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:
0
760
2480
Анхаарлаа төвлөрүүлэх нь
00:15
Not that easy, is it?
1
3280
1240
амаргүй зүйл. Тиймүү?
00:17
It's because our attention is pulled
in so many different directions at a time,
2
5520
5016
Бидний анхаарал олон зүйлд
зэрэг сатаарч байдаг учир
00:22
and it's in fact pretty impressive
if you can stay focused.
3
10560
4080
төвлөрч чаддаг байх нь гайхалтай хэрэг.
00:28
Many people think that attention
is all about what we are focusing on,
4
16360
4056
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.
5
20440
4800
энэ нь тархины шүүж буй
мэдээллийн тухай ойлголт юм.
00:38
There are two ways
you direct your attention.
6
26320
2720
Анхаарлаа төвлөрүүлэх хоёр арга бий.
00:41
First, there's overt attention.
7
29600
1560
Эхнийх нь ил төвлөрөлт.
00:43
In overt attention,
you move your eyes towards something
8
31640
4136
Энэ нь аливаа зүйлийг дагуулан харж
00:47
in order to pay attention to it.
9
35800
1560
анхаарахыг хэлнэ.
00:50
Then there's covert attention.
10
38360
1976
Нөгөөх нь далд төвлөрөл.
00:52
In covert attention,
you pay attention to something,
11
40360
4016
Энэ нь нүдээ хөдөлгөхгүйгээр
00:56
but without moving your eyes.
12
44400
1560
анхаарал төвлөрүүлэхийг хэлнэ.
00:59
Think of driving for a second.
13
47040
1640
Машин барихыг бодоод үзье.
01:02
Your overt attention,
your direction of the eyes,
14
50960
3016
Ил төвлөрөл нь нүдний харсан зүг буюу
01:06
are in front,
15
54000
1656
урагшаа чиглэсэн байна.
01:07
but that's your covert attention
16
55680
1776
Харин далд төвлөрөлт нь
01:09
which is constantly scanning
the surrounding area,
17
57480
3080
эргэн тойрноо шууд харахгүй ч
01:13
where you don't actually look at them.
18
61600
1880
шинжиж ажигласаар байдаг.
01:17
I'm a computational neuroscientist,
19
65519
1937
Би тархины мэдрэлийг тооцооллын аргаар
01:19
and I work on cognitive
brain-machine interfaces,
20
67480
3096
судалдаг эрдэмтэн бөгөөд тархи,
технологи хоёрын уялдааг судалж
01:22
or bringing together
the brain and the computer.
21
70600
3040
эдгээрийг хослуулдаг гэсэн үг.
01:26
I love brain patterns.
22
74720
1600
Би тархины бүтцэд дуртай.
01:28
Brain patterns are important for us
23
76720
1696
Тархины бүтэц бидэнд их чухал.
01:30
because based on them
we can build models for the computers,
24
78440
3496
Учир нь үүн дээр үндэслэн
компьютерийн загваруудыг бүтээж,
01:33
and based on these models
25
81960
1416
01:35
computers can recognize
how well our brain functions.
26
83400
4216
эдгээр загварт үндэслэн
бидний тархи хэр сайн ажиллаж байгааг
компьютер тодорхойлдог.
01:39
And if it doesn't function well,
27
87640
1600
Хэрэв сайн ажиллахгүй тохиолдолд
01:42
then these computers themselves
can be used as assistive devices
28
90080
3920
компьютер нь эмчилгээ хийхэд туслах
төхөөрөмж болох юм.
01:46
for therapies.
29
94760
1200
01:48
But that also means something,
30
96480
1640
Гэвч нэг анхаарах зүйл бий.
Хэрвээ буруу давтамжийг
сонгосон тохиолдолд
01:51
because choosing the wrong patterns
31
99360
2496
01:53
will give us the wrong models
32
101880
1896
буруу загвар гарч,
01:55
and therefore the wrong therapies.
33
103800
1656
улмаар буруу эмчилгээ хийгдэнэ.
01:57
Right?
34
105480
1200
01:59
In case of attention,
35
107640
1656
Анхаарал төвлөрлийн хувьд
02:01
the fact that we can
36
109320
1280
бид нүдээ заавал хөдөлгөхгүйгээр,
02:03
shift our attention not only by our eyes
37
111800
3496
бодол санаагаараа анхаарлыг удирдаж
чаддаг байх нь
02:07
but also by thinking --
38
115320
1320
02:09
that makes covert attention
an interesting model for computers.
39
117440
4080
далд анхаарлыг компьютерийн
сайн загвар болгож байгаа юм.
02:14
So I wanted to know
what are the brainwave patterns
40
122280
3456
Иймээс ч би тархины долгион
02:17
when you look overtly
or when you look covertly.
41
125760
3680
ил ба далд анхаарлын үед
ямар байгааг мэдэхийг хүссэн.
02:22
I set up an experiment for that.
42
130440
1760
Үүний тулд нэг туршилт явуулсан.
02:24
In this experiment
there are two flickering squares,
43
132960
2736
Энэ туршилтад анивчиж байгаа
2 дөрвөлжинг ашигласан.
02:27
one of them flickering
at a slower rate than the other one.
44
135720
3360
Нэг нь нөгөөхөөсөө удаан анивчдаг.
02:32
Depending on which of these flickers
you are paying attention to,
45
140600
3816
Та аль дөрвөлжинд
анхаарлаа хандуулснаас хамааран
02:36
certain parts of your brain
will start resonating in the same rate
46
144440
3960
тархины тодорхой хэсгийн долгион
тухайн дүрстэй
ижил давтамжтай болж өөрчлөгдөнө.
02:41
as that flickering rate.
47
149200
1440
02:44
So by analyzing your brain signals,
48
152000
2936
Ингэж тархины долгионыг судалснаар
02:46
we can track where exactly
you are watching
49
154960
3040
бид таны юу харж байгааг
эсвэл юунд анхаарч байгааг мэдэж чадна.
02:50
or you are paying attention to.
50
158760
1560
02:55
So to see what happens in your brain
when you pay overt attention,
51
163000
4216
Ингээд ил төвлөрлийн үед
тархинд юу болдгийг мэдэхийн тулд
02:59
I asked people to look directly
in one of the squares
52
167240
3256
би хүмүүст аль нэг дөрвөлжин рүү
03:02
and pay attention to it.
53
170520
1280
анхаарлаа хандуулахыг хүссэн.
03:04
In this case, not surprisingly,
we saw that these flickering squares
54
172760
5296
Бидний таамаглаж байсанчлан,
анивчих дөрвөлжингүүд
03:10
appeared in their brain signals
55
178080
1936
тархины долгионд илэрч байлаа.
03:12
which was coming
from the back of their head,
56
180040
2360
Энэ нь тархины ар талын
03:15
which is responsible for the processing
of your visual information.
57
183560
3400
зурган мэдээлэл боловсруулдаг
хэсгээс гарч байсан.
03:20
But I was really interested
58
188280
2336
Гэхдээ далд төвлөрлийн үед
03:22
to see what happens in your brain
when you pay covert attention.
59
190640
3160
тархинд юу болдгийг
бид мэдэхийг хүсэж байлаа.
03:26
So this time I asked people
to look in the middle of the screen
60
194480
3896
Тиймээс энэ удаа би дэлгэцийн
дунд хэсэг рүү
03:30
and without moving their eyes,
61
198400
1880
нүдээ хөдөлгөлгүй анхаарлаа хандуулж,
03:33
to pay attention
to either of these squares.
62
201120
2720
дөрвөлжин дүрсүүдийг
анхаарахгүй байхыг хүссэн.
03:37
When we did that,
63
205120
1616
Ингэж харсны дараа тархинд
03:38
we saw that both of these flickering rates
appeared in their brain signals,
64
206760
3936
хоёр давтамжийн аль аль нь
тархины дохионд илэрсэн.
03:42
but interestingly,
65
210720
1200
Хамгийн сонирхолтой нь,
03:44
only one of them,
which was paid attention to,
66
212640
3536
анхаарлаа хандуулж байсан анивчилтын
03:48
had stronger signals,
67
216200
1656
дохио нь илүү хүчтэй байсан.
03:49
so there was something in the brain
68
217880
2256
Тархинд энэ мэдээллийг зохицуулдаг
03:52
which was handling this information
69
220160
2536
ямар нэг зүйл байсан бөгөөд
03:54
so that thing in the brain was basically
the activation of the frontal area.
70
222720
6200
тархины энэ зүйл үндсэндээ духны хэсгийн
идэвхжилттэй холбоотой байсан.
04:02
The front part of your brain
is responsible
71
230440
2976
Харин тархины духны энэ хэсэг
04:05
for higher cognitive functions as a human.
72
233440
2880
хүний танин мэдэхүйн
өндөр ур чадварыг хариуцдаг.
04:09
The frontal part,
it seems that it works as a filter
73
237160
4440
Духны хэсэг яг л шүүлтүүр шиг ажиллаж,
04:14
trying to let information come in
only from the right flicker
74
242640
4376
таны анхаарал төвлөрүүлж буй
дүрснээс ирэх дохиог хүлээн авч,
04:19
that you are paying attention to
75
247040
1640
харин анхаарахгүй байгаа
04:21
and trying to inhibit the information
coming from the ignored one.
76
249400
3960
дүрснээс ирэх дохиог
авахгүй байхыг хичээдэг.
04:27
The filtering ability of the brain
is indeed a key for attention,
77
255400
5296
Тархины энэхүү шүүх чадвар
анхаарал төвлөрлийн гол түлхүүр бөгөөд
04:32
which is missing in some people,
78
260720
2776
зарим хүмүүст байдаггүй.
Жишээ нь, "анхаарал дутмагшил, хэт
хөдөлгөөнтөх эмгэг"-тэй хүмүүст байдаггүй.
04:35
for example in people with ADHD.
79
263520
2480
04:38
So a person with ADHD
cannot inhibit these distractors,
80
266640
5016
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.
81
271680
4760
нэг ажилд удаан хугацаагаар
төвлөрч чаддаггүй.
04:49
But what if this person
82
277600
1536
Харин ийм хүн
04:51
could play a specific computer game
83
279160
3536
тархиа компьютерт холбож байгаад
04:54
with his brain connected to the computer,
84
282720
2880
тодорхой нэг компьютерын тоглоом тоглож,
04:58
and then train his own brain
85
286440
2120
дараа нь тархиа эдгээр сатааруулагчийг
05:01
to inhibit these distractors?
86
289360
2440
анхаардаггүй болгож сургавал ямар вэ?
05:05
Well, ADHD is just one example.
87
293680
2480
АДХХЭ бол зөвхөн нэг жишээ.
05:09
We can use these cognitive
brain-machine interfaces
88
297200
3256
Бид тархины эдгээр
танин мэдэхүйн холбоосыг
05:12
for many other cognitive fields.
89
300480
2200
өөр олон талбарт ашиглаж болно.
05:15
It was just a few years ago
90
303760
1776
Хэдхэн жилийн өмнө
05:17
that my grandfather had a stroke,
and he lost complete ability to speak.
91
305560
5720
миний өвөө саа өвчин тусч,
ярих чадвараа алдсан.
05:24
He could understand everybody,
but there was no way to respond,
92
312640
3336
Тэр бүгдийг ойлгож байсан ч
хариу өгөх ямар ч аргагүй байлаа.
05:28
even not writing
because he was illiterate.
93
316000
2480
Учир нь өвөө маань бичиг үсэг
тайлагдаагүй байсан юм.
05:32
So he passed away in silence.
94
320000
2520
Ингээд тэр чимээгүй байсаар
нас барсан билээ.
Би тэр үед түүний өмнөөс
ярьж чаддаг компьютер
05:36
I remember thinking at that time:
95
324800
2336
05:39
What if we could have a computer
96
327160
3896
байсан бол яах байсан бол гэж
боддог байв.
05:43
which could speak for him?
97
331080
1360
05:45
Now, after years that I am in this field,
98
333840
2216
Харин одоо энэ салбарт олон жил ажиллахдаа
05:48
I can see that this might be possible.
99
336080
2320
үүнийг боломжтой гэдгийг ойлгосон юм.
05:52
Imagine if we can find brainwave patterns
100
340240
2856
Хэрэв хүмүүс дүрс
эсвэл үсэг дотроо бодоход,
05:55
when people think
about images or even letters,
101
343120
3440
яг л "А" эсвэл "Б" гэдэг шиг үсэг бодоход
05:59
like the letter A generates
a different brainwave pattern
102
347720
2936
үүсэх тархины долгионыг
ялгаж чаддаг болчихвол
06:02
than the letter B, and so on.
103
350680
1720
яахыг төсөөл дөө.
06:04
Could a computer one day
communicate for people who can't speak?
104
352960
3680
Нэг л өдөр компьютер хэлгүй хүний өмнөөс
бусадтай харилцдаг болох болов уу?
06:09
What if a computer
105
357640
1440
Хэрэв компьютер
06:11
can help us understand
the thoughts of a person in a coma?
106
359960
4560
комд орсон хүний бодлыг
бидэнд дамжуулдаг болчихвол ямар вэ?
06:17
We are not there yet,
107
365840
1616
Бид хараахан тэнд хүрээгүй ч
06:19
but pay close attention.
108
367480
2736
анхааралтай ажиглаарай.
06:22
We will be there soon.
109
370240
1696
Удахгүй зорилгодоо хүрэх болно.
06:23
Thank you.
110
371960
1496
Баярлалаа.
06:25
(Applause)
111
373480
5632
(Алга ташилт)
Translated by Amgalantuul Purevsuren
Reviewed by Munkhbaatar Lkhagvaa

▲Back to top

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
THE ORIGINAL VIDEO ON TED.COM