So hello everyone, this is the recording for the next practical class.

So we just had a look at neural interfaces and I hope you had also looked at the papers

and you realized that by studying the neural patterns we can predict behavior in a very

accurate way and this can be done on multiple levels of the nervous system.

So now we will look at this practical class and in this practical class, in this exercise

class, we will look how to analyze motor unit spike trains.

So something that you have to always remember that you have when you have volatilon of neurons

either in the spinal cord or in the brain or in different neural structures that generate

an action potential.

So the motor neurons respond with an all or none response.

Every time that we looked at that, we looked already this in the physiological lectures

that when you have a current in motor neuron somas and this reaches a threshold, the motor

neuron will find an action potential.

And this generates a behavior in another target neuron or for example in the muscle fiber

which will generate movement.

So if we look at the neurons, we have an interface with the function.

But in the brain we have millions, we have billions of neurons.

So you have to understand that this is a very complex problem.

But now we will look how to use these neurons and these are basically the motor unit action

potential recorded from the muscle and how to use them to perform a very simple mathematical

operation which is finding the average discharge rate but from the cumulative spike trains

of the active neurons.

So we are looking at what is the muscle receiving from an average.

So have a look, this is always the introduction, but the task number one.

So in the task number one you are given EMG motor unit pulses and sampling frequencies.

That this corresponds to the EMG data and the motor unit pulses and sampling.

So motor unit pulses is a cell array.

So motor unit pulses, and let's have a look here, for example motor unit pulses, this

is a cell array.

Each of these cells correspond to one neuron.

This is a motor unit action potential.

It's a spinal motor neuron.

But let's call it a neuron.

It is to also make it easier.

So if we call motor unit pulses number one, so this is the time sample of when this neuron

is active.

So if we call the first one, this neuron was active at this time sample.

If we divide this, we obtain in second when this neuron was active.

This neuron was active at 9.3.

Then it was active again at 9.51.

So we have 20 millisecond difference between these two firing.

So sorry, 200 millisecond difference.

So now we have, you are given this variable, but you also are given the EMG.

As before, you have an EMG array.

And wait, let me open it somewhere.

So in this case, I will just open a file that will be easier for you to understand.

I thought this had everything, but actually it didn't.

So one second.

There we go.

So we just open one like that here.