 Magic. Okay. I'm going to tell you about our platform. The platform is a research platform, although there are components that we are considering for development for business opportunities, some of them are much further along than others. What I'll try and do in the time that I have here is explain sort of the ground framework for the platform and then talk about the three avenues that we're pursuing in the business domain. The platform itself, it's open source completely. We actually had a workshop here over the last two days where we trained a bunch of energetic young students to use the platform for their own purposes. It's been developed over roughly 10 years as a research platform. We had funding from multiple governmental as well as foundation sources of around $50 million to put the platform forward. One of the challenges as well in terms of the commercialization development of this is also multinational platform. So to deal with the jurisdictions across the pond in terms of putting together term sheets and patent agreements and so on and so forth. But the platform itself, if you do get a hold of it, you'll notice it's actually I think quite well formed. And part of the reason for that is we did partner with the company in Germany to develop the platform in terms of industry standards to make sure that it had a decent amount of usability as well as curation of the software going forward. What you see in this slide is the workflow and the notion of the virtual brain is to try and make use of existing data to create simulations of a brain. You can do this level of entire population so you can mine large data sets or you can do it in the level of individuals and that's where the commercial opportunity comes in. This one here just shows you again the workflow you've got in the case of data that are existing you can get MRI data from almost anybody now quite easily both in terms of the person's own geometry in terms of their connections in the brain as well as in terms of the functions that are being instantiated and use that to form sort of the basis of a high level model so you can take their again geometry you can estimate their structural connectivity and then implement some maths to generate dynamics of local cell populations to generate functional data. You can stimulate the model itself as well and then generate data that you use then to fit the computation model back to the empirical data. The notion there is you're trying to infer some of the dynamics at the level of the cell populations that produced the data that you measured from the individual so your inferences are based on the biophysical parameters that produce the data as opposed to the data themselves. So that capacity has led to at least three different avenues. So I mentioned we can do this on a level of populations again the the idea for the commercial developments is really to focus on the fact that we can personalize this. We can do it across 500 individuals we can do it across one individual as well. So the first application which has probably been the most successful thus far is for using it in the context of pre-surgical planning and epilepsy that's being done in France primarily driven by Victor Yersa in Marseille I'll talk about that in a second. The second application is to use it for prognosis and diagnosis and stroke and dementia. We have a proper principle for that we're actually trying to build a business case for that through the Toronto chapter which I'm involved with and the last one is brain health monitoring using a similar sort of motivation that Graham talked about with the Muse platform to use portable devices to help monitor brain health and use it for entertainment platform that's actually been driven by Petra Ritter who's sitting in the back with her children right now. Hi Petra. Okay the epilepsy application this again is the pipeline this is being used as I said in the large clinical trial nationally being collected in France. The notion is to take the clinical data in this particular case you've got stereotaxic EEG data where you've got needle electrodes and that are implanted to measure the local field potentials from different parts of the brain. You also have the structural information that's then put into the virtual brain pipeline to construct their own avatar to incorporate the functional measures that are from the SEG and to degenerate the model for that for the individual person and the goal for the model is to help again support clinical decisions in terms of where is the likely source of the epilepsy itself, where is the propagation zone and use that to determine how you intervene with the patient. Do you excise the tissue, do you stimulate the tissue to try and alleviate the seizure and so on. So from that you get a fingerprint for the patient you get sort of a virtual chart that's then used to guide the intervention for the patient and that again is part of a clinical trial so it's quite exciting in terms of the potential outcome for the virtual brain. So that application would be more sort of providing a solution that could be used then on the clinic and this is all along the similar lines using it for the prognosis and diagnosis for different diseases in this particular case it's prognosis for recovery from stroke. This is an example of a brain that's had a stroke you can see the discoloration here which is actually not supposed to be there so if you have that in your brain go see somebody. You can take this brain put it in again to the computational modeling framework and look at what the dynamics that are there that are generated by that particular individual and again make the inferences about the capacity of that person's brain to generate dynamics and see how that relates to their clinical indications at that point in time. What we found was that across about 40 stroke subjects that the parameters that are estimated actually predicted how well they would recover to rehab both initially as well as one year after rehab so how well they responded and saved the rehab outcomes. So obviously we're following that up to get more evidence that that's in fact a good prognosis for therapeutic outcome. And there is an example of a similar application to use to differentiate cognitive dysfunction going from healthy aging to MCI to dementia using a very similar modeling platform. The publication is listed at the bottom of the slide there. In the last application it's called brain modes again Petra Ritter's been driving that one and the notion there is again focusing on the fact that we can individualize the data and make customized models for individuals so the idea there is to create your own virtual brain and use that interface with for example the EG headset that Graham was talking about or other similar platforms to drive the data into your model and use that for a neurofeedback platform using that for brain health but also using that in the case of entertainment so we can use it actually for a gaming platform as well. This one's had some seed funding is actually moving along at a slow pace but it's actually moving nevertheless. So all of these these are examples of of business forays if you will to try and help develop the virtual brains that can be used for its initial purpose to actually help diagnose some clinical conditions but there's also other aspects which have come into play like brain modes that weren't initially part of the plan but sort of came about as we started talking with industry partners started thinking about how can we use this application talking to artists for example as well and they're saying how cool is this can you actually think about ways you can interface the graphics we get from the brain data themselves into something that's actually enticing for the user and that's how we developed the brain modes application. So we're not even close yet because you're having revenue we're sort of pie in the sky but it's fun but it takes a lot of time for sure and there's always challenges along the way in terms of SMEs and so on which you all quite well know. So with that I will just acknowledge the main people on the project just Petra in the back there Victor and France Anna Salotkin has been involved in the stroke and dementia part and me who's the maestro I guess of the project so thank you for that.