Dr. Poppy Crum

And so that edge, that ability to get access to that information is phenomenal, I think.

And when you can tap into that, that becomes a very powerful thing.

So like probabilistic inference goes up when I've played 40 hours of Call of Duty.

But...

Then what I like to do is take it and say, okay, here's a training environment.

I had a couple of Stanford's top soccer players in my course this year and we got – our focus was, okay, what data do you not have and how can we build a closed-loop environment and make it something so that you're gaining better neurological –

access to your performance based on data like my acceleration, my velocity, not at the end of my two-hour practice, but in real time and getting auditory feedback so that I'm actually tapping into more neural training.

So we had

sensors, you know, like on their calves that were measuring acceleration velocity and able to give us feedback in real time as they were doing, you know, a sort of somewhat gamified training.

I don't want to use gamified.

It's overused.

But let's say...

It felt like fun environment, but it's also based on computation of that acceleration data and what their targets were.

It's feeding them different sonic cues so that they're building that resolution.

When I say resolution, what I mean is...

Especially as a novice, I can't tell the difference between whether I've accelerated successfully or not.

But if you give me more gradation in the feedback that I get with that sort of that closed-loop behavior, I start to – my neural representation of that is going to start differentiating more.

So with that, that's where the auditory feedback.

So they're getting that in real time.

And you build that kind of closed-loop environment that helps build that –