Bliss Chapman

Yeah, so there are three major components to the technology that we're building. One is the device, the thing that's actually recording these neural chatters. We call it N1 implant or the link. We have a surgical robot that's actually doing an implantation of these tiny, tiny wires that we call threads that are smaller than human hair.

Yeah, so there are three major components to the technology that we're building. One is the device, the thing that's actually recording these neural chatters. We call it N1 implant or the link. We have a surgical robot that's actually doing an implantation of these tiny, tiny wires that we call threads that are smaller than human hair.

Yeah, so there are three major components to the technology that we're building. One is the device, the thing that's actually recording these neural chatters. We call it N1 implant or the link. We have a surgical robot that's actually doing an implantation of these tiny, tiny wires that we call threads that are smaller than human hair.

And once everything is surgeries, you have these neural signals, these spiking neurons that are coming out of the brain, and you need to have some sort of software to decode what the users intend to do with that. So there's what's called a Neuralink application or B1 app that's doing that translation.

And once everything is surgeries, you have these neural signals, these spiking neurons that are coming out of the brain, and you need to have some sort of software to decode what the users intend to do with that. So there's what's called a Neuralink application or B1 app that's doing that translation.

And once everything is surgeries, you have these neural signals, these spiking neurons that are coming out of the brain, and you need to have some sort of software to decode what the users intend to do with that. So there's what's called a Neuralink application or B1 app that's doing that translation.

It's running the very, very simple machine learning model that decodes these inputs that are neural signals and then convert it to a set of outputs that allows our participant, first participant, Nolan, to be able to control a cursor. And this is done wirelessly. And this is done wirelessly. So our implant is actually a two-part.

It's running the very, very simple machine learning model that decodes these inputs that are neural signals and then convert it to a set of outputs that allows our participant, first participant, Nolan, to be able to control a cursor. And this is done wirelessly. And this is done wirelessly. So our implant is actually a two-part.

It's running the very, very simple machine learning model that decodes these inputs that are neural signals and then convert it to a set of outputs that allows our participant, first participant, Nolan, to be able to control a cursor. And this is done wirelessly. And this is done wirelessly. So our implant is actually a two-part.

The link has these flexible tiny wires called threads that have multiple electrodes along its length. And they're only inserted into the cortical layer, which is about three to five millimeters in a human brain. In the motor cortex region, that's where the intention for movement lies in.

The link has these flexible tiny wires called threads that have multiple electrodes along its length. And they're only inserted into the cortical layer, which is about three to five millimeters in a human brain. In the motor cortex region, that's where the intention for movement lies in.

The link has these flexible tiny wires called threads that have multiple electrodes along its length. And they're only inserted into the cortical layer, which is about three to five millimeters in a human brain. In the motor cortex region, that's where the intention for movement lies in.

And we have 64 of these threads, each thread having 16 electrodes along the span of three to four millimeters, separated by 200 microns. So you can actually record along the depth of the insertion. And based on that signal, there's custom integrated circuit or ASIC that we built that amplifies the neural signals that you're recording and then digitizing it.

And we have 64 of these threads, each thread having 16 electrodes along the span of three to four millimeters, separated by 200 microns. So you can actually record along the depth of the insertion. And based on that signal, there's custom integrated circuit or ASIC that we built that amplifies the neural signals that you're recording and then digitizing it.

And we have 64 of these threads, each thread having 16 electrodes along the span of three to four millimeters, separated by 200 microns. So you can actually record along the depth of the insertion. And based on that signal, there's custom integrated circuit or ASIC that we built that amplifies the neural signals that you're recording and then digitizing it.

And then has some mechanism for detecting whether there was an interesting event that is a spiking event. and decide to send that or not send that through Bluetooth to an external device, whether it's a phone or a computer that's running this Neuralink application.

And then has some mechanism for detecting whether there was an interesting event that is a spiking event. and decide to send that or not send that through Bluetooth to an external device, whether it's a phone or a computer that's running this Neuralink application.

And then has some mechanism for detecting whether there was an interesting event that is a spiking event. and decide to send that or not send that through Bluetooth to an external device, whether it's a phone or a computer that's running this Neuralink application.

Yeah. So it does the signal processing to kind of really compress the amount of signal that you're recording. So we have a total of thousand electrodes, um, sampling at, uh, you know, just under 20 kilohertz with 10 bit each. So, uh, that's 200 megabits, um, that's coming through to the chip, uh, from thousand, uh, channel simultaneous, uh, neural recording. And that's quite a bit of data.

Yeah. So it does the signal processing to kind of really compress the amount of signal that you're recording. So we have a total of thousand electrodes, um, sampling at, uh, you know, just under 20 kilohertz with 10 bit each. So, uh, that's 200 megabits, um, that's coming through to the chip, uh, from thousand, uh, channel simultaneous, uh, neural recording. And that's quite a bit of data.