ABOUT THE SPEAKER
Mehdi Ordikhani-Seyedlar - Neuroscientist
Mehdi Ordikhani-Seyedlar is a computational neuroscientist, researching brain signals and their usage in brain-machine interfaces.

Why you should listen

Mehdi Ordikhani-Seyedlar is a research scientist interested in brain-wave patterns generated by neural activities in the brain. Since embarking on his research on neuroscience, Ordikhani-Seyedlar has been working on different brain functions such as learning, memory, pain and, more recently, visual attention in humans. He also conducted a part of his research on monkeys when he was in Dr. Miguel Nicolelis' lab at Duke University. His findings help implement more accurate brain-machine interfaces to treat people who are suffering from attention deficiency.

After receiving his Ph.D  in Biomedical Engineering, Ordikhani-Seyedlar was offered a postdoctoral position by Duke University to develop algorithms to process large-scale neuronal activity and brain-machine interfaces. However, due to political complications in the United States, Ordikhani-Seyedlar -- an Iranian citizen -- changed his plan to continue his brain research outside the US for some time.

As a passionate neuroscientist and neuroengineer, Ordikhani-Seyedlar's aim is to improve brain pattern detectability in computers. This enhances the ability of brain-machine interfaces substantially to better target the defected brain function which in turn enhances the sustainability of treatment effect.

More profile about the speaker
Mehdi Ordikhani-Seyedlar | Speaker | TED.com
TED2017

Mehdi Ordikhani-Seyedlar: What happens in your brain when you pay attention?

Мэхди Ордикани-Сэедлар: Анхаарлаа төвлөрүүлэхэд тархинд юу болдог вэ?

Filmed:
3,083,456 views

Анхаарал төвлөрөл гэдэг нь бидний анхаарч буй зүйлс төдийгүй тархины тэндээс шүүж байгаа мэдээллийг хэлдэг. Төвлөрөх үеийн тархины бүтцийг судалснаар тархины мэдрэл судлаач Мэхди Ордикани-Сэедлар компьютер болон тархийг улам ойртуулж, "анхаарлын дутмагшил, хэт хөдөлгөөнтөх" эмгэгийг эмчлэх, харилцах чадвараа алдсан хүмүүст туслахыг зорьж байна. Энэ богино боловч сонирхолтой илтгэлээс гайхалтай шинжлэх ухааны талаар сонсоорой.
- Neuroscientist
Mehdi Ordikhani-Seyedlar is a computational neuroscientist, researching brain signals and their usage in brain-machine interfaces. Full bio

Double-click the English transcript below to play the video.

00:12
Paying close attention to something:
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Анхаарлаа төвлөрүүлэх нь
00:15
Not that easy, is it?
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амаргүй зүйл. Тиймүү?
00:17
It's because our attention is pulled
in so many different directions at a time,
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Бидний анхаарал олон зүйлд
зэрэг сатаарч байдаг учир
00:22
and it's in fact pretty impressive
if you can stay focused.
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төвлөрч чаддаг байх нь гайхалтай хэрэг.
00:28
Many people think that attention
is all about what we are focusing on,
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Ихэнх хүмүүс ямар нэг зүйлд төвлөрөхийг
анхаарал гэж боддог ч
00:32
but it's also about what information
our brain is trying to filter out.
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энэ нь тархины шүүж буй
мэдээллийн тухай ойлголт юм.
00:38
There are two ways
you direct your attention.
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Анхаарлаа төвлөрүүлэх хоёр арга бий.
00:41
First, there's overt attention.
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Эхнийх нь ил төвлөрөлт.
00:43
In overt attention,
you move your eyes towards something
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Энэ нь аливаа зүйлийг дагуулан харж
00:47
in order to pay attention to it.
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анхаарахыг хэлнэ.
00:50
Then there's covert attention.
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Нөгөөх нь далд төвлөрөл.
00:52
In covert attention,
you pay attention to something,
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Энэ нь нүдээ хөдөлгөхгүйгээр
00:56
but without moving your eyes.
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анхаарал төвлөрүүлэхийг хэлнэ.
00:59
Think of driving for a second.
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Машин барихыг бодоод үзье.
01:02
Your overt attention,
your direction of the eyes,
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Ил төвлөрөл нь нүдний харсан зүг буюу
01:06
are in front,
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урагшаа чиглэсэн байна.
01:07
but that's your covert attention
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Харин далд төвлөрөлт нь
01:09
which is constantly scanning
the surrounding area,
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эргэн тойрноо шууд харахгүй ч
01:13
where you don't actually look at them.
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шинжиж ажигласаар байдаг.
01:17
I'm a computational neuroscientist,
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Би тархины мэдрэлийг тооцооллын аргаар
01:19
and I work on cognitive
brain-machine interfaces,
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судалдаг эрдэмтэн бөгөөд тархи,
технологи хоёрын уялдааг судалж
01:22
or bringing together
the brain and the computer.
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эдгээрийг хослуулдаг гэсэн үг.
01:26
I love brain patterns.
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Би тархины бүтцэд дуртай.
01:28
Brain patterns are important for us
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Тархины бүтэц бидэнд их чухал.
01:30
because based on them
we can build models for the computers,
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Учир нь үүн дээр үндэслэн
компьютерийн загваруудыг бүтээж,
01:33
and based on these models
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01:35
computers can recognize
how well our brain functions.
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эдгээр загварт үндэслэн
бидний тархи хэр сайн ажиллаж байгааг
компьютер тодорхойлдог.
01:39
And if it doesn't function well,
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Хэрэв сайн ажиллахгүй тохиолдолд
01:42
then these computers themselves
can be used as assistive devices
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компьютер нь эмчилгээ хийхэд туслах
төхөөрөмж болох юм.
01:46
for therapies.
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01:48
But that also means something,
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Гэвч нэг анхаарах зүйл бий.
Хэрвээ буруу давтамжийг
сонгосон тохиолдолд
01:51
because choosing the wrong patterns
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01:53
will give us the wrong models
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буруу загвар гарч,
01:55
and therefore the wrong therapies.
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улмаар буруу эмчилгээ хийгдэнэ.
01:57
Right?
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01:59
In case of attention,
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Анхаарал төвлөрлийн хувьд
02:01
the fact that we can
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бид нүдээ заавал хөдөлгөхгүйгээр,
02:03
shift our attention not only by our eyes
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бодол санаагаараа анхаарлыг удирдаж
чаддаг байх нь
02:07
but also by thinking --
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02:09
that makes covert attention
an interesting model for computers.
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далд анхаарлыг компьютерийн
сайн загвар болгож байгаа юм.
02:14
So I wanted to know
what are the brainwave patterns
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Иймээс ч би тархины долгион
02:17
when you look overtly
or when you look covertly.
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ил ба далд анхаарлын үед
ямар байгааг мэдэхийг хүссэн.
02:22
I set up an experiment for that.
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Үүний тулд нэг туршилт явуулсан.
02:24
In this experiment
there are two flickering squares,
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Энэ туршилтад анивчиж байгаа
2 дөрвөлжинг ашигласан.
02:27
one of them flickering
at a slower rate than the other one.
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Нэг нь нөгөөхөөсөө удаан анивчдаг.
02:32
Depending on which of these flickers
you are paying attention to,
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Та аль дөрвөлжинд
анхаарлаа хандуулснаас хамааран
02:36
certain parts of your brain
will start resonating in the same rate
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тархины тодорхой хэсгийн долгион
тухайн дүрстэй
ижил давтамжтай болж өөрчлөгдөнө.
02:41
as that flickering rate.
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02:44
So by analyzing your brain signals,
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Ингэж тархины долгионыг судалснаар
02:46
we can track where exactly
you are watching
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бид таны юу харж байгааг
эсвэл юунд анхаарч байгааг мэдэж чадна.
02:50
or you are paying attention to.
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02:55
So to see what happens in your brain
when you pay overt attention,
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Ингээд ил төвлөрлийн үед
тархинд юу болдгийг мэдэхийн тулд
02:59
I asked people to look directly
in one of the squares
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би хүмүүст аль нэг дөрвөлжин рүү
03:02
and pay attention to it.
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анхаарлаа хандуулахыг хүссэн.
03:04
In this case, not surprisingly,
we saw that these flickering squares
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Бидний таамаглаж байсанчлан,
анивчих дөрвөлжингүүд
03:10
appeared in their brain signals
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тархины долгионд илэрч байлаа.
03:12
which was coming
from the back of their head,
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Энэ нь тархины ар талын
03:15
which is responsible for the processing
of your visual information.
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зурган мэдээлэл боловсруулдаг
хэсгээс гарч байсан.
03:20
But I was really interested
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Гэхдээ далд төвлөрлийн үед
03:22
to see what happens in your brain
when you pay covert attention.
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тархинд юу болдгийг
бид мэдэхийг хүсэж байлаа.
03:26
So this time I asked people
to look in the middle of the screen
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Тиймээс энэ удаа би дэлгэцийн
дунд хэсэг рүү
03:30
and without moving their eyes,
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нүдээ хөдөлгөлгүй анхаарлаа хандуулж,
03:33
to pay attention
to either of these squares.
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дөрвөлжин дүрсүүдийг
анхаарахгүй байхыг хүссэн.
03:37
When we did that,
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Ингэж харсны дараа тархинд
03:38
we saw that both of these flickering rates
appeared in their brain signals,
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хоёр давтамжийн аль аль нь
тархины дохионд илэрсэн.
03:42
but interestingly,
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Хамгийн сонирхолтой нь,
03:44
only one of them,
which was paid attention to,
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анхаарлаа хандуулж байсан анивчилтын
03:48
had stronger signals,
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дохио нь илүү хүчтэй байсан.
03:49
so there was something in the brain
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Тархинд энэ мэдээллийг зохицуулдаг
03:52
which was handling this information
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ямар нэг зүйл байсан бөгөөд
03:54
so that thing in the brain was basically
the activation of the frontal area.
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тархины энэ зүйл үндсэндээ духны хэсгийн
идэвхжилттэй холбоотой байсан.
04:02
The front part of your brain
is responsible
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Харин тархины духны энэ хэсэг
04:05
for higher cognitive functions as a human.
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хүний танин мэдэхүйн
өндөр ур чадварыг хариуцдаг.
04:09
The frontal part,
it seems that it works as a filter
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Духны хэсэг яг л шүүлтүүр шиг ажиллаж,
04:14
trying to let information come in
only from the right flicker
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таны анхаарал төвлөрүүлж буй
дүрснээс ирэх дохиог хүлээн авч,
04:19
that you are paying attention to
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харин анхаарахгүй байгаа
04:21
and trying to inhibit the information
coming from the ignored one.
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дүрснээс ирэх дохиог
авахгүй байхыг хичээдэг.
04:27
The filtering ability of the brain
is indeed a key for attention,
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Тархины энэхүү шүүх чадвар
анхаарал төвлөрлийн гол түлхүүр бөгөөд
04:32
which is missing in some people,
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зарим хүмүүст байдаггүй.
Жишээ нь, "анхаарал дутмагшил, хэт
хөдөлгөөнтөх эмгэг"-тэй хүмүүст байдаггүй.
04:35
for example in people with ADHD.
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04:38
So a person with ADHD
cannot inhibit these distractors,
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АДХХЭ-тэй хүмүүс анхаарал сарниулагч
хүчин зүйлсийг тусгаарлаж чаддагүй тул
04:43
and that's why they can't focus
for a long time on a single task.
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нэг ажилд удаан хугацаагаар
төвлөрч чаддаггүй.
04:49
But what if this person
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Харин ийм хүн
04:51
could play a specific computer game
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тархиа компьютерт холбож байгаад
04:54
with his brain connected to the computer,
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тодорхой нэг компьютерын тоглоом тоглож,
04:58
and then train his own brain
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дараа нь тархиа эдгээр сатааруулагчийг
05:01
to inhibit these distractors?
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анхаардаггүй болгож сургавал ямар вэ?
05:05
Well, ADHD is just one example.
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АДХХЭ бол зөвхөн нэг жишээ.
05:09
We can use these cognitive
brain-machine interfaces
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Бид тархины эдгээр
танин мэдэхүйн холбоосыг
05:12
for many other cognitive fields.
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өөр олон талбарт ашиглаж болно.
05:15
It was just a few years ago
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Хэдхэн жилийн өмнө
05:17
that my grandfather had a stroke,
and he lost complete ability to speak.
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миний өвөө саа өвчин тусч,
ярих чадвараа алдсан.
05:24
He could understand everybody,
but there was no way to respond,
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Тэр бүгдийг ойлгож байсан ч
хариу өгөх ямар ч аргагүй байлаа.
05:28
even not writing
because he was illiterate.
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Учир нь өвөө маань бичиг үсэг
тайлагдаагүй байсан юм.
05:32
So he passed away in silence.
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Ингээд тэр чимээгүй байсаар
нас барсан билээ.
Би тэр үед түүний өмнөөс
ярьж чаддаг компьютер
05:36
I remember thinking at that time:
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05:39
What if we could have a computer
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байсан бол яах байсан бол гэж
боддог байв.
05:43
which could speak for him?
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05:45
Now, after years that I am in this field,
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Харин одоо энэ салбарт олон жил ажиллахдаа
05:48
I can see that this might be possible.
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үүнийг боломжтой гэдгийг ойлгосон юм.
05:52
Imagine if we can find brainwave patterns
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Хэрэв хүмүүс дүрс
эсвэл үсэг дотроо бодоход,
05:55
when people think
about images or even letters,
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яг л "А" эсвэл "Б" гэдэг шиг үсэг бодоход
05:59
like the letter A generates
a different brainwave pattern
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үүсэх тархины долгионыг
ялгаж чаддаг болчихвол
06:02
than the letter B, and so on.
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яахыг төсөөл дөө.
06:04
Could a computer one day
communicate for people who can't speak?
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Нэг л өдөр компьютер хэлгүй хүний өмнөөс
бусадтай харилцдаг болох болов уу?
06:09
What if a computer
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Хэрэв компьютер
06:11
can help us understand
the thoughts of a person in a coma?
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комд орсон хүний бодлыг
бидэнд дамжуулдаг болчихвол ямар вэ?
06:17
We are not there yet,
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Бид хараахан тэнд хүрээгүй ч
06:19
but pay close attention.
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анхааралтай ажиглаарай.
06:22
We will be there soon.
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Удахгүй зорилгодоо хүрэх болно.
06:23
Thank you.
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Баярлалаа.
06:25
(Applause)
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(Алга ташилт)

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ABOUT THE SPEAKER
Mehdi Ordikhani-Seyedlar - Neuroscientist
Mehdi Ordikhani-Seyedlar is a computational neuroscientist, researching brain signals and their usage in brain-machine interfaces.

Why you should listen

Mehdi Ordikhani-Seyedlar is a research scientist interested in brain-wave patterns generated by neural activities in the brain. Since embarking on his research on neuroscience, Ordikhani-Seyedlar has been working on different brain functions such as learning, memory, pain and, more recently, visual attention in humans. He also conducted a part of his research on monkeys when he was in Dr. Miguel Nicolelis' lab at Duke University. His findings help implement more accurate brain-machine interfaces to treat people who are suffering from attention deficiency.

After receiving his Ph.D  in Biomedical Engineering, Ordikhani-Seyedlar was offered a postdoctoral position by Duke University to develop algorithms to process large-scale neuronal activity and brain-machine interfaces. However, due to political complications in the United States, Ordikhani-Seyedlar -- an Iranian citizen -- changed his plan to continue his brain research outside the US for some time.

As a passionate neuroscientist and neuroengineer, Ordikhani-Seyedlar's aim is to improve brain pattern detectability in computers. This enhances the ability of brain-machine interfaces substantially to better target the defected brain function which in turn enhances the sustainability of treatment effect.

More profile about the speaker
Mehdi Ordikhani-Seyedlar | Speaker | TED.com

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