the overfitting and your consideration for the random distribution. But with the Trf. In my experience it doesn't make much of a difference
Giovanni Di Liberto: to the point that if you want to get a thousand shuffles.
Giovanni Di Liberto: It may be justifiable to do it that way.
CNSP: you mean with one lambda not optimizing.
Giovanni Di Liberto: No, no, I just mean fitting a good model and predicting wrong data. If you're talking about the univariate model or the model with 2 or 3 features.
Giovanni Di Liberto: and
Giovanni Di Liberto: there is for overfitting in that sense it's really little compared to a Cca. So II tried again, small
Giovanni Di Liberto: in in my own experiments. And the difference was not that
problematic, not that big.
Giovanni Di Liberto: Of course, in my, in my view, there is one optimal shuffle, which is.
Giovanni Di Liberto: if you retrain everything, because that takes into account the risk for overfitting the hyper parameter. In that case.
Giovanni Di Liberto: and we have environmentalize. The other one is a weaker shuffle, that's all.
Giovanni Di Liberto: If it is substantially like
Giovanni Di Liberto: higher, you know it's fine. If it is threshold close to threshold, then yeah, it's it's tricky.
Ole: Also, in the end. It's still, whatever we're getting out, there is just the p-value, and the P value in itself isn't really all that meaningful right? It's just tells you tells you whether the effect is like non random
Ole: under normal distribution, which is often like a very.
Ole: a very limited
Ole: like conclusion, which might not be that might not be worth like having to run like code for days and days to go through all the permutations.
Giovanni Di Liberto: Exactly. You're you're you're talking like an engineer now, that's good. And but the reviewers want a p-value.
Giovanni Di Liberto: No, they don't want it anymore, Aaron. They want the p-value. They want the effect size. They want all the possible statistics around it.
CNSP: I mean, that's a pretty good point, I think, Ola, is that I mean at the end of the day we're chasing a stupidly reduced
CNSP: like metric here. I mean we? It's got a lot better metrics to use than that.
CNSP: I mean, that might be the the straw that puts me in my place. Finally.
Ole: yeah, what I thought about is there? I mean, I haven't like come to anything yet, but since I like
Ole: dabbled a bit into like Bayesian statistics, whether you could do something like a like a Bayesian implementation of the Trf. Where you would then in the end, in your grf, you wouldn't just get a a single line, but you would rather get like a posterior distribution
Ole: for the for the Trf. And in that way you could sort of judge from the distribution, like how how certain you are in your estimate that you're at like certain points.
CNSP: Maybe you can do that.
Ole: I mean, probably someone can do that. I'm not sure if I can do that.
CNSP: Sure, I could do that.
Giovanni Di Liberto: And one thing is for sure, we need to increase the size of those effects. We need to increase those effect. Size those metrics are very small. And so
Giovanni Di Liberto: thing is, is that how do you do it? So I've been working on this in a couple of ways.
Giovanni Di Liberto: And 1 one of the things is
Giovanni Di Liberto: with the with the baby started the time about to publish after like 40 years and learning to phoning, tracking.
Giovanni Di Liberto: Yes, so George is in that one. That's a that's a that's still. That's still a secret we can't say. But it's it's it's very. It's very good.
Giovanni Di Liberto: And and in that case for measuring.
Giovanni Di Liberto: So because babies, the data from babies is rubbish. And it's not that it's really, really noisy.
Giovanni Di Liberto: said it in simple words. so there are. One thing that that was the reviewers were complaining about was, and the result was coming out with the usual analysis.
Giovanni Di Liberto: But then they were like, Yeah, but the effect size is so small. Are you really sure? So what we did was to. So the the problem with the statistics was that their numbers were so unstable between different babies because of the noise, those little data. So I was thinking of using Mcca there.
Giovanni Di Liberto: and in which way, in the in the end, I didn't use Mcca. We we average across subjects which is horrible, but it works
Giovanni Di Liberto: in which way we. This was Alan's idea from ages ago getting a ground truth signal.
Giovanni Di Liberto: So you assume that all the subjects have the same response, which is a false assumption, but you make it every time you average Drfs. So you have the same assumption. And so you average the easy across all participants
Giovanni Di Liberto: or across the left out portion, or or whatever, and you use, and when you do your prediction, you fit your model, you predict the Eeg, and you correlate your prediction, not with the data from that subject, but with the average participant.
Giovanni Di Liberto: and which is different from the generic model, the generic model we were averaging the participants.
Giovanni Di Liberto: Now we are, have. We have using the single subject model
Giovanni Di Liberto: and assuming that that we are getting the actual ground truth behind the signal. We are correlating that with the ground truth, so that the results are a little bit more stable. but a good bit more stable
Giovanni Di Liberto: even though the Tiraf is the same
meet.
CNSP: So you average people's Eegs.
Giovanni Di Liberto: Yes, Alan would be disgusted, and but we had done it with MCCA. It was working.
Giovanni Di Liberto: The problem is that the Mcca you have these parameters to choose, and the reviewers were not super happy of that. How do you choose them? And it? You know, it sounds a lot lots of hand picking. So we said, Okay, we just average across participants. You can't say anything, and this thing works.
Giovanni Di Liberto: So the the
Giovanni Di Liberto: so we just went for that. But we had 50 participants.
Giovanni Di Liberto: So it was quite a bit.
CNSP: I'm looking forward to that one.
CNSP: What else?
Giovanni Di Liberto: Agenda is the the future.
CNSP: I mean, yeah, we could.
citizen.
Giovanni Di Liberto: about cats.
CNSP: I don't wanna belabor it here, though it's like no one has any questions. I don't wanna like, keep people on the hook.
CNSP: you know.
CNSP: What do you think? Should we call it? Anyone wanna pipe in? No, okay, I'm gonna call it. Then. unless Joe objects and then wants to talk about the future.
Stephanie Haro: I guess the last thing we can mention is that
Stephanie Haro: like about the research application, the research Grant application.
Stephanie Haro: Oh, yeah, maybe we can email this out. There's only 2 people here. Yeah.
7.
Stephanie Haro: You mean, the the project thing.
CNSP: is there a link? That link?
Stephanie Haro: Yeah, that's the link to the Pdf, kind of advertisement that has the Google drive.
Stephanie Haro: Sorry the Google form. URL embedded into it.
Giovanni Di Liberto: Right? What's that like? Sunday
Stephanie Haro: copy that link? But into their chat
CNSP: the third Saturday?
Giovanni Di Liberto: Yeah. yeah, we got a few, a good few applications last year. There, you some people wanted to come for a week, other people for for a month.
Giovanni Di Liberto: And the way we did it last year was to to to get all the organizers to to vote, and all the speakers to, to vote as well, to make it a little bit more.
Giovanni Di Liberto: I say, less biased.
Giovanni Di Liberto: If that makes sense.
CNSP: So it ended up being like we had 2 each to look over.
CNSP: Is that right?
Stephanie Haro: I think so
CNSP: that seems fine to me.
Nick.
CNSP: Joe, did you want to talk about the future, or should we go?
Giovanni Di Liberto: I suppose? Just 1 min. I mean we we can. We can leave the participants.
Giovanni Di Liberto: you know, free, if if they like, but they're free to stay just for
Giovanni Di Liberto: couple of minutes.
Giovanni Di Liberto: and One thing is, you know.
Giovanni Di Liberto: it could be also a good time to start thinking about. Do we want to get someone else in the organization for for the future. That's one thing to keep in mind, because I know that once we close this call like last year, we'll disappear
Giovanni Di Liberto: apart from the project will disappear. And and it will be very hard to reach people over email. So that's why I'm asking you to bear with with me now. And so Nate is already gone, and I don't expect him to be much more active in the next couple of months.
Giovanni Di Liberto: So
Giovanni Di Liberto: he did mention to me that he
CNSP: felt compelled to help next year. I mean, he didn't say I feel compelled, he said. Maybe I'll maybe I need to help out again next year, so he might be back on board.
Giovanni Di Liberto: And that's fantastic. I'm just saying helping with the workshop is not what I'm talking about here.
CNSP: The initiative.
Giovanni Di Liberto: The thing is, you know, in the last year I spent a lot of time trying to put these things together.
Giovanni Di Liberto: So there was a lot of effort. and I need a break.
Giovanni Di Liberto: and
Giovanni Di Liberto: so so II won't be working on this for the next couple of months, anyway. Certainly. Certainly, you know from from December, after the teaching of the first semester is over. I can get back to it
Giovanni Di Liberto: and just driving the the, you know, when we leave we have a few people asking for bug fixes and stuff, and they won't have the fan, the hands to to fix that stuff so as long as there is a plan for the future. It doesn't have to be a plan for January, but planning on for next September.
Giovanni Di Liberto: So that's why I'm saying the kind of effort I'm going to to to put in here is to figure out some grant or something.
Giovanni Di Liberto: and maybe we can get add to to to get in touch with that guy again to figure out some some money, because even if it was a part time research assistant. or something like that that could be super helpful. And students don't like these kind of projects.
Giovanni Di Liberto: they want to do all the all the students want to do project with me. The master students. They want to do scientific projects rather than a toolbox. So so it's a. It may be tricky to to figure that out.
Giovanni Di Liberto: but I keep doing it myself, but I'm I'll be slow.
So raising money is one thing.
Giovanni Di Liberto: and And then it might be time also when we what Marlis was saying about this, the cog here.
Giovanni Di Liberto: you know, they're they're
Giovanni Di Liberto: trying to collect. That's that's Malcolm, of course, trying to collect all different resources. Different data sets and stuff that's great for us in a way, because once we have those data sets in whatever format we can, you know.
Giovanni Di Liberto: put them in in in C and D as well, and and get this.
Giovanni Di Liberto: try, try to get more out of this. The question is, what is what do we do, do we? We could try to reach out to people to see if some one would like to get their hands dirty. Maybe also, some some one has more time
Giovanni Di Liberto: or more competence than than I have
Giovanni Di Liberto: or or or do you think that going for applying for money is the better routes? What? What do people think?
CNSP: I think the most successful is probably gonna be trying to get some money
CNSP: and then and then like having something for someone
CNSP: like a motivation.
CNSP: I think it's gonna take someone that's like paid
CNSP: and like, take over some of the
CNSP: heavy lifting on those things.
Yeah.
Giovanni Di Liberto: post up. Now, now things are getting trickier, you know. There are too many students to
Giovanni Di Liberto: take care of. So things go slowly. I got a couple of Uc students to help this year.
Giovanni Di Liberto: So the the the graphical interface, Martin, he he helped quite a bit with that, and the research assistant had for 3 months she had quite a bit with that as well.
Giovanni Di Liberto: But yeah, maybe it's time to get some money and get someone specifically for this project. But I need some help to
Giovanni Di Liberto: to find these grants. And you know, having also being also in different countries, we could
Giovanni Di Liberto: have a better reach. yeah, that doesn't. I mean, I don't know if I could submit anything
CNSP: to like where I could submit something to as a post docker, I mean, pretty soon I'm gonna be
CNSP: non tenure track faculty.
CNSP: so I don't know if that'll open up any doors for me, for, like Nsf. Or Nih or anything, or Nih for sure I don't know about Nsf.
Giovanni Di Liberto: I was looking with that, but I can't apply with that with this Irish slash
Giovanni Di Liberto: American. You know us Irish collaborations.
CNSP: cause you were his grad student.
Giovanni Di Liberto: No, that's the problem. I'm not. I can't apply with that because I was students. So that's why I was saying, you can. You have like that conflict of interest.
CNSP: They're not really conflicts of it.
Giovanni Di Liberto: Yeah, let you know it has to be a new thing, etc., and act a new thing, but also not with your supervisor, maybe, but
Giovanni Di Liberto: maybe with one of you guys with you. If you have this new position, Aaron.
maybe even getting money for a short amount of time that that fits your your contract.
Giovanni Di Liberto: Do you have a star to eat?
CNSP: No.
CNSP: should be around the New Year, though
CNSP: I mean II might. Uvr. Has like a 5 year end of a post, Doc.
CNSP: and that happened in September, and Ed come up, came up to me, and like August it was like.
CNSP: so I didn't even think about your contract is ending, and it's ending, and we don't have a solution for that. So
CNSP: fortunately, the girl in Bme like figured this out ahead of time, and like a picked up the slack for Ed, and we got a 4 month extension on my contract so that I can
CNSP: formally apply
CNSP: so that contract is up at the New Year. So that's should be when the new one hits
Mick Crosse: nice.
Giovanni Di Liberto: Yeah, people get Mccain as a company
Giovanni Di Liberto: like we already have a network. You know. thing is finding the calls, etc. So maybe if everyone can keep an eye out on calls.
Giovanni Di Liberto: And I mean, Stephanie, you're just starting your post, Doc, so don't worry about calls now, just to rely.
CNSP: You should be worrying about those worrying about those calls.
Stephanie Haro: Right?
Stephanie Haro: I'm super confused about how Post Dog Fund is gonna work out because I was given a fellowship through the school. So I'm like trying to figure out
Stephanie Haro: I haven't even spent time trying to figure out how like applying to funding as a post. Doc works when you're not like you, and you don't need a stipend for yourself
Stephanie Haro: like, when do you start transitioning to like fellowship money? Or when do you apply to?
Stephanie Haro: Thank you? I mean, you could be paid off of a grant.
CNSP: and then you
CNSP: you can have funding through someone else like you're paid off your pis, Grant, or you have a or something like that from a department. But then you get your own funding, and you just pull off of that funding onto your own whenever you want
Stephanie Haro: like. If I have my stipend completely covered from my university
Stephanie Haro: like.
Stephanie Haro: would I apply to like post, Doc. Fellowship, from Nih, and then just not take the money.
CNSP: No, you would. You would take the Nih money and give
CNSP: I mean, I don't know exactly how you would want to do it, or how they would do it at your department, but, like at Vanderbilt, like I was.
CNSP: I could have been on A. Then I applied to a T. An. And the plan would have been that I would have relinquished the money which is the department's money, and taken my own money, or whichever one of us for free doctoral.
CNSP: And I mean, it's going to be about the same amount of money. You might even get more money with your own personal funding. But.
CNSP: like
CNSP: the way I understood the is, that was just a spot for whoever I took it up.
Stephanie Haro: and if I wasn't taking that spot someone else could have it.
Stephanie Haro: I see they hired me at Brown as a as a an employee, so I don't know where that money is coming from. I guess it's coming from the fellowship like I have a internal university fellowship. So then it would offset some of that money. And okay, so it's the same as undergrad. It's it's the same as grad school. Where? Okay?
Stephanie Haro: Yeah, I mean, I'm I'm assuming. That's the way it sounds like it would have been for me
Giovanni Di Liberto: what what I do I don't know. If you saw that link I was sharing earlier on
CNSP: the Imperial College.
CNSP: I got that.
Giovanni Di Liberto: Oh, this one! No, wait.
Giovanni Di Liberto: I don't know. No call. Yeah. I mean this kind of stuff. They're all very different from what I'm used to look at, but what I could do is to find one of these right the ground for it. Maybe you know
Giovanni Di Liberto: II can't do it now until November, December. But maybe in December I start drafting something
Giovanni Di Liberto: or one of these things, and some of these like this one seems to be like
Giovanni Di Liberto: free money. I don't remember where it was.
Giovanni Di Liberto: Works out pretty well
CNSP: if you want to start at like November December on writing something, if if this would if it's something that's gonna benefit from having, like
CNSP: some like transatlantic collaboration. that timing would work out great for me
Giovanni Di Liberto: when I see a deadline here for a letter of intent.
Giovanni Di Liberto: These things are usually fairly relaxed, I mean for this one, for example, I could try em. What is the scenario? They say, you know.
Giovanni Di Liberto: alright quickly, and if it goes well, this could be one. But again, I'm not not. I don't care about that license. I'm just saying
Giovanni Di Liberto: there could be other things here.
Giovanni Di Liberto: Small development grants I don't know.
CNSP: Maybe we have a look through some of these and
CNSP: make some notes and see which one are going to be the most feasible. What we're trying to do
be great
CNSP: cool.
Giovanni Di Liberto: I know that for the for the Irish one, yeah, for the Irish. You asked me to ask, because he knows how that works there might be. There might have to be a Northern Irish partner as well. I'm not sure. But there, there are a few
Giovanni Di Liberto: but if we got that like, if we got one person working on this part-time, even just part time for a couple of years that would change everything
Giovanni Di Liberto: cause I've I've seen how this Ra. Worked for me for 3 months.
Giovanni Di Liberto: and it's it's just incredible, you know, the amount of work they can do when that did they do that full time, you know, writing documentation and fixing box. You know, the web data browser could actually become a thing, because at the moment the web data browser don't know if you did you, Sue? Did you see it?
CNSP: Yeah, I didn't use it. But I
Giovanni Di Liberto: I went to it and like messed around. it has very few parameters for now.
Giovanni Di Liberto: what's that?
giorgia cantisani: I tried it?
Giovanni Di Liberto: Okay.
giorgia cantisani: well, yesterday, right? It's it's really nice. It looks really different from
Giovanni Di Liberto: yeah, I mean, it's it's not, it's it's slow, of course. And but again, the the speed depends on how much money you pay for now we don't pay anything.
Giovanni Di Liberto: It runs completely on. All is a version of the Terra and Terra toolbox.
Giovanni Di Liberto: and the idea would be to like. Here you have the Csb
Giovanni Di Liberto: data browser with all the options, basically right preprocessor. And he arrived. All this stuff works all the data sets take imagery, and suddenly have all these, all the different features here.
Giovanni Di Liberto: and different conditions. You know.
Giovanni Di Liberto: the idea would be to have a data browser with that. and then you can load the ear brain functions. You can load the neural networks you can load. Well, it doesn't have to be on on the anti ref.
Giovanni Di Liberto: It's just something that you can where you can do this stuff easily, which it greatly helps me when I talk with people that are more on the applied side.
Giovanni Di Liberto: like, I'm trying to get people, you know.
Giovanni Di Liberto: new collaborations on on autism, for example, research. And they're like, Oh, but the experiments can be just this lines and that sort of stuff. You just go there. And and it's it's really useful, you know.
Giovanni Di Liberto: Maybe you don't even get a paper out of it. But you can get new collaborations, maybe.
Giovanni Di Liberto: but it's just a proof of concept. It's not feasible to keep it up there. Because. yeah.
Giovanni Di Liberto: it's free. At the moment
Giovanni Di Liberto: we have a limited number of calls we can do.
CNSP: Oh, really like, if if someone runs something like it's N minus one that is left? Or is it a time? Limited thing like you can only do in per unit time
Giovanni Di Liberto: and calls per month?
Giovanni Di Liberto: Because otherwise. After that you after that you pay.
Giovanni Di Liberto: and so we we put a limit to whatever before we pay.
and but we could make it.
Giovanni Di Liberto: You know we? We have some funding, of course, from from the workshop and stuff. So if we said, if we build something that is nice, you know, this time next year. We have a nice web browser that is cool. And we say, Okay, we want to to invest
Giovanni Di Liberto: €300 a year. and we got a super.
Giovanni Di Liberto: you know, useful thing for people. If people find it useful, we can send a pole around.
Giovanni Di Liberto: but we need to build it first.
Giovanni Di Liberto: It wouldn't be too hard. It's all about getting this money
Giovanni Di Liberto: if you think it's worth it. If you don't think it's worth it, you tell me, and and we can just be happy on the paper, and then some one else will do it in the future. We don't need to be the ones to do it.
CNSP: I mean, if we're gonna
CNSP: I don't know. I don't think it would be too hard for us to write something to submit.
CNSP: I mean, those can't be that. I mean, if we're only paying for like a person.
CNSP: These sorts of grants can't be that long, though. Right? Like maybe 5 pages 6 pages.
Giovanni Di Liberto: 3 pages, 4 pages mail. It's a methodological
Giovanni Di Liberto: grant. I mean, they're they're not. You don't need to go into the
Giovanni Di Liberto: theoretical foundations. Yeah, it's a. It's a scientific software. So
Giovanni Di Liberto: alright. fairly easy to show to show that we don't have that much in our field to compare to bioinformatics and other fields. You know.
Giovanni Di Liberto: I don't know. I think we have a strong, strong chance to get some money there, because we have a network, and we've done workshop 3 times and
Giovanni Di Liberto: receive the paper that's published. That will give us a better chance.
CNSP: Yeah.
CNSP: I say, we go through some of the I say, we go through this list and see if we can find something that works or find a couple.
CNSP: I'll do that in the coming months
Giovanni Di Liberto: sounds great, and if you hear of any company. I'm talking with companies and stuff.
Giovanni Di Liberto: Of course they want their.
Giovanni Di Liberto: They need to have a reason to do that. But some some big companies like to give free money for these these things, just to say that they
Giovanni Di Liberto: like even even a few €1,000, you know, just to get a British assistant for 6 months to start with part time. You don't need that much money.
CNSP: do we have to slap the company's logo on the trf like
CNSP: application?
Giovanni Di Liberto: I don't know. But look in in Ireland doesn't cost that much. So I had. I got the ground, for I think it was €20,000
Giovanni Di Liberto: for something else. And with that I got an array for for 3 months.
Giovanni Di Liberto: So it's it's not bad.
CNSP: damn I wanna be making €80,000 as an Ra.
Giovanni Di Liberto: yeah, maybe 10,000, maybe.
Okay.
Giovanni Di Liberto: you want to talk about future workshop before everyone leaves. And Nick is really wants to leave because it's 9 pm. Here. Georgia is 10 Pm. I don't have I. It's not late here, so I'm I don't care. But I am trying. I would like to be respectful of the people it's really late for. So yeah, I mean, we should talk about it, maybe, but shortly.
CNSP: I mean, I like I don't have anything to say about it. So what were you thinking?
Giovanni Di Liberto: This was just to make sure once again that like.
Giovanni Di Liberto: maybe it doesn't have to be next year. But it could be 25. I don't know. I'd love to do this with a component I've been in touch with someone in in Roma.
Giovanni Di Liberto: near Rome, I'll I'll show it to you just to tease you.
Giovanni Di Liberto: Please spend it.
CNSP: do you think? Do you think an in person one would be more like a paired down Telly ride.
Giovanni Di Liberto: No, I mean, I
Giovanni Di Liberto: look, the goal is is always to to to teach people to get students to learn rather than to get students to.
Giovanni Di Liberto: you know, to work their ass off on your own project. And but but the
Giovanni Di Liberto: and maybe it wouldn't be as long. No, no, no, I wouldn't think there'd be 2 weeks.
Giovanni Di Liberto: Yeah. I mean, if it was. Imagine a week or 10 days like, imagine that we were still doing the worship online that here.
Giovanni Di Liberto: But then maybe there were 20 people.
Giovanni Di Liberto: and maybe you know, 5 of us, 4, 4 or 5 of us, and then 15 students.
Giovanni Di Liberto: They come with their data set because maybe we don't have time to record data, or they want to do something real time. I don't know but they come with something and
Giovanni Di Liberto: and and we help them, you know. and we actually get some results out with
Giovanni Di Liberto: it's it's it's a it's a I see, there's a thing for trying something new, cool. Maybe someone can work on metals a bit like Telluride. But others could be practically people that don't know how to analyze this stuff.
Giovanni Di Liberto: They come and we give them a kick, and and it's good for us. We get our name in in a paper. It's good with these people, because they save 3 months of work by coming and and and getting a good push.
Giovanni Di Liberto: So yeah.
Giovanni Di Liberto: and having small is also sustainable because we're not talking about getting people from all over the world. They're caught talking about doing it local.
Giovanni Di Liberto: the
Giovanni Di Liberto: necessarily event, and getting a few people from all over the world, but not like Tally, right where you got all over the world. And so many people
Giovanni Di Liberto: in order to mean like 5 people extra, you and
Giovanni Di Liberto: the rest you or and then another year can be in the Us. I don't know.
CNSP: I like it. I would like to do something in person small like that.
CNSP: I'm looking at pictures of this city. And the the top pictures on Google Maps is has like snow everywhere. And like. Does it snow in Italy, or like that far south?
Giovanni Di Liberto: If if there is mountains there are, there is a big mountains. And look at. Look! Look at. Look at this thing. It's it's a beautiful location, because it's cheap.
Giovanni Di Liberto: It's it's really as you say, old
Giovanni Di Liberto: in terms of amazing buildings and all buildings and stuff. But like this stuff. Where is it? There is snow in the town here. There's mountains nearby.
Giovanni Di Liberto: so you can go for hikes. No problem.
Giovanni Di Liberto: and it's very good food, very, and fairly cheap, anyway.
Giovanni Di Liberto: there was a big earthquake years ago.
CNSP: and there's a stone hinge.
Mick Crosse: It is Stonehenge. Yeah, some sort of Colosseum, is it?
CNSP: Yeah, it's not Stonehenge. It was something up just looked like Stonehenge.
Giovanni Di Liberto: But the thing is that you fly into Rome, and then and then you're you're you're not too far from there. So a friend of mine works works works there, had. It is a university. They are good university.
Giovanni Di Liberto: He works there, his mathematician actually.
Giovanni Di Liberto: And
Giovanni Di Liberto: and he was saying that it's easy to organize there if you want to, but it could be anywhere. Just Dublin is completely impractical because it's too expensive.
Giovanni Di Liberto: And
Giovanni Di Liberto: so I was thinking about Italy because it's cheap because I can
Giovanni Di Liberto: figure things out.
Giovanni Di Liberto: but you know it's all up for negotiation.
CNSP: Not a bad place to hang out to.
Giovanni Di Liberto: Yeah. I mean, people can fly into Rome easily
Giovanni Di Liberto: speak airport.
giorgia cantisani: I'm sorry I really have to leave you guys about to kill me, for dinner is calling me from the window. Just gives us thumb thumbs thumbs up or not, for
giorgia cantisani: I mean, anyway, we left to choose the the best project III think, in a in a
Giovanni Di Liberto: Yeah.
giorgia cantisani: hmm, that's a that's the shortest term goal. So we should meet anyway.
giorgia cantisani: to to both. And okay, let's take this as a teaser, then, and then we we can. I think it's nicer to keep
giorgia cantisani: a meeting from time to time, like regular on a regular basis. And and in worst case, we just say there's nothing to do and have a chutz.
CNSP: Yeah.
giorgia cantisani: I like that I'm also headed down.
giorgia cantisani: okay, thanks ola, thanks. Ola.
Giovanni Di Liberto: this is brilliant. Thank you.
Giovanni Di Liberto: Okay, we just close it. Close it here. Then.
Mick Crosse: yeah, I think so. Yeah.
Stephanie Haro: I'm officially almost 30. Instead of having a pint. I have an ibuprofen at the end.
CNSP: I don't even have a pint here. What kind of this is stupid might need to go get some beers.
Giovanni Di Liberto: That's why we need to do this in person. Is anyone coming to a road this year or next year?
CNSP: I don't know
Stephanie Haro: where my post, Doc, who would pay for me to go to Arrow as a first or postdoc.
Giovanni Di Liberto: Stephanie. II made that mistake when I moved to a landslap.
Giovanni Di Liberto: I had some work from add, but I didn't want to learn to spend his money for me to present the work I did with that biggest, biggest mistake of my life. I could have gone to to bomb to auditory cortex on on the Rocky Mountains. Instead of so naive I should have gone.
Mick Crosse: Everyone says it was amazing.
CNSP: I've also heard that in a half, Fomo
Mick Crosse: it is
Giovanni Di Liberto: alright.
Giovanni Di Liberto: That was brilliant work. That's congratulations.
Mick Crosse: Yeah. Well, everyone.
Stephanie Haro: I'll I'll schedule something, for whenever
CNSP: we start getting project proposals I might. I'll probably send out a new email soon, maybe tomorrow.
CNSP: Participants. Do you want that to be just the participants that get it? Or should I? We also advertise on Twitter stuff like that.
CNSP: what would you like to
Giovanni Di Liberto: just participants last year?
CNSP: I don't really see any reason to not open it up to everyone
CNSP: would would listen to reasons, not to.
Giovanni Di Liberto: It's usually something that you know. When you go to a conference there is a travel grant of the conference and conference, not in person. You could open it up to all the Cnsp people like to all the mailing list of the Google group.
Giovanni Di Liberto: If that makes sense. More applications are fine, but if you open it up to people that don't know what we're talking about here,
Giovanni Di Liberto: I'm just afraid that they'll do their own thing like at the point that they should also use our kind of resources and contribute to the
Giovanni Di Liberto: initiative in some way, like Giorgio. Did. You know, he's going to share it when he has the data said he's going to share it
Giovanni Di Liberto: in on the website and gave a talk. And these details are in the call. Right?
CNSP: They say you need to be able to share everything after you're done.
Giovanni Di Liberto: hey?
Sharing sharing on the Cns.
Stephanie Haro: Yeah.
Giovanni Di Liberto: Yeah. And I explained in the talk as well may maybe all all the list of emails of everyone that participated in the workshop.
Giovanni Di Liberto: If you have it, hand, the other the Google group. The Google group, is fine.
Giovanni Di Liberto: I don't think I have one handy. I can maybe look and see if there's I think there's something from last year I might look through that and add those names to it. Cool
Giovanni Di Liberto: last here. anyway.
Giovanni Di Liberto: Thanks, Amita. That was brilliant. I didn't do anything, and I'm I'm glad to see that I am absolutely redundant the X. Was a bit harsh.
Giovanni Di Liberto: but I'll give you a report on the money on how much we have
Giovanni Di Liberto: and that could be useful. By the way, sorry that's going to be used for the paper part of it.
Giovanni Di Liberto: So I'll let you know. I'll let you know how that goes. It's we. We have more than we have double than what we need
Giovanni Di Liberto: so if you have ideas
Giovanni Di Liberto: more than welcome, otherwise we can use them to top up whatever grant we get for the research assistant, you know.
CNSP: Sounds good.
Giovanni Di Liberto: Make Mick. You could give us money.
Mick Crosse: Me, personally.
Mick Crosse: Yeah, you work in a company. I have lots of lots of money.
Giovanni Di Liberto: Okay, we'll catch up for a pint next week, Mick, and I'm sorry we won't catch up for a pint for a while. If you don't count today, Arrow.
Mick Crosse: I'm gonna see if I can. Probably won't.
Giovanni Di Liberto: Please come. Thanks, Amelia, and everyone see you.
Giovanni Di Liberto: So doggo.