CNSP: We'll move on to Giovanni.
Giovanni Di Liberto: I mean, yeah.
CNSP: So Giovanni will give us some updates about Cnsb, what he's been doing over the last year or so what we've been doing, and then he'll introduce a his visiting student, Giorgio, who will give us an update on
CNSP: the project. So, Giovanni, please take over.
Giovanni Di Liberto: I'm stealing the screen. Now.
CNSP: please.
Giovanni Di Liberto: Is this the right? Can you see my slides?
CNSP: Not yet?
Giovanni Di Liberto: Oh.
Giovanni Di Liberto: what can you see?
CNSP: 2 pictures and your group.
Giovanni Di Liberto: Oh, great.
Giovanni Di Liberto: So these are the slides and Lucas. Thanks, Amelia, that was great and also the format. I like this interactive
Giovanni Di Liberto: format for online presentations.
Giovanni Di Liberto: I'll have to switch back to the old format, and
Giovanni Di Liberto: but it's very brief. So before before moving on with the next, invite the speaker, who's Giorgio Piazza, I'll just give you this brief update
Giovanni Di Liberto: on the work we have been doing, but also at the end I'll give a brief mention on the travel. Grant, supported by sponsored by a ambient train.
Giovanni Di Liberto: and let me just prepare a slide. One of the embarrassing slides with lots of faces and nobody looks at. But it's it's it's a necessary to thank all the people that helped in the last 3 years in all the work we did with the workshop and also with the resources.
Giovanni Di Liberto: So, Luke, as I've shown this picture in different flavors on the board, on the slides mit Ctl. And but the idea is, yes, we have in the different type of experiments that we deal with, that the Csb
Giovanni Di Liberto: initiative and workshop care about. We talk about, you know, some neural recordings and some
Giovanni Di Liberto: sounds that are continuous, or some videos or or everything that Lucas has has mentioned. And ultimately we have an X
Giovanni Di Liberto: and the why in machine learning sense so, and next, where we have, if you want some stimulus features, and the Y where we have the neural signal.
Giovanni Di Liberto: and we want to relate them somehow. So
Giovanni Di Liberto: when we have. And again, the way that Lucas described, when we have multiple features, imagine. And and this is something that happened to me. Anyway, we had recorded a data set thinking about phonology. And then that same data set has been reanalyzed in
Giovanni Di Liberto: I don't know how many different ways. So with so many different papers from different labs can come out from the same data. And so this, this is an opportunity.
Giovanni Di Liberto: It's an opportunity to to reuse data from, you know, rather than having to record a thousand times
Giovanni Di Liberto: the same kind of experiment.
Giovanni Di Liberto: and then the type of tasks that we're talking about, like listening to speech, and music is just more pleasant
Giovanni Di Liberto: mit Ctl, and so it gives you better access to particular cohorts that wouldn't be as willing to take long experiments where they have to look at, you know, flashing lights or individual syllables.
Giovanni Di Liberto: So just more pleasant the challenges are that we want to tackle one of the challenges that you know the correct use and interpretation of the methodologies we are talking about. Right? It's it's very important that if we start sharing resources, we start sharing code or or toolboxes.
Giovanni Di Liberto: that we also, you know, make sure that that there is no misuse of these tools. And so that's why we try to publish papers and and and also organize this workshop where we try to provide these
Giovanni Di Liberto: resources for for guiding towards the interpretation, and how not to use these methods.
Giovanni Di Liberto: And then the one thing that is very practical, and even within the same lab.
Giovanni Di Liberto: what happens is that is that we just end up using different versions of the same code for doing the same thing which is problematic, it causes it increased the risk for errors.
Giovanni Di Liberto: and also makes everything slower. So code reusability.
Giovanni Di Liberto: So with here Cnsb, at the center of this slide, what I'm trying to say is what Cnsb is is about. So one element is
Giovanni Di Liberto: trying to share some standard standardized analysis code for running different types of analysis.
Giovanni Di Liberto: And of course, we started from the kind of analysis we were doing already. And by we I mean Aaron and I and Nick, and so on.
Giovanni Di Liberto: All the organizers to share standardized code. We need to agree on some standardized format for for the data. And that's also another activity we have been working on.
Giovanni Di Liberto: and then trying to take some existing data sets and putting them in the same format. So that basically that same standardized code can be run instantly on on all of these different data sets without wasting time.
Giovanni Di Liberto: Then, of course, we have the workshops where we try to to share new research and new tutorials, question announcers, and so on.
Giovanni Di Liberto: And finally, we see this as an opportunity, for. you know, creating a community for networking, for connecting people that
Giovanni Di Liberto: mit Ctl and are more on the methodological side. And instead, other scientists that are more, you know they have maybe less confidence on the methods. And they want to connect with someone that has that expertise
Giovanni Di Liberto: on on doing more applied research.
Giovanni Di Liberto: And for students, of course. And that's this is the kind of resources I use also in my own lab. So every student, Phd student or master student that joins. I just tell them, okay, open the Csp website and download such and such data sets download these scripts and try to to learn from these 2.
Giovanni Di Liberto: We we have these new sections that we didn't have last year on lectures and tutorials from the from the various editions of the workshop. So you you find that 2023 here as well, and it is not just a repetition every year. Right? So, for example, last year we covered Cca. We won't cover it this year. So we don't need to repeat things that we have seen already, so that we leave space for new things.
Giovanni Di Liberto: So check out those things.
Giovanni Di Liberto: so what's new? So the first thing that is new this year and is the C and D format. So the continuous event neural data format.
Giovanni Di Liberto: It's a data structure that that we proposed for storing neural data.
Giovanni Di Liberto: and that is specific to continuous sensory tasks like listening to speech.
Giovanni Di Liberto: So it was, as I said, was a necessity. Because if we want to share standardized code, we had to find a way to agree on on some standardized data format.
Giovanni Di Liberto: And the idea is that if you save your data in this way, then you can run these scripts that we're sharing directly. and then it also enables the design of graphical user interfaces and that sort of stuff.
Giovanni Di Liberto: So C and D, this data format
Giovanni Di Liberto: somewhat after their raw data. So it's not your raw data. It's minimally pre-processed in a way that your stimulus features and your Eeg are aligned, and they are with the same sampling rate.
Giovanni Di Liberto: And so you can run Trfs and Cca. Or intercept the correlation more rapidly. And so you can. You have access in this case to see a space script.
Giovanni Di Liberto: But also we connected
Giovanni Di Liberto: this year. We connected this format with the work from, and Christian brought back, and Jonathan Simon and and Nima's lab
Giovanni Di Liberto: on these toolboxes that they design. So you can load Cnsb, sorry, C. And D
Giovanni Di Liberto: data files from their toolboxes now, and you can easily transition between bits and C and D. They are. They are connected, and we included all the functions for doing so.
Giovanni Di Liberto: But in reality this is not something complicated. It's it's just basically a guy guidance in terms of what is the folder structure you should use? Where should you put the code? Where should you put the tutorials? Sorry, the the code, for example.
Giovanni Di Liberto: where should you put the data sets, how should you call the file name? So if you follow these instructions, then basically it's it's just much easier to run the code we share
Giovanni Di Liberto: and and we share this on our github. See if you just go on. Our Github and the links are all on the on the website. I'll show them in a second. You have this folder structure with the example scripts. We have more tutorials throughout here.
Giovanni Di Liberto: The libraries are not ours. Some of these are ours, but others they're just dependencies that we use. And and then the data sets are empty.
Giovanni Di Liberto: You just need to go to the website, download the data set and put it into this folder structure. And then you can run the scripts.
Giovanni Di Liberto: We are setting up a new documentation page. It's a work in progress. But you can find you can already find some instructions on again, how to save your data in in this format, and so on.
Giovanni Di Liberto: So on the website, you have this on the resource page. You have all of these links, the Github, the documentation. and these other things. I'll show you in a second.
Giovanni Di Liberto: The data browser. So we one thing that we we built in the last year is a graphical user interface.
Giovanni Di Liberto: So just an interface like this.
Giovanni Di Liberto: which and is built in Matlab in this case, and wait for the next slide, because that's much cooler.
Giovanni Di Liberto: So the idea.
Giovanni Di Liberto: apart from the ugly looking interface, which is model of style, and this gives you an idea of the parameters that you need to decide when you when you fit these models.
Giovanni Di Liberto: And it gives you an easy access to to do so. So basically, what you can do is
Giovanni Di Liberto: and I'll let's see if I can pick it up here. Yeah. split it on top.
Giovanni Di Liberto: So this is just the the the gui in my in my computer. And you can open here and you have access to whatever data set you have on your computer. And they're all in the same format so you can switch and
Giovanni Di Liberto: it loads. And then it's going to give you the stimulus feature for that particular data set. And you can say, Oh, I want to fit the model on this number of participants on this amount of data per participant forward backward models.
Giovanni Di Liberto: And just for sake of time, I don't have time to run it now. But basically
Giovanni Di Liberto: you can run the usual trfs, get prediction correlations get trf weights.
Giovanni Di Liberto: But you can also compare different data sets. You can take your speech data, set your music datasets. You can plot them on top of each other. There is still work to do, but it's it's a starting point to to make things a bit a bit faster, a bit easier when we want to look at data that we have already.
Giovanni Di Liberto: you know, available without having to talk with the person that that actually share that data every time.
Giovanni Di Liberto: now, this is a proof of concept. We, it's a work in progress.
Giovanni Di Liberto: It is a web-based data browser.
Giovanni Di Liberto: So while the other one is a standalone application built in Matlab, you can just. You don't need to have Matlab. You just install it, but you still need to install it.
Giovanni Di Liberto: This thing is that is in your browser. So you just go under your browser. You type this link which I'll share on the chat in a second. and you can fit
Giovanni Di Liberto: forward your apps back back backward er apps, and so on, so encoding decoding models.
Giovanni Di Liberto: Why do I think this is useful. And again, lots of this stuff is done selfishly because because we use it.
Giovanni Di Liberto: And so it happened to me, for example, to talk with scientists that wanted to run a new experiment. And they were asking me.
Giovanni Di Liberto: Can I run this speech listening experiment, or this music listening experiment
Giovanni Di Liberto: with 5 min of data, because my particular population can't deal with experiments that are longer than 5 min.
Giovanni Di Liberto: And usually my answer is, I don't know. I need to open my Matlab and run some rerun, reanalyze some of my code.
Giovanni Di Liberto: So with interface, basically, you can go to some load some existing data and select how much data you want to.
Giovanni Di Liberto: You want to use and see basically for yourself, if that is a suitable amount of data for your experiment.
Giovanni Di Liberto: and much more.
Giovanni Di Liberto: So again. For the sake of time, I'll I'll
Giovanni Di Liberto: I'll cut it short. We describe lots of these new components in a paper that we just submitted to archive.
Giovanni Di Liberto: So the C and D data structure, the analysis pipeline resources. And we also include the simulation toolkit
Giovanni Di Liberto: where you can simulate Eeg data in different ways.
Giovanni Di Liberto: And I encourage using that because simulating
Giovanni Di Liberto: data can be really, really useful. especially when your hypothesis are not that clear? It's not clear what you would get from a Trf analysis.
Giovanni Di Liberto: So maybe before actually running an experiment, it can be quick and useful to to use these these functions.
Giovanni Di Liberto: Okay.
Giovanni Di Liberto: so just to conclude the call for project proposal so ambrain train, and which is one of the most interesting producers of
Giovanni Di Liberto: portable, eg. Systems. They have been supporting us with the scholarship last year, and and also this year it's €1,500. So what we encourage you to do is to propose a project and to write this proposal in 500 words.
Giovanni Di Liberto: you can decide to to say, Okay, I want to visit Giovanni's lab in in Dublin, or I want to visit Aaron's lab in Rochester, or Segosia, or Nottingham, Trent, or a Condom superior. You can visit any of these institutions in the list.
Giovanni Di Liberto: and that are related to the organizers, or you can propose some other visit to someone else as long as it makes sense with Cnsp. So as long as it has something to do with. You know the resources that we share, or something related to that.
Giovanni Di Liberto: or, anyway, something that is has an open science mindset.
Giovanni Di Liberto: So whatever data you deal with, we would encourage you to share it.
Giovanni Di Liberto: the call for proposal is on the website. You can find it here on the workshops. Page.
Giovanni Di Liberto: Okay, that's all from me. So yeah, right on time. I'm a bit late. Sorry.