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as a bit of echo?

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Well, well, Mutaz talk about. Yes.

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Well, well, Mutaz talk about. Yes.

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Thank you so much for giving me
this opportunity.

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For me, it feels really, really special
to be back in in Madrid.

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I'm really sorry I have to do this
in English.

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After ideas in the UK,
I've got used to giving talks in English.

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I think if I did it in Spanish
it would be a complete disaster.

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And starting from,
how do you say, optically

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pumped magnetometers in Spanish,
I have no idea.

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And so, yeah,
just do you I'm going to give you

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a bit of introduction
of what Meg magnesium.

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So photography is used for

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and also
the limitations and why we're doing this.

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These, these work.

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Then I'll introduce the,
the optics, the optical upon

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magnetometers,
the sensors that we're using,

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and then I'll go on to talk
about the journey

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of the technology
showing some demonstrations

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and then finishing with the system
how it looks now.

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So a bit of an introduction

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to the neural neuroimaging neuroscience

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field.

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As you probably know,
there are many neurological mental

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health conditions, so I'm just going to go
through a few of these.

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For example, epilepsy.

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Around 60 million people
worldwide suffer from this,

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which is a very debilitating disorder.

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Also, one in 100 people suffers
from schizophrenia.

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One person
every 95 seconds is admitted to hospital

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after having had a concussion.

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One in four people will suffer
a mental health disorder at some point.

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Also, Alzheimer's.

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In an aging population,
dementia is growing markedly and we don't

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really know what the underlying mechanisms
are happening in the brain.

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And the same happens.

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We know relatively little
what happens in the brain

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from the moment
we are born to going through

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childhood and adulthood.

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So sometimes the techniques

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that we have available to study
some of these conditions

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like MRI or Medigap,

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we are looking
at the structure of the brain,

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but sometimes the structure
looks completely

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healthy.

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But we need new ways
of assessing the function of the brain.

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So looking at the brain activity

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and one of these techniques is to make
magnets is for photography.

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So the name means magnetars.

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So magnetic fields measured from that
come from the head.

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So like any other electrical current
that produces magnetic field, our brains

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and the neurons in the brain produce
current electrical currents,

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and we can pick up the magnetic fields
that they create.

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So the systems look a bit like this

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so we can get a map of magnetic fields

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on the scalp outside the head,

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and then we can reconstruct these
magnetic fields that we have

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outside the

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heads, doing some mathematical
modeling on source localization.

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We can then get the current
that is has produced those magnetic fields

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so we can get these images
of current density

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and we can overlay it
onto a magnetic resonance image

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to to look at this activity whilst

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the participants perform a task.

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So some examples of how

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Meg can help us understand
more about the brain.

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So it has really good spatial resolution.

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This is an example of a paper
from a few years back

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where subjects were asked to

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to move their index index finger
on their little finger.

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And we know that these regions
in the brain, in the motor

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cortex, are separated by very,
very small distances.

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And Meg can pick up these differences.

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Also clinically, Maggie's

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were used worldwide for epilepsy.

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It is used to localize the abnormal part

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of the brain where the epileptic seizures
are coming from,

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and then surgeons can base these there.

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The resection of the part of the brain,

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they can based it on the on
the MEG results.

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So it's been shown in a paper
on a thousand patients that the outcome

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of having how to make a scan
before the surgery is it

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it gives it gives higher chance of seizure

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freedom in the future

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also in a mental health

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field.

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There's also this is an example
of some work done in Nottingham

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a few years back looking at schizophrenia
and comparing it.

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A group of patients with schizophrenia
compared with healthy subjects.

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So here on the right there, it's a plot
that we normally look at in Meg where

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we have frequency on the vertical axis
and time on the, on the horizontal axis.

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And this is a very simple task.

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We just ask people to move their finger
for 2 seconds and then stop

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and we see a decrease in the activity
during that movement of the finger

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and then followed by an increase over
baseline, then going back to baseline.

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And if we compare with the patients
with schizophrenia,

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we already can see
some qualitatively changes.

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Like if I go back that increase

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followed
by the cessation of movement is decrease.

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So we can already start
to pick up differences in some patients

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groups.

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But Meg has problems and that's why
I'm giving this talk, I guess.

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So the magnetic fields that we're
measuring, they're really, really small.

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This is

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sort of a scale of magnetic fields
that we have out there.

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So an MRI scanner is a few Tesla.

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We're comparing it to a billion times
smaller than the Earth's field,

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which is what the field
we're sitting in now.

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So measuring

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the max signal is really, really tricky.

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And we need to do this inside
a magnetically shielded room.

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So max systems are housed in these rooms

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to attenuate external interference
from the earth,

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but also other interference
like cars and computers and everything.

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You have it around us.

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The hardware,

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the sensors that are used in Meg
are called Squid's superconducting quantum

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interference devices, and they're really,
really sensitive to magnetic fields.

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So you have around three FEM to Tesla.

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So we're in the region
of measuring brain fields

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and we have

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so conventional systems,
the ones that we have

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there's here in Murray very
there are hundreds of these squids

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and that are placed inside this big dewar

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that has liquid helium inside
because there are superconducting sensors

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and this is the adult version
and this is a baby

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version as well.

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So squids, they're really sensitive.

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They can pick up the magnetic fields
from the brain with high accuracy.

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They are they have high bandwidth,
whole head culverts.

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These systems have have been around
for four decades now.

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They're well-characterized.

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They're the the occurrence
of these systems is that the distance

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from the sensitive sensor to the to
the head

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is is quite large.

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They are fixed in in location.

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They have to be inside the Dewar
and they need cryogenic cooling.

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So this translates into low signal
to noise ratio

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because the fields that we're measuring
are really small and we're quite far

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the fixed sensor location
means it's a one size fits all.

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You might have the adult version,
the baby version, but

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it means that the brain

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to sensor distance is going to be bigger
for children, for babies,

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if using the same system
also means that you need to keep still.

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So that's quite challenging for scanning
kids or adults with movement disorders.

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And also the cryogenic cooling

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means there are high running costs
associated with it.

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So this brings us to talk about
optical power,

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magnetometer is

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a few maybe about ten years ago,

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advances in the quantum technologies.

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So a rapid development in these sensors

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and they started to compete against squid

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to measure magnetic fields,

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very coming of shapes and sizes.

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These are from these fan groups

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in the U.S.

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But it was really the militarization
of the sensors that

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made the MEG community to get excited
for these new type of sensors.

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So these are some examples of the groups
around the world

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developing different versions
of of the sensors.

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And also some companies
started to do to join the

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the efforts of

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making these sensors
also commercially available.

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So very briefly
their work in principle of an OPM,

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we have a photodetector
a glass cell with some

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alkali atoms
inside a vapor of atoms and a laser.

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So when there's no and when there's
no magnetic field of laser,

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the the atomic spins of these atoms
are all randomized.

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Then we shine a laser.

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This is the the pumping, the works of
the optical pump magnetometer.

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So we pump the atoms.

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So that means that all the atomic spends
align with the laser.

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So at the photodetector,
we measure the highest.

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So it goes through the glass cell
and we see the highest

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transmission of the laser.

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What happens when we have a magnetic
field, like, for example,

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the brain near the sensor,
the atomic spins are going to change

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and this is going to translate

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into a change in the laser
light picked up by the photodetector.

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So by looking at the change in light,
we can also know

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what the magnetic field
caused This change.

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So comparing with hopes, the sensitivity
really depends on the size of OPM's on

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their attack showed many different groups
developing them.

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But he's getting very competitive,
very similar to squids.

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The bandwidth is a bit more limited,
but enough

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for measuring magnetic pressure
on the brain.

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The number of channels is increasing
quite rapidly

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and multichannel
systems are being characterized.

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The good thing is that these sensors
reduce the distance to the scalp.

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They are flexible
so we can put them anywhere

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we are not limited by the viewer,

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They're not kept inside any anything
and we don't depend on liquid helium.

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So this brings me to

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talk about the the journey of the work
that we did during my Ph.D.

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in in Nottingham.

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And the vision back then

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was can we turn these big, heavy,

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ugly machine expensive
into something that we can wear?

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We can put sensors on a helmet
more similar, like an EEG,

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like a electro and photography

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device.

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So we started doing some simulations
which basically men can we bring these?

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If we bring the sensors
closer to the scalp,

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we're going to get higher signal.

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We're going to wear closer.

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So we were going to pick up more signal.

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And that overall

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meant that we get a theoretical advantage
of a55 times

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more signal just by putting the sensors
sensors closer to the head.

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It was later in 2017 when we did our first

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one channel
recording with a sensor four from Houston.

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And these

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think Brian knows
this is Gareth Barnes from UCL

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and we made this helmet for for him
based on, on an MRI.

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So we knew where the sensors
where in respect to so his brain

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and we proved experimentally
that it was about four times higher.

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So agreeing with the simulations in blue,

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you see the LPM signal and in in red
you see the squid signal multiply

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by four is about four times
higher for the OPM.

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And then he was later
adding some hardware to the to the system

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that we did
our first wearable OPM recordings.

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The problems
is that so as you saw in this photo here,

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we had the subject clamped on to the bed.

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So it was not very comfortable
and it really defeats

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the point of flexibility of OPM.

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So we wanted to have people
with the sensors free to move their head.

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But if we actually if we move the sensors
like is shown

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in this video,
I just go and take a drink the

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the signal of the OPM's satellites
and we we don't get

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we don't get we cannot use that data

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because we've exceeded the dynamic range
of the sensors, which is quite limited.

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So we need to provide a better

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magnetic field environment
within our room.

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So this is when my colleague

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now home joined and he

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he designed these spy plane

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00:14:18,320 --> 00:14:21,000
coils that you can see these photo there

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originally that were made to fit around
an existing cryogenic mech.

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But Niall designed these
by applying coils to

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to create ascension here.

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So to create the magnetic
fields needed to compensate

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for the remnant field in the room.

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Actually, these designs are adapted
from MRI methods.

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And actually so Peter
Mansfield's work in the building

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00:14:46,880 --> 00:14:50,200
that we take his name in Nottingham

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is based on some of the developments,
some of the legacy

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00:14:54,520 --> 00:14:56,160
of these these work for MRI.

249
00:14:57,640 --> 00:14:59,800
So thanks to those coils,

250
00:14:59,800 --> 00:15:02,720
we can reduce the magnetic field
inside the room to.

251
00:15:02,880 --> 00:15:08,280
So it was around 30 so monitors
and then we go to pick a Tesla.

252
00:15:08,280 --> 00:15:10,240
So much, much smaller.

253
00:15:10,240 --> 00:15:13,520
This allows the sensors to keep working
even when the subject moves.

254
00:15:13,520 --> 00:15:16,720
So here you can see a video

255
00:15:17,640 --> 00:15:21,920
of me
putting a ping pong ball on a on a bat.

256
00:15:21,920 --> 00:15:25,760
And we can see that
the head is completely unrestricted

257
00:15:25,760 --> 00:15:27,440
where there's a bit of movement.

258
00:15:27,440 --> 00:15:30,600
But still we can see we can get really

259
00:15:32,160 --> 00:15:35,080
high fidelity data
even though we have the head moving.

260
00:15:35,080 --> 00:15:38,760
So reconstructing to the motor
area of the brain

261
00:15:39,680 --> 00:15:41,800
and then batting the ball for 10 seconds,
we see that

262
00:15:42,040 --> 00:15:45,680
decreasing amplitude
followed by an increase.

263
00:15:45,680 --> 00:15:49,960
As I show to in the the other light.

264
00:15:49,960 --> 00:15:51,160
So this was all very exciting.

265
00:15:51,160 --> 00:15:55,720
And after that we started
exploring all the ways of of doing magic.

266
00:15:55,720 --> 00:15:59,560
So before scanning children below

267
00:15:59,560 --> 00:16:05,000
the age of eight was really tricky
because they don't, they don't keep still.

268
00:16:05,360 --> 00:16:08,840
So we did our first pediatric experiment

269
00:16:08,840 --> 00:16:14,480
without the two brothers, a two year old
and a five year old with a modified helmet

270
00:16:14,480 --> 00:16:17,760
that we bought on Amazon
and just put some sensors.

271
00:16:17,760 --> 00:16:19,520
And we did.

272
00:16:19,520 --> 00:16:21,720
We got really good results.

273
00:16:21,720 --> 00:16:24,240
This was just a sensory task with a mum,

274
00:16:24,240 --> 00:16:28,720
the mother stroke
the hand of the of the kid and we see that

275
00:16:28,720 --> 00:16:32,560
changing in, in activity
in that sensory part.

276
00:16:34,320 --> 00:16:35,160
And then we wanted to

277
00:16:35,160 --> 00:16:39,120
play a bit with virtual reality
because now we, we allow people

278
00:16:39,120 --> 00:16:42,160
to move their head
than can we immerse them into a

279
00:16:42,960 --> 00:16:45,360
Yeah, a virtual

280
00:16:46,120 --> 00:16:48,440
virtual reality environment.

281
00:16:48,440 --> 00:16:52,600
This was really tricky, but nevertheless
we managed to get some good data

282
00:16:53,560 --> 00:16:56,960
using this headset

283
00:16:57,080 --> 00:17:01,320
and then luckily
the sensors became much smaller.

284
00:17:01,320 --> 00:17:02,080
So this is that.

285
00:17:02,080 --> 00:17:05,640
So the second generation of sensors
are just as the size of a

286
00:17:06,200 --> 00:17:08,880
of a Lego level piece.

287
00:17:10,000 --> 00:17:11,920
So we started in 2019,

288
00:17:11,920 --> 00:17:15,000
the first experiments
with this second generation.

289
00:17:15,000 --> 00:17:18,000
One of the first things we did
was to compare it with EEG

290
00:17:18,200 --> 00:17:21,760
because these might be of interest
in some clinical

291
00:17:23,560 --> 00:17:24,920
work, perhaps.

292
00:17:24,920 --> 00:17:25,720
So we did.

293
00:17:25,720 --> 00:17:30,840
We had an EEG cap
and then placed to ops on top

294
00:17:31,520 --> 00:17:34,280
and perform the same the same task we

295
00:17:34,600 --> 00:17:38,840
we put the sensors on the
the optimal place to get the, the,

296
00:17:38,840 --> 00:17:41,760
the motor response
that we were going to do.

297
00:17:42,080 --> 00:17:43,040
And we got really

298
00:17:44,120 --> 00:17:47,800
similar data across EEG and on OPM.

299
00:17:49,160 --> 00:17:52,320
However, we saw that when moving.

300
00:17:52,400 --> 00:17:54,440
So if you have a subject moving

301
00:17:54,440 --> 00:17:59,160
the EEGs much more susceptible
to to muscle artifacts,

302
00:17:59,160 --> 00:18:07,040
also the cup might be moving
and the the data that we have them,

303
00:18:07,440 --> 00:18:10,920
the sun electrodes moving on the head,
that also degrades the data.

304
00:18:11,120 --> 00:18:14,080
So we saw that
he was about ten times worse than

305
00:18:15,200 --> 00:18:17,720
when using the ops

306
00:18:19,040 --> 00:18:21,680
and then that by the end of

307
00:18:21,800 --> 00:18:25,240
so towards the end of the year,
we had a 50 channel

308
00:18:25,800 --> 00:18:29,720
50 sensor system.

309
00:18:29,720 --> 00:18:33,160
So I'll I'll show you
some of the demonstration

310
00:18:33,160 --> 00:18:35,920
with this multichannel,

311
00:18:36,320 --> 00:18:37,280
multichannel system.

312
00:18:37,280 --> 00:18:39,560
So this is an old photo now

313
00:18:41,000 --> 00:18:43,520
we moved, so we got a bit of funding,

314
00:18:43,520 --> 00:18:48,640
so we moved to a new room
which is dedicated to open mics.

315
00:18:48,640 --> 00:18:51,760
So the room that we were in before
where we had a

316
00:18:51,920 --> 00:18:55,640
a CTF system,
one of the cryogenic companies

317
00:18:56,400 --> 00:18:59,520
there, the field there was 30 Nano Tesla,

318
00:18:59,520 --> 00:19:02,760
so quite large for the ops to, to operate

319
00:19:04,160 --> 00:19:07,160
these rooms that are manufactured
by magnetic shields.

320
00:19:07,160 --> 00:19:10,400
A company in in England they

321
00:19:10,640 --> 00:19:13,160
they started working on making these rooms

322
00:19:13,880 --> 00:19:17,520
with lower magnetic background field.

323
00:19:17,520 --> 00:19:21,000
So we're able to to to use the census

324
00:19:22,120 --> 00:19:25,200
which we start with the census
a much better place.

325
00:19:25,440 --> 00:19:26,400
We still have these.

326
00:19:26,400 --> 00:19:30,520
So you can see here
a newer version of the biplane

327
00:19:30,520 --> 00:19:33,560
A coils that you can see
in that photo there on the back.

328
00:19:34,960 --> 00:19:39,320
We also have gone through
a few iterations of helmets, so we started

329
00:19:39,320 --> 00:19:45,520
with these subject specific ones
and based on MRIs from the participants,

330
00:19:46,200 --> 00:19:50,880
then we went through a bike helmet,
something that kids could wear and

331
00:19:51,320 --> 00:19:57,920
flexible caps and then more 3D printed,
but now generic that more people can use.

332
00:19:57,920 --> 00:20:00,920
And later on I will talk more about this.

333
00:20:00,920 --> 00:20:02,320
But with Serco, we've been

334
00:20:03,560 --> 00:20:04,400
making these

335
00:20:04,400 --> 00:20:06,640
generic helmets that are lightweight,

336
00:20:08,440 --> 00:20:11,320
so we them multichannel systems.

337
00:20:11,320 --> 00:20:13,880
So we have 50 now sensors.

338
00:20:14,640 --> 00:20:17,920
We we did comparison
one with the cryogenic,

339
00:20:17,920 --> 00:20:21,840
which has about 300 sensors,
but nevertheless we found that.

340
00:20:21,840 --> 00:20:26,080
So this is we scanned the subjects
six times in each of these.

341
00:20:26,080 --> 00:20:28,800
So we've created helmet
with a flexible helmet

342
00:20:28,800 --> 00:20:32,360
and then in the cryogenic
and during a very simple task,

343
00:20:32,880 --> 00:20:37,280
a visual multitask, we see the visual
response and the motor response.

344
00:20:37,760 --> 00:20:40,160
And very
so these are all the different runs,

345
00:20:40,960 --> 00:20:43,720
very repeatable results.

346
00:20:43,720 --> 00:20:48,000
And also in terms of of in our comparing
50 sensors ops

347
00:20:48,320 --> 00:20:51,080
with 300 cryogenic sensors

348
00:20:52,160 --> 00:20:55,040
and then also use this data
to look at conductivity.

349
00:20:55,040 --> 00:20:59,080
So it's so quiet,
I would say hot topic in Meg to,

350
00:20:59,160 --> 00:21:02,600
to look at connections
across the whole brain

351
00:21:04,400 --> 00:21:07,040
and in the different frequency bands
and different regions.

352
00:21:07,040 --> 00:21:10,440
So we got very similar results

353
00:21:10,880 --> 00:21:14,720
comparing the OPM
to the Cryogenic as well.

354
00:21:14,720 --> 00:21:17,600
And also it was here,
it's probably easy to see

355
00:21:18,320 --> 00:21:20,520
we could pick up also subject differences.

356
00:21:20,520 --> 00:21:23,200
So two subjects were scanned
multiple times and

357
00:21:23,760 --> 00:21:29,080
this is the connectivity that the OPM
system is picking up for both subjects.

358
00:21:29,080 --> 00:21:32,840
And this is the cryogenic and both OPM
and cryogenic pick up differences

359
00:21:33,360 --> 00:21:35,840
in the same region of the brain

360
00:21:35,840 --> 00:21:39,480
for both subjects.

361
00:21:39,600 --> 00:21:43,040
Then we've been also doing
all the types of experiments.

362
00:21:43,040 --> 00:21:47,480
So Motorola and and this is something
that my colleague Ryan Heil is working on.

363
00:21:48,680 --> 00:21:52,120
So paradigms
that we cannot do in a conventional.

364
00:21:52,400 --> 00:21:56,200
Meg, if I go back,
you can play that video that requires

365
00:21:56,200 --> 00:22:00,320
a very large head movement
to be able to to look at the instrument

366
00:22:01,520 --> 00:22:04,400
and play
it, and we can get this once again.

367
00:22:04,760 --> 00:22:09,320
He scanned a few subjects multiple times,
I think every day for a week,

368
00:22:09,680 --> 00:22:14,200
and we get really, really good data
repeatable results,

369
00:22:14,200 --> 00:22:19,160
even though we are making
very large movements.

370
00:22:19,160 --> 00:22:24,640
Then something more exciting now on
this is quite new.

371
00:22:24,640 --> 00:22:26,360
Nigel Holmes.

372
00:22:26,360 --> 00:22:29,720
He's been developing
new types of of coil systems.

373
00:22:29,720 --> 00:22:33,280
So the ones that you showed
a biplane across which can be seen here

374
00:22:34,240 --> 00:22:35,640
at the back that I'll show you.

375
00:22:35,640 --> 00:22:39,680
I think there's another photo later on
but he's been working on different

376
00:22:40,000 --> 00:22:44,480
types of coils
that can tune can bring the field down

377
00:22:45,560 --> 00:22:48,120
following a subject as they move.

378
00:22:48,120 --> 00:22:51,800
So in here he's moving
randomly, sitting down and turning around

379
00:22:52,200 --> 00:22:55,160
whilst he's pressing buttons and still

380
00:22:56,240 --> 00:22:58,520
he can get

381
00:22:58,520 --> 00:23:03,040
decent data
even though he's moving around the room.

382
00:23:03,040 --> 00:23:08,360
But you can pick up these changes
in the brain.

383
00:23:08,360 --> 00:23:11,480
And again, we had to do it this time.

384
00:23:11,480 --> 00:23:14,160
Not just me, but playing against my boss.

385
00:23:14,200 --> 00:23:17,240
Matt We played ping pong the two of us,

386
00:23:17,240 --> 00:23:20,520
and here you can see these coils
that I was talking about.

387
00:23:20,720 --> 00:23:23,640
So these new coils

388
00:23:23,640 --> 00:23:27,560
can noodle
the field in two different regions.

389
00:23:27,560 --> 00:23:31,920
So where the two heads are allowing
for these movements of the head

390
00:23:33,200 --> 00:23:35,480
and we get really good also.

391
00:23:35,640 --> 00:23:40,120
And data in the motor region whilst both

392
00:23:41,000 --> 00:23:45,560
both participants are playing ping pong,

393
00:23:45,560 --> 00:23:49,800
this is some work using the same sensors
that we use from Q spin.

394
00:23:49,800 --> 00:23:54,160
This is from Brussels
and from the group of Xavier

395
00:23:54,440 --> 00:23:57,200
where they've recently published a paper

396
00:23:57,200 --> 00:24:02,120
where they actually measured
epileptic seizures

397
00:24:02,640 --> 00:24:05,120
with the OPS, which is really exciting

398
00:24:05,520 --> 00:24:09,960
and really exciting finding
that it hadn't been done previously.

399
00:24:10,280 --> 00:24:13,840
And so this is another application of ops

400
00:24:15,080 --> 00:24:18,080
and also the flexibility of opens gives us

401
00:24:18,800 --> 00:24:21,360
not only ways
of measuring the brain activity,

402
00:24:21,360 --> 00:24:25,440
but now we can start to think of
measuring the

403
00:24:25,640 --> 00:24:29,880
the world, the human heart
or the, the, the fetus heart.

404
00:24:31,000 --> 00:24:34,640
Hopefully the brain,
the fetus brain as well.

405
00:24:34,640 --> 00:24:40,160
So we've done preliminarily
some experiments where we've picked up the

406
00:24:40,640 --> 00:24:44,360
the maternal heart on the fetal heart
with open arms by placing them

407
00:24:45,240 --> 00:24:47,840
on the on the belly.

408
00:24:47,840 --> 00:24:51,720
But yep, this shows that opens gives
you also different

409
00:24:52,400 --> 00:24:54,800
different ways of measuring by magnetism

410
00:24:54,800 --> 00:24:58,360
from the from the body.

411
00:24:58,360 --> 00:25:02,120
I mean this is a bit of a new

412
00:25:02,760 --> 00:25:05,200
so we
I show you the first generation of sensors

413
00:25:05,200 --> 00:25:09,440
that they were quite large
and we then got the second generation.

414
00:25:09,440 --> 00:25:12,800
This will be
the third generation of sensors.

415
00:25:12,800 --> 00:25:16,240
So now before we had what

416
00:25:16,240 --> 00:25:19,520
we call dual axes because we can measure
the feeling to direction.

417
00:25:19,520 --> 00:25:23,360
So we place it plays
the sensors on the head, so we get a radio

418
00:25:23,720 --> 00:25:26,040
and a tangential component of the field.

419
00:25:26,040 --> 00:25:28,040
Now we have try actual sensors.

420
00:25:28,040 --> 00:25:29,840
So there's another.

421
00:25:29,840 --> 00:25:33,160
So the laser that's in
the sensors is split and you can

422
00:25:34,840 --> 00:25:36,160
you can pick up

423
00:25:36,160 --> 00:25:39,440
and you can measure the
the other component of the magnetic field.

424
00:25:39,920 --> 00:25:41,160
And this

425
00:25:41,640 --> 00:25:45,760
in a paper by a few years,
couple of years ago showed that

426
00:25:45,920 --> 00:25:50,000
these can help
with rejecting interference better

427
00:25:50,000 --> 00:25:52,280
because you have more information of what
the fields

428
00:25:53,280 --> 00:25:55,360
look like also gives

429
00:25:55,360 --> 00:25:59,760
more uniform coverage
so more homogeneous sensitivity,

430
00:25:59,760 --> 00:26:04,640
especially in case I'll show you
in the slide in a moment, and also gives

431
00:26:04,640 --> 00:26:08,280
more signal because you have, again,
more information of the fields.

432
00:26:09,480 --> 00:26:13,000
So this is the
the theoretical advantages of traversal.

433
00:26:13,040 --> 00:26:15,320
So in the middle
here is the radial sensors.

434
00:26:15,320 --> 00:26:20,000
This is what all the experiments that I
have shown you with the previous sensors.

435
00:26:20,880 --> 00:26:24,480
So this is for an adult and then for a
two, four year old and a two year old.

436
00:26:24,480 --> 00:26:28,400
And you can see that the pattern,
the sensitivity profile

437
00:26:28,400 --> 00:26:31,920
starts
to get quite patchy, but we use its actual

438
00:26:33,080 --> 00:26:34,560
array of sensors.

439
00:26:34,560 --> 00:26:37,360
The it gets more homogeneous,
so we're picking up

440
00:26:37,360 --> 00:26:39,440
more signal from the brain.

441
00:26:41,240 --> 00:26:44,280
And we've done
a few experiments of these Dirac shows

442
00:26:44,520 --> 00:26:47,960
just to check that
we're still getting a really good data

443
00:26:48,680 --> 00:26:52,520
and this is some work from last year
we can actually we can pick up.

444
00:26:53,120 --> 00:26:56,240
These are a single trial responses,

445
00:26:56,240 --> 00:26:59,200
so really good sensitivity
from these fractures.

446
00:26:59,400 --> 00:27:04,160
And we can now get a 3D visualization
of the field that we couldn't do before

447
00:27:04,160 --> 00:27:06,360
because we didn't
have that extra component.

448
00:27:08,040 --> 00:27:10,760
So we the tracks are open
now that we have in Nottingham.

449
00:27:10,760 --> 00:27:13,600
We've been doing more

450
00:27:13,640 --> 00:27:16,720
new tasks
that require large head movements.

451
00:27:16,720 --> 00:27:20,160
So this is the work
that Mollie Wray has done

452
00:27:21,200 --> 00:27:23,200
with a 90 channel array

453
00:27:23,240 --> 00:27:28,040
of track shows where subjects were asked
to, to to write down

454
00:27:28,040 --> 00:27:32,280
a word that appeared on the screen
and that involved large heft movements.

455
00:27:32,280 --> 00:27:35,600
But again, the data was looking really,

456
00:27:35,720 --> 00:27:38,720
really good.

457
00:27:38,720 --> 00:27:42,080
And something that I particularly
I'm really excited about and

458
00:27:42,920 --> 00:27:46,200
is the
is the pediatric make that we can now

459
00:27:47,600 --> 00:27:48,760
scan children that

460
00:27:48,760 --> 00:27:51,440
we were not able
to do in conventional systems.

461
00:27:51,800 --> 00:27:56,320
So this is work
when Ryan, Natalie and Lucas are involved

462
00:27:57,080 --> 00:28:00,120
and so we've been developing
these later helmets

463
00:28:00,120 --> 00:28:05,320
with Searhc and other companies
and there's an ongoing study

464
00:28:05,320 --> 00:28:09,240
where we are trying to recruit children
from,

465
00:28:09,240 --> 00:28:11,600
well, newborn to 13 years old.

466
00:28:12,280 --> 00:28:16,480
We've scanned 11 kits
so far and we've done two tasks.

467
00:28:16,480 --> 00:28:22,160
So one of them is this is a paradigm
that is used in sick kids where they

468
00:28:22,160 --> 00:28:26,200
they scan children
and typically develop children,

469
00:28:26,200 --> 00:28:29,680
but also children with autism.

470
00:28:29,680 --> 00:28:32,240
So one of the tasks is just

471
00:28:32,240 --> 00:28:36,440
a few faces up on the screen
and also some concentric circles

472
00:28:36,440 --> 00:28:40,240
to look at some gamma bands
or higher frequency responses.

473
00:28:40,520 --> 00:28:43,240
And then there's also we've done a sensory

474
00:28:43,240 --> 00:28:46,360
task where these Braille stimulators

475
00:28:47,360 --> 00:28:49,880
stimulate the index and the little finger,

476
00:28:51,080 --> 00:28:54,080
and this results
are looking really promising.

477
00:28:54,080 --> 00:28:56,560
These are the emotional faces.

478
00:28:56,560 --> 00:28:59,840
We can get large evoked responses

479
00:29:00,040 --> 00:29:02,360
and at the back of the brain,
in the visual

480
00:29:02,840 --> 00:29:06,560
and primary visual areas
and also with high

481
00:29:07,160 --> 00:29:10,640
SNR in the visual areas
and also the FUSIFORM

482
00:29:11,440 --> 00:29:15,520
and the Braille paradigm as well,
we get a and evoke response.

483
00:29:15,520 --> 00:29:19,520
And also, as I've been showing for a while
now, they this drop

484
00:29:19,520 --> 00:29:22,840
in the frequency band during movement,

485
00:29:23,360 --> 00:29:26,360
while during the stimulation story
and B to band or

486
00:29:27,680 --> 00:29:32,480
localize to the sensory cortex as well.

487
00:29:32,480 --> 00:29:35,720
So now I'll go through what

488
00:29:35,720 --> 00:29:39,080
the system is now
and going through a bit more.

489
00:29:39,080 --> 00:29:41,600
My involvement with Circa Magnetic. So

490
00:29:43,360 --> 00:29:47,680
and clearly there was a lot
of interest in OPM technology

491
00:29:48,920 --> 00:29:53,280
and we we wanted to, to set this up to

492
00:29:53,840 --> 00:29:58,400
and to facilitate this technology,
to go to other places, to other labs

493
00:29:58,400 --> 00:30:01,280
where they can do their their
their specific

494
00:30:02,240 --> 00:30:04,320
research topic.

495
00:30:04,680 --> 00:30:08,400
So we with the University of Nottingham
on the company

496
00:30:08,400 --> 00:30:11,480
magnetic shields
that make the the enclosure

497
00:30:12,520 --> 00:30:14,840
we formed circa in July 2020.

498
00:30:16,720 --> 00:30:19,960
And so far we've installed our system

499
00:30:20,120 --> 00:30:24,720
with so 44 dual axis system
in SickKids in Toronto,

500
00:30:25,520 --> 00:30:29,000
a 64 sensor in young epilepsy

501
00:30:29,160 --> 00:30:32,040
in the south of England and very recently

502
00:30:33,360 --> 00:30:38,960
in Boystown in Nebraska,
another 64 system.

503
00:30:38,960 --> 00:30:41,640
So I'll just briefly go through that.

504
00:30:41,640 --> 00:30:42,720
These three.

505
00:30:42,720 --> 00:30:46,040
So in SickKids,
the Hospital for Sick Children

506
00:30:46,440 --> 00:30:49,880
and we retrofitted
we call it a retrofit system

507
00:30:49,880 --> 00:30:55,760
because they already had a shielded room
there from a from an old cryogenic system.

508
00:30:55,760 --> 00:30:57,640
You can see that at the back.

509
00:30:57,640 --> 00:31:01,040
So we installed the biplane,
our coils to go around

510
00:31:01,240 --> 00:31:04,640
and to bring the to to compensate
for these changes

511
00:31:04,640 --> 00:31:07,240
in in magnetic field

512
00:31:07,760 --> 00:31:10,960
and their main study,
their main research is on

513
00:31:12,000 --> 00:31:13,120
autism.

514
00:31:14,480 --> 00:31:16,840
It was probably not the easiest site

515
00:31:17,120 --> 00:31:21,080
that we could have started
with after forming Saga because

516
00:31:22,920 --> 00:31:25,680
like here, the CTV is in

517
00:31:26,760 --> 00:31:29,800
quite a quiet, I'm getting sicker and

518
00:31:31,000 --> 00:31:34,200
in a very quiet part of my life.

519
00:31:34,400 --> 00:31:41,240
But here in SickKids, it's
in our city center hospital where there is

520
00:31:41,240 --> 00:31:45,920
lots of interference from elevators
to the metro to building works.

521
00:31:46,880 --> 00:31:48,760
I think the mighty of garage.

522
00:31:48,760 --> 00:31:53,480
So basically everything
you don't want next to a mic system.

523
00:31:54,120 --> 00:31:55,240
So it was quite tricky.

524
00:31:55,240 --> 00:31:57,680
You can see these blue lines

525
00:31:59,000 --> 00:32:03,400
that's just the sensors in the room
not doing anything.

526
00:32:03,400 --> 00:32:05,760
They go out of their dynamic range

527
00:32:06,600 --> 00:32:10,680
very quickly and compared to Nottingham
with where we are in

528
00:32:11,360 --> 00:32:13,920
in the university campus in the middle of

529
00:32:15,200 --> 00:32:17,600
green fields, there's nothing around you.

530
00:32:17,640 --> 00:32:18,760
You don't see that much

531
00:32:21,000 --> 00:32:25,280
interference, but with the coils

532
00:32:26,160 --> 00:32:29,000
compensating dynamically for these changes

533
00:32:29,000 --> 00:32:32,320
in field, we can bring the, the sensors

534
00:32:32,320 --> 00:32:37,160
down to their operational range
and we can perform,

535
00:32:37,600 --> 00:32:39,400
make experiments

536
00:32:42,880 --> 00:32:45,840
and which

537
00:32:48,320 --> 00:32:50,800
would be

538
00:32:50,800 --> 00:32:53,240
interesting the way.

539
00:32:53,240 --> 00:32:57,320
Yeah, as you say.

540
00:32:57,920 --> 00:33:00,680
And so yeah

541
00:33:01,240 --> 00:33:07,480
this is so Ryan went out there
to set up this system in Toronto and he

542
00:33:08,240 --> 00:33:10,280
so he scanned himself

543
00:33:11,440 --> 00:33:16,160
five or six times in, in Nottingham
and then he said kids and we,

544
00:33:16,160 --> 00:33:20,240
we see sort of similar from that paper
from a couple of years ago,

545
00:33:20,880 --> 00:33:24,280
very comparable results
across to two very different sites.

546
00:33:24,280 --> 00:33:26,840
One very quiet,
magnetically quiet and one,

547
00:33:27,920 --> 00:33:31,360
yeah, very, very different.

548
00:33:31,360 --> 00:33:33,840
The other sites in young epilepsy

549
00:33:34,400 --> 00:33:37,760
in, in the UK, again
this was a retrofit so

550
00:33:37,760 --> 00:33:41,320
there was already the the shielded
room there because of a project

551
00:33:41,840 --> 00:33:44,440
from well between magnetic

552
00:33:44,440 --> 00:33:47,760
shields Nottingham UCL and young epilepsy.

553
00:33:47,760 --> 00:33:51,320
They with this a UK
project of light new room.

554
00:33:52,160 --> 00:33:55,720
They wanted to make a cheaper, lighter
shielded room.

555
00:33:55,720 --> 00:34:00,840
So getting rid of one layer of the the
the metal that they're made of

556
00:34:01,600 --> 00:34:04,600
but having coils
you can see in this photo here

557
00:34:05,000 --> 00:34:07,320
having the coils
inside the walls of the room.

558
00:34:08,200 --> 00:34:10,600
Can we give enough back around

559
00:34:10,640 --> 00:34:13,040
magnetic field for the sensors to operate?

560
00:34:13,640 --> 00:34:18,360
So then we installed
a 128 tunnel system there and the

561
00:34:18,600 --> 00:34:22,000
then the patient supported the helmets
and the

562
00:34:22,760 --> 00:34:26,200
the software and what they
what they're going to be doing various

563
00:34:28,080 --> 00:34:30,200
they will be doing some clinical trials

564
00:34:30,440 --> 00:34:32,960
involving scanning children with epilepsy.

565
00:34:34,600 --> 00:34:38,480
This is some work that's been going on
there as well.

566
00:34:38,480 --> 00:34:41,840
So doing concurrently, OPM's on an EEG.

567
00:34:41,840 --> 00:34:45,040
So this is work by silica where

568
00:34:45,960 --> 00:34:49,400
you should use the 64 sensor helmet

569
00:34:49,400 --> 00:34:51,400
and then some electrodes

570
00:34:52,640 --> 00:34:56,240
on the scalp and you get can very

571
00:34:57,360 --> 00:35:00,840
yes, similar results from
it make an EEG in a simple

572
00:35:00,840 --> 00:35:05,480
task of just eyes open, eyes closed.

573
00:35:05,480 --> 00:35:09,680
And recently I have
two of my colleagues are currently there

574
00:35:09,680 --> 00:35:11,800
in Boystown, in Nebraska,

575
00:35:13,480 --> 00:35:15,600
finishing the installation of this

576
00:35:15,600 --> 00:35:18,920
or the third system,

577
00:35:18,920 --> 00:35:21,880
which has been the first one
where we've done all of it.

578
00:35:21,880 --> 00:35:24,880
So the installation of the room
now you can see there,

579
00:35:24,880 --> 00:35:29,120
which is the same as the young epilepsy
and 128 tunnel system.

580
00:35:29,760 --> 00:35:32,840
And they recently they've done
very nice videos of the

581
00:35:33,040 --> 00:35:35,360
the inauguration of their of the center.

582
00:35:36,760 --> 00:35:38,840
So I think that's

583
00:35:40,080 --> 00:35:42,480
the I'm nearing the the end so

584
00:35:43,200 --> 00:35:46,280
to conclude these new generation of

585
00:35:46,880 --> 00:35:49,280
of sensors of quantum

586
00:35:49,280 --> 00:35:53,080
magnetic field sensors have enabled
these wearable

587
00:35:53,360 --> 00:35:57,920
make magnets
and so photography to become a reality.

588
00:35:58,880 --> 00:36:03,640
And now we can have participants moving
and doing

589
00:36:03,640 --> 00:36:07,400
some different tasks that they were not
they were not able to do before

590
00:36:08,080 --> 00:36:11,720
whilst getting really good
and high fidelity data.

591
00:36:12,840 --> 00:36:15,520
And also this technology opens up

592
00:36:15,520 --> 00:36:18,160
new ways of doing new neuroscience

593
00:36:19,280 --> 00:36:21,920
research, but also hopefully help

594
00:36:21,920 --> 00:36:24,080
in the clinical setting as well.

595
00:36:25,160 --> 00:36:28,040
And so finally, I think for me,

596
00:36:28,040 --> 00:36:32,840
bringing open
that to Spain is like closing my circle.

597
00:36:32,840 --> 00:36:36,080
I started, I studied here, I went away

598
00:36:36,080 --> 00:36:38,320
and now for me it would be a great

599
00:36:39,800 --> 00:36:42,400
it will be a dream
to bring opium to Spain,

600
00:36:42,400 --> 00:36:45,160
but not appearing on a trailer offer

601
00:36:46,000 --> 00:36:49,280
of Amazon Prime series up here in Spain.

602
00:36:49,280 --> 00:36:51,720
Completely random. But it was.

603
00:36:52,320 --> 00:36:54,520
Yeah, it was quite funny to see.

604
00:36:54,520 --> 00:36:57,560
But for me, actually
bringing that technology

605
00:36:57,560 --> 00:37:01,000
and putting the system in
the industry to be would be,

606
00:37:02,200 --> 00:37:05,240
yeah, a really

607
00:37:06,320 --> 00:37:07,600
a pleasurable dream.

608
00:37:07,600 --> 00:37:09,680
A dream come true.

609
00:37:09,680 --> 00:37:12,240
So with that I'll just

610
00:37:12,360 --> 00:37:15,560
I want to thank all of my collaborators
and colleagues and funders

611
00:37:15,560 --> 00:37:18,440
and to all of you for listening